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Sökning: WFRF:(Munkhammar Joakim 1982 )

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1.
  • Fachrizal, Reza, 1993-, et al. (författare)
  • Combined PV-EV hosting capacity assessment for a residential LV distribution grid with smart EV charging and PV curtailment
  • 2021
  • Ingår i: Sustainable Energy, Grids and Networks. - : Elsevier BV. - 2352-4677. ; 26
  • Tidskriftsartikel (refereegranskat)abstract
    • Photovoltaic (PV) systems and electric vehicles (EVs) integrated in local distribution systems are considered to be two of the keys to a sustainable future built environment. However, large-scale integration of PV generation and EV charging loads poses technical challenges for the distribution grid. Each grid has a specific hosting capacity limiting the allowable PV and EV share. This paper presents a combined PV-EV grid integration and hosting capacity assessment for a residential LV distribution grid with four different energy management system (EMS) scenarios: (1) without EMS, (2) with EV smart charging only, (3) with PV curtailment only, and (4) with both EV smart charging and PV curtailment. The combined PV-EV hosting capacity is presented using a novel graphical approach so that both PV and EV hosting capacity can be analyzed within the same framework. Results show that the EV smart charging can improve the hosting capacity for EVs significantly and for PV slightly. While the PV curtailment can improve the hosting capacity for PV significantly, it cannot improve the hosting capacity for EVs at all. From the graphical analysis, it can be concluded that there is a slight positive correlation between PV and EV hosting capacity in the case of residential areas.
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2.
  • Fachrizal, Reza, 1993-, et al. (författare)
  • Residential building with rooftop solar PV system, battery storage and electric vehicle charging : Environmental impact and energy matching assessments for a multi-family house in a Swedish city
  • 2022
  • Ingår i: 21st Wind & Solar Integration Workshop (WIW 2022). - : The Institution of Engineering and Technology (IET). - 9781839538339 ; , s. 565-572
  • Konferensbidrag (refereegranskat)abstract
    • In this paper, environmental impact and energy matching assessments for a residential building with a rooftop photovoltaic (PV)system, battery energy storage system (BESS) and electric vehicles (EV) charging load are conducted. This paper studies a real multi-family house with a rooftop PV system in a city located on the west-coast of Sweden, as a case study. The environmental impact parameter assessed in this study is CO2 equivalent (CO2-eq) emissions. It should be noted that the CO2-eqemission assessment takes into account the whole life cycle, not only the operational processes. The assessments consider boththe household and transport energy demands for the building’s residents. Results show that, CO2-eq emissions from the building electricity usage are increased by 1.65 ton/year with the integrationof PV-BESS system. This is because the Swedish electricity mix has a lower CO2-eq emissions than the PV-BESS system. The total CO2-eq emissions from the transport needs of the building’s residents are significantly decreased, by 32.9 ton/year, if they switch from fossil-fuel-powered cars to EVs. However, the integration of EVs increases the power demand significantly which could be problematic for the power system. In such scenario, the highly-utilized distributed PV systems, enhanced by BESS, can be a low-carbon solution to address the increased power demand challenges coming from transport electrification.
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3.
  • Fachrizal, Reza, 1993-, et al. (författare)
  • Smart charging of electric vehicles considering photovoltaic power production and electricity consumption : a review
  • 2020
  • Ingår i: eTransporation. - : Elsevier. - 2590-1168. ; 4
  • Forskningsöversikt (refereegranskat)abstract
    • Photovoltaics (PV) and electric vehicles (EVs) are two emerging technologies often considered as cornerstones in the energy and transportation systems of future sustainable cities. They both have to be integrated into the power systems and be operated together with already existing loads and generators and, often, into buildings, where they potentially impact the overall energy performance of the buildings. Thus, a high penetration of both PV and EVs poses new challenges. Understanding of the synergies between PV, EVs and existing electricity consumption is therefore required. Recent research has shown that smart charging of EVs could improve the synergy between PV, EVs and electricity consumption, leading to both technical and economic advantages. Considering the growing interest in this field, this review paper summarizes state-of-the-art studies of smart charging considering PV power production and electricity consumption. The main aspects of smart charging reviewed are objectives, configurations, algorithms and mathematical models. Various charging objectives, such as increasing PV utilization and reducing peak loads and charging cost, are reviewed in this paper. The different charging control configurations, i.e., centralized and distributed, along with various spatial configurations, e.g., houses and workplaces, are also discussed. After that, the commonly employed optimization techniques and rule-based algorithms for smart charging are reviewed. Further research should focus on finding optimal trade-offs between simplicity and performance of smart charging schemes in terms of control configuration, charging algorithms, as well as the inclusion of PV power and load forecast in order to make the schemes suitable for practical implementations.
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4.
  • Fachrizal, Reza, 1993- (författare)
  • Synergy between Photovoltaic Power Generation and Electric Vehicle Charging in Urban Energy Systems : Optimization Models for Smart Charging and Vehicle-to-Grid
  • 2023
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Cities are responsible for around 75% of global primary energy use and 70% of global greenhouse gas (GHG) emissions, with buildings and urban mobility being two key contributors. Actions to reduce GHG emissions have been promoted and implemented in many countries in the world. These include switching to electric vehicles (EVs) and renewable energy sources (RES), such as solar photovoltaics (PV). The transition has led to rapid increase in EV and PV adoption worldwide in the recent decades. However, large-scale integration of EVs and PV in urban energy systems poses new challenges such as increased peak loads, power mismatch, component overloading, and voltage violations. Improved synergy between EVs, PV and other loads can overcome these challenges. Coordinated charging of EVs, or so-called EV smart charging, is potentially a promising solution to improve the synergy. The synergy can be further enhanced with vehicle-to-grid (V2G) schemes, where an EV can not only charge, but also discharge power from its battery. This doctoral thesis investigates the synergy between EV charging and PV power generation with the application of EV smart charging and V2G schemes. The investigation was carried out through simulation studies on the system levels of residential buildings, workplaces, distribution grid, and city-scale. Smart charging and V2G optimization models with an objective to reduce the net-load (load minus generation) variability were developed and simulated. The results show that the PV-EV synergy can be improved with the proposed smart charging schemes. However, the levels of improvement depend highly on the user mobility behavior from and to the destined charging locations. PV-EV synergy is limited in residential buildings due to low EV occupancy during high solar power production, but has high potential at workplace charging stations due to high EV occupancy during the same time. In the case studies presented in this thesis, it was found that the implementation of smart charging can improve the synergy by up to around 9 percentage points in residential buildings and up to around 40 percentage points in workplaces. On a city-scale level, both optimal sizing and V2G play essential roles in improving city-scale generation-load synergy, as they can increase the load matching from 33% to 84%. The results also show that improved synergy leads to enhanced power grid performance and combined PV-EV grid hosting capacity.In conclusion, the thesis demonstrates that EV smart charging schemes can improve PV-EV synergy, leading to enhanced performance of urban energy systems.
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5.
  • Fachrizal, Reza, 1993- (författare)
  • Synergy between Residential Electric Vehicle Charging and Photovoltaic Power Generation through Smart Charging Schemes : Models for Self-Consumption and Hosting Capacity Assessments
  • 2020
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • The world is now in a transition towards a more sustainable future. Actions to reduce the green-house gases (GHG) emissions have been promoted and implemented globally, including switching to electric vehicles (EVs) and renewable energy technologies, such as solar photovoltaics (PV). This has led to a massive increase of EVs and PV adoption worldwide in the recent decade.However, large integration of EVs and PV in buildings and electricity distribution systems pose new challenges such as increased peak loads, power mismatch, component overloading, and voltage violations, etc. Improved synergy between EVs, PV and other building electricity load can overcome these challenges. Coordinated charging of EVs, or so-called EV smart charging, is believed to a promising solution to improve the synergy.This licentiate thesis investigates the synergy between residential EV charging and PV generation with the application of EV smart charging schemes. The investigation in this thesis was carried out on the individual building, community and distribution grid levels. Smart charging models with an objective to reduce the net-load (load - generation) variability in residential buildings were developed and simulated. Reducing the net-load variability implies both reducing the peak loads and increasing the self-consumption of local generation, which will also lead to improved power grid performance. Combined PV-EV grid hosting capacity was also assessed.      Results show that smart charging schemes could improve the PV self-consumption and reduce the peak loads in buildings with EVs and PV systems. The PV self-consumption could be increased up to 8.7% and the peak load could be reduced down to 50%. The limited improvement on self-consumption was due to low EV availability at homes during midday when the solar power peaks. Results also show that EV smart charging could improve the grid performance such as reduce the grid losses and voltage violation occurrences. The smart charging schemes improve the grid hosting capacity for EVs significantly and for PV slightly. It can also be concluded that there was a slight positive correlation between PV and EV hosting capacity in the case of residential electricity distribution grids.
