引用本文: | 康健,靳斌,段秀娟,等.基于贝叶斯-粒子群算法的微电网优化运行[J].电力系统保护与控制,2018,46(12):32-41.[点击复制] |
KANG Jian,JIN Bin,DUAN Xiujuan,et al.Optimal operation of microgrid based on Bayesian-PSO algorithm[J].Power System Protection and Control,2018,46(12):32-41[点击复制] |
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摘要: |
针对目前微网调度难于全局最优收敛的问题,从概率网络的角度出发,将贝叶斯网络(Bayesian Network, BN)理论与粒子群算法(Particle Swarm Optimization, PSO)相结合,提出了基于贝叶斯-粒子群算法(BN-PSO)的微电网优化运行新策略。首先建立了微网数学模型和系统约束条件,考虑风能和光伏系统的概率分布情况,引入可再生因子和单位电力生产成本,以实现微网系统满足节能减排条件下的总费用最低的优化目标。最后以一个典型的微网系统进行算例仿真分析。结果表明:BN-PSO算法能有效解决包含随机概率事件的新能源微网优化运行问题,是解决此类问题的一个新思路;与目前的主流算法相比,BN-PSO算法能克服局部最优的缺陷,实现快速收敛。 |
关键词: 微电网 贝叶斯网络 粒子群算法 优化运行 概率分布 |
DOI:10.7667/PSPC170847 |
投稿时间:2017-06-07修订日期:2017-07-20 |
基金项目:教育部“春晖计划”(Z2014076) |
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Optimal operation of microgrid based on Bayesian-PSO algorithm |
KANG Jian,JIN Bin,DUAN Xiujuan,SHANG Xiaohua,LI Wei |
(School of Electric Engineering and Electronic Information, Xihua University, Chengdu 610039, China) |
Abstract: |
Aiming at the problem that the global optimal of the day-ahead schedule for micro-grid is hard to convergence, a new optimal operation of micro-grid based on Bayesian and PSO algorithm is proposed, which combines the Bayesian Network (BN) theory with the Particle Swarm Optimization (PSO) algorithm from the perspective of probability network. Initially, the mathematical models of microgrid and the system constraints are established by considering the probability distribution of wind power and PV system, then the renewable factor and unit power production costs are introduced to achieve the optimization goal which contains the lowest total cost under the condition of energy conservation and emissions reduction. Finally, the simulation analysis comes from a typical microgrid system. The result shows that the BN-PSO algorithm can effectively solve the optimal operation problems of microgrid which includes random probability event, it’s a new way to solve such problems; when compared with the current mainstream algorithms, the BN-PSO algorithm can overcome the defect of local optimum and achieve convergence rapidly. This work is supported by the “Chunhui Plan” of Ministry of Education (No. Z2014076). |
Key words: microgrid Bayesian network particle swarm optimization optimal operation probability distribution |