摘要
针对传统无功补偿配置方法受人工经验影响或存在收敛性问题的缺陷,提出了一种基于多背包问题求解的电网无功补偿配置方案,首先计算各变电站的无功缺额,再将无功平衡过程抽象为多背包问题的求解,无功富余的变电站作为背包、无功存在缺额的变电站作为物品,以背包所装物品价值最大为目标,采用遗传算法求得最优解,并解码得无功平衡结果。最后针对平衡后仍存在无功缺额的变电站,根据就近归整的原则进行无功补偿增配。本文首次将多背包组合优化求解引入到电网的无功补偿配置分析中,并采用智能算法提高了无功平衡的分析效率,降低了无功规划的工作量。算例分析验证了本方案可行有效,对电网无功优化管理具有参考和应用价值。
As for the fact that random factors or convergence problem in the traditional reactive power compensation,a kind of compensation scheme based on multi knapsack problem is proposed in this paper. Firstly, reactive power deficiency of each substation is calculated, then, the reactive power balance progress is abstracted out as a multi knapsack problem. In that way,the substation with and without extra reactive power is defined as knapsacks and subjects respectively. The optimal solution is obtained by way of genetic algorithm and the reactive power balance result is obtained by way of decoding. Finally, as for the substations still having reactive power deficiency after balance,the reactive power compensation supplementation is made as per the principle of handy regression. In this paper,the multi knapsack comb- inatorial optimization problem is introduced into reactive power compensation analysis for the first time, and intelligent algorithm is used to increase analysis efficiency of reactive power balance and reduce the workload of reactive planning. It is verified by calculation analysis that this solution is feasible and has reference and application value for the reactive optimization management of grid.
出处
《电力电容器与无功补偿》
北大核心
2016年第5期98-102,共5页
Power Capacitor & Reactive Power Compensation
关键词
多背包问题
无功补偿配置
遗传算法
multi knapsack problem
reactive power compensation
genetic algorithm