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6.
  • Fachrizal, Reza, 1993-, et al. (författare)
  • Urban-scale energy matching optimization with smart EV charging and V2G in a net-zero energy city powered by wind and solar energy
  • 2024
  • Ingår i: eTransporation. - : Elsevier. - 2590-1168. ; 20
  • Tidskriftsartikel (refereegranskat)abstract
    • Renewable energy sources (RES) and electric vehicles (EVs) are two promising technologies that are widely recognized as key components for achieving sustainable cities. However, intermittent RES generation and increased peak load due to EV charging can pose technical challenges for the power systems. Many studies have shown that improved load matching through energy system optimization can minimize these challenges. This paper assesses the optimal urban-scale energy matching potentials in a net-zero energy city powered by wind and solar energy, considering three EV charging scenarios: opportunistic charging, smart charging, and vehicle-to-grid (V2G). This paper takes a city on the west coast of Sweden as a case study. The smart charging and V2G schemes in this study aim to minimize the mismatch between generation and load and are formulated as quadratic programming problems. Results show that the optimal load matching performance is achieved in a net-zero energy city with the V2G scheme and a wind-PV electricity production share of 70:30. The load matching performance is increased from 68% in the opportunistic charging scenario to 73% in the smart charging scenario and to 84% in the V2G scenario. It is also shown that a 2.4 GWh EV battery participating in the V2G scheme equals 1.4 GWh stationary energy storage in improving urban-scale load matching performance. The findings in this paper indicate a high potential from EV flexibility in improving urban energy system performance. 
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7.
  • Grahn, Pia, 1984-, et al. (författare)
  • PHEV Home-Charging Model Based on Residential Activity Patterns
  • 2013
  • Ingår i: IEEE Transactions on Power Systems. - 0885-8950 .- 1558-0679. ; 28:3, s. 2507-2515
  • Tidskriftsartikel (refereegranskat)abstract
    • Plug-in hybrid electric vehicles (PHEVs) have received an increased interest lately since they provide an opportunity to reduce greenhouse gas emissions. Based on the PHEV introduction level in the car park, the charging behaviors in an area will induce changes in the load profiles of the power system. Hence, it becomes important to investigate what impact a given PHEV introduction level has on load profiles due to expected charging behavior of residents.
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8.
  • Johari, Fatemeh, et al. (författare)
  • Analysis of large-scale energy retrofit of residential buildings and their impact on the electricity grid using a validated UBEM
  • 2024
  • Ingår i: Applied Energy. - : Elsevier. - 0306-2619 .- 1872-9118. ; 361
  • Tidskriftsartikel (refereegranskat)abstract
    • To evaluate the effects of different energy retrofit scenarios on the residential building sector, in this study, an urban building energy model (UBEM) was developed from open data, calibrated using energy performance certificates (EPCs), and validated against hourly electricity use measurement data. The calibrated and validated UBEM was used for implementing energy retrofit scenarios and improving the energy performance of the case study city of Varberg, Sweden. Additionally, possible consequences of the scenarios on the electricity grid were also evaluated in this study. The results showed that for a calibrated UBEM, the MAPE of the simulated versus delivered energy to the buildings was 26 %. Although the model was calibrated based on annual values from some of the buildings with EPCs, the validation ensured that it could produce reliable results for different spatial and temporal levels than calibrated for. Furthermore, the validation proved that the spatial aggregation over the city and temporal aggregation over the year could considerably improve the results. The implementation of the energy retrofit scenarios using the calibrated and validated UBEM resulted in a 43 % reduction of the energy use in residential buildings renovated based on the Passive House standard. If this was combined with the generation of on-site solar energy, except for the densely populated areas of the city, it was possible to reach near zero (and in some cases positive) energy districts. The results of grid simulation and power flow analysis for a chosen low-voltage distribution network indicated that energy retrofitting of buildings could lead to an increase in voltage by a maximum of 7 %. This particularly suggests that there is a possibility of occasional overvoltages when the generation and use of electricity are not in perfect balance.
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9.
  • Johari, Fatemeh, et al. (författare)
  • Evaluation of simplified building energy models for urban-scale energy analysis of buildings
  • 2022
  • Ingår i: Building and Environment. - : Elsevier. - 0360-1323 .- 1873-684X. ; 211
  • Tidskriftsartikel (refereegranskat)abstract
    • Simplification of building energy models is one of the most common approaches for efficiently estimating the energy performance of buildings over the whole city. The abstraction of a building into an information model, and the division of the model into representative thermal zones, are no longer customized based on building-specific conditions but they are generic and applicable to many buildings. Considering the limited research on the performance of such methods, in this study, a comprehensive evaluation of the most relevant assumptions on zoning configurations and levels of details is conducted in three building energy simulation tools IDA ICE, TRNSYS and EnergyPlus. The findings from the evaluation of zoning configuration on building-level and its comparison with the measured energy performance of buildings suggest that a single-zone model of a building gives a very similar result to a multi-zone model with one core zone and perimeter zones for every floor of the building. For the single-zone model, IDA ICE overestimates and EnergyPlus underestimates the energy demand compared to the more complex models, by approximately the same amount, but EnergyPlus is preferred due to the shorter simulation time. It is also proven that higher levels of detail in building models can increase the accuracy of the results by approximately 6% annually. By extending the scope of the study from building- to district-level analysis, it is also noted that in large-scale studies where a somewhat lesser degree of accuracy can be allowed on the individual building level, the simplified models give acceptable results.
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10.
  • Lingfors, David, PhD, 1987-, et al. (författare)
  • Modelling City Scale Spatio-temporal Solar Energy Generation and Electric Vehicle Charging Load
  • 2018
  • Ingår i: Proc. of the 8th International Workshop on the Integration of Solar Power into Power Systems. - 9783982008004
  • Konferensbidrag (refereegranskat)abstract
    • This study presents a model for estimatingbuilding-applied photovoltaic (PV) energy yield and electric ve- hicle (EV) charging temporally over time and spatially on a city scale. The model enables transient assessment of the synergy between EV and PV, thus is called the EV-PV Synergy Model. Spatio-temporal data on solar irradiance is used in combination with Light Detection and Ranging (LiDAR) data to generate realistic spatio-temporal solar power generation profiles. The spatio-temporal EV charging profiles are produced with a stochastic Markov chain model trained on a large Swedish data set of travel patterns combined with OpenStreetMap (OSM) for deterministically identifying parking spaces in cities. The modelled estimates of solar power generation andEV charging are combined to determine the magnitude and correlation between PV power generation and EV charging over time on city scale for Uppsala, Sweden. Two months (January and July) were simulated to represent Sweden’s climate extremes. The EV penetration level was assumed to be 100% and all the roofs with yearly irradiation higher than 1000 kWh/m2 were assumed to have PV panels. The results showed that, even in January with the lowestsolar power generation and maximum EV load, there can be a positive net-generation (defined as the integration of PV generation minus EV charging load over time) in some locations within the city. Central locations exhibited a positive temporal correlation between EV charging load and PV generation. Negative temporal correlations were observed in the outskirts of the city, where typically night time home-charging was prevalent. In the highest PV power generation month (July) the solar generation was 16 times higher than the EV charging load. Spatially, the net-generation was positive in almost the entire city. However, the time-series correlation between the EV charging load and the PV generation reached more extreme positive and negative values in comparison with January. This was a result of the higher variability in irradiance during July in comparison with January. In summary, we find that there is a favorable synergy of EV-PV technology within the city center with assumptions of workplace charging behaviors for both winter and summer months. An unfavorable synergy with suburban areas where typically nighttime charging behaviors negatively correlate to PV generation. This suggests that distributed PV should be targeted around city center/workplace EV charging stations.
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11.
