Arouna Oloulade, A. M. Imano, F. Fifatin, Auriole Prudence Omoremy, Amédée Ganye, Ramanou Badarou, A. Viannou, Mahamoud Tanimomon
{"title":"基于U-NSGA-III遗传算法的STATCOM存在下能源组合经济、环境、静态和动态调度多点分析","authors":"Arouna Oloulade, A. M. Imano, F. Fifatin, Auriole Prudence Omoremy, Amédée Ganye, Ramanou Badarou, A. Viannou, Mahamoud Tanimomon","doi":"10.11648/J.EPES.20200905.11","DOIUrl":null,"url":null,"abstract":"In an energy environment with multiple production sources, operators are generally confronted with the optimal choice of sources which minimizes polluting gas emissions, losses and marginal production costs while meeting the contractual requirements for maintaining voltage in the ranges required. The present work consisted of optimizing an energy mix in the presence of multi-STATCOM in an interconnected network. Indeed, the (DEE) is a concrete real time problem in electrical energy production systems. This paper shows the impact of STATCOM on static DEE (DEES) and on dynamic DEE (DEED) using the modern genetic algorithm of type U-NSGA-III, which is based on non-dominance sorting. The optimal positioning of two STATCOMs in the application network associated with dynamic dispatching has contributed to the reduction of the total production cost, toxic gas emissions, active losses and then to the improvement of the voltage profiles and the transit of power in the branches. It is observed that the combination of DEED with the optimal positioning of FACTS in an interconnected network constitutes an efficient technico-ecological means to act in the direction of reduction on the triplet consisting of (gas emissions, losses, production cost). The relevance of the results obtained compared to the real case of operating the CEB's interconnected network, justifies the performance of the algorithmic tools developed in the context of this work.","PeriodicalId":43153,"journal":{"name":"International Journal of Power and Energy Systems","volume":"20 1","pages":"74"},"PeriodicalIF":0.3000,"publicationDate":"2020-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Multi-point Analysis of Economic, Environmental, Static and Dynamic Dispatching of an Energy Mix in the Presence of STATCOM by the U-NSGA-III Genetic Algorithm\",\"authors\":\"Arouna Oloulade, A. M. Imano, F. Fifatin, Auriole Prudence Omoremy, Amédée Ganye, Ramanou Badarou, A. Viannou, Mahamoud Tanimomon\",\"doi\":\"10.11648/J.EPES.20200905.11\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In an energy environment with multiple production sources, operators are generally confronted with the optimal choice of sources which minimizes polluting gas emissions, losses and marginal production costs while meeting the contractual requirements for maintaining voltage in the ranges required. The present work consisted of optimizing an energy mix in the presence of multi-STATCOM in an interconnected network. Indeed, the (DEE) is a concrete real time problem in electrical energy production systems. This paper shows the impact of STATCOM on static DEE (DEES) and on dynamic DEE (DEED) using the modern genetic algorithm of type U-NSGA-III, which is based on non-dominance sorting. The optimal positioning of two STATCOMs in the application network associated with dynamic dispatching has contributed to the reduction of the total production cost, toxic gas emissions, active losses and then to the improvement of the voltage profiles and the transit of power in the branches. It is observed that the combination of DEED with the optimal positioning of FACTS in an interconnected network constitutes an efficient technico-ecological means to act in the direction of reduction on the triplet consisting of (gas emissions, losses, production cost). 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Multi-point Analysis of Economic, Environmental, Static and Dynamic Dispatching of an Energy Mix in the Presence of STATCOM by the U-NSGA-III Genetic Algorithm
In an energy environment with multiple production sources, operators are generally confronted with the optimal choice of sources which minimizes polluting gas emissions, losses and marginal production costs while meeting the contractual requirements for maintaining voltage in the ranges required. The present work consisted of optimizing an energy mix in the presence of multi-STATCOM in an interconnected network. Indeed, the (DEE) is a concrete real time problem in electrical energy production systems. This paper shows the impact of STATCOM on static DEE (DEES) and on dynamic DEE (DEED) using the modern genetic algorithm of type U-NSGA-III, which is based on non-dominance sorting. The optimal positioning of two STATCOMs in the application network associated with dynamic dispatching has contributed to the reduction of the total production cost, toxic gas emissions, active losses and then to the improvement of the voltage profiles and the transit of power in the branches. It is observed that the combination of DEED with the optimal positioning of FACTS in an interconnected network constitutes an efficient technico-ecological means to act in the direction of reduction on the triplet consisting of (gas emissions, losses, production cost). The relevance of the results obtained compared to the real case of operating the CEB's interconnected network, justifies the performance of the algorithmic tools developed in the context of this work.
期刊介绍:
First published in 1972, this journal serves a worldwide readership of power and energy professionals. As one of the premier referred publications in the field, this journal strives to be the first to explore emerging energy issues, featuring only papers of the highest scientific merit. The subject areas of this journal include power transmission, distribution and generation, electric power quality, education, energy development, competition and regulation, power electronics, communication, electric machinery, power engineering systems, protection, reliability and security, energy management systems and supervisory control, economics, dispatching and scheduling, energy systems modelling and simulation, alternative energy sources, policy and planning.