摘要
以教与学优化算法(TLBO)解决在电力系统完全可观的条件下实现相量测量单元(PMU)下的配置问题。TLBO算法能够解决包含零注入量测和不包含零注入量测的PMU的优化配置。提出的算法在标准测试系统(如IEEE-14节点、IEEE-30节点和IEEE-57节点)中测试,测试的结果与其他算法(如遗传算法、二进制粒子群算法)进行比较。最后在量测配置使系统完全可观的情况下进行配电网的谐波状态估计,验证谐波状态估计的准确度,进而验证了该算法的有效性。
Teaching-learning-based optimization algorithm (TLBO) is presented for solving the problem of placement of phasor measurement units (PMU) optimally in a power system network for complete observability. The TLBO algorithm enables optimal PMU placement by zero injection measurements and also by not including zero injection measurements. The algorithm has been tested on standard test systems such as IEEE 14-bus, IEEE 30-bus, IEEE 57-bus and the results are contrasted with other optimization algorithms like genetic algorithm and binary PSO. Fin ally, the harmonic state estimation of distribution network is carried out under the condition that the measurement configuration makes the system completely observable. The accuracy of harmonic state estimation is verified, and the validity of the proposed algorithm is verified.
作者
李小东
景明玉
LI Xiaodong;JING Mingyu(School of Electrical Engineering and Information Engineering, Lanzhou University of Technology,Lanzhou 730050, China;State Grid Gansu Electric Power Company Qingyang Power Supply Company,Qingyang 745000, China)
出处
《电气应用》
2019年第6期89-94,共6页
Electrotechnical Application
基金
国家自然科学基金资助项目(51267012)
甘肃省自然科学基金资助项目(1308RJZA245)
关键词
相量量测单元
可观测性分析
教与学优化算法
谐波状态估计
量测误差
phasor measurement units
observable analysis
teaching-learning-based optimization algorithm
harmonic state estimation
measurement error