  • Luthander, Rasmus, 1988-, et al. (författare)
  • Photovoltaics and opportunistic electric vehicle charging in a Swedish distribution grid
  • 2017
  • Ingår i: Proceedings of the 7th International Workshop on Integration of Solar into Power Systems. - Darmstadt, Germany : Energynautics GmbH. - 9783981654950
  • Konferensbidrag (refereegranskat)abstract
    • Renewable distributed generation and electric vehicles (EVs) are two important components in the transitions to a more sustainable society. However, both distributed generation and EV charging pose new challenges to the power system due to intermittent generation and high-power EV charging. In this case study, a power system consisting of a low- and medium-voltage distribution grid with more than 5000 customers, high penetration of roof-top mounted photovoltaic (PV) power systems and a fully electrified car fleet is used to assess the impact of the intermittent PV generation and high-power EV charging loads. Two summer weeks and two winter weeks with and without EV charging and a PV penetration varying between 0% and 100% of the annual electricity consumption are examined using measured and simulated data. Results show that the electricity consumption increases with 9% and 18% during the studied periods, and that EV charging only marginally can contribute to lowering the risk of overvoltage for customers resulting from PV overproduction. The most significant result is the increase in undervoltage in the winter when EV charging is introduced. The share of customers affected by undervoltage increases from 0% to close to 1.5% for all PV penetration levels.
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12.
  • Luthander, Rasmus, 1988-, et al. (författare)
  • Photovoltaics and opportunistic electric vehicle charging in the power system : a case study on a Swedish distribution grid
  • 2019
  • Ingår i: IET Renewable Power Generation. - : Institution of Engineering and Technology (IET). - 1752-1416 .- 1752-1424. ; 13:5, s. 710-716
  • Tidskriftsartikel (refereegranskat)abstract
    • Renewable distributed generation and electric vehicles (EVs) are two important components in the transition to a more sustainable society. However, both pose new challenges to the power system due to the intermittent generation and EV charging load. In this case study, a power system consisting of a low- and medium-voltage rural and urban distribution grid with 5174 customers, high penetration of photovoltaic (PV) electricity and a fully electrified car fleet were assumed, and their impact on the grid was assessed. The two extreme cases of two summer weeks and two winter weeks with and without EV charging and a PV penetration varying between 0 and 100% of the annual electricity consumption were examined. Active power curtailment of the PV systems was used to avoid overvoltage. The results show an increased electricity consumption of 9.3% in the winter weeks and 17.1% in the summer weeks, a lowering of the minimum voltage by 1% at the most, and a marginal contribution by the EV charging to lower the need of PV power curtailment. This shows the minor impact of EV charging on the distribution grid, both in terms of allowing more PV power generation and in terms of lower voltage levels.
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13.
  • Luthander, Rasmus, 1988- (författare)
  • Self-Consumption of Photovoltaic Electricity in Residential Buildings
  • 2018
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Worldwide installations of photovoltaics (PV) have increased rapidly due to national subsidies and decreasing prices. One important market segment is building-applied PV systems, for which the generated electricity can be self-consumed. Self-consumption is likely to become important both for the profitability and to facilitate integration of high shares of PV in the power system. The purpose of this doctoral thesis is to examine opportunities and challenges with distributed PV in the power system on four system levels: detached houses, communities, distribution systems and national level. This was done through literature studies and computer simulations. Previous research has shown a larger potential to increase the PV self-consumption in detached houses by using battery storage rather than shifting the household appliance loads. This thesis shows that, on the community level, the self-consumption increased more when sharing one large storage instead of individual storages in each house. On the distribution system level, PV power curtailment was identified as an effective solution to reduce the risk of overvoltage due to high PV penetration levels. However, the curtailment losses were high: up to 28% of the electricity production had to be curtailed in the studied distribution grid with a PV penetration of 100% of the yearly electricity consumption. However, the penetration of distributed PV on a national level is not likely to reach these levels. Around 12% of the Swedish households were estimated to have PV systems in 2040, although the uncertainties in the results were high, mainly related to the development of the electricity prices. The low profits from both PV but especially battery systems reduce future market shares. If residential batteries could also be used for primary frequency control, the profitability and thus the market shares for PV and battery systems could increase. The overall conclusions are that improved self-consumption can increase the profitability of PV systems and lower the negative impacts on grids with high PV penetration. Energy storage has a large potential to increase the self-consumption, but the profitability is still low for a storage that is only used to increase the self-consumption.     
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14.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • A Bernoulli distribution model for plug-in electric vehicle charging based on time-use data for driving patterns
  • 2014
  • Ingår i: 2014 IEEE International Electric Vehicle Conference, IEVC 2014. - : IEEE conference proceedings. - 9781479960750
  • Konferensbidrag (refereegranskat)abstract
    • This paper presents a Bernoulli distribution model for plug-in electric vehicle (PEV) charging based on high resolution activity data for Swedish driving patterns. Based on the activity 'driving vehicle' from a time diary study a Monte Carlo simulation is made of PEV state of charge which is then condensed down to Bernoulli distributions representing charging for each hour during weekday and weekend day. These distributions are then used as a basis for simulations of PEV charging patterns. Results regarding charging patterns for a number of different PEV parameters are shown along with a comparison with results from a different stochastic model for PEV charging. A convergence test for Monte Carlo simulations of the distributions is also provided. In addition to this we show that multiple PEV charging patterns are represented by Binomial distributions via convolution of Bernoulli distributions. Also the distribution for aggregate charging of many PEVs is shown to be normally distributed. Finally a few remarks regarding the applicability of the model are given along with a discussion on potential extensions.
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15.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • A copula method for simulating correlated instantaneous solar irradiance in spatial networks
  • 2017
  • Ingår i: Solar Energy. - : Elsevier BV. - 0038-092X .- 1471-1257. ; 143, s. 10-21
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents a method for generating correlated instantaneous solar irradiance data for an arbitrary set of spatially dispersed locations. Based on the empirical clear-sky index distribution for one location and the cross-correlation between clear-sky index data at all location pairs, a copula is used to represent the dependence between locations. The method is primarily intended for probabilistic simulations of electricity distribution grids with high penetrations of photovoltaic (PV) systems, in which solar irradiance data for nodes in the grid can be sampled from the model. The method is validated against a 10-s resolution solar irradiance data set for 14 locations, dispersed within an array of approximately 1 km 1.2 km, at the Island of Oahu, Hawai’i, USA. The results are compared with previous results for along- and cross-wind pairs of locations, and with models for adjacent (completely correlated) and dispersed (completely uncorrelated) locations. It is shown that the copula approach performs better than the adjacent model for a majority of all location pairs and for all but one pair of locations separated more than 500 m. It outperforms the dispersed model for all pairs of locations. In conclusion, the proposed method can generate correlated data and estimate the aggregate clear-sky index for any set of locations based only on the distribution of the clear-sky index for a single location.
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16.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • A Markov-chain probability distribution mixture approach to the clear-sky index
  • 2018
  • Ingår i: Solar Energy. - : Elsevier BV. - 0038-092X .- 1471-1257. ; 170, s. 174-183
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents a Markov-chain probability distribution mixture approach to the clear-sky index (CSI). The main assumption is that the temporal variability of the state of clear and the state of cloudy can be described by a two-state Markov-chain, and the variability within each state can be approximated by a probability distribution, unique for each state. Measurables such as the mean clear-sky index, fraction of bright sunshine, expected duration of clearness and expected duration of cloudiness events are shown to be related to the parameters of the method. Additionally, the Ångström equation, which relates mean normalized solar irradiance to the fraction of bright sunshine, is shown to arise as the expectation of the method. In order to numerically verify the method, a simulation model is constructed based on data sets for two different climatic regions: Norrköping, Sweden and Oahu, Hawaii, USA. Results from the simulation model based on training data shows good agreement with testing data, and when comparing the results to existing models in the literature it is comparable to the state of the art. It is shown that the simulation model generates a non-trivial, generally non-zero, autocorrelation function. Finally, challenges with the method and open problems are discussed.
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17.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • A spatiotemporal Markov-chain mixture distribution model of the clear-sky index
  • 2019
  • Ingår i: Solar Energy. - : PERGAMON-ELSEVIER SCIENCE LTD. - 0038-092X .- 1471-1257. ; 179, s. 398-409
  • Tidskriftsartikel (refereegranskat)abstract
    • This study presents a spatiotemporal Markov-chain mixture distribution model of the clear-sky index for an arbitrary number of locations, and is particularly suited for simulations of small-scale spatial networks with a span of 10 km or less. The model is statistical, but in practice data-driven and based on clear-sky index input from an arbitrary number of locations to generate synthetic time-series for the same locations. When trained on clear-sky index data based on the NREL Hawaii network radiometer solar irradiance data, dispersed within 1 km x 1.2 km, the model is shown to have high goodness-of-fit compared with test data from the network in terms of probability distributions, autocorrelations, location pair-correlations and k-lag correlations between locations. It is also shown to perform comparably to state of the art temporal, spatial and spatiotemporal clear-sky index generators. All measures of model goodness-of-fit are shown to improve with increased number of bins, up to a certain limit of N > 4, where the performance improvements reaches a plateau. The results are also shown to be insensitive with respect to choice of training and test data sets as well as number of output time-steps.
