| 引用本文: | 吴大立,郑中祥,尹项根,王义凯,徐彪,庞帅.基于Petri网和多种群遗传算法的海洋核动力平台电力系统网络重构[J].电力自动化设备,2020,40(8): |
| WU Dali,ZHENG Zhongxiang,YIN Xianggen,WANG Yikai,XU Biao,PANG Shuai.Network reconstruction of offshore nuclear power platform power system based on Petri net and multi-population genetic algorithm[J].Electric Power Automation Equipment,2020,40(8): |
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| 基于Petri网和多种群遗传算法的海洋核动力平台电力系统网络重构 |
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吴大立1, 郑中祥1, 尹项根2,3, 王义凯2,3, 徐彪2,3, 庞帅2,3
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1.武汉第二船舶设计研究所，湖北 武汉 430064;2.华中科技大学 强电磁工程与新技术国家重点实验室，湖北 武汉 430074;3.华中科技大学 电力安全与高效湖北省重点实验室，湖北 武汉 430074
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| 摘要: |
| 针对现有海洋核动力平台电力系统网络重构方法中功率流分析复杂，且重构模型求解算法难以稳定收敛到全局最优解的问题，提出一种基于Petri网和多种群遗传算法的核动力平台电力系统网络重构方法。综合故障后负荷恢复量、开关操作代价和发电机运行效率指标建立系统网络重构目标函数；基于Petri网对系统进行拓扑建模，将储能装置等效为负值“负荷”，通过动态更新机制确定功率流分布；采用多种群遗传算法求解网络重构问题，获取满足系统约束的最佳开关状态组合方案。典型核动力平台电力系统算例表明，所提方法能有效防止算法局部收敛以及减少迭代次数，快速提供完备的系统重构方案。 |
| 关键词: 核动力平台电力系统 网络重构 Petri网 功率流分析 多种群遗传算法 |
| DOI：10.16081/j.epae.202007020 |
| 分类号:TM73 |
| 基金项目:国家重点研发计划资助项目(2017YFC0307800) |
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| Network reconstruction of offshore nuclear power platform power system based on Petri net and multi-population genetic algorithm |
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WU Dali1, ZHENG Zhongxiang1, YIN Xianggen2,3, WANG Yikai2,3, XU Biao2,3, PANG Shuai2,3
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1.Wuhan Second Ship Design and Research Institute, Wuhan 430064, China;2.State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074, China;3.Hubei Electric Power Security and High Efficiency Key Laboratory, Huazhong University of Science and Technology, Wuhan 430074, China
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| Abstract: |
| Aiming at the problem that the existing power flow analysis in network reconstruction method for offshore nuclear power platform power system is complex and the solving algorithm of the reconstruction model is hardly stably converged to the global optimal solution, a network reconstruction method based on Petri net and multi-population genetic algorithm is proposed for nuclear power platform power system. The indexes of load recovery amount after fault, switching operation cost, and generator operation efficiency are integrated to build the objective function of network reconstruction. The topological model of the system is built based on Petri net, in which, the energy storage device is equivalent to a negative load, and the power flow distribution is determined by dynamic update mechanism. Multi-population genetic algorithm is adopted to solve the network reconstruction problem, and the optimal switching state combination scheme satisfying system constraints is obtained. The example of a typical nuclear power platform power system shows that the proposed method can effectively prevent local convergence of the algorithm and reduce the iteration times, which provides complete reconstruction scheme quickly. |
| Key words: nuclear power platform power system network reconstruction Petri net power flow analysis multi-population genetic algorithm |
