Alexander Hobert, Heiko Schroeder, Björn Uhlemeyer, M. Zdrallek, D. Aschenbrenner, Pascal Biesnebach, Lena Seeger
{"title":"Power to Heat as Flexibility Option in Low Voltage Grids from Urban Districts","authors":"Alexander Hobert, Heiko Schroeder, Björn Uhlemeyer, M. Zdrallek, D. Aschenbrenner, Pascal Biesnebach, Lena Seeger","doi":"10.1109/SEST48500.2020.9203183","DOIUrl":"https://doi.org/10.1109/SEST48500.2020.9203183","url":null,"abstract":"This paper analyses how the implementation of demand response on power to heat systems can be used to enable an increased integration of photovoltaic systems in urban districts. In a first step, a thermal model for residential buildings is presented. The next step explains how power to heat systems can apply with a demand response system and how a load shifting works in this context. In the last chapter the added value of power to heat applications that operate by a demand response signal will be investigated. The demand response approach increased the correlation between the entire load and the feed-in of the photovoltaics in the district. Therefore, the residual load could be reduced and the costs as well as the carbon dioxide exhaust for heating energy demand is significantly decreasing.","PeriodicalId":302157,"journal":{"name":"2020 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115902313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Wasserstein-Distance-Based Temporal Clustering for Capacity-Expansion Planning in Power Systems","authors":"L. Condeixa, Fabricio Oliveira, A. Siddiqui","doi":"10.1109/SEST48500.2020.9203449","DOIUrl":"https://doi.org/10.1109/SEST48500.2020.9203449","url":null,"abstract":"As variable renewable energy sources are steadily incorporated in European power systems, the need for higher temporal resolution in capacity-expansion models also increases.Naturally, there exists a trade-off between the amount of temporal data used to plan power systems for decades ahead and time resolution needed to represent renewable energy variability accurately. We propose the use of the Wasserstein distance as a measure of cluster discrepancy using it to cluster demand, wind availability, and solar availability data. When compared to the Euclidean distance and the maximal distance, the hierarchical clustering performed using the Wasserstein distance leads to capacity-expansion planning that 1) more accurately estimates system costs and 2) more efficiently adopts storage resources. Numerical results indicate an improvement in cost estimation by up to 5% vis-à-vis the Euclidean distance and a reduction of storage investment that is equivalent to nearly 100% of the installed capacity under the benchmark full time resolution.","PeriodicalId":302157,"journal":{"name":"2020 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116911661","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Impact of seasonal weather on forecasting of power quality disturbances in distribution grids","authors":"K. Michałowska, Volker Hoffmann, C. Andresen","doi":"10.1109/SEST48500.2020.9203492","DOIUrl":"https://doi.org/10.1109/SEST48500.2020.9203492","url":null,"abstract":"Power supply disruptions, including short-time disturbances, can lead to large direct and indirect financial losses. The ability to predict the risk of these disturbances allows for preventive actions and increases the reliability of the supply. This paper investigates the impact of using seasonal data of combined common weather conditions on the power quality prediction in distribution grids. Our main contribution consists of weather-based predictive models for three types of events that frequently occur in these grids, as well as an analysis of the influence of two training approaches: with either seasonal or all-year data, on their performance. All developed models score higher than arbitrary guessing; in several instances the improvement is considerable. It is demonstrated that in some cases the models improve when the training data is limited to a subset corresponding to a particular meteorological season. Examining variable importance values and distributions of the models’ data, it is shown that this situation takes place particularly when weather conditions correlated with the occurrence of power grid events vary across seasons.","PeriodicalId":302157,"journal":{"name":"2020 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117324441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
M. Rezaei, M. Dehghani, N. Vafamand, Bita Shayanfard, M. Javadi, J. Catalão
{"title":"Selecting the Optimal Signals in Phasor Measurement Unit-based Power System Stabilizer Design","authors":"M. Rezaei, M. Dehghani, N. Vafamand, Bita Shayanfard, M. Javadi, J. Catalão","doi":"10.1109/SEST48500.2020.9203546","DOIUrl":"https://doi.org/10.1109/SEST48500.2020.9203546","url":null,"abstract":"Phasor Measurement Unit (PMU) provides beneficial information for dynamic power system stability, analysis and control. One main application of such useful information is data-driven control. This paper is devoted to presenting an approach for optimal signal selection in PMU-based power system stabilizer (PSS) design. In this paper, for selecting the optimal input and output signals for PSS, an algorithm is suggested in which the combination of clustering the generators and the buses of the system with ICA, modal analysis and PCA techniques is used. The solution for optimal PSS input-output selection is found to increase the observability and damping of the power system. This method is simulated on a 68 buses system with 16 machines. To compare the results with the previous methods, the system is simulated and the results of two previously-developed algorithms are compared with the proposed approach. The results show the benefit of the suggested method in reducing the required signals, which lowers the number of required PMUs while the system damping is not deteriorated.","PeriodicalId":302157,"journal":{"name":"2020 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115470442","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Andrea Cimmino, N. Andreadou, Alba Fernández-Izquierdo, Christos Patsonakis, A. Tsolakis, Alexandre Lucas, D. Ioannidis, E. Kotsakis, D. Tzovaras, R. García-Castro
