基于蝙蝠算法的电力恢复机组选择多目标优化  

Multi-objective optimal strategy for units start-up during power system restoration based on bat algorithm

作　　者：裴文杰[1] 汪沨[1] 谭阳红[1] 尹健[1] 蒋勤稷 PEI Wenjie;WANG Feng;TAN Yanghong;YIN Jian;JIANG Qinji(College of Electrical and Information Engineering, Hunan University, Changsha 410082, China)

机构地区：[1]湖南大学电气与信息工程学院,长沙410082

出　　处：《计算机工程与应用》2017年第2期225-230,252,共7页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61102039;No.51107034);高等学校博士学科点专项科研基金资助课题(No.20120161110009);湖南省自然科学基金(No.14JJ7029);中央高校基金和湖南省教改课题

摘　　要：目前电力系统恢复机组选择的优化目标通常单一地追求发电量最大,忽视系统的安全稳定运行、机组重要性与恢复机组在系统的全局分布情况。在实际情况下尚不足以保证电力系统恢复的可靠与高效地进行。通过建立联合考虑电压相关安全指标、机组重要性与最大发电量的目标函数,将优化问题抽象为一个多目标组合优化背包问题。通过一定约束条件进行机组预选之后,由蝙蝠算法求解出优化模型的Pareto最优解集。通过算例进行仿真建模与其他算法进行多方面对比后,验证说明了蝙蝠算法在解决此多目标决策问题上的合理性与有效性。The current optimal goal for units start-up during power system restoration is usually a single pursuit, which ignores the safe and stable operation of the system, the importance and distribution of the units. That’s still not enough to ensure a reliable and effective power system restoration in the actual situation. Through establishing the objective function of combination of voltage safety index, importance of unit and unit generating capacity, the optimization problem can be abstracted as a multi-objective combinatorial optimization knapsack problem. After the unit preliminary election by constraint condition, it can solve out the optimization model Pareto optimal solution set by the bat algorithm. Through the example simulation in many aspects compared with other algorithms, it can illustrate the rationality and validity of bat algorithm on solving the multi-objective decision problem.

关 键 词：电力恢复 黑启动 电压稳定指标 多目标优化 蝙蝠算法 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]