基于自适应人工鱼群算法的大型光伏电站燃气轮机组的优化配置  

Adaptive Artificial Fish Swarm Algorithm Based Optimization Configuration of Gas Turbine Unit in Large-scale Photovoltaic Power Station

作　　者：李孝宇[1] 李涛[2] 李鹏[2] 张风棣 王飞[4] 

机构地区：[1]华北电力大学经济管理系,河北保定071000 [2]新能源电力系统国家重点实验室华北电力大学,河北保定071000 [3]东营供电公司,山东东营257091 [4]河北电力建设监理有限责任公司,河北石家庄050021

出　　处：《陕西电力》2013年第8期15-20,共6页Shanxi Electric Power

基　　金：国家自然科学基金项目(50977029);河北省自然科学基金项目(E2013502074)

摘　　要：采用改进人工鱼群算法求解大型光伏电站中燃气轮机组的优化配置问题,通过建立光/燃互补发电系统优化配置模型,解决了光伏发电随机性、间歇性导致的难以控制、难以调度的问题,以光燃互补发电系统的售电收益和燃气轮机组的投资成本、运行和维护成本、环境成本、燃料成本为基础的目标函数,在充分考虑多种约束的条件下实现了燃气轮机组的容量优化配置,有效平抑了光伏发电功率的波动。并针对美国某100 MW光伏电站进行仿真验证,验证了该方法的正确性和有效性。This paper carries out the optimal allocation of the gas turbine unit in the large-scale photovohaic power station by using adaptive artificial fish swarm algorithm, establishes the optimal allocation model for photovohaic/turbine complementary power generation system to solve the difficulty of control and dispatching caused by the randomness and intermittence of photovohaic generation. Objective function is composed by the gain from power selling of the complementary power generation system, Investment costs, operation cost, maintenance cost, environment cost and fuel cost of gas turbine units, in order to achieve the optimal configuration of the gas turbine unit capacity considering fully many constraints, and restrains power fluctuation of photovohaic generation effectively. Finally the paper carries out a simulation on a 100 MW photovohaic plant in America,and the results show that the correctness and validity of the model.

关 键 词：光 燃互补发电系统 燃气轮机组 优化配置 自适应人工鱼群算法 

分 类 号：TM611.24[电气工程—电力系统及自动化]