考虑大规模风电接入的发电机组检修计划最小失负荷期望模型  

Generation maintenance scheduling based on minimum loss of load expectation considering significant wind power penetration

作　　者：王海彪[1] 郭瑞鹏[1] 姜忠民[2] 赵舫[1] 范长澜[3] 

机构地区：[1]浙江大学电气工程学院,浙江杭州310027 [2]东方电子集团有限公司,山东烟台264000 [3]上海市电力公司电力科学研究院设备状态评价中心,上海300433

出　　处：《电力系统保护与控制》2013年第4期26-32,共7页Power System Protection and Control

基　　金：国家863高技术基金项目(2011AA05A118)~~

摘　　要：风电出力的随机性和不稳定性对系统安全带来巨大压力。针对由于风电出力的随机性可能导致系统在不合理机组检修计划下出现备用不足的情况,采用基于风电概率分布的机组检修计划最小失负荷期望模型。通过考虑发电机组随机停运下可能产生的失负荷期望值对机组检修计划进行合理优化,减小甚至消除产生失负荷的可能性,保障系统安全运行。针对所采用的机组检修计划模型,提出了新型高效0-1问题粒子群算法。在IEEERTS-96系统中的验证结果表明该模型与新型粒子群算法可行有效。The randomness and instability of wind power have brought huge pressure to system security. The randomness of wind power may lead to reserve shortage under unreasonable unit maintenance scheduling. This paper introduces a unit maintenance scheduling model to minimize expected loss of load based on wind power probability distribution. Unit maintenance scheduling is reasonably optimized by considering the expected loss of load with respect to random outage of generators, so that the expected loss of load can be decreased or even eliminated to guarantee the safe operation of system. A novel efficient 0-1 particle swarm optimization algorithm is described. Simulation results on IEEE RTS-96 system show the feasibility of the proposed model and the efficiency of the proposed particle swarm optimization algorithm. This work is supported by National High-tech R＆D Program of China （863 Program） （No. 2011AA05A118）.

关 键 词：失负荷期望 机组检修计划 大规模风电接入 粒子群算法 WEIBULL分布 

分 类 号：TM714[电气工程—电力系统及自动化] TM614