Mixed-integer second-order cone programming method for active distribution network
Developing a novel type of power system is an important means of achieving the “dual carbon” goals of achieving peak carbon emissions and carbon neutrality in the near future. Given that the distribution network has access to a wide range of distributed and flexible resources, reasonably controlling...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-08-01
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| Series: | Frontiers in Energy Research |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fenrg.2023.1259445/full |
| _version_ | 1797737659053899776 |
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| author | Dai Wan Dai Wan Miao Zhao Zimu Yi Fei Jiang Qi Guo Qianfan Zhou |
| author_facet | Dai Wan Dai Wan Miao Zhao Zimu Yi Fei Jiang Qi Guo Qianfan Zhou |
| author_sort | Dai Wan |
| collection | DOAJ |
| description | Developing a novel type of power system is an important means of achieving the “dual carbon” goals of achieving peak carbon emissions and carbon neutrality in the near future. Given that the distribution network has access to a wide range of distributed and flexible resources, reasonably controlling large-scale and adjustable resources is a critical factor influencing the safe and stable operation of the active distribution network (ADN). In light of this, the authors of this study propose a mixed-integer second-order cone programming method for an active distribution network by considering the collaboration between distributed, flexible resources. First, Monte Carlo sampling is used to simulate the charging load of electric vehicles (EVs), and the auto regressive moving average (ARMA) and the scenario reduction algorithms (SRA) based on probability distance are used to generate scenarios of the outputs of distributed generation (DG). Second, we establish an economical, low-carbon model to optimize the operation of the active distribution network to reduce its operating costs and carbon emissions by considering the adjustable characteristics of the distributed and flexible resources, such as on-load tap changer (OLTC), devices for reactive power compensation, and EVs and electric energy storage equipment (EES). Then, the proposed model is transformed into a mixed-integer second-order cone programming (SOCP) model with a convex feasible domain by using second-order cone relaxation (SOCR), and is solved by using the CPLEX commercial solver. Finally, we performed an arithmetic analysis on the improved IEEE 33-node power distribution system, the results show that ADN’s day-to-day operating costs were reduced by 47.9% year-on-year, and carbon emissions were reduced by 75.2% year-on-year. The method proposed in this paper has significant effects in reducing the operating cost and carbon emissions of ADNs, as well as reducing the amplitude of ADN node voltages and branch currents. |
| first_indexed | 2024-03-12T13:31:38Z |
| format | Article |
| id | doaj.art-993d9f1f9c954af48f0aebc8cb04a812 |
| institution | Directory Open Access Journal |
| issn | 2296-598X |
| language | English |
| last_indexed | 2024-03-12T13:31:38Z |
| publishDate | 2023-08-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Energy Research |
| spelling | doaj.art-993d9f1f9c954af48f0aebc8cb04a8122023-08-24T10:41:44ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2023-08-011110.3389/fenrg.2023.12594451259445Mixed-integer second-order cone programming method for active distribution networkDai Wan0Dai Wan1Miao Zhao2Zimu Yi3Fei Jiang4Qi Guo5Qianfan Zhou6State Grid Hunan Electric Power Company Limited Research Institute, Changsha, ChinaState Grid Joint Laboratory for Intelligent Application and Key Equipment in Distribution Network, Changsha, ChinaState Grid Hunan Electric Power Company Limited Research Institute, Changsha, ChinaCollege of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, ChinaCollege of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha, ChinaCollege of Electrical and Information Engineering, Hunan University, Changsha, ChinaState Grid Hunan Electric Power Company Limited Research Institute, Changsha, ChinaDeveloping a novel type of power system is an important means of achieving the “dual carbon” goals of achieving peak carbon emissions and carbon neutrality in the near future. Given that the distribution network has access to a wide range of distributed and flexible resources, reasonably controlling large-scale and adjustable resources is a critical factor influencing the safe and stable operation of the active distribution network (ADN). In light of this, the authors of this study propose a mixed-integer second-order cone programming method for an active distribution network by considering the collaboration between distributed, flexible resources. First, Monte Carlo sampling is used to simulate the charging load of electric vehicles (EVs), and the auto regressive moving average (ARMA) and the scenario reduction algorithms (SRA) based on probability distance are used to generate scenarios of the outputs of distributed generation (DG). Second, we establish an economical, low-carbon model to optimize the operation of the active distribution network to reduce its operating costs and carbon emissions by considering the adjustable characteristics of the distributed and flexible resources, such as on-load tap changer (OLTC), devices for reactive power compensation, and EVs and electric energy storage equipment (EES). Then, the proposed model is transformed into a mixed-integer second-order cone programming (SOCP) model with a convex feasible domain by using second-order cone relaxation (SOCR), and is solved by using the CPLEX commercial solver. Finally, we performed an arithmetic analysis on the improved IEEE 33-node power distribution system, the results show that ADN’s day-to-day operating costs were reduced by 47.9% year-on-year, and carbon emissions were reduced by 75.2% year-on-year. The method proposed in this paper has significant effects in reducing the operating cost and carbon emissions of ADNs, as well as reducing the amplitude of ADN node voltages and branch currents.https://www.frontiersin.org/articles/10.3389/fenrg.2023.1259445/fulldistributed flexible resourceactive distribution networkcollaborative optimizationlow-carbon economysecond-order cone relaxation |
| spellingShingle | Dai Wan Dai Wan Miao Zhao Zimu Yi Fei Jiang Qi Guo Qianfan Zhou Mixed-integer second-order cone programming method for active distribution network Frontiers in Energy Research distributed flexible resource active distribution network collaborative optimization low-carbon economy second-order cone relaxation |
| title | Mixed-integer second-order cone programming method for active distribution network |
| title_full | Mixed-integer second-order cone programming method for active distribution network |
| title_fullStr | Mixed-integer second-order cone programming method for active distribution network |
| title_full_unstemmed | Mixed-integer second-order cone programming method for active distribution network |
| title_short | Mixed-integer second-order cone programming method for active distribution network |
| title_sort | mixed integer second order cone programming method for active distribution network |
| topic | distributed flexible resource active distribution network collaborative optimization low-carbon economy second-order cone relaxation |
| url | https://www.frontiersin.org/articles/10.3389/fenrg.2023.1259445/full |
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