{"title":"Semantic Interoperability for DR Schemes Employing the SGAM Framework","authors":"Andrea Cimmino, N. Andreadou, Alba Fernández-Izquierdo, Christos Patsonakis, A. Tsolakis, Alexandre Lucas, D. Ioannidis, E. Kotsakis, D. Tzovaras, R. García-Castro","doi":"10.1109/SEST48500.2020.9203338","DOIUrl":"https://doi.org/10.1109/SEST48500.2020.9203338","url":null,"abstract":"Demand Response (DR) systems are gaining momentum in the EU energy markets albeit based on fragmented standards that, as a result, hinder interoperability. These discrepancies necessitate the introduction of a semantically enriched umbrella framework that will allow DR systems to exchange and consume data transparently, an issue that is currently unaddressed. Furthermore, to support semantically interoperable DR architectures, a multi-layer compliance testing framework is required that will examine and quantify the technical, syntactic and semantic properties of individual DR systems. In this work, the aforementioned gaps in the literature are addressed by, first, introducing an OpenADR-based semantic enrichment component. According to the guidelines of the Smart Grid Architecture Model (SGAM) framework, a concrete evaluation procedure of this component is presented, which allows for a step-by-step syntactic and semantic testing. Following the identification of the instruments composing the testbed and the equipment/links under test at SGAM’s communication and information layers, the Basic Application Interoperability Profiles (BAIOPs) are defined and their involved steps are described. Experiments demonstrate the validity of the presented methodology, while also evaluating the introduced component.","PeriodicalId":302157,"journal":{"name":"2020 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115672404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Information-Gap Decision Theory for Robust Operation of Integrated Electricity and Natural Gas Transmission Networks","authors":"A. Rostami, H. Ameli, M. Ameli, G. Strbac","doi":"10.1109/SEST48500.2020.9203435","DOIUrl":"https://doi.org/10.1109/SEST48500.2020.9203435","url":null,"abstract":"Natural gas consumption and the share of renewable energy in meeting global energy demand has grown dramatically in the recent years. On the other hand, the rapid growth of gas-fired generating units (GFU) (i.e., producing lower carbon dioxide emissions compared to coal-fired generating units), could play a key role in more integration of renewable energy sources (RESs) into the system due to their high flexibility. Therefore, the interaction between the electricity and natural gas networks (ENGN) becomes more challenging. This paper proposes a robust multi objective integrated mixed integer nonlinear optimization model, utilizing information-gap decision theory (IGDT), for secure and optimal operation of ENGN considering security constraints as well as gas and electricity load demand uncertainties. This bi-objective optimization problem is modified using normalization in the weighted sum method in order to ensuring the consistency of the optimal solutions. The proposed framework is validated on the modified IEEE 24-bus power system with a 15-node natural gas system.","PeriodicalId":302157,"journal":{"name":"2020 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127135318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alper Nabi Akpolat, Yongheng Yang, F. Blaabjerg, Erkan Dursun, Ahmet Emin Kuzucuoğlu
{"title":"Li-ion-based Battery Pack Designing and Sizing for Electric Vehicles under Different Road Conditions","authors":"Alper Nabi Akpolat, Yongheng Yang, F. Blaabjerg, Erkan Dursun, Ahmet Emin Kuzucuoğlu","doi":"10.1109/SEST48500.2020.9203196","DOIUrl":"https://doi.org/10.1109/SEST48500.2020.9203196","url":null,"abstract":"For the past decades, the world has been suffering from global warming. Although technology develops rapidly with burning fossil fuels to generate energy, resources fade conversely and greenhouse gases are released into the atmosphere. Thus, the concept of renewable energy has gained much importance. In response to the energy transition, the auto industry has gone towards electric vehicles (EVs). The utilization of EVs is inevitable due to their quietness, environmental friendliness, and high efficiency. As the main power source of EVs, battery storage systems (BSSs) are crucial. Within this scope, Li-ion batteries are broadly preferred in the EV industry. The aim of this paper is to determine the battery sizing for EVs under safety battery operation with the dependence of a driving cycle. The BSS model of EVs is designed and developed in MATLAB/Simulink platform. The model gives an optimal battery size connected in parallel and/or series according to the system topology and the EV range. Various road conditions, e.g., flat, downhill, and uphill are presented to compare and analyze the behavior of EVs with designed battery pack.","PeriodicalId":302157,"journal":{"name":"2020 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"442 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125765335","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
