General Solutions to Multi-objective Optimization of PMU Placement
- Resource Type
- Conference
- Authors
- Xiaomeng Bian; Jiaju Qiu
- Source
- 2006 6th World Congress on Intelligent Control and Automation Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on. 2:7641-7645 2006
- Subject
- Robotics and Control Systems
Computing and Processing
Phasor measurement units
Genetic mutations
Power system measurements
State estimation
Control systems
Genetic algorithms
Monitoring
Power system control
Power systems
Signal processing algorithms
optimal PMU placement
multi-objective optimization
SGA
stepwise mutation
- Language
PMUs can improve performances of monitored control systems in various fields of power system. Two general types of objective functions for Optimal PMU Placement (OPP) problems are proposed according to whether the PMU number is known or not. The first type can be solved with a Standard Genetic Algorithm (SGA) when all the schemes are collated and coded properly. Decided by both the PMU number and the installed sites, the second type has locally optimal solutions. The stepwise mutation Genetic Algorithm (SMGA) is proposed to get the globally optimal solution quickly. It will adjust both the manner and the probability of mutation to avoid the possible prematurity, once the PMU numbers of individuals in the population become too close. Both the general functions and the algorithms are compared and verified in a multipurpose example of IEEE 30-bus.