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18.
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19.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • An autocorrelation-based copula model for generating realistic clear-sky index time-series
  • 2017
  • Ingår i: Solar Energy. - : Elsevier BV. - 0038-092X .- 1471-1257. ; 158, s. 9-19
  • Tidskriftsartikel (refereegranskat)abstract
    • This study presents a method for using copulas to model the temporal variability of the clear-sky index, which in turn can be used to produce realistic time-series of photovoltaic power generation. The method utilizes the autocorrelation function of a clear-sky index time-series, and based on that a correlation matrix is set up for the dependency between clear-sky indices at Ntime-steps. With the use of this correlation matrix an N-dimensional copula function is configured so that correlated samples for these N time-steps can be obtained. Results from the copula model are compared with the original data set and an uncorrelated model based on zero correlated clear-sky index data in terms of distribution, autocorrelation, step changes and distribution. The copula model is shown to be superior to the uncorrelated model in these aspects. As a validation the model is tested with solar irradiance for two different geographical regions: Norrköping, Sweden and Hawaii, USA. The copula model is also applied to a set of bins of daily mean clear-sky index and the use of bins is shown to improve the results.
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20.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • An autocorrelation-based copula model for producing realistic clear-sky index and photovoltaic power generation time-series
  • 2017
  • Ingår i: 2017 IEEE 44Th Photovoltaic Specialist Conference (PVSC). - Washington : IEEE. - 9781509056057 ; , s. 3067-3072
  • Konferensbidrag (refereegranskat)abstract
    • This study presents a method for using copulas to model the temporal variability of the clear-sky index. The method utilizes the autocorrelation function and correlated outputs for N time-steps are obtained. Results from the copula model are, in terms of distribution, autocorrelation, step changes and mean daily distribution, compared with the original data set and with an uncorrelated model based on random clear-sky index data. The copula model is shown to be superior to the uncorrelated model in all these aspects.
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21.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • An N-state Markov-chain mixture distribution model of the clear-sky index
  • 2018
  • Ingår i: Solar Energy. - : Elsevier BV. - 0038-092X .- 1471-1257. ; 173, s. 487-495
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents an N-state Markov-chain mixture distribution approach to model the clear-sky index. The model is based on dividing the clear-sky index data into bins of magnitude and determining probabilities for transitions between bins. These transition probabilities are then used to define a Markov-chain, which in turn is connected to a mixture distribution of uniform distributions. When trained on measured data, this model is used to generate synthetic data as output. The model is an N-state generalization of a previously published two-state Markov-chain mixture distribution model applied to the clear-sky index. The model is tested on clear-sky index data sets for two different climatic regions: Norrköping, Sweden, and Oahu, Hawaii, USA. The model is also compared with the two-state model and a copula model for generating synthetic clear-sky index time-series as well as other existing clear-sky index generators in the literature. Results show that the N-state model is generally on par with, or superior to, state-of-the-art synthetic clear-sky index generators in terms of Kolmogorov–Smirnov test statistic, autocorrelation and computational speed.
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22.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • Copula correlation modeling of aggregate solar irradiance in spatial networks
  • 2016
  • Ingår i: Proceedings of the 6th lnternational Workshop on Integration of Solar Power into Power Systems. - Wien.
  • Konferensbidrag (refereegranskat)abstract
    • Estimating solar irradiance over several locations in a spatial network is of interest for a wide variety of applications, in particular for simulations of distribution grid with high photovoltaic (PV) penetration. This paper presents a method for estimating the clear-sky index for N locations in any spatial network of locations. The model is based on the clear-sky index distribution for one location, and the cross-correlation of clear-sky index between all location pairs. The correlated clear-sky index for each location is obtained from a copula model of correlation based on the station pair correlations and the clear-sky index for a single location. In this paper the clear-sky index for a single location is obtained by a bimodal mixture distribution model and the correlation between station pairs is modeled via an exponential model. The model bridges the gap between estimating the clear-sky index for adjacent and maximally dispersed locations. Applications of this model to simulations of aggregate photovoltaic power generation is also discussed.
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23.
  • Munkhammar, Joakim, 1982- (författare)
  • Distributed Photovoltaics, Household Electricity Use and Electric Vehicle Charging : Mathematical Modeling and Case Studies
  • 2015
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Technological improvements along with falling prices on photovoltaic (PV) panels and electric vehicles (EVs) suggest that they might become more common in the future. The introduction of distributed PV power production and EV charging has a considerable impact on the power system, in particular at the end-user in the electricity grid.In this PhD thesis PV power production, household electricity use and EV charging are investigated on different system levels. The methodologies used in this thesis are interdisciplinary but the main contributions are mathematical modeling, simulations and data analysis of these three components and their interactions. Models for estimating PV power production, household electricity use, EV charging and their combination are developed using data and stochastic modeling with Markov chains and probability distributions. Additionally, data on PV power production and EV charging from eight solar charging stations is analyzed.Results show that the clear-sky index for PV power production applications can be modeled via a bimodal Normal probability distribution, that household electricity use can be modeled via either Weibull or Log-normal probability distributions and that EV charging can be modeled by Bernoulli probability distributions. Complete models of PV power production, household electricity use and EV home-charging are developed with both Markov chain and probability distribution modeling. It is also shown that EV home-charging can be modeled as an extension to the Widén Markov chain model for generating synthetic household electricity use patterns. Analysis of measurements from solar charging stations show a wide variety of EV charging patterns. Additionally an alternative approach to modeling the clear-sky index is introduced and shown to give a generalized Ångström equation relating solar irradiation to the duration of bright sunshine.Analysis of the total power consumption/production patterns of PV power production, household electricity use and EV home-charging at the end-user in the grid highlights the dependency between the components, which quantifies the mismatch issue of distributed intermittent power production and consumption. At an aggregate level of households the level of mismatch is shown to be lower.
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24.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • Downscaling global, beam and diffuse horizontal irradiance based on hour resolution global horizontal irradiance using Markov mixture distribution modeling
  • 2022
  • Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
    • This study introduces a downscaling method for generating beam, diffuse and global horizontal irradiance based on hour resolution global horizontal irradiance. The study adapts and evaluates the two time-series Markov-chain Mixture distribution model for generating correlated solar irradiance components for downscaling from hour to minute resolution. The model is tested on radiometer data from two climatic regions: Oahu, Hawaii, USA and Norrk\"oping, Sweden. Results show that the downscaled normalized global, beam and diffuse solar irradiance components are statistically similar to the test data for both locations. As a test of universality, the model trained on SMHI data is tested on NREL data and vice versa. It can be concluded that the output time-series are still realistic, but not neccessarily statistically applicable to the specific climatic region. The downscaling method is available at Github JoakimMunkhammar/N2.
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25.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • Electric Vehicle Charging and Photovoltaic Power Production from Eight Solar Charging Stations in Sweden
  • 2014
  • Ingår i: 4th Solar Integration Workshop. - Darmstadt : Energynautics. - 9783981654905 ; , s. 425-429
  • Konferensbidrag (refereegranskat)abstract
    • This paper quantifies and analyzes data for electric vehicle (EV) charging and photovoltaic(PV) power production from eight charging stations in Sweden withadjacent PV power production provided by Solelia Greentech AB. This study aims toshow the grid interaction of EV charging and PV power production from these solar charging stationswhich are distributed in pairs at four different locations across Sweden. This study utilizesone minute resolution data on power consumption and production from between 281 and310 consecutive days depending on available solar charging station data. Each site, correspondingto two adjacent solar charging stations, has a specific setup regarding EV charging consumer availability.EV charging at two of the sites were available only for the local company/municipality employees and visitors to the company/municipalitywhile the other two sites were public. There was no economical charge for EV charging at any of the stations.Results show that EV charging magnitude and use patterns over timevaried considerably between the stations. Half of the stations had a net consumption of electricityand the other half of stations had a net production of electricity during the metering period.Self-consumption of PV power production was estimated to be between 0.2 and 10 percentdepending on station.
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26.
