Pub Date : 2017-09-01DOI: 10.1109/ISAP.2017.8071364
A. Shahid
Smart grids are becoming practical nowadays with their integrated, complex and communicative architecture. The addition of renewable energy sources, control automation, information and communication technologies (ICT), advanced monitoring and protection and smart metering has further increased the complexity. Next generation smart grid will act as an interactive energy web with multi-way communication, multi-directional power flow, distributed intelligence including control, stability and optimization. To enable this type of architecture, the performance constraints in control design such as power fluctuations, voltage unbalance, frequency mismatch, transition management and fault handling need to be addressed. This intelligent network must be scalable and flexible under variable operating conditions for efficient, reliable, and economic operation. An overview of the control architecture for next generation smart grids is provided in this paper.
{"title":"An overview of control architecture for next generation smart grids","authors":"A. Shahid","doi":"10.1109/ISAP.2017.8071364","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071364","url":null,"abstract":"Smart grids are becoming practical nowadays with their integrated, complex and communicative architecture. The addition of renewable energy sources, control automation, information and communication technologies (ICT), advanced monitoring and protection and smart metering has further increased the complexity. Next generation smart grid will act as an interactive energy web with multi-way communication, multi-directional power flow, distributed intelligence including control, stability and optimization. To enable this type of architecture, the performance constraints in control design such as power fluctuations, voltage unbalance, frequency mismatch, transition management and fault handling need to be addressed. This intelligent network must be scalable and flexible under variable operating conditions for efficient, reliable, and economic operation. An overview of the control architecture for next generation smart grids is provided in this paper.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"203 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123017861","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}
Pub Date : 2017-09-01DOI: 10.1109/ISAP.2017.8071365
Qin Yan, Cheng Qian, Bei Zhang, M. Kezunovic
This paper establishes stochastic model of plug-in electric vehicle (PEV) charging and derives the probabilistic description of the electricity needs from EV charging for one charging station at any hour of a day. Three key variables are used to characterize the stochastic behavior of EV charging: starting time of charging, state of charge (SOC), and total number of charging EVs. The electricity needs of an EV charging station is a function of time, which can be depicted by the expectation of charging needs at a certain time of day. Numerical simulations are implemented to validate the proposed analysis approach and illustrate the impact of EVs' charging demand on the distribution systems.
{"title":"Statistical analysis and modeling of plug-in electric vehicle charging demand in distribution systems","authors":"Qin Yan, Cheng Qian, Bei Zhang, M. Kezunovic","doi":"10.1109/ISAP.2017.8071365","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071365","url":null,"abstract":"This paper establishes stochastic model of plug-in electric vehicle (PEV) charging and derives the probabilistic description of the electricity needs from EV charging for one charging station at any hour of a day. Three key variables are used to characterize the stochastic behavior of EV charging: starting time of charging, state of charge (SOC), and total number of charging EVs. The electricity needs of an EV charging station is a function of time, which can be depicted by the expectation of charging needs at a certain time of day. Numerical simulations are implemented to validate the proposed analysis approach and illustrate the impact of EVs' charging demand on the distribution systems.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125184142","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}
Pub Date : 2017-09-01DOI: 10.1109/ISAP.2017.8071368
Zeyu Mao, T. Xu, T. Overbye
The growing installation of phasor measurement units (PMUs) provide grid operators wide-area situational awareness while introducing additional vulnerabilities to power systems from the cyber security point of view. This paper presents an online method to detect ongoing contingencies in the system and bad data injection on its PMU network. To do so, the principal component analysis is applied to leverage the spatial and temporal correlations among the synchrophasor data. Pattern match and data reconstruction are proposed to identify incident types and find their most possible locations. Case studies are carried out on a 150-bus system to demonstrate the effectiveness of the proposed scheme.
{"title":"Real-time detection of malicious PMU data","authors":"Zeyu Mao, T. Xu, T. Overbye","doi":"10.1109/ISAP.2017.8071368","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071368","url":null,"abstract":"The growing installation of phasor measurement units (PMUs) provide grid operators wide-area situational awareness while introducing additional vulnerabilities to power systems from the cyber security point of view. This paper presents an online method to detect ongoing contingencies in the system and bad data injection on its PMU network. To do so, the principal component analysis is applied to leverage the spatial and temporal correlations among the synchrophasor data. Pattern match and data reconstruction are proposed to identify incident types and find their most possible locations. Case studies are carried out on a 150-bus system to demonstrate the effectiveness of the proposed scheme.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117269469","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}
Pub Date : 2017-09-01DOI: 10.1109/ISAP.2017.8071412
Muhammad Umer Qureshi, S. Grijalva
In this paper, we propose a distributed open loop control algorithm for large-scale transmission systems having multiple control areas exchanging power through tie-lines. Inspired from graph theoretic methods in multi-agent systems, it ensures a high degree of coordination among control areas to improve the frequency response with minimal inter-area oscillations in case of sudden loss of generation. Local nodes associated with generation units coordinate with regional nodes monitoring tie-line flows to ensure load-generation balance is maintained at all times with sparse information exchange. We develop a Cyber-Physical abstraction which allows for a scalable architecture that is independent of the internal dynamics of the control areas. Consequently, these areas can quantitatively predefine their contribution in frequency restoration during primary control. We perform simulations on a test system resulting in improved frequency response and reduced deviation from the nominal frequency, demonstrating the efficacy of our proposed protocol.
