基于两阶段分层组合优化算法的电力系统机组组合

Unit combination of power system based on combinatorial optimization algorithm

机组组合是一个调度问题,由于机组状态(启动和停止)的二元决策变量的存在而变得复杂。因此,机组组合问题是一个大规模的非线性混合整数组合问题,传统的优化算法不适用于求解大型电力系统。针对大型电力系统机组组合求解速度慢的问题。本文以机组耗煤成本和启停成本最小为优化目标,并考虑线路安全能力等约束条件。首先采用转移因子法求解线路潮流约束,然后提出了非线性规划和遗传算法的两阶段分层优化模型。在某地的6机30节点大电力系统上进行了验证,算例结果表明,组合分层优化模型能有效降低算法复杂度,节省计算时间,具有较好的可行性和有效性。

Unit combination is a scheduling problem,and the existence of binary decision variables of unit state(start and stop)complicates the unit problem.Therefore,the unit combination problem is a large-scale nonlinear mixed integer combination problem,which is difficult to obtain the optimal solution.The conventional optimization algorithm is not suitable for large power system.In this paper,aiming at the problem of slow solving speed of unit combination in large power system,the optimization objective is to minimize the coal consumption cost and start-stop cost of the unit,and constraints such as line safety capacity are considered.Based on the above,the transfer factor method is used to solve the line power flow constraint,and a two-stage hierarchical optimization model of nonlinear programming and Genetic Algorithm is proposed.The simulation results show that the combined hierarchical optimization model could effectively reduce the algorithm complexity,save the calculation time,and has good feasibility and effectiveness.