摘要
关于微电网的优化配置问题,是在功率平衡等一系列约束的前提下,以投资成本、环境因素等为目标,优化配置微电网中各微电源的数量。微电网的优化配置是一个动态多维非线性优化问题,传统的优化算法收敛速度慢,容易陷入局部最优,而量子行为粒子群算法以其搜索能力强、收敛速度快和解的精度高等特点,可以很好的求解微电网的优化配置问题。以某地的气象和负荷数据为例,在满足用户的冷热电负荷需求前提下,求解微电网的配置。结果表明,采用量子行为粒子群算法,可以得到各微电源容量的最佳配比方案。
The optimization allocation of a micro -grid is to optimize the numbers of different kind of Micro power sources under a series of constraints such as power balance. Its objective function includes the investment and envi- ronment factors. Micro - grid optimization allocation problem is a dynamic multi - dimensional non - linear optimization problem. Conventional optimization is usually slow for convergence and easy goes to local optima when dealing with this issue. But Quantum - behaved Particle Swarm Optimization has the advantages of high searching ability, fast convergence and high precision solution. So it is better for solving the micro - grid optimization allocation prob- lem. Taking the practical meteorological and load data of an area as an example, to solve the optimal allocation of the micro - grid under the condition of meeting the need of the cool, heat and power load in the micro - grid. The simu- lation results show that the Quantum - behaved Particle Swarm Optimization can be used to solve the problem and finds out the scheme of optimal capacity allocation of the micro - grid sources.
出处
《计算机仿真》
CSCD
北大核心
2014年第8期120-124,208,共6页
Computer Simulation
基金
上海市科委项目资助(14ZR1400700)