{"title":"Multi-agent based distributed power agreement for enhanced frequency response of transmission systems","authors":"Muhammad Umer Qureshi, S. Grijalva","doi":"10.1109/ISAP.2017.8071412","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071412","url":null,"abstract":"In this paper, we propose a distributed open loop control algorithm for large-scale transmission systems having multiple control areas exchanging power through tie-lines. Inspired from graph theoretic methods in multi-agent systems, it ensures a high degree of coordination among control areas to improve the frequency response with minimal inter-area oscillations in case of sudden loss of generation. Local nodes associated with generation units coordinate with regional nodes monitoring tie-line flows to ensure load-generation balance is maintained at all times with sparse information exchange. We develop a Cyber-Physical abstraction which allows for a scalable architecture that is independent of the internal dynamics of the control areas. Consequently, these areas can quantitatively predefine their contribution in frequency restoration during primary control. We perform simulations on a test system resulting in improved frequency response and reduced deviation from the nominal frequency, demonstrating the efficacy of our proposed protocol.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129073871","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}
Pub Date : 2017-09-01DOI: 10.1109/ISAP.2017.8071409
M. Ramirez, R. Castellanos, J. Calderón
A modified Teaching-Learning Based Optimization (MTLBO) Algorithm is proposed to reduce the computational time involved in the optimization process of the original TLBO technique. Proposed MTLBO is applied to the design of a power oscillation damping controller (PODC), inserted in one of the converters of a VSC-HVDC link, to modulate active power and contribute to enhancing the inter-area power oscillations of a two-area power system model. Performance comparison of MTLBO and TLBO algorithms during the optimization process is carried out and the effect of PODCs tuned with both of these techniques is evaluated and illustrated through the application and simulation of system perturbations in the sample power system. Simulation results show that MTLBO can achieve a very comparable performance to TLBO, but at a significantly reduced computational time.
{"title":"Modified teaching-learning based optimization algorithm and damping of inter-area oscillations through VSC-HVDC","authors":"M. Ramirez, R. Castellanos, J. Calderón","doi":"10.1109/ISAP.2017.8071409","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071409","url":null,"abstract":"A modified Teaching-Learning Based Optimization (MTLBO) Algorithm is proposed to reduce the computational time involved in the optimization process of the original TLBO technique. Proposed MTLBO is applied to the design of a power oscillation damping controller (PODC), inserted in one of the converters of a VSC-HVDC link, to modulate active power and contribute to enhancing the inter-area power oscillations of a two-area power system model. Performance comparison of MTLBO and TLBO algorithms during the optimization process is carried out and the effect of PODCs tuned with both of these techniques is evaluated and illustrated through the application and simulation of system perturbations in the sample power system. Simulation results show that MTLBO can achieve a very comparable performance to TLBO, but at a significantly reduced computational time.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114104543","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}
Pub Date : 2017-09-01DOI: 10.1109/ISAP.2017.8071408
M. Ramirez, R. Castellanos, J. Calderón
A fuzzy logic controller is proposed to perform the functions of supplementary inertial and frequency control in wind turbine generating units. Expert knowledge governing the performance of the proposed fuzzy logic approach for frequency support in this study is expressed by a set of fuzzy rules extracted from a common symmetrical rule table widely used in the literature. A sample multi-machine power system is used to evaluate the performance of the proposed fuzzy controller under system frequency drop perturbations. Time domain simulation results show that the proposed alternative can indeed improve the frequency nadir following grid frequency declines, as compared to the performance of a conventional inertial controller.
