基于粒子群算法的发电机启停调度快速优化方法

Generator start-stop scheduling optimization method based on particle swarm algorithm

摘要

针对目前发电机启停调度难以适应新能源和负荷快速变化的问题，在常用的调度方案基础上，提出了一种以经济效益为目标，以系统安全稳定为约束的发电机启停优化调度模型，并引入粒子群算法，通过对模型进行线性化处理以减少求解所需时间，提高了求解效率。通过IEEE-30节点算例对提出的方法进行仿真验证，提出的发电机启停调度优化方法准确度和效率高。相比于目前发电机启停调度方法，该方法误差在5%以内，计算时间能够节省50%以上。

Abstract

In order to solve the problem of difficulty in adapting to renewable energy and rapid load changes in generator start-stop scheduling, a generator start-stop optimization scheduling model with economic benefits as the goal and system safety and stability as the constraint is proposed on the basis of commonly used scheduling schemes. Besides, the particle swarm algorithm is introduced to linearize the model to reduce the required solving time and improve the solving efficiency. The proposed method was simulated and verified by IEEE-30 node system under the condition that the system hot standby ratio was 60%, respectively. The proposed generator start-stop scheduling optimization method has high accuracy and efficiency. Compared with the current generator start-stop scheduling method, the method proposed has an error of less than 5% and can save more than 50% of calculation time.

关键词

粒子群算法 / 发电机启停顺序 / 潮流优化调度 / 直流法潮流计算 / 运行成本

Key words

particle swarm arithmetic / generator start-stop sequence / tide optimization scheduling / dc power flow calculation / operating costs

Author summay

康赫然(1989—), 男, 工程师, 博士, 主要从事电力系统规划研究。E-mail: [e-mail]

基金资助

国网内蒙古东部电力有限公司科技研发项目(526606230005)

国家自然科学基金项目(U22B20109)