원문정보
초록
영어
A new strategy on reactive power optimization for power grid with wind farm integration is proposed. The mathematical model is built by using the optimal scenario analysis method and the modified particle swarm optimization algorithm (MPSO). The method about how to obtain the optimal scenarios is discussed. The optimal scenarios position for wind power is deduced based on the Wasserstein distance metric, and the occurrence probability is also studied simultaneously. In order to avoid falling into local optimum, the self-adapting mutagenic factor and mutation probability are designed in MPSO. Simulation examples show the effectiveness of MPSO. The mutagenic factor takes effect when the objective function value tends to be constant. Power loss and voltage stability margin are considered in the objective function. In initial phase of MPSO, the general particle swarm optimization algorithm (PSO) is processed, and this can guarantee the rapid convergence for the optimization procedure. After some iterations, the mutagenic factor begins to have an impact to ensure the global optimum can be obtained. The IEEE 69-bus distribution system is used to the experiment. In the experiment, the optimal scenarios position and scenario occurrence probability are worked out. Test results show that the new strategy is effective.
목차
1. Introduction
2. The Optimal Scenarios Division
2.1 The Method of Getting Optimal Scenario
2.2 The Optimal Scenario for Wind Power
3. The Modified Particle Swarm Optimization Algorithm (MPSO)
3.1. The Introduce of MPSO
3.2. The Simulation Examples for MPSO
4. The Mathematical Model for Reactive Power Optimization
4.1 The Objective Function
4.2 The Constraints
4.3 Coding Format
5. Experiment and Analysis
6. Conclusions
References