  • Munkhammar, Joakim, 1982- (författare)
  • Markov-chain modeling of energy users and electric vehicles : Applications to distributed photovoltaics
  • 2012
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Technological improvements and falling prices on photovoltaic panels andelectric vehicles suggest that they might become more common in future households.The introduction of a photovoltaic system and an electric vehiclehas considerable impact on the energy balance of a household. This licentiate thesis investigates the power consumption- and productionpatterns associated with the photovoltaic (PV) electricity production,household electricity consumption and home charged plug-in electric vehicle(PEV) electricity consumption. This investigation is carried out on both an individual and aggregate household level. The methodology used in this thesis is interdisciplinary but the maincontributions are mathematical modeling and simulations of the three main components. Theoretical estimates of electricityconsumption were constructed from extensions to the Wid\'{e}n Markov-chain model for generating synthetichousehold electricity use patterns. The main research contribution in thisthesis is the development and analysis of two extensions of this Markov-chain model: (I) Electricity use from a home charged PEV,(II) Flexibility of end-user power use. These two extensions were used in studiesregarding the coincidence - in particular the level of self-consumption - between PV electricityproduction and household electricity use. PV electricity production was modeledfrom high resolution solar irradiance data from the Ångström laboratory.\\Results show that the home charged PEV load would increase the household loadconsiderably. It was also shown that the level of correlation between PEV load and PVelectricity production was low, but that to some extent the PEV load could help increasethe self-consumption of PV power, both on individual and aggregate household level.\\The modeling and simulations of end-user flexibility showed that the householdload profile could be altered to a certain degree. It was also shown thatcertain flexibility setup could improve the self-consumption of PV power production, more so than theintroduction of a PEV.
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27.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • Modeling combined global, beam, and diffuse clear-sky indices with Markov-chain mixture distribution models
  • 2021
  • Ingår i: Journal of Renewable and Sustainable Energy. - : American Institute of Physics (AIP). - 1941-7012. ; 13:6
  • Tidskriftsartikel (refereegranskat)abstract
    • This study uses the N-state Markov-chain mixture distribution model and the multiple-component N-state Markov-chain mixture distribution model to simulate global, beam, and diffuse horizontal clear-sky index. The models are data-driven such that when trained on single or multiple clear-sky index time-series, the models generate arbitrarily long synthetic clear-sky index time-series for the same components. The models were tested on solar irradiance datasets from two different climatic regions: Norrköping, Sweden, and Oahu, Hawaii, USA. The results show high probability distribution and temporal autocorrelation goodness-of-fit for all models and high cross correlation goodness-of-fit as well as accurate correlation between the component datasets for the multiple component model simulations. When combined with, e.g., the Hay and Davies model, the output from this model could, for example, be used to generate realistic time-series of incident solar irradiance on tilted planes.
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28.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • On a Probability Distribution Convolution Approach to Clear-Sky Index and a Generalized Ångström Equation
  • Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
    • We show that by modeling solar beam irradiance approximately as a simple Bernoulli distribution and diffuse irradiance as a Gamma distribution, a generalized Ångström equation relating solar irradiation to sunshine hours follows directly as aconsequence of the convolution of beam and diffuseirradiance distributions into a distribution for the clear-sky index.
  •  
29.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • On a probability distribution model combining household power consumption, electric vehicle home-charging and photovoltaic power production
  • 2015
  • Ingår i: Applied Energy. - : Elsevier BV. - 0306-2619 .- 1872-9118. ; 142, s. 135-143
  • Tidskriftsartikel (refereegranskat)abstract
    • In this paper we develop a probability distribution model combining household power consumption, electric vehicle (EV) home-charging and photovoltaic (PV) power production. The model is set up using a convolution approach to merge three separate existing probability distribution models for household electricity use, EV home-charging and PV power production. This model is investigated on two system levels: household level and aggregate level of multiple households. Results for the household level show the power consumption/production mismatch as probability distributions for different time bins. This is further investigated with different levels of PV power production. The resulting yearly distribution of the aggregate scenario of multiple uncorrelated households with EV charging and PV power production is shown to not be normally distributed due to the mismatch of PV power production and household power consumption on a diurnal and annual basis.
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30.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • Photovoltaic self-consumption potential of alternative year-round daylight savings time
  • 2013
  • Ingår i: Proceedings of the 28th European Photovoltaic Solar Energy Conference (EU PVSEC), Paris, France, September 30 - October 4, 2013.. - 3936338337 ; , s. 4753-4757
  • Konferensbidrag (refereegranskat)abstract
    • In a mature photovoltaic (PV) market where feed-in tariffs have declined, managing of the hosting capacity of the distribution grid becomes essential by maximizing the utilization of PV. One way to increase hosting capacity is to increase self-consumption of the self-produced PV power. This paper investigates the effect of an alternative year-round daylight savings time (DST) – where the time of the entire society is changed relative to the sun - on the level of self-consumption in terms of solar fraction and load fraction of PV power both on household- and national level. Household electricity use was modeled with a Markov-chain model, PV power production was modeled from solar irradiance data, and the national level was simulated using national electricity data. Results show that one hour year-round DST shifted ahead might increase self-consumption by a fraction of one percentage point for a net-zero energy household. For a 30 GWp PV installation on a national scale with a 140 TWh annual electricity use one hour DST shift ahead had almost no effect on self-consumption. The optimal self-consumption of PV power on the national level was concluded to be the current DST setup.
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31.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • Probabilistic forecasting of high-resolution clear-sky index time-series using a Markov-chain mixture distribution model
  • 2019
  • Ingår i: Solar Energy. - : Elsevier BV. - 0038-092X .- 1471-1257. ; 184, s. 688-695
  • Tidskriftsartikel (refereegranskat)abstract
    • This study presents a Markov-chain mixture (MCM) distribution model for forecasting the clear-sky index-normalized global horizontal irradiance. The model is presented in general, but applied to, and tested or minute resolution clear-sky index data for the two different climatic regions of Norrkoping, Sweden, and Hawaii USA. Model robustness is evaluated based on a cross-validation procedure and on that basis a reference con figuration of parameter settings for evaluating the model performance is obtained. Simulation results ar compared with persistence ensemble (PeEn) and quantile regression (QR) model simulations for both data set and for D = 1,...,5 steps ahead forecasting scenarios. The results are evaluated by a set of probabilistic fore casting metrics: reliability mean absolute error (reliability MAE), prediction interval normalized average widti (PINAW), continuous ranked probability score (CRPS) and continuous ranked probability skill score (skill). Botl in terms of reliability MAE and CRPS, the MCM model outperforms PeEn for all simulated scenarios. In terms c reliability MAE, the QR model outperforms the MCM model for most simulated scenarios. However, in terms c mean CRPS, the MCM model outperforms the QR model in most simulated scenarios. A point forecasting esti mate is also provided. The MCM model is concluded to be a computationally inexpensive, accurate and pars meter insensitive probabilistic model. Based on this, it is suggested as a candidate benchmark model in prop abilistic forecasting, in particular for solar irradiance forecasting. For applicability, a Python script of the MCA model is available as SheperoMah/MCM-distribution-forecasting at GitHub.
  •  
32.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • Probabilistic forecasting of the clear-sky index using Markov-chain mixture distribution and copula models
  • 2019
  • Ingår i: 2019 Ieee 46Th Photovoltaic Specialists Conference (PVSC). - New York : IEEE. - 9781728104942 ; , s. 2428-2433
  • Konferensbidrag (refereegranskat)abstract
    • Two probabilistic forecasting models for the clear-sky index, based on the Markov-chain mixture distribution (MCM) and copula clear-sky index generators, are presented and evaluated. In terms of performance, these models are compared with two benchmark models: a Quantile Regression (QR) model and the Persistence Ensemble (PeEn). The models are tested on minute resolution clear-sky index data, which was estimated from irradiance data for two different climatic regions: Hawaii, USA and Norrkoping, Sweden. Results show that the copula model generally outperforms the PeEn, while the MCM and QR models are superior in all tested aspects. Comparing MCM and QR reliability, the QR is superior, while the MCM is superior in mean CRPS and skill score. The MCM model is proposed as a potential benchmark for probabilistic solar forecasting. The MCM model is available in Python as SheperoMah/MCM-distribution-forecasting at GitHub.
