Pub Date : 2017-09-01DOI: 10.1109/ISAP.2017.8071373
Md Emrad Hossain
In this paper the transient stability improvement analysis of DFIG based variable speed wind generator (WG) is performed among the promising series fault current limiters (fCLs) like the solid-state fault current limiter (SSFCL), and series dynamic braking resistor (SDBR) with the proposed new parallel resonance bridge type fault current limiter (NPR-BFCL). The transient stability analysis is done among the series FCLs in terms of transient stability performances, implementation feasibility, control structure, and cost. A temporary balanced and unbalanced fault was applied in the DFIG based test system to demonstrate the transient stability performance among the series compensating devices. In this work extensive simulations were executed in Matlab/Simulink software and simulation result shows that the mentioned series devices can augment the transient stability during the fault, however, the SSFCL and the NPR-BFCL is the most effective series devices and performed well in comparison to SDBR.
{"title":"Transient stability improvement analysis among the series fault current limiters for DFIG based wind generator","authors":"Md Emrad Hossain","doi":"10.1109/ISAP.2017.8071373","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071373","url":null,"abstract":"In this paper the transient stability improvement analysis of DFIG based variable speed wind generator (WG) is performed among the promising series fault current limiters (fCLs) like the solid-state fault current limiter (SSFCL), and series dynamic braking resistor (SDBR) with the proposed new parallel resonance bridge type fault current limiter (NPR-BFCL). The transient stability analysis is done among the series FCLs in terms of transient stability performances, implementation feasibility, control structure, and cost. A temporary balanced and unbalanced fault was applied in the DFIG based test system to demonstrate the transient stability performance among the series compensating devices. In this work extensive simulations were executed in Matlab/Simulink software and simulation result shows that the mentioned series devices can augment the transient stability during the fault, however, the SSFCL and the NPR-BFCL is the most effective series devices and performed well in comparison to SDBR.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"59 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":"128915323","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.2017.8071390
M. Majidi, A. Ozdemir, O. Ceylan
Modern smart grid implementations bring several advantages in terms of operational controls. Distributed generation and storage facilities near the load centers are probably the most important concepts that are used to improve the quality and the reliability of the consumed energy. Siting and sizing of DG generations in distribution systems may create several problems in traditional radial power systems, which were originally designed for unidirectional power flows. This paper presents an optimal DG allocation and sizing approach in a traditional distribution network where the whole year load variation is taken into account. Optimization aims to minimize both the total voltage variation, TVV, in a day and daily percentage energy losses along the feeder branches. The two objectives are first formulated as singular optimization problems and then combined in a multi-optimization problem. Meta-heuristic Cuckoo search algorithm is used to solve the resulting constrained optimization problem. The proposed formulation is applied to a 12-bus radial distribution system and the MATLAB simulations are performed to validate the performance of the approach.
{"title":"Optimal DG allocation and sizing in radial distribution networks by Cuckoo search algorithm","authors":"M. Majidi, A. Ozdemir, O. Ceylan","doi":"10.1109/ISAP.2017.8071390","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071390","url":null,"abstract":"Modern smart grid implementations bring several advantages in terms of operational controls. Distributed generation and storage facilities near the load centers are probably the most important concepts that are used to improve the quality and the reliability of the consumed energy. Siting and sizing of DG generations in distribution systems may create several problems in traditional radial power systems, which were originally designed for unidirectional power flows. This paper presents an optimal DG allocation and sizing approach in a traditional distribution network where the whole year load variation is taken into account. Optimization aims to minimize both the total voltage variation, TVV, in a day and daily percentage energy losses along the feeder branches. The two objectives are first formulated as singular optimization problems and then combined in a multi-optimization problem. Meta-heuristic Cuckoo search algorithm is used to solve the resulting constrained optimization problem. The proposed formulation is applied to a 12-bus radial distribution system and the MATLAB simulations are performed to validate the performance of the approach.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"123 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":"121769579","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.2017.8071397
Rafik Fainti, M. Alamaniotis, L. Tsoukalas
The aim of this study is to develop and evaluate an autonomous method to perform real time monitoring of power line overloading. To that end, an Artificial Neural Network (ANN) that is repeatedly trained every hour with the most recently acquired measurements is utilized for conducting automated monitoring. The ANN is trained by using the Levenberg-Marquardt algorithm synergistically with Bayesian regularization, which is used to avoid overfitting of the training data. Obtained results by applying the ANN to a set of simulated data taken with the Gridlab-d software exhibit the potentiality of the method in monitoring and predicting line overloading at each line of a three-phase line system in nearly real-time manner.
