Oscar Diaz-Caballero, Paulo Manuel De Oliveira-De Jesus, J. Yusta
{"title":"Market Equilibrium Analysis Considering Electric Vehicle Aggregators and Wind Power Producers Without Storage Capabilities","authors":"Oscar Diaz-Caballero, Paulo Manuel De Oliveira-De Jesus, J. Yusta","doi":"10.1109/CPE-POWERENG48600.2020.9161570","DOIUrl":"https://doi.org/10.1109/CPE-POWERENG48600.2020.9161570","url":null,"abstract":"This paper is devoted to analyze market equilibrium solutions when new market agents, such as renew- able/intermittent producers, elastic demands and electric vehicles, are exposed to time-varying Locational Marginal Prices in the context of a competitive electricity market. Two economic equilibrium models are studied in detail. First, we analyze the perfect competition solution driven by a benevolent planner in which real and reactive power dispatches as well as the battery charge-discharge schedule aims to maximize the global social welfare. Secondly, we also address the monopoly solution when the total profit of electric vehicle (EV) aggregators and renewable generators are maximized considering that both producers belong to the same firm. The perfect competition and monopoly system models were applied to an illustrative 3-node test system. Solution shows that under perfect competition, the battery dispatch is smooth in order to get maximum social welfare and therefore minimal grid losses. Conversely, when battery and renewable power injections are managed by only one firm capable to alter the locational prices, the maximum firm profit is get by producing a non-smooth battery dispatch and high grid losses.","PeriodicalId":111104,"journal":{"name":"2020 IEEE 14th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)","volume":"350 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132500018","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}
G. Rigatos, P. Siano, P. Wira, M. Abbaszadeh, V. Ambrožič
{"title":"Nonlinear H-infinity control for hybrid excited synchronous generators","authors":"G. Rigatos, P. Siano, P. Wira, M. Abbaszadeh, V. Ambrožič","doi":"10.1109/CPE-POWERENG48600.2020.9161627","DOIUrl":"https://doi.org/10.1109/CPE-POWERENG48600.2020.9161627","url":null,"abstract":"The model of a hybrid excited synchronous generator is analyzed and a nonlinear optimal (H-infinity) control method is proposed for it. This type of generator receives primary excitation at its stator’s winding through an AC/DC and DC/AC converter, and auxiliary excitation at a secondary winding that is fed by an AC to DC converter. Through the hybrid excitation scheme more control inputs are applied to the generator, thus achieving better performance for the system’s control loop. To implement the proposed control method the dynamic model of the generator undergoes approximate linearization around a temporary operating point which is recomputed at each time-step of the control algorithm. The linearization procedure relies on Taylor series expansion and on the computation of the associated Jacobian matrices. For the approximately linearized model of the hybrid excited synchronous generator a stabilizing H-infinity feedback controller is designed. To compute the controller’s feedback gains an algebraic Riccati equation is repetitively solved at each iteration of the control method. The global stability properties of the control scheme are proven through Lyapunov stability analysis.","PeriodicalId":111104,"journal":{"name":"2020 IEEE 14th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126485965","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}
Tiago J. L. Oliveira, L. Caseiro, A. Mendes, S. Cruz, M. Perdigão
{"title":"Switching frequency reduction for efficiency optimization in two paralleled UPS systems","authors":"Tiago J. L. Oliveira, L. Caseiro, A. Mendes, S. Cruz, M. Perdigão","doi":"10.1109/CPE-POWERENG48600.2020.9161560","DOIUrl":"https://doi.org/10.1109/CPE-POWERENG48600.2020.9161560","url":null,"abstract":"In this paper, the switching frequency reduction in two paralleled Uninterruptible Power Supplies (UPS) is studied in order to obtain maximum global system efficiency. Typically, by reducing the switching frequency of a converter, its efficiency increases. However, when connected in parallel, UPSs are subjected to a Zero Sequence Circulating Current (ZSCC) that compromises a correct system operation and increases the losses of the global system. Experimental results show that to achieve the maximum system efficiency, the ZSCC must be effectively eliminated. Finite Control Set Model Predictive Control (FCSMPC) is used as the control scheme.","PeriodicalId":111104,"journal":{"name":"2020 IEEE 14th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126854541","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}
Noman Shabbir, Roya Amadiahangar, H. Raja, L. Kütt, A. Rosin
{"title":"Residential Load Forecasting Using Recurrent Neural Networks","authors":"Noman Shabbir, Roya Amadiahangar, H. Raja, L. Kütt, A. Rosin","doi":"10.1109/CPE-POWERENG48600.2020.9161565","DOIUrl":"https://doi.org/10.1109/CPE-POWERENG48600.2020.9161565","url":null,"abstract":"In Electrical systems, load forecasting is very important as it has implications on flexibility, smooth operation, and economical aspects as well. The residential load depends on household size, weather season, numbers of load, number of occupants and their behavior, types of devices, etc. Thus, making its accurate forecasting a very difficult job. In this research, machine learning and deep learning-based Recurrent Neural Networks (RNN) algorithms are used for the day-ahead load forecasting of an Estonian household. A data set based on measured load values of an Estonian household is used in the development of this forecasting model. The simulation results indicate that the RNN based algorithm gives better forecasting based on lower Root Mean Square Error (RMSE) value.","PeriodicalId":111104,"journal":{"name":"2020 IEEE 14th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115010357","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":"Location Analysis of Electric Vehicle Charging Stations for Maximum Capacity and Coverage","authors":"I. S. Bayram, S. Bayhan","doi":"10.1109/CPE-POWERENG48600.2020.9161639","DOIUrl":"https://doi.org/10.1109/CPE-POWERENG48600.2020.9161639","url":null,"abstract":"Electric vehicle charging facility location is a critical component of long-term strategic planning. Integration of electric vehicles into mainstream adoption has unique characteristics as it requires a careful investigation of both electric and transportation networks. In this paper, we provide an overview of recent approaches in location analyses of electric vehicle charging infrastructures. We review approaches from classical operations research for fast and slow charging stations. Sample formulations along with case studies are presented to provide insights. We discuss that classical methods are appropriate to address the coverage of charging networks which is defined as average time or distance to reach a charging station when needed. On the other hand, calculating required capacity, defined as the individual charging resources at each node, is still an open research topic. In the final part, we present stochastic facility location theory that uses queuing and other probabilistic approaches.","PeriodicalId":111104,"journal":{"name":"2020 IEEE 14th International Conference on Compatibility, Power Electronics and Power Engineering (CPE-POWERENG)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130153189","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}