{"title":"Fuzzy logic approach for inertial and frequency response from converter based wind power units","authors":"M. Ramirez, R. Castellanos, J. Calderón","doi":"10.1109/ISAP.2017.8071408","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071408","url":null,"abstract":"A fuzzy logic controller is proposed to perform the functions of supplementary inertial and frequency control in wind turbine generating units. Expert knowledge governing the performance of the proposed fuzzy logic approach for frequency support in this study is expressed by a set of fuzzy rules extracted from a common symmetrical rule table widely used in the literature. A sample multi-machine power system is used to evaluate the performance of the proposed fuzzy controller under system frequency drop perturbations. Time domain simulation results show that the proposed alternative can indeed improve the frequency nadir following grid frequency declines, as compared to the performance of a conventional inertial controller.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131265572","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}
Pub Date : 2017-09-01DOI: 10.1109/ISAP.2017.8071367
Joshua Johnson, S. Hossain-McKenzie, U. Bui, Sriharsha Etigowni, K. Davis, S. Zonouz
Historically, the structure of an Artificial Neural Network (ANN) has been defined through trial-and-error or excessive computation leading to reduced accuracy and increased training time, respectively. For many disciplines, especially power systems, models must both be accurate and support fast computations in order to be viable for large-scale use. These requirements often render poorly structured ANNs useless. However, using power system behavioral knowledge to create an ANN structure could provide a near best case estimate for a model that maximizes accuracy and minimizes computational run-time. This paper considers the relationship between the dominant modes of a power system and the hidden neurons (units) in an ANN. In this study, several ANNs were created with varying number of neurons. These ANNs were used to predict rotor angle response to faults at generator buses that were cleared at varying times and compared with actual responses, as obtained through simulation. The number of neurons used include the hypothesized dominant mode number and five known heuristic estimates. The resultant method is a domain-dependent algorithm to structure an ANN without relying on trial-and-error or additional unnecessary computation time for power system models.
{"title":"Improving power system neural network construction using modal analysis","authors":"Joshua Johnson, S. Hossain-McKenzie, U. Bui, Sriharsha Etigowni, K. Davis, S. Zonouz","doi":"10.1109/ISAP.2017.8071367","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071367","url":null,"abstract":"Historically, the structure of an Artificial Neural Network (ANN) has been defined through trial-and-error or excessive computation leading to reduced accuracy and increased training time, respectively. For many disciplines, especially power systems, models must both be accurate and support fast computations in order to be viable for large-scale use. These requirements often render poorly structured ANNs useless. However, using power system behavioral knowledge to create an ANN structure could provide a near best case estimate for a model that maximizes accuracy and minimizes computational run-time. This paper considers the relationship between the dominant modes of a power system and the hidden neurons (units) in an ANN. In this study, several ANNs were created with varying number of neurons. These ANNs were used to predict rotor angle response to faults at generator buses that were cleared at varying times and compared with actual responses, as obtained through simulation. The number of neurons used include the hypothesized dominant mode number and five known heuristic estimates. The resultant method is a domain-dependent algorithm to structure an ANN without relying on trial-and-error or additional unnecessary computation time for power system models.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134364950","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}
Pub Date : 2017-09-01DOI: 10.1109/ISAP.2017.8071403
S. Mashayekh, K. Butler-Purry
Isolated microgrids are prone to large frequency and voltage deviations, due to limited generation capacity, finite generation inertia, and possibly including large portions of dynamic loads. They require effective security-constrained power management methods, which operate the system optimally, while satisfying the security constraints. Region-based security assessment is popular for real-time security-constrained power management, thanks to its low calculation burden. This paper presents a systematic method to assess an approximation of the system deterministic or probabilistic (risk-based) Dynamic Secure Region (DSR) in isolated microgrids. To demonstrate how the method works, it was implemented on a notional isolated microgrid in an all-electric ship. The results showed the effectiveness of the proposed DSR assessment method.
{"title":"A novel deterministic and probabilistic dynamic security assessment approach for isolated microgrids","authors":"S. Mashayekh, K. Butler-Purry","doi":"10.1109/ISAP.2017.8071403","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071403","url":null,"abstract":"Isolated microgrids are prone to large frequency and voltage deviations, due to limited generation capacity, finite generation inertia, and possibly including large portions of dynamic loads. They require effective security-constrained power management methods, which operate the system optimally, while satisfying the security constraints. Region-based security assessment is popular for real-time security-constrained power management, thanks to its low calculation burden. This paper presents a systematic method to assess an approximation of the system deterministic or probabilistic (risk-based) Dynamic Secure Region (DSR) in isolated microgrids. To demonstrate how the method works, it was implemented on a notional isolated microgrid in an all-electric ship. The results showed the effectiveness of the proposed DSR assessment method.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133652943","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}
Pub Date : 2017-09-01DOI: 10.1109/ISAP.2017.8071375
M. Vallem, B. Vyakaranam, Jesse T. Holzer, N. Samaan, Y. Makarov, R. Diao, Qiuhua Huang, Xinda Ke
Power systems are vulnerable to extreme contingencies (like an outage of a major generating substation) that can cause significant generation and load loss and can lead to further cascading outages of other transmission facilities and generators in the system. Some cascading outages are seen within minutes following a major contingency, which may not be captured using only the dynamic simulation of the power system that are usually run for 30 or 40 seconds. The utilities plan for contingencies based on either dynamic or steady-state analysis separately, which may not accurately capture the effect of one process on the other. We addressed this gap in cascading outage analysis by developing the Dynamic Contingency Analysis Tool (DCAT), which can analyze the hybrid dynamic and steady-state behavior of power systems including protection system models in dynamic simulations, and by simulating corrective actions in post-transient steady-state conditions. One of the important implemented steady-state processes is to mimic operator corrective actions to mitigate aggravated states caused by dynamic cascading. This paper formulates an optimization model, called Optimal Power Flow with Corrective Actions (OPFCA), for selecting corrective actions that utility operators can take during major contingencies and thus automate hybrid dynamic/steady-state cascading outage mitigation. The improved DCAT framework with OPFCA is demonstrated on the 3120-bus Polish system.