T. Guimarães, Luís Miguel Costa, H. Leite, Luís Filipe Azevedo
{"title":"A Hybrid Approach to Load Forecast at a Micro Grid level through Machine Learning algorithms","authors":"T. Guimarães, Luís Miguel Costa, H. Leite, Luís Filipe Azevedo","doi":"10.1109/SEST48500.2020.9203308","DOIUrl":"https://doi.org/10.1109/SEST48500.2020.9203308","url":null,"abstract":"Electric power systems’ operation has been facing new challenges. Intermittent renewable energy production and the consumption side uncertainty has been increasing, not only due to the integration of renewable sources but also flexible loads such as plug-in electric vehicles charging and storage devices. For these reasons, electricity load forecasting is crucial, in the sense of being able to determine the stability of the generation system and maintenance of scalable loads. This paper addresses the forecasts of electricity demand in a Micro Grid context and presents the novel HALOFMI methodology, which includes a Micro Grid scenario, selection and reduction of features and subsequently feeding these entries to the Artificial Neural Network. Final measures include validating the results attained from the developed 24-hour load forecast model defined throughout the work, based on performance metrics.","PeriodicalId":302157,"journal":{"name":"2020 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125153153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alireza Akbari-Dibavar, M. Daneshvar, B. Mohammadi-ivatloo, K. Zare, A. Anvari‐Moghaddam
{"title":"Optimal Robust Energy Management of Microgrid with Fuel Cells, Hydrogen Energy Storage Units and Responsive Loads","authors":"Alireza Akbari-Dibavar, M. Daneshvar, B. Mohammadi-ivatloo, K. Zare, A. Anvari‐Moghaddam","doi":"10.1109/SEST48500.2020.9203215","DOIUrl":"https://doi.org/10.1109/SEST48500.2020.9203215","url":null,"abstract":"To provide net-zero emission conditions for the power grid, this paper aims to provide a coordinated operation for the integrated fuel cell and hydrogen storage systems. Given the sustainability feature of the micro power grid system (MPGS) in engaging different types of distributed energy resources, wind turbines and PV panels are used for clean energy production in the MPGS. Moreover, the battery energy storage system is intended for the appropriate usage of renewable energy resources (RERs) outputs. In order to model the stochastic behaviors of the uncertain parameters, the robust optimization approach is applied in the deregulated environment. Indeed, this method is used to consider the worst state of the uncertain parameters’ occurrence with the aim of providing robust conditions in the system. Also, the time-based demand response program is developed for improving the flexibility of the MPGS with a high contribution of the RERs. In this study, the modified IEEE 21-bus test system is selected for validating the studied system. The simulation results prove the effectiveness of the proposed model in optimal energy management of the power grid.","PeriodicalId":302157,"journal":{"name":"2020 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130558954","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
W. Schram, N. Brinkel, Gilbert Smink, T. van Wijk, W. V. van Sark
{"title":"Empirical Evaluation of V2G Round-trip Efficiency","authors":"W. Schram, N. Brinkel, Gilbert Smink, T. van Wijk, W. V. van Sark","doi":"10.1109/SEST48500.2020.9203459","DOIUrl":"https://doi.org/10.1109/SEST48500.2020.9203459","url":null,"abstract":"The business case of vehicle-to-grid (V2G) technology and its potential to provide grid services is heavily dependent on the round-trip efficiency of this technology. Surprisingly, very little empirical research is conducted to determine the V2G round-trip efficiency of electric vehicles currently available in the market, resulting in a wide range of efficiency values used in V2G modelling studies. This study aims to create more insight in the current V2G round-trip efficiency to stimulate that more uniform and realistic efficiency values are used in other studies. A field experiment is executed to measure the round-trip energy efficiency of V2G for different dates, current rates and average state of charge. It was found that the average round-trip efficiency (i.e., combined inverter and battery efficiency) when charging between a state of charge 25% and 75% with 3x16 Ampere was 87.0%(±1%). However, various external factors could influence the measured efficiencies, which had a total range from 79.1% to 87.8%. Charging at lower ambient temperatures and lower current rates had a statistically significant adverse effect on the round-trip efficiency. Efficiency at high and low state of charge was found to be marginally lower than around medium state of charges. Two different electric vehicle + charging station models were tested, one with on-board AC/DC converter, which is a novel V2G setup, and one with external AC/DC converter, rendering no statistically different efficiency values.","PeriodicalId":302157,"journal":{"name":"2020 International Conference on Smart Energy Systems and Technologies (SEST)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130726929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}