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33.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • Quantifying self-consumption of on-site photovoltaic power generation in households with electric vehicle home charging
  • 2013
  • Ingår i: Solar Energy. - : Elsevier BV. - 0038-092X .- 1471-1257. ; 97, s. 208-216
  • Tidskriftsartikel (refereegranskat)abstract
    • Photovoltaic (PV) power production and residential power demand are negatively correlated at high latitudes on both annual and diurnal basis. If PV penetration levels increase, methods to deal with power overproduction in the local distribution grids are needed to avoid costly grid reinforcements. Increased local consumption is one such option. The introduction of a home-charged plug-in electric vehicle (PEV) has a significant impact on the household load and potentially changes the coincidence between household load and photovoltaic power production. This paper uses a stochastic model to investigate the effect on the coincidence between household load and photovoltaic power production when including a PEV load. The investigation is based on two system levels: (I) individual household level and (II) aggregate household level. The stochastic model produces theoretical high-resolution load profiles for household load and home charged PEV load over time. The photovoltaic power production model is based on high-resolution irradiance data for Uppsala, Sweden. It is shown that the introduction of a PEV improves the self-consumption of the photovoltaic power both on an individual and an aggregate level, but the increase is limited due to the low coincidence between the photovoltaic power production pattern and the charging patterns of the PEV.
  •  
34.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • Simulating dispersed photovoltaic power generation using a bimodal mixture model of the clear-sky index
  • 2015
  • Konferensbidrag (refereegranskat)abstract
    • Improved probability distribution models for power generation are useful e.g. forprobabilistic power flow simulations. This paper presents a distribution modelfor photovoltaic (PV) power generation based on the clear-sky index.With the use of minute-resolution data on globalhorizontal irradiation (GHI) we fit unimodal normal,bimodal normal and trimodal normal mixture distributionfamilies to the clear-sky index. Based on Kolmogorov-Smirnov (K-S) teststhe best fit distribution family consisting of a bimodal normal distribution isthen used for estimating an aggregate clear-sky index for multipledispersed locations that are assumed to be uncorrelated in terms of sky clearness.For five or more locations the aggregate clear-sky indexfollows a normal distribution due to the central limit theorem.Models for solar radiation on tilted planes and PV power generation areapplied to the clear-sky index to generate probability distributions for anarbitrary PV system.
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35.
  • Munkhammar, Joakim, 1982-, et al. (författare)
  • Very short term load forecasting of residential electricity consumption using the Markov-chain mixture distribution (MCM) model
  • 2021
  • Ingår i: Applied Energy. - : Elsevier. - 0306-2619 .- 1872-9118. ; 282
  • Tidskriftsartikel (refereegranskat)abstract
    • This study utilizes the Markov-chain mixture distribution model (MCM) for very short term load forecasting of residential electricity consumption. The model is used to forecast one step ahead half hour resolution residential electricity consumption data from Australia. The results are compared with Quantile Regression (QR) and Persistence Ensemble (PeEn) as advanced and simple benchmark models. The results were compared in terms of reliability, reliability mean absolute error (rMAE), prediction interval normalized average width (PINAW) and normalized continuous ranked probability score (nCRPS). For 10 steps conditioning for QR and PeEn, the MCM results were on par with QR, and superior to PeEn. As a sensitivity analysis, simulations were performed where the number of data points for conditioning QR and PeEn was varied and compared to the MCM output, which is based on only one data point for conditioning. It was shown that in terms of nCRPS and rMAE the QR results converged towards the MCM results for lower number of conditioning points included in QR. The nCRPS of PeEn never reached the superior MCM and QR results, but in rMAE, for number of conditioning points above 24, PeEn was the most reliable. Based on the sparse complexity design of MCM, high computational speed and competitive performance, it is suggested as a candidate for benchmark model in probabilistic forecasting of electricity consumption.
  •  
36.
  • Ramadhani, Umar Hanif, et al. (författare)
  • A city-level assessment of residential PV hosting capacity for low-voltage distribution systems considering rooftop data and uncertainties
  • 2024
  • Ingår i: Applied Energy. - : Elsevier. - 0306-2619 .- 1872-9118. ; 371
  • Tidskriftsartikel (refereegranskat)abstract
    • The increasing trend of small-scale residential photovoltaic (PV) system installation in low-voltage (LV) distribution networks poses challenges for power grids. To quantify these impacts, hosting capacity has become a popular framework for analysis. However, previous studies have mostly focused on small-scale or test feeders and overlooked uncertainties related to rooftop azimuth and tilt. This paper presents a comprehensive evaluation of city-level PV hosting capacity using data from over 300 real LV systems in Varberg, Sweden. A previously developed rooftop azimuth and tilt model is also applied and evaluated. The findings indicate that the distribution systems of the city, with a definition of PV penetration as the percentage of houses with 12 kW installed PV systems, can accommodate up to 90\% PV penetration with less than 1\% risk of overvoltage, and line loading is not a limiting factor. The roof facet orientation modeling proves to be suitable for city-level applications due to its simplicity and effectiveness. Sensitivity studies reveal that PV size assumptions significantly influence hosting capacity analysis. The study provides valuable insights for planning strategies to increase PV penetration in residential buildings and offers technical input for regulators and grid operators to facilitate and manage residential PV systems.
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37.
  •  
38.
  • Ramadhani, Umar Hanif, et al. (författare)
  • On the properties of residential rooftop azimuth and tilt uncertainties for photovoltaic power generation modeling and hosting capacity analysis
  • 2023
  • Ingår i: Solar Energy Advances. - : Elsevier BV. - 2667-1131. ; 3
  • Tidskriftsartikel (refereegranskat)abstract
    • One of the essential epistemic uncertainties that has not yet been studied enough for distributed photovoltaic systems is the azimuth and tilt of rooftop photovoltaic panels, as previous studies of grid impacts and hosting capacity have tended to assume uniform and optimal roof facet conditions. In this study, rooftop facet orientation distributions are presented and analyzed for all single-family buildings in the Swedish city of Uppsala, based on LiDAR-based data that consist of every roof facet from the around 13,500 single-family buildings in the city. From these distributions, novel methods to proportionally include less suitable roofs for every penetration level are proposed using a simple method based on normal and uniform probability density functions, and are tested for both time-series and stochastic hosting capacity analysis. The results show that under the assumption that the best roof facets are utilized first, a uniform distribution for rooftop facet azimuth and a normal distribution for rooftop facet tilt with parameters that depend linearly on the penetration level were shown to be accurate. The hosting capacity simulations demonstrate how the proposed methods perform significantly better in estimating the photovoltaic hosting capacity than the more common simplified methods for both time-series and stochastic hosting capacity analysis. The proposed model could help distribution system operators as well as researchers in this area to model the rooftop facet orientation uncertainty better and improve the quality of aggregated photovoltaic generation models and hosting capacity analyses.
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39.
  • Ramadhani, Umar Hanif, et al. (författare)
  • Probabilistic load flow analysis of electric vehicle smart charging in unbalanced LV distribution systems with residential photovoltaic generation
  • 2021
  • Ingår i: Sustainable cities and society. - : Elsevier. - 2210-6707. ; 72, s. 103043-
  • Tidskriftsartikel (refereegranskat)abstract
    • Several studies have presented electric vehicle smart charging schemes to increase the temporal matching between photovoltaic generation and electric vehicle charging, including a smart charging scheme with an objective to minimize the net-load variance. This method has proved, through simulations, that the self consumption could be increased, but the benefit of the approach has not been tested on a low voltage distribution system. To increase the quality of grid impact analyses of the smart charging scheme, probabilistic methods that include input and spatial allocation uncertainties are more appropriate. In this study, a probabilistic load flow analysis is performed by modelling the variability of electric vehicle mobility, household load, photovoltaic system generation, and the adoption of photovoltaic system and electric vehicle in society. The results show that the smart charging scheme improves the low voltage distribution system performance and increases the correlations between network nodes. It is also shown that concentrated allocation has more severe impacts, in particular at lower penetration levels. This paper can form the basis for the development of probabilistic impact analysis of smart charging to allow society to integrate more electric vehicles and photovoltaic systems for a more sustainable future.
  •  
40.