{"title":"Three-phase line overloading predictive monitoring utilizing artificial neural networks","authors":"Rafik Fainti, M. Alamaniotis, L. Tsoukalas","doi":"10.1109/ISAP.2017.8071397","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071397","url":null,"abstract":"The aim of this study is to develop and evaluate an autonomous method to perform real time monitoring of power line overloading. To that end, an Artificial Neural Network (ANN) that is repeatedly trained every hour with the most recently acquired measurements is utilized for conducting automated monitoring. The ANN is trained by using the Levenberg-Marquardt algorithm synergistically with Bayesian regularization, which is used to avoid overfitting of the training data. Obtained results by applying the ANN to a set of simulated data taken with the Gridlab-d software exhibit the potentiality of the method in monitoring and predicting line overloading at each line of a three-phase line system in nearly real-time manner.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"21 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":"127443141","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.2017.8071418
F. Lezama, Enrique Muñoz de Cote, L. Sucar, J. Soares, Z. Vale
In the smart grid (SG) era, the energy resource management (ERM) in power systems is facing an increase in complexity, mainly due to the high penetration of distributed resources, such as renewable energy and electric vehicles (EVs). Therefore, advanced control techniques and sophisticated planning tools are required to take advantage of the benefits that SG technologies can provide. In this paper, we introduce a new approach called multi-dimensional signaling evolutionary algorithm (MDS-EA) to solve the large-scale ERM problem in SGs. The proposed method uses the general framework from evolutionary algorithms (EAs), combined with a previously proposed rule-based mechanism called multi-dimensional signaling (MDS). In this way, the proposed MDS-EA evolves a population of solutions by modifying variables of interest identified during the evaluation process. Results show that the proposed method can reduce the complexity of metaheuristics implementation while achieving competitive solutions compared with EAs and deterministic approaches in acceptable times.
{"title":"Evolutionary framework for multi-dimensional signaling method applied to energy dispatch problems in smart grids","authors":"F. Lezama, Enrique Muñoz de Cote, L. Sucar, J. Soares, Z. Vale","doi":"10.1109/ISAP.2017.8071418","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071418","url":null,"abstract":"In the smart grid (SG) era, the energy resource management (ERM) in power systems is facing an increase in complexity, mainly due to the high penetration of distributed resources, such as renewable energy and electric vehicles (EVs). Therefore, advanced control techniques and sophisticated planning tools are required to take advantage of the benefits that SG technologies can provide. In this paper, we introduce a new approach called multi-dimensional signaling evolutionary algorithm (MDS-EA) to solve the large-scale ERM problem in SGs. The proposed method uses the general framework from evolutionary algorithms (EAs), combined with a previously proposed rule-based mechanism called multi-dimensional signaling (MDS). In this way, the proposed MDS-EA evolves a population of solutions by modifying variables of interest identified during the evaluation process. Results show that the proposed method can reduce the complexity of metaheuristics implementation while achieving competitive solutions compared with EAs and deterministic approaches in acceptable times.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"70 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":"127731643","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.2017.8071376
Zibo Zhao, Andrew L. Liu
Real-time electricity pricing (RTP) for consumers has long been argued to be key to realize the many envisioned benefits of a smart energy grid. How to actually implement an RTP scheme, however, is still under debate. Since most of the organized wholesale power markets in the US implement a two-settlement system, with day-ahead electricity price forecasts guiding financial and physical transactions in the next day and real-time ex post prices settling any real-time imbalances, it is a natural idea to let consumers respond to the day-ahead prices. Such an idea, however, may lead to consumers all respond in the same fashion, causing large swings of the energy demand and prices, which may jeopardize system stability and increase consumers' financial risks. To overcome this issue, we propose a game-theoretic framework in which each consumer solves a multi-armed bandit problem; that is, consumers learn from the history and attempts to minimize their regrets. The consequence is drastically reduced volatility on real-time prices and much flatter load curves for the entire grid. Such results are not only based on simulation, but are also supported by theories of mean-field equilibria in multi-armed bandit games.
