Reactive Power Optimization Strategy of Power Grid Incorporating Renewable Energy Based on Interval Modeling
[Introduction] New energy power generation is intermittent and random, and its power is uncertain data, which will cause changes in grid voltage and frequency, thus pose a threat to the safe operation of the power system. In order to ensure the safety of grid voltage after large-scale new energy gri...
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| Format: | Article |
| Language: | English |
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Energy Observer Magazine Co., Ltd.
2021-12-01
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| Series: | 南方能源建设 |
| Subjects: | |
| Online Access: | https://www.energychina.press/en/article/doi/10.16516/j.gedi.issn2095-8676.2021.04.013 |
| _version_ | 1818966278606422016 |
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| author | WANG Zhongfu |
| author_facet | WANG Zhongfu |
| author_sort | WANG Zhongfu |
| collection | DOAJ |
| description | [Introduction] New energy power generation is intermittent and random, and its power is uncertain data, which will cause changes in grid voltage and frequency, thus pose a threat to the safe operation of the power system. In order to ensure the safety of grid voltage after large-scale new energy grid connection, considering the uncertainty of new energy generation, a reactive power optimization strategy of power grid incorporating renewable energy based on interval modeling is proposed. [Method] This strategy used interval to describe uncertain parameters in reactive power optimization model, and then established interval reactive power optimization model. The interval power flow algorithm based on optimization scenario was used to solve the interval power flow equation, thus obtaining the interval of state variables and determining the feasibility of control variables. On this basis, the improved particle swarm optimization algorithm was used to solve the interval reactive power optimization model, and the local search method and discrete variable cross-processing operation were added to the particle swarm optimization algorithm to improve optimization ability. In order to verify the effectiveness and superiority of the proposed method, IEEE 14 - bus and IEEE 30 - bus examples were used for simulation, and the proposed algorithm was compared with the adaptive genetic algorithm and the ordinary particle swarm optimization algorithm. [Result] The simulation results show that compared with adaptive genetic algorithm and ordinary particle swarm optimization algorithm, the improved particle swarm interval reactive power optimization strategy has a faster convergence speed, stronger optimization capabilities, and can effectively solve the discrete variables in the model. [Conclusion] Our data suggest that the proposed strategy can effectively solve the interval reactive power optimization problem and ensure the operation safety of grid voltage after large-scale new energy grid connection. |
| first_indexed | 2024-12-20T13:30:22Z |
| format | Article |
| id | doaj.art-347d60bd48f44e31be7ca9a49d84a27e |
| institution | Directory Open Access Journal |
| issn | 2095-8676 |
| language | English |
| last_indexed | 2024-12-20T13:30:22Z |
| publishDate | 2021-12-01 |
| publisher | Energy Observer Magazine Co., Ltd. |
| record_format | Article |
| series | 南方能源建设 |
| spelling | doaj.art-347d60bd48f44e31be7ca9a49d84a27e2022-12-21T19:39:07ZengEnergy Observer Magazine Co., Ltd.南方能源建设2095-86762021-12-01849510610.16516/j.gedi.issn2095-8676.2021.04.013Reactive Power Optimization Strategy of Power Grid Incorporating Renewable Energy Based on Interval ModelingWANG Zhongfu0China Energy Engineering Group Guangdong Electric Power Design Institute Co., Ltd., Guangzhou 510663, China[Introduction] New energy power generation is intermittent and random, and its power is uncertain data, which will cause changes in grid voltage and frequency, thus pose a threat to the safe operation of the power system. In order to ensure the safety of grid voltage after large-scale new energy grid connection, considering the uncertainty of new energy generation, a reactive power optimization strategy of power grid incorporating renewable energy based on interval modeling is proposed. [Method] This strategy used interval to describe uncertain parameters in reactive power optimization model, and then established interval reactive power optimization model. The interval power flow algorithm based on optimization scenario was used to solve the interval power flow equation, thus obtaining the interval of state variables and determining the feasibility of control variables. On this basis, the improved particle swarm optimization algorithm was used to solve the interval reactive power optimization model, and the local search method and discrete variable cross-processing operation were added to the particle swarm optimization algorithm to improve optimization ability. In order to verify the effectiveness and superiority of the proposed method, IEEE 14 - bus and IEEE 30 - bus examples were used for simulation, and the proposed algorithm was compared with the adaptive genetic algorithm and the ordinary particle swarm optimization algorithm. [Result] The simulation results show that compared with adaptive genetic algorithm and ordinary particle swarm optimization algorithm, the improved particle swarm interval reactive power optimization strategy has a faster convergence speed, stronger optimization capabilities, and can effectively solve the discrete variables in the model. [Conclusion] Our data suggest that the proposed strategy can effectively solve the interval reactive power optimization problem and ensure the operation safety of grid voltage after large-scale new energy grid connection.https://www.energychina.press/en/article/doi/10.16516/j.gedi.issn2095-8676.2021.04.013interval optimizationreactive voltage controlinterval power flowimproved particle swarm optimizationoptimized scenario method |
| spellingShingle | WANG Zhongfu Reactive Power Optimization Strategy of Power Grid Incorporating Renewable Energy Based on Interval Modeling 南方能源建设 interval optimization reactive voltage control interval power flow improved particle swarm optimization optimized scenario method |
| title | Reactive Power Optimization Strategy of Power Grid Incorporating Renewable Energy Based on Interval Modeling |
| title_full | Reactive Power Optimization Strategy of Power Grid Incorporating Renewable Energy Based on Interval Modeling |
| title_fullStr | Reactive Power Optimization Strategy of Power Grid Incorporating Renewable Energy Based on Interval Modeling |
| title_full_unstemmed | Reactive Power Optimization Strategy of Power Grid Incorporating Renewable Energy Based on Interval Modeling |
| title_short | Reactive Power Optimization Strategy of Power Grid Incorporating Renewable Energy Based on Interval Modeling |
| title_sort | reactive power optimization strategy of power grid incorporating renewable energy based on interval modeling |
| topic | interval optimization reactive voltage control interval power flow improved particle swarm optimization optimized scenario method |
| url | https://www.energychina.press/en/article/doi/10.16516/j.gedi.issn2095-8676.2021.04.013 |
| work_keys_str_mv | AT wangzhongfu reactivepoweroptimizationstrategyofpowergridincorporatingrenewableenergybasedonintervalmodeling |