A Decentralized Optimization Strategy for Distributed Generators Power Allocation in Microgrids Based on Load Demand–Power Generation Equivalent Forecasting
In order to guarantee the economic and reliable operation of renewable Distributed Generators (DGs) in microgrids, a decentralized optimization strategy for DGs power allocation is proposed in this paper. According to the method, all processes and parameters are designed in a fully distributed way....
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-02-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/13/3/648 |
| _version_ | 1811301094203064320 |
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| author | Shicong Zhang Zilong Yu Bowen Zhou Zhile Yang Dongsheng Yang |
| author_facet | Shicong Zhang Zilong Yu Bowen Zhou Zhile Yang Dongsheng Yang |
| author_sort | Shicong Zhang |
| collection | DOAJ |
| description | In order to guarantee the economic and reliable operation of renewable Distributed Generators (DGs) in microgrids, a decentralized optimization strategy for DGs power allocation is proposed in this paper. According to the method, all processes and parameters are designed in a fully distributed way. To achieve decentralization and to maintain the balance between power supply and load demand, a load demand−power generation equivalent forecasting method is proposed to improve the strategy through replacing information of load demand by predicted power output, which removes the load prediction center and load sensor devices. The data of historical power generation, which is used for prediction, has already satisfied the balance constraint between power supply and load demand. Therefore, when the balance between the real power output and the predicted power output is gained, the balance constraint of power supply and load demand is achieved. Meanwhile, the uncertainty and forecasting errors of renewable generation are taken into account in the cost functions to optimize the expense of DG operation comprehensively. Then, the proposed algorithm is expounded in detail and the convergence is proved by eigenvalue perturbation theory. Finally, various cases are simulated to verify the accuracy and effectiveness of the proposed method. In summary, the proposed method are effective tools for DGs economic power allocation and the decentralization of microgrid system. |
| first_indexed | 2024-04-13T07:01:28Z |
| format | Article |
| id | doaj.art-df5dcf39ccff4607951c58e5b28a94a5 |
| institution | Directory Open Access Journal |
| issn | 1996-1073 |
| language | English |
| last_indexed | 2024-04-13T07:01:28Z |
| publishDate | 2020-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj.art-df5dcf39ccff4607951c58e5b28a94a52022-12-22T02:57:06ZengMDPI AGEnergies1996-10732020-02-0113364810.3390/en13030648en13030648A Decentralized Optimization Strategy for Distributed Generators Power Allocation in Microgrids Based on Load Demand–Power Generation Equivalent ForecastingShicong Zhang0Zilong Yu1Bowen Zhou2Zhile Yang3Dongsheng Yang4College of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaThe University of Sydney, Sydney 2008, AustraliaCollege of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaShenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, ChinaCollege of Information Science and Engineering, Northeastern University, Shenyang 110819, ChinaIn order to guarantee the economic and reliable operation of renewable Distributed Generators (DGs) in microgrids, a decentralized optimization strategy for DGs power allocation is proposed in this paper. According to the method, all processes and parameters are designed in a fully distributed way. To achieve decentralization and to maintain the balance between power supply and load demand, a load demand−power generation equivalent forecasting method is proposed to improve the strategy through replacing information of load demand by predicted power output, which removes the load prediction center and load sensor devices. The data of historical power generation, which is used for prediction, has already satisfied the balance constraint between power supply and load demand. Therefore, when the balance between the real power output and the predicted power output is gained, the balance constraint of power supply and load demand is achieved. Meanwhile, the uncertainty and forecasting errors of renewable generation are taken into account in the cost functions to optimize the expense of DG operation comprehensively. Then, the proposed algorithm is expounded in detail and the convergence is proved by eigenvalue perturbation theory. Finally, various cases are simulated to verify the accuracy and effectiveness of the proposed method. In summary, the proposed method are effective tools for DGs economic power allocation and the decentralization of microgrid system.https://www.mdpi.com/1996-1073/13/3/648microgriddecentralizationequivalent forecastingconsensusoptimization |
| spellingShingle | Shicong Zhang Zilong Yu Bowen Zhou Zhile Yang Dongsheng Yang A Decentralized Optimization Strategy for Distributed Generators Power Allocation in Microgrids Based on Load Demand–Power Generation Equivalent Forecasting Energies microgrid decentralization equivalent forecasting consensus optimization |
| title | A Decentralized Optimization Strategy for Distributed Generators Power Allocation in Microgrids Based on Load Demand–Power Generation Equivalent Forecasting |
| title_full | A Decentralized Optimization Strategy for Distributed Generators Power Allocation in Microgrids Based on Load Demand–Power Generation Equivalent Forecasting |
| title_fullStr | A Decentralized Optimization Strategy for Distributed Generators Power Allocation in Microgrids Based on Load Demand–Power Generation Equivalent Forecasting |
| title_full_unstemmed | A Decentralized Optimization Strategy for Distributed Generators Power Allocation in Microgrids Based on Load Demand–Power Generation Equivalent Forecasting |
| title_short | A Decentralized Optimization Strategy for Distributed Generators Power Allocation in Microgrids Based on Load Demand–Power Generation Equivalent Forecasting |
| title_sort | decentralized optimization strategy for distributed generators power allocation in microgrids based on load demand power generation equivalent forecasting |
| topic | microgrid decentralization equivalent forecasting consensus optimization |
| url | https://www.mdpi.com/1996-1073/13/3/648 |
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