| 1. |
- Abrahamsson, Lars, 1979-, et al.
(författare)
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Evaluating a constant-current load model through comparative transient stability case-studies of a synchronous-synchronous rotary frequency converter-fed railway
- 2019
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Ingår i: 2019 Joint Rail Conference. - : ASME Press.
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- This paper continues the pursuit of getting a deeper understanding regarding the transient stability of low-frequency AC railway power systems operated at 16 2/3 Hz synchronously to the public grid. The focus is set on the impact of different load models. A simple constant-current load model is proposed and compared to a previously proposed and studied load model in which the train’s active power is regulated.The study and comparison is made on exactly the same cases as and grid as with the already proposed and more advanced load model. The railway grid is equipped with a low-frequency AC high-voltage transmission line which is subjected to a fault. The study is limited to railways being fed by different distributions of RFC (Rotary Frequency Converter) types. Both AT (auto transformer) and BT (booster transformer) catenaries are considered.The RFC dynamic models are essentially Anderson-Fouad models of two synchronous machines coupled mechanically by their rotors being connected to the same shaft.The differences in load behaviour between the proposed constant-current load model and the previously proposed and studied voltage-dependent active power load model are analyzed and described in the paper.
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| 2. |
- Ackeby, Susanne, et al.
(författare)
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Prosumer with demand-response:Distribution network impact and mitigation
- 2013
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Rapport (övrigt vetenskapligt/konstnärligt)abstract
- This report is the result from a project funded by ELFORSK done by STRI. Theproject is studying the effects the introduction of so called “prosumers”(customers with own production) and electrical vehicles will have on differenttypes of networks. Four different cases are studied: covering urban and ruralareas with different types of customers.In the urban areas the power through the transformer will be the limitingfactor. The major impact in the cases studied is from the introduction ofproduction from photovoltaics at the customer-side of the meter. This willresult in an introduction of surplus due to production which in one case led toan increase of the absolute power through the transformer with more than30%, which resulted in transformer overloading.In the rural areas the voltage drop or rise will be the limiting factor. The casesstudied had already high voltage drops even in the base cases. In the casestudies it was seen that the voltage drop could be slightly reduced whenintroducing more local production, but the production also led to that voltagerise could appear. As a result the interval of the voltage variations wasincreased, which in turn leads to difficulties with designing the network suchthat neither overvoltage nor undervoltage occurs.Introducing control algorithms had a very positive effect on reducing the netproduction from the photovoltaics. Using both hard and soft curtailment madeit possible to remove all overcurrents or overvoltages. Using hard curtailment,where all production is turned off during overcurrent or overvoltage, leadshowever to a large reduction in energy from renewable energy sources.Therefore soft curtailment should as much as possible be used.The control algorithms studied for reducing the net consumption had a morelimited effect and even resulted in an increase of the maximum netconsumption. When trying to reduce the net consumption during an overload,the reason of the overload could only be moved in time and not removed as inthe case of reducing the net production. And since often the period duringwhich the power exceeds the limit is longer than the number of hours possibleto move the energy, sometimes moving the energy had an adverse effect.The model used for controlling the net consumption needs furtherdevelopment, but it is still possible to draw the conclusion that this type ofcontrol offers only limited possibilities for mitigating overload or undervoltage.The effects of introducing prosumers and more electrical vehicles as defined inthe selected cases did not show any alarming results in this study. However,studies to learn more about the possible consequences of changes atcustomer-side are important to be able to handle the impact of such changeson the network.Further future studies needed: database with load and production data;improved control algorithms; demonstration project; experience from othercountries and studies on reactive power compensation.