{"title":"Hybrid cascading outage analysis of extreme events with optimized corrective actions","authors":"M. Vallem, B. Vyakaranam, Jesse T. Holzer, N. Samaan, Y. Makarov, R. Diao, Qiuhua Huang, Xinda Ke","doi":"10.1109/ISAP.2017.8071375","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071375","url":null,"abstract":"Power systems are vulnerable to extreme contingencies (like an outage of a major generating substation) that can cause significant generation and load loss and can lead to further cascading outages of other transmission facilities and generators in the system. Some cascading outages are seen within minutes following a major contingency, which may not be captured using only the dynamic simulation of the power system that are usually run for 30 or 40 seconds. The utilities plan for contingencies based on either dynamic or steady-state analysis separately, which may not accurately capture the effect of one process on the other. We addressed this gap in cascading outage analysis by developing the Dynamic Contingency Analysis Tool (DCAT), which can analyze the hybrid dynamic and steady-state behavior of power systems including protection system models in dynamic simulations, and by simulating corrective actions in post-transient steady-state conditions. One of the important implemented steady-state processes is to mimic operator corrective actions to mitigate aggravated states caused by dynamic cascading. This paper formulates an optimization model, called Optimal Power Flow with Corrective Actions (OPFCA), for selecting corrective actions that utility operators can take during major contingencies and thus automate hybrid dynamic/steady-state cascading outage mitigation. The improved DCAT framework with OPFCA is demonstrated on the 3120-bus Polish system.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131577211","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}
Pub Date : 2017-09-01DOI: 10.1109/ISAP.2017.8071410
T. Pinto, A. Gazafroudi, Francisco Prieto-Castrillo, Gabriel Santos, Francisco Silva, J. Corchado, Z. Vale
This paper proposes a new model to allocate reserve costs among the involved players, considering the characteristics of the several entities, and the particular circumstances at each moment. The proposed model is integrated in the Multi-Agent Simulator of Competitive Electricity Markets (MASCEM), which enables complementing the multi-agent simulation of diverse electricity market models, by including the joint simulation of energy and reserve markets. In this context, the proposed model allows allocating the payment of reserve costs that result from the reserve market. A simulation based on real data from the Iberian electricity market — MIBEL, is presented. Simulation results show the advantages of the proposed model in sharing the reserve costs fairly and accordingly to the different circumstances. This work thus contributes the study of novel market models towards the evolution of power and energy systems by adapting current models to the new paradigm of high penetration of renewable energy generation.
{"title":"Reserve costs allocation model for energy and reserve market simulation","authors":"T. Pinto, A. Gazafroudi, Francisco Prieto-Castrillo, Gabriel Santos, Francisco Silva, J. Corchado, Z. Vale","doi":"10.1109/ISAP.2017.8071410","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071410","url":null,"abstract":"This paper proposes a new model to allocate reserve costs among the involved players, considering the characteristics of the several entities, and the particular circumstances at each moment. The proposed model is integrated in the Multi-Agent Simulator of Competitive Electricity Markets (MASCEM), which enables complementing the multi-agent simulation of diverse electricity market models, by including the joint simulation of energy and reserve markets. In this context, the proposed model allows allocating the payment of reserve costs that result from the reserve market. A simulation based on real data from the Iberian electricity market — MIBEL, is presented. Simulation results show the advantages of the proposed model in sharing the reserve costs fairly and accordingly to the different circumstances. This work thus contributes the study of novel market models towards the evolution of power and energy systems by adapting current models to the new paradigm of high penetration of renewable energy generation.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128507402","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}
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