  • Ramadhani, Umar Hanif, et al. (författare)
  • Review of probabilistic load flow approaches for power distribution systems with photovoltaic generation and electric vehicle charging
  • 2020
  • Ingår i: International Journal of Electrical Power & Energy Systems. - : Elsevier BV. - 0142-0615 .- 1879-3517. ; 120
  • Forskningsöversikt (refereegranskat)abstract
    • The currently increasing penetration of photovoltaic (PV) generation and electric vehicle (EV) charging in electricity distribution grids leads to higher system uncertainties. This makes it vital for load flow analyses to use probabilistic methods that take into account the uncertainty in both load and generation. Such probabilistic load flow (PLF) approaches typically involve three main components: (1) probability distribution models, (2) correlation models, and (3) PLF computations. In this review, state-of-the-art approaches to each of these components are discussed comprehensively, including suggestions of preferred modelling methods specifically for distribution systems with PV generation and EV charging. Research gaps that need to be explored are also identified. For further development of PLF analysis, improving input distribution modelling to be more physically realistic for load, PV generation, and EV charging is vital. Further correlation modelling efforts should focus on developing an effective spatio-temporal correlation model that is able to cope with high-dimensional inputs. The computational speed of PLF analysis needs to be improved to accommodate more complex distribution system models, and time-series approaches should be developed to meet operational needs. Furthermore, collection of higher-quality data is crucial for PLF studies, especially for improving the accuracy in the input variables.
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41.
  • Ramadhani, Umar Hanif, 1993- (författare)
  • Uncertainty and correlation modeling for load flow analysis of future electricity distribution systems : Probabilistic modeling of low voltage networks with residential photovoltaic generation and electric vehicle charging
  • 2021
  • Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • The penetration of photovoltaic (PV) and electric vehicles (EVs) continues to grow and is predicted to claim a vital share of the future energy mix. It poses new challenges in the built environment, as both PV systems and EVs are widely dispersed in the electricity distribution system. One of the vital tools for analyzing these challenges is load flow analysis, which provides insights on power system performance. Traditionally, for simplicity, load flow analysis utilizes deterministic approaches and neglecting  correlation between units in the system. However, the growth of distributed PV systems and EVs increases the uncertainties and correlations in the power system and, hence, probabilistic methods are more appropriate.This thesis contributes to the knowledge of how uncertainty and correlation models can improve the quality of load flow analysis for electricity distribution systems with large numbers of residential PV systems and EVs. The thesis starts with an introduction to probabilistic load flow analysis of future electricity distribution systems. Uncertainties and correlation models are explained, as well as two energy management system strategies: EV smart charging and PV curtailment. The probabilistic impact of these energy management systems in the electricity distribution system has been assessed through a comparison of allocation methods and correlation analysis of the two technologies.The results indicate that these energy management system schemes improve the electricity distribution system performance. Furthermore, an increase in correlations between nodes is also observed due to these schemes. The results also indicate that the concentrated allocation has more severe impacts, in particular at lower penetration levels. Combined PV-EV hosting capacity assessment shows that a combination of EV smart charging with PV curtailment in all buildings can further improve the voltage profile and increase the hosting capacity.  The smart charging scheme also increased the PV hosting capacity slightly. The slight correlation between PV and EV hosting capacity shows that combined hosting capacity analysis of PV systems and EVs is beneficial and is suggested to be done in one framework. Overall, this thesis concludes that an improvement of uncertainty and correlation modeling is vital in probabilistic load flow analysis of future electricity distribution systems.
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42.
  • Ramadhani, Umar Hanif, 1993- (författare)
  • Uncertainty modeling for load flow and hosting capacity analysis of urban electricity distribution systems
  • 2023
  • Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
    • Urban demographics are changing, with more than half of the global population currently residing in urban areas. Traditionally, cities are often seen as passive energy consumers relying on external centralized systems. Motivated by the need to mitigate climate change, a shift is underway as cities actively shape energy systems. This shift involves decentralized power generation, electric vehicle (EV)-related electricity usage shifts, enhanced building energy efficiency, and increasing interaction between local power generation and load. This poses some challenges to distribution grid operation such as voltage violation, decreased power quality, equipment damage, power losses, and reliability issues. Addressing these issues requires load flow analysis, and to quantify the impacts based on load flow analysis, the hosting capacity concept has been introduced. Although traditional load flow analysis lacks uncertainty consideration, the growth of distributed photovoltaics (PV) generation and EVs demands enhanced accuracy through uncertainty modeling.This thesis contributes to the knowledge of how uncertainty and correlation models can improve the quality of load flow and hosting capacity analysis for urban electricity distribution systems with high penetration of residential PV systems and EVs through the combination of methodological and case studies. Methodological studies propose uncertainty models for input variables and investigate their impact on load flow and hosting capacity assessment. Case studies demonstrate enhanced hosting capacity analysis quality through applied uncertainty models.Results show that concentrated allocation of PV systems and EVs had more severe impacts, in particular at lower penetration levels, and smart charging in concentrated allocation had more significant benefits to reduce peak load and voltage drop. Results regarding residential building roofs show that the inclusion of more residential buildings when the PV penetration increases will require including a lot of less-optimal facets, and, hence, a novel method has been proposed to proportionally include less optimal roofs at every penetration level. The smart charging scheme, which has as its main objective to reduce the net-load variability, improves the electricity distribution system performance, and combined with PV curtailment, can further increase the hosting capacity. An increase in correlations between nodes is also observed due to this smart charging scheme. The city-level simulations show that the distribution system of the city can accommodate a 90% penetration level of PV with less than 1% risk of overvoltage and line loading does not limit the hosting capacity. The method used to model roof facet orientation proves effective for city level applications, given its simplicity and effectiveness.In summary, this thesis concludes that the quality and knowledge of load flow and hosting capacity analysis for urban electricity distribution systems can be improved by several methods, including: the probabilistic model of PV power generation and EV charging profiles, the inclusion of EMS, the consideration of spatial allocation methods of PV and EV, the assessment of the correlation between PV and EV, and the consideration of rooftop tilt and azimuth uncertainties.
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43.
  • Shepero, Mahmoud, 1992-, et al. (författare)
  • A generative hidden Markov model of the clear-sky index
  • 2019
  • Ingår i: Journal of Renewable and Sustainable Energy. - : AIP Publishing. - 1941-7012. ; 11:4
  • Tidskriftsartikel (refereegranskat)abstract
    • Clear-sky index (CSI) generative models are of paramount importance in, e.g., studying the integration of solar power in the electricity grid. Several models have recently been proposed with methodologies that are related to hidden Markov models (HMMs). In this paper, we formally employ HMMs, with Gaussian distributions, to generate CSI time-series. The authors propose two different methodologies. The first is a completely data-driven approach, where an HMM with Gaussian observation distributions is proposed. In the second, the means of these Gaussian observation distributions were predefined based on the fraction of time of bright sunshine from the site. Finally, the authors also propose a novel method to improve the autocorrelation function (ACF) of HMMs in general. The two methods were tested on two datasets representing two different climate regions. The performance of the two methodologies varied between the two datasets and among the compared performance metrics. Moreover, both the proposed methods underperformed in reproducing the ACF as compared to state-of-the-art models. However, the method proposed to improve the ACF was able to reduce the mean absolute error (MAE) of the ACF by up to 19%. In summary, the proposed models were able to achieve a Kolmogorov-Smirnov test score as low as 0.042 and MAE of the ACF as low as 0.012. These results are comparable with the state-of-the-art models. Moreover, the proposed models were fast to train. HMMs are shown to be viable CSI generative models. The code for the model and the simulations performed in this paper can be found in the GitHub repository: HMM-CSI-generativeModel.
  •  
44.
  • Shepero, Mahmoud, 1992-, et al. (författare)
  • Estimating the spatiotemporal potential of self-consuming photovoltaic energy to charge electric vehicles in rural and urban Nordic areas
  • 2020
  • Ingår i: Journal of Renewable and Sustainable Energy. - : AIP Publishing. - 1941-7012. ; 12:4
  • Tidskriftsartikel (refereegranskat)abstract
    • The penetration of electric vehicles (EVs) and photovoltaic (PV) systems has increased globally in the last decade. For planning purposes, the spatiotemporal variability of distributed PV power generation and EV charging needs to be quantified for urban and rural areas. This study introduces a state-of-the-art, open, and generally applicable model framework for assessing the spatiotemporal mismatch between EV load and PV generation for urban and rural areas. The model is applied to a rural and an urban area, both 16 km × 16 km and located in Sweden, and is evaluated for the extreme months of January and July. The results show that an energy deficit of, at most, 86% and an up to ten times surplus took place in January and July, respectively. A high self-consumption (SC) of 77% was observed for January and a high self-sufficiency (SS) of 69% for July. This is to say that during July, PV can fulfill 69% of the EV charging load. Moreover, there were no observed correlations between the PV-EV temporal matching scores (the SS and the SC) and the dominant type of charging, e.g., workplace charging in each grid cell (1 km × 1 km) of the areas. This can be partially attributed to the wide distribution of the rooftop orientations in both areas. This challenges the assumption of low PV-EV temporal matching in residential parts of the city. Applying the proposed methodology to other regions is incentivized.
