| 1. |
- Fachrizal, Reza, 1993-
(author)
-
Synergy between Residential Electric Vehicle Charging and Photovoltaic Power Generation through Smart Charging Schemes : Models for Self-Consumption and Hosting Capacity Assessments
- 2020
-
Licentiate thesis (other academic/artistic)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.
|
|
| 2. |
- Ramadhani, Umar Hanif, 1993-
(author)
-
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
-
Licentiate thesis (other academic/artistic)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.
|
|
| 3. |
- Fachrizal, Reza, 1993-, et al.
(author)
-
Combined PV-EV hosting capacity assessment for a residential LV distribution grid with smart EV charging and PV curtailment
- 2021
-
In: Sustainable Energy, Grids and Networks. - : Elsevier BV. - 2352-4677. ; 26
-
Journal article (peer-reviewed)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.
|
|
| 4. |
- Fachrizal, Reza, 1993-, et al.
(author)
-
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
-
In: 21st Wind & Solar Integration Workshop (WIW 2022). - : The Institution of Engineering and Technology (IET). - 9781839538339 ; , s. 565-572
-
Conference paper (peer-reviewed)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.
|
|
| 5. |
- Fachrizal, Reza, 1993-, et al.
(author)
-
Smart charging of electric vehicles considering photovoltaic power production and electricity consumption : a review
- 2020
-
In: eTransporation. - : Elsevier. - 2590-1168. ; 4
-
Research review (peer-reviewed)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.
|
|
| 6. |
- Fachrizal, Reza, 1993-, et al.
(author)
-
Urban-scale energy matching optimization with smart EV charging and V2G in a net-zero energy city powered by wind and solar energy
- 2024
-
In: eTransporation. - : Elsevier. - 2590-1168. ; 20
-
Journal article (peer-reviewed)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.
|
|
| 7. |
- Munkhammar, Joakim, 1982-, et al.
(author)
-
A Bernoulli distribution model for plug-in electric vehicle charging based on time-use data for driving patterns
- 2014
-
In: 2014 IEEE International Electric Vehicle Conference, IEVC 2014. - : IEEE conference proceedings. - 9781479960750
-
Conference paper (peer-reviewed)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.
|
|
| 8. |
- Johari, Fatemeh, et al.
(author)
-
Urban Building Energy Modeling : State of the Art and Future Prospects
- 2020
-
In: Renewable & sustainable energy reviews. - : Elsevier BV. - 1364-0321 .- 1879-0690. ; 128
-
Research review (peer-reviewed)abstract
- During recent years, urban building energy modeling has become known as a novel approach for identification, support and improvement of sustainable urban development initiatives and energy efficiency measures in cities. Urban building energy models draw the required information from the energy analysis of buildings in the urban context and suggest options for effective implementation of interventions. The growing interest in urban building energy models among researchers, urban designers and authorities has led to the development of a diversity of models and tools, evolving from physical to more advanced hybrid models. By critically analyzing the published research, this paper incorporates an updated overview of the field of urban building energy modeling and investigates possibilities, challenges and shortcomings, as well as an outlook for future improvements. The survey of previous studies identifies technical bottlenecks and legal barriers in access to data, systematic and inherent uncertainties as well as insufficient resources as the main obstacles. Furthermore, this study suggests that the main route to further improvements in urban building energy modeling is its integration with other urban models, such as climate and outdoor comfort models, energy system models and, in particular, mobility models.
|
|
| 9. |
- Sandels, Claes, 1985-, et al.
(author)
-
Day-Ahead Predictions of Electricity Consumption in a Swedish Office Building from Weather, Occupancy, and Temporal data
- 2015
-
In: Energy and Buildings. - : Elsevier. - 0378-7788 .- 1872-6178. ; 108
-
Journal article (peer-reviewed)abstract
- An important aspect of Demand Response (DR) is to make accurate predictions for the consumption in the short term, in order to have a benchmark load profile which can be compared with the load profile influenced by DR signals. In this paper, a data analysis approach to predict electricity consumption on load level in office buildings on a day-ahead basis is presented. The methodology is: (i) exploratory data analysis, (ii) produce linear models between the predictors (weather and occupancies) and the outcomes (appliance, ventilation, and cooling loads) in a step wise function, and (iii) use the models from (ii) to predict the consumption levels with day-ahead prognosis data on the predictors. The data has been collected from a Swedish office building floor. The results from (ii) show that occupancy is correlated with appliance load, and outdoor temperature and a temporal variable defining work hours are connected with ventilation and cooling load. It is concluded from the results in (iii) that the error rate decreases if fewer predictors are included in the predictions. This is because of the inherent forecast errors in the day-ahead prognosis data. The achieved error rates are comparable with similar prediction studies in related work.
|
|
| 10. |
|
|
