基于改进GA-PSO算法的孤立微网日前经济调度
摘要：针对孤立微网中电源、负荷类型较多,日前调度复杂且较难收敛于全局最优解的问题,采用粒子群遗传混合算法(GA-PSO)求解这一混合整数非线性(MINL)问题。首先建立了孤立微网内微型燃气轮机、蓄电池和各种负荷的调度模型及日前调度的目标函数。对蓄电池放电深度模型进行了改进,以更合理地描述其充放电成本;按补偿合同对负荷直接调度;在保证可靠性的前提下,考虑微网运行成本,以微网运行收益最大为目标建立了目标函数。其次提出了新的粒子群遗传混合算法,最后采用该算法针对一个微网算例进行仿真验证,结果表明该算法能有效解决混合整数非线性规划问题。该方法对多时段、多种单元混合的微网优化调度,能够快速收敛。
Abstract:As to the problem that the global optimal solution of the day-ahead schedule is complex and hard to convergence for isolated microgrid that includes many types of power supplies and loads, the particle swarm optimization combined with genetic algorithm (GA-PSO) is adopted to solve this mixed-integer nonlinear problem. Initially, the day-ahead scheduling objective function and the scheduling models of micro turbine, battery and all kinds of loads are built, in which the battery discharge depth model is modified to describe the charging and discharging cost of battery more reasonably. Then loads are directly scheduled according to the compensation contract. By considering the operation cost of microgrid, the objective function is built to maximize the operation benefits of the microgrid on the premise of guaranteeing reliability. Then a new GA-PSO method is proposed, and it is verified through a microgrid example. The result shows that the day-ahead schedule problem can be solved effectively by using the proposed algorithm. In addition, this method acquires a quick convergence as to scheduling optimization of microgrid that includes multiple periods and multiple hybrid units.
标题：基于改进GA-PSO算法的孤立微网日前经济调度
英文标题：GA-PSO Algorithm Based Day-ahead Economic Schedule for Isolated Microgrid
作者：朱晓荣, 刘冠强,
关键词：粒子群遗传混合算法(GA-PSO), 日前调度, 孤立微网, 蓄电池充放电成本,
发表日期：2017-02-09
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- 1.27 MB
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