{"title":"Intelligent demand response for electricity consumers: A multi-armed bandit game approach","authors":"Zibo Zhao, Andrew L. Liu","doi":"10.1109/ISAP.2017.8071376","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071376","url":null,"abstract":"Real-time electricity pricing (RTP) for consumers has long been argued to be key to realize the many envisioned benefits of a smart energy grid. How to actually implement an RTP scheme, however, is still under debate. Since most of the organized wholesale power markets in the US implement a two-settlement system, with day-ahead electricity price forecasts guiding financial and physical transactions in the next day and real-time ex post prices settling any real-time imbalances, it is a natural idea to let consumers respond to the day-ahead prices. Such an idea, however, may lead to consumers all respond in the same fashion, causing large swings of the energy demand and prices, which may jeopardize system stability and increase consumers' financial risks. To overcome this issue, we propose a game-theoretic framework in which each consumer solves a multi-armed bandit problem; that is, consumers learn from the history and attempts to minimize their regrets. The consequence is drastically reduced volatility on real-time prices and much flatter load curves for the entire grid. Such results are not only based on simulation, but are also supported by theories of mean-field equilibria in multi-armed bandit games.","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":"125752131","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.2017.8071382
Shu Su, Hang Zhao, Hongzhi Zhang, Xiangning Lin, Feipeng Yang, Zhengtian Li
With the popularization of intelligent navigation system on electric vehicles, it's possible to obtain real-time distribution of electric vehicles in a given region. Based on traffic flow model and M/M/s queuing theory, this paper presents a mathematical model for the prediction of charging load at charging station. To get the charging distribution generated in the driving process, an optimal path planning model based on the Dijkstra algorithm is proposed. Besides, for the sake of formulating the dynamic spatial charging demand distribution map of the traffic network region, the Monte Carlo sampling method is adopted. The simulation results demonstrate the effectiveness of the proposed models in analyzing the charging demand distribution.
{"title":"Forecast of electric vehicle charging demand based on traffic flow model and optimal path planning","authors":"Shu Su, Hang Zhao, Hongzhi Zhang, Xiangning Lin, Feipeng Yang, Zhengtian Li","doi":"10.1109/ISAP.2017.8071382","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071382","url":null,"abstract":"With the popularization of intelligent navigation system on electric vehicles, it's possible to obtain real-time distribution of electric vehicles in a given region. Based on traffic flow model and M/M/s queuing theory, this paper presents a mathematical model for the prediction of charging load at charging station. To get the charging distribution generated in the driving process, an optimal path planning model based on the Dijkstra algorithm is proposed. Besides, for the sake of formulating the dynamic spatial charging demand distribution map of the traffic network region, the Monte Carlo sampling method is adopted. The simulation results demonstrate the effectiveness of the proposed models in analyzing the charging demand distribution.","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":"116755547","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.2017.8071380
Qiushi Cui, K. El-Arroudi, G. Joós
High impedance fault (HIF) is problematic in various distribution systems, specially in rural distribution feeders. The fault current of HIF is with low magnitude, non-linear, asymmetrical and random, therefore extracting useful detection features from HIF current and voltage is the key to solve this issue. This paper experiments with 246 conventional electrical features and their combinations and proposes an effective feature set (EFS) via a feature ranking algorithm utilizing simple signal processing technique of discrete Fourier transform and Kalman filter estimation. This EFS is tested in six types of distribution systems and exhibits a promising detection performance in terms of accuracy, dependability and security once a proper pattern recognition classifier is determined. Besides conventional batch learning algorithms, the proposed detection method demonstrates a significant performance in online machine learning environment. Therefore it shows the potential of processing instantaneous signals and updating its prediction model adaptively to detect more HIFs in future smart grid.
{"title":"An effective feature extraction method in pattern recognition based high impedance fault detection","authors":"Qiushi Cui, K. El-Arroudi, G. Joós","doi":"10.1109/ISAP.2017.8071380","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071380","url":null,"abstract":"High impedance fault (HIF) is problematic in various distribution systems, specially in rural distribution feeders. The fault current of HIF is with low magnitude, non-linear, asymmetrical and random, therefore extracting useful detection features from HIF current and voltage is the key to solve this issue. This paper experiments with 246 conventional electrical features and their combinations and proposes an effective feature set (EFS) via a feature ranking algorithm utilizing simple signal processing technique of discrete Fourier transform and Kalman filter estimation. This EFS is tested in six types of distribution systems and exhibits a promising detection performance in terms of accuracy, dependability and security once a proper pattern recognition classifier is determined. Besides conventional batch learning algorithms, the proposed detection method demonstrates a significant performance in online machine learning environment. Therefore it shows the potential of processing instantaneous signals and updating its prediction model adaptively to detect more HIFs in future smart grid.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"34 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":"129435331","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.2017.8071388
S. Hossain-McKenzie, K. Davis, M. Kazerooni, Sriharsha Etigowni, S. Zonouz
Distributed controllers have a ubiquitous presence in the electric power grid and play a prominent role in its daily operation. The failure or malfunction of distributed controllers is a serious threat whose mechanisms and consequences are not currently well understood and planned against. For example, if certain controllers are maliciously compromised by an adversary, they can be manipulated to drive the power system to an unsafe state. We seek to develop proactive strategies to protect the power grid from distributed controller compromise or failure. This research formalizes the roles that distributed controllers play in the grid, quantifies how their loss or compromise impacts the system, and develops effective strategies for maintaining or regaining system control. Specifically, an analytic method based on controllability analysis is derived using clustering and factorization techniques on controller sensitivities.
