含运行协调性并改进差分进化算法的机组组合

Unit Commitment with Operation Coordination and Improved Differential Evolution Algorithm

为解决大规模风电并网后传统调度策略易致线路长时间重载运行问题,提出含运行协调性的多目标优化模型及采用含动态搜索空间的混沌多目标差分进化算法求解。对多目标差分进化算法与搜索空间的动态更新机制进行有机结合,将随机生成算法的初始种群改为采用改进Tent映射的混沌化初始种群来提高算法的寻优精度。IEEE 30节点算例结果表明,所提优化算法可提高帕累托前沿的收敛性与均匀性,所提优化模型可将调度运行和预想故障下满载、超载支路的负载率降低至安全运行范围内,满载支路的负载率由100%降低至65%以下,预想故障中超载支路的负载率由120%降低至80%以下,提高了系统安全运行水平。

To solve the problem of long-time heavy-load operation caused by traditional dispatching strategies after a large-scale wind power grid-connection,a multi-objective optimization model with operation coordination is proposed,which is further solved by a chaotic multi-objective differential evolution algorithm with dynamic search space.The multi-objective differential evolution algorithm is organically combined with the dynamic update mechanism of the search space,and the initial population of the random generation algorithm is changed to the chaotic initial population of improved Tent mapping to improve the optimization accuracy of the algorithm.The results of an IEEE 30-node numeri-cal example show that the proposed optimization algorithm can improve the convergence and uniformity of the Pareto front,and the corresponding optimization model can reduce the load rate of full-load and overload branches under the scheduled operation and expected failure to a safe operation range.Specifically,the load rate of the full-load branch is reduced from 100%to less than 65%,and that of the overload branch is reduced from 120%to less than 80%under expected fault,thus improving the safe operation of the system.