  •  
45.
  • Shepero, Mahmoud, 1992-, et al. (författare)
  • Future load in substations of medium sized Swedish cities : Electric vehicles and photovoltaics
  • 2023
  • Rapport (övrigt vetenskapligt/konstnärligt)abstract
    • The electrical system is currently undergoing a transition, where newhigh-power flexible loads, e.g., electric vehicles (EVs), are penetrating residential areas, and distributed power production from e.g., photovoltaic (PV) panels are also rapidly increasing in the low voltage (LV) grid. This transition requires new modeling methods to accurately predict the vulnerabilities and the needs to upgrade the current grid. A methodology to utilize spatiotemporal Markov based models of PV and EV charging to evaluate the impacts of these technologies on the high voltage (HV)/medium voltage (MV) substations is presented in this report. Furthermore, a case study on a large Swedish city was made. In this case study, penetrations of 100% for the EVs and PV were simulated. The results indicated that EV charging increases the peak load in the city by up to 18%–28%, and the peak load in the substations increased by up to 55%. During July, the PV yield was at most 45% of the winter consumption peak in the city and the summer-time net in-feed was at most 77% in any of the primary substations. Only 3 out of 10 substations experienced overloading events, and in all but one substation these events were shorter than 17 h/year. These overloading have negligible impact on the life-time of the main transformers as they predominantly occur when the ambient temperature is low. To avoid expensive upgrades to the MV transformers, the reserve transformers in the substations can be used to alleviate these overloading incidences. This solution however will not solve hosting capacity limitations in the underlying grid.
  •  
46.
  • Shepero, Mahmoud, 1992-, et al. (författare)
  • Modeling of photovoltaic power generation and electric vehicles charging on city-scale : A review
  • 2018
  • Ingår i: Renewable & sustainable energy reviews. - : PERGAMON-ELSEVIER SCIENCE LTD. - 1364-0321 .- 1879-0690. ; 89, s. 61-71
  • Forskningsöversikt (refereegranskat)abstract
    • Photovoltaics (PV) and electric vehicles (EVs) are promising technologies for increasing energy efficiency and the share of renewable energy sources in power and transport systems. As regards the deployment, use and system integration of these technologies, spatio-temporal modeling of PV power production and EV charging is of importance for several purposes such as urban planning and power grid design and operation. There is an abundance of studies and reviews on modeling of PV power production and EV charging available in the literature. However, there is a lack of studies that review the opportunities for combined modeling of the power consumption and production associated with these technologies. This paper aims to fill this research gap by presenting a review of previous research regarding modeling of spatio-temporal PV power production and charging load of EVs. The paper provides a summary of previous work in both fields and the combination of the fields. Finally, research gaps that need to be further explored are identified. This survey revealed some research gaps that need to be further addressed. Improving the accuracy of PV power production ramp-rate modeling in addition to quantifying the aggregate clear-sky index on city-scale are two priorities for the PV potential studies. For the EV charging load models, differences in model assumptions, such as charging locations, charging powers and charging profiles, need to be studied more extensively. Moreover, there is an imminent need for metering the load of charging stations. This is essential in developing accurate models and time series forecasting techniques. For studies exploring both the PV and EV impacts, local weak points in a spatial network need to be discovered, especially for the city-scale studies. Cooperation between eminent researchers in the PV and EV fields might propagate state-of-the-art models from the separate fields to the combined studies.
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47.
  • Shepero, Mahmoud, 1992-, et al. (författare)
  • Potential of battery storage systems to increase the self-consumption of photovoltaics in charging of electric vehicles in residential buildings
  • 2019
  • Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
    • Electric vehicles (EVs) and photovoltaics (PV) are swiftly being adopted to improve sustainability in both the transportation and the electricity sectors. Residential buildings might benefit from self-consuming the locally produced PV electricity to charge the EVs of the residents. However, the temporal mismatch between midday solar power production and late afternoon EV charging reduces the self-consumption (SC) potential. Here, we investigate the potential of battery storage in improving this SC. The batteries are intended to be used to store the PV energy, from midday, to charge the EVs during the late afternoon. Here we estimate the SC with various battery capacities. This work might be of value to grid operators interested in temporal load matching using battery storages. The results indicate that the houses benefit the most from a 5 kWh battery capacity in comparison with 10 kWh or larger. Using a 5 kWh battery, the SC and self-sufficiency (SS) of the median house without an EV improved by 40% and 14%, respectively. With EVs, the same scores improved by 38% and 11%, respectively. This indicates that the batteries were predominantly used to cover the load of the house and were rarely used to supply the load of the EVs.
  •  
48.
  • Shepero, Mahmoud, 1992-, et al. (författare)
  • Residential probabilistic load forecasting : A method using Gaussian process designed for electric load data
  • 2018
  • Ingår i: Applied Energy. - : Elsevier BV. - 0306-2619 .- 1872-9118. ; 218, s. 159-172
  • Tidskriftsartikel (refereegranskat)abstract
    • Probabilistic load forecasting (PLF) is of important value to grid operators, retail companies, demand response aggregators, customers, and electricity market bidders. Gaussian processes (GPs) appear to be one of the promising methods for providing probabilistic forecasts. In this paper, the log-normal process (LP) is newly introduced and compared to the conventional GP. The LP is especially designed for positive data like residential load forecasting—little regard was taken to address this issue previously. In this work, probabilisitic and deterministic error metrics were evaluated for the two methods. In addition, several kernels were compared. Each kernel encodes a different relationship between inputs. The results showed that the LP produced sharper forecasts compared with the conventional GP. Both methods produced comparable results to existing PLF methods in the literature. The LP could achieve as good mean absolute error (MAE), root mean square error (RMSE), prediction interval normalized average width (PINAW) and prediction interval coverage probability (PICP) as 2.4%, 4.5%, 13%, 82%, respectively evaluated on the normalized load data.
  •  
49.
  • van der Meer, Dennis, et al. (författare)
  • Clear-sky index space-time trajectories from probabilistic solar forecasts : Comparing promising copulas
  • 2020
  • Ingår i: Journal of Renewable and Sustainable Energy. - : AMER INST PHYSICS. - 1941-7012. ; 12:2
  • Tidskriftsartikel (refereegranskat)abstract
    • Short-term probabilistic solar forecasts are an important tool in decision-making processes in which uncertainty plays a non-negligible role. Purely statistical models that produce temporal or spatiotemporal probabilistic solar forecasts are generally trained individually, and the combined forecasts therefore lack the temporal or spatiotemporal correlation present in the data. To recover the spatiotemporal dependence structure, a copula can be employed, which constructs a multivariate distribution from which spatially and temporally correlated uniform random numbers can be sampled, which in turn can be used to generate the so-called space-time trajectories via the inverse probability integral transform. In this study, we employ the recently introduced ultra-fast preselection algorithm to leverage the spatiotemporal information present in a pyranometer network and compare its accuracy to that of quantile regression forecasts that only consider temporal information. We show that the preselection algorithm improves both the calibration and sharpness of the predictive distributions. Furthermore, we employ four copulas, i.e., (1) Gaussian, (2) Student-t, (3) Clayton, and (4) empirical, to generate space-time trajectories. The results highlight the necessity to rigorously assess the calibration of the space-time trajectories and the correct modeling of the spatiotemporal dependence structure, which we show through techniques introduced in atmospheric sciences. The code used to generate the results in this study can be found at https://github.com/DWvanderMeer/SpaceTimeTrajectories.
  •  
50.
  • van der Meer, Dennis, et al. (författare)
  • Probabilistic clear-sky index forecasts using Gaussian process ensembles
  • 2018
  • Ingår i: 2018 IEEE 7th World Conference On Photovoltaic Energy Conversion (WCPEC). - : IEEE. - 9781538685297 ; , s. 2724-2729
  • Konferensbidrag (refereegranskat)abstract
    • In this paper, we investigate the performance of ensembles of Gaussian processes (GPs) to provide more accurate probabilistic forecasts of the clear-sky index (CSI), based on data from a network of pyranometers on Hawaii. This idea follows from the multiple-state model of the CSI in which its probability density can he represented as a combination of Gaussian densities, and the well-documented advantage of ensembles of prediction models. More specifically, we employ a Gaussian mixture model (GMM) and convolution to produce ensembles of GPs, and show that the GMM ensemble outperforms the individual and convoluted GP models, especially by improving the lower limit of the skill score.
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