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| 3. |
- Ahmed, Kazi Main Uddin, 1989-
(författare)
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On the Energy Efficiency and Reliability of Data Centers in Operation
- 2023
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The new generation information technology (IT) services like mobile Internet, Internet of things (IoT), cloud computing, processing of big data, applications of artificial intelligence, etc. are becoming popular with the development of the information and communication technology (ICT) industry. In this industry, the dependency on the data centers is also increasing to ensure the quality of services (QoS). Thus, the energy consumption of the data centers is increasing with the increasing demand for computational resources in it because the load sections of the data center with sensitive equipment run $24$ hours a day, $365$ days of the year. Regarding data center operation, it is becoming a technical challenge to make a trade-off between reducing the energy consumption to limit the operational costs and ensuring higher reliability of the data center.A way to help data center operators to cope with the posed challenges is by identifying the ``right size of the computational resource'', considering the power losses and service availability of the data center. This endeavor requires power consumption models that can consider different load sections with different types of equipment. The power consumption models of the load sections can address the electrical load demand and the power losses, especially losses in the internal power conditioning system (IPCS). On the other hand, the service availability of the data center mainly depends on the availability of the computational resources like servers and on the availability of the power supply through the IPCS. It is important to characterize the servers' failure and repair times to develop the stochastic model of the server unavailability in operation. The availability of adequate power supply through the IPCS depends on its component failures and the power supply capacity of its components. The bottleneck of the power supply capacity of the IPCS is subjected to the power losses of the equipment in the IPCS. Additionally, the voltage disturbances like voltage dips and swells in the IPCS also interrupt the power supply units (PSUs) of the servers, which also degrades the QoS of the data center.The outcomes of this thesis can be synthesized as follows: 1) A comparative analysis of the energy consumption models of the major load sections in the data center, and an analysis of the impact of the power losses in the IPCS on the outage probability of the servers. 2) Reliability indices to assess the adequacy of the computational resources in the data center considering the outages of power supplies and the servers in operation. 3) The impacts of voltages disturbances in the IPCS on the power supply outages, hence on the interruptions of servers. 4) An analysis of the trade-off between the energy efficiency and reliability in operational planning of the data center.
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| 4. |
- Alhamwi, Mouaz, et al.
(författare)
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Empirical Analysis of Voltage Variations in Low Voltage Distribution Grids from Photovoltaic
- 2019
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Ingår i: Solar Integration Workshop 2019. - : Energynautics GmbH. - 9783982008042
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Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- The rapid expansion of photovoltaic (PV) systems has raised voltage concerns. This paper investigates voltage variations measured at four hundred on-line PV installations in Sweden. Small (<10 kW inverter size) three phase residential PV systems had the least impact whereas single phase systems had the most impact for the same amount of power injected per phase. PV systems were grouped based on post code location into urban and rural areas. Urban areas were found to be more resilient to PV induced voltage fluctuations with a narrower back-ground voltage band in comparison to rural areas, indicating that PV inverter measurements can be an efficient method to empirically determine grid strength.
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| 5. |
- Alvarez Perez, Manuel Alejandro, 1980-
(författare)
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Stochastic Planning of Smart Electricity Distribution Networks
- 2017
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The penetration of intermittent Distributed Generation (DG) brought additional uncertainty to the system operation and planning. To cope with uncertainties the Distribution System Operator (DSO) could implement several strategies. These strategies range from the inclusion of smart technologies which will increment system’s flexibility and resiliency, to improvements in forecasting, modeling, and regulatory pledge that will facilitate the planning activity. Regardless of the nature of the solutions, they could be collected in a sort of toolbox. The planner will access the toolbox to conform cost effective plans, better able to deal with any uncertainty. The present work will address the problem of distribution system planning under uncertainties, considering smart solutions along with traditional reinforcements, in the short-term lead time up to 3 years ahead. The work will be focused on three aspects that are the cornerstones of this work: • A planning facilitating strategy: Distribution Capacity Contracts (DCCs). • A flexibility enabler technology: Energy Storage. • A binding methodology: Multistage Stochastic Programming. Stochastic dual dynamic programming (SDDP). Under the present directive of the European Parliament concerning common rules for the internal market in electricity, distribution companies are not allowed to own DG but entitled to include it as a planning option to differ investment in traditional grid reinforcements. An evaluation of the regulatory context will lead this work to consider DCCs as a planning alternative available in the toolbox. The impact of this type of contract on the remuneration of the DG owner will be assessed in order to provide insight on its willingness to participate. The DCCs might aid the DSO to defer grid i ii investments during planning stages and to control the network flows during operation. Given that storage solutions help to match in time production from intermittent sources with load consumption, they will play a major role in dealing with uncertainties. A generic storage model (GSM) based on a future cost piecewise approximation will be developed. This model inspired by hydro-reservoirs will help assessing the impact of storage in planning decisions. This model will be tested by implementing it in short-term hydro scheduling and unit commitment studies. To trace a path towards the future of this research work, a discussion on the planning problem formulation, under consideration of the lead time, the expansion options, the smart strategies, and the regulatory framework will be presented. Special focus will be given to multistage stochastic programming methods and in particular to the SDDP approach.