{"title":"Distributed controller role and interaction discovery","authors":"S. Hossain-McKenzie, K. Davis, M. Kazerooni, Sriharsha Etigowni, S. Zonouz","doi":"10.1109/ISAP.2017.8071388","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071388","url":null,"abstract":"Distributed controllers have a ubiquitous presence in the electric power grid and play a prominent role in its daily operation. The failure or malfunction of distributed controllers is a serious threat whose mechanisms and consequences are not currently well understood and planned against. For example, if certain controllers are maliciously compromised by an adversary, they can be manipulated to drive the power system to an unsafe state. We seek to develop proactive strategies to protect the power grid from distributed controller compromise or failure. This research formalizes the roles that distributed controllers play in the grid, quantifies how their loss or compromise impacts the system, and develops effective strategies for maintaining or regaining system control. Specifically, an analytic method based on controllability analysis is derived using clustering and factorization techniques on controller sensitivities.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"57 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":"134043334","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.2017.8071411
Gabriel Santos, T. Pinto, Isabel Praça, Z. Vale
Electricity markets worldwide are complex and dynamic environments with very particular characteristics. The markets' restructuring and evolution into regional and continental scales, along with the constant changes brought by the increasing necessity for an adequate integration of renewable energy sources are the main drivers. Multi-agent based software is particularly well fitted to analyse dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This paper proposes the use of ontologies to enable the exchange of information and knowledge, to test different market models and to allow market players from different systems to interact in common market environments. Focusing, namely, on the EPEX electricity market.
{"title":"EPEX ontology: Enhancing agent-based electricity market simulation","authors":"Gabriel Santos, T. Pinto, Isabel Praça, Z. Vale","doi":"10.1109/ISAP.2017.8071411","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071411","url":null,"abstract":"Electricity markets worldwide are complex and dynamic environments with very particular characteristics. The markets' restructuring and evolution into regional and continental scales, along with the constant changes brought by the increasing necessity for an adequate integration of renewable energy sources are the main drivers. Multi-agent based software is particularly well fitted to analyse dynamic and adaptive systems with complex interactions among its constituents, such as electricity markets. This paper proposes the use of ontologies to enable the exchange of information and knowledge, to test different market models and to allow market players from different systems to interact in common market environments. Focusing, namely, on the EPEX electricity market.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"51 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":"132263936","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.2017.8071414
A. D. da Silva, Fernando A. de Assis, L. Manso, Muriell R. Freire, S. Flávio
This paper proposes a new methodology for solving the transmission expansion planning problem, considering the "N-1" security criterion. The proposed optimization tool, classified as constructive metaheuristic, is built combining two techniques: a constructive heuristic algorithm and an evolutionary metaheuristic. A linearized DC network model that includes transmission losses is adopted for evaluating the obtained configurations. Network sensitivity indices are used in the constructive process. They are evaluated considering the intact network, "N-0", and also single transmission contingencies established by the "N-1" security criterion. These indices are used to measure the attractiveness and effectiveness of reinforcements to be added or removed during the constructive process. The proposed method resembles the way system planners search for the best transmission expansion configurations. Two networks, a well-known academic system and a configuration of the Brazilian network, are used to test the proposed tool.
{"title":"Constructive metaheuristics applied to transmission expansion planning with security constraints","authors":"A. D. da Silva, Fernando A. de Assis, L. Manso, Muriell R. Freire, S. Flávio","doi":"10.1109/ISAP.2017.8071414","DOIUrl":"https://doi.org/10.1109/ISAP.2017.8071414","url":null,"abstract":"This paper proposes a new methodology for solving the transmission expansion planning problem, considering the \"N-1\" security criterion. The proposed optimization tool, classified as constructive metaheuristic, is built combining two techniques: a constructive heuristic algorithm and an evolutionary metaheuristic. A linearized DC network model that includes transmission losses is adopted for evaluating the obtained configurations. Network sensitivity indices are used in the constructive process. They are evaluated considering the intact network, \"N-0\", and also single transmission contingencies established by the \"N-1\" security criterion. These indices are used to measure the attractiveness and effectiveness of reinforcements to be added or removed during the constructive process. The proposed method resembles the way system planners search for the best transmission expansion configurations. Two networks, a well-known academic system and a configuration of the Brazilian network, are used to test the proposed tool.","PeriodicalId":257100,"journal":{"name":"2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)","volume":"103 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":"131563855","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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