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| 6. |
- Bagheri, Azam
(författare)
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Artificial Intelligence-Based Characterization and Classification Methods for Power Quality Data Analytics
- 2018
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Doktorsavhandling (övrigt vetenskapligt/konstnärligt)abstract
- One of the important developments in the electric power system is the fast increasing amount of data. An example of such data is formed by the voltages and currents coming from power-quality measurements. Power quality disturbances like voltage dips, harmonics and voltage transient can have a serious negative impact on the performance of equipment exposed to such disturbances. Voltage dips, short duration reductions in voltage magnitude, are especially considered as important disturbances because they regularly lead to stoppages in industrial process installations and subsequently to high costs.The overall aim of this dissertation is the development of automatic analysis methods and other methods for extracting information from large amounts of power-quality data. This includes, methods to detect and extract event characteristics from recorded data and classify the events, for instance, based on their origins or their impact on equipment. The classification facilitates further analysis steps including reasoning and interpretation. Once the data corresponding to each class is available, a proper characterization method can be used to create more semantic data useful for information extraction. The resulting information can be used to improve the performance of the whole system, e.g., updating grid-codes, or immunity requirements of sensitive installations or processes.This dissertation proposes different methods to fulfil each one of the above-mentioned steps. It proposes particularly a space-phasor model (SPM) of the three phase-to-neutral voltages as basis for analytic methods. The SPM is especially suitable as it is a time-domain transform without loss of any information. Another important contribution of the work is that most of the developed methods have been applied to a large dataset of about 6000 real-world voltage dips measured in existing HV and MV power networks.The main contributions of this dissertation are as follows:A complete framework has been proposed for automatic voltage quality analysis based on the SPM. The SPM has been used before, but this is the first time it has been used in a framework covering a range of voltage quality disturbances. A Gaussian-based anomaly detection method is used to detect and extract voltage quality disturbances. A principal component analysis (PCA) algorithm is used for event characterization. The obtained single-event characteristics are used to extract additional information like origin, fault type and location. Two deep learning-based voltage dip classifier has been developed. In both classifier a 2D convolutional neural network (2D-CNN) architecture has been employed to perform automatic feature extraction task. The soft-max activation function fulfills supervised classification method in first classifier. The second classifier uses a semi-supervised classification method based on generative-discriminative model pairs in active learning context.The same SPM was shown to enable the effective extraction of dip characteristics for multi-stage voltage dips. Applying the k-means clustering algorithm, the event is clustered into its individual stages. For each stage of the dip, a logistic regression algorithm is used to characterize that stage. The proposed method offers a new solution to the problem with transition segments that is one of the main challenges of existing methods for characterization of multi-stage dips. It is also shown in the dissertation that the SPM is an effective method for voltage transient analysis. It is possible to extract corresponding sample data and get appropriate single-event characteristics.A systematic way has been developed and applied for comparing different sets of voltage dip characteristics. With this method, both measured and synthetic voltage dips are applied to generic models of sensitive loads. The best set of characteristics is the one most accurately reproducing the behavior of equipment when exposed to measured voltage dips.The dissertation further contains a number of practical applications of the before-mentioned theoretical contributions: a proposal to an international standard-setting group; energy storage for voltage-dip ride-through of microgrids; impact of different voltage dips on wind-power installations.
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| 9. |
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| 10. |
- Bollen, Math H.J., et al.
(författare)
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The power grid as part of a sustainable energy system
- 2024. - 2
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Ingår i: Large Scale Grid Integration of Renewable Energy Sources. - : Institution of Engineering and Technology. ; , s. 1-30
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Bokkapitel (övrigt vetenskapligt/konstnärligt)abstract
- We are currently experiencing a truly global energy crisis. Globally, high fuel prices are responsible for 90% of the average cost increase in electricity generation, with natural gas alone accounting for 50%. The Russian invasion of Ukraine in February 2022 has amply demonstrated how geopolitics can have a profound impact on energy systems, but above all, it has revealed the reality of our pattern of energy consumption and generation. As seen in Figure 1.1, fossil fuels supplied 84.3% of global energy use, while the share of wind and solar power (after decades of heavy government subsidies) was only 3.3%, even though there was almost enough installed wind and solar power capacity to supply all their electricity if they were to generate electricity at rated output continuously. Fossil fuel support in 51 countries across the world nearly doubled to $697.2 billion in 2021, up from $362.4 billion in 2020 [1]. However, many developing countries found themselves in a situation where they cannot afford fossil fuels while renewable energy is scarce. This has resulted, on the one hand, in 75 million people who had recently gained access to electricity no longer being able to afford it, and on the other hand, in 100 million people no longer being able to cook with clean fuels, being forced to rely on wood, cow dung, and other unsafe and unhealthy sources. This implies that "much more energy will be needed over the next few generations to extend decent lives for the majority of the world's growing population" [2]. In these countries, access to affordable energy is considered at least as important as controversial climate change. This reality is shown particularly in the countries selected in Figure 1.1(b). Particularly in coal consumption, its decrease takes place mostly in the developed world, particularly in Europe and North America. However, this decline is compensated by growth in coal consumption in developing economies, particularly in Asia. More on this interesting topic at [3].
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