基于粒子群算法的局域供能配比优化方法

Local energy supply ratio optimization method based on particle swarm optimization

针对现有的局域多能互补系统中供能设备种类多、系统结构复杂等原因导致的供能设备能源利用率低,以及多能互补系统整体运营效率低等问题。文中基于适用于园区的局域多能互补系统的典型结构,提出了一种供能配比优化模型,以局域多能互补系统中的电负荷、热负荷、冷负荷等多种能源需求作为约束条件,利用最小投资回收期、最大化投资净现值、最大化项目内部收益率作为目标建立模型,再通过粒子群算法对模型进行求解。仿真结果表明,该局域供能配比优化方法可以在满足园区内各种能源需求的前提下,有效提高能源利用率,并降低系统总成本。

Aiming at the problems of low energy efficiency of energy supply equipment and low overall operational efficiency of multi energy complementary systems due to various types of energy supply equipment and complex system structure in the existing local multi energy complementary system,based on the local area applicable to the park The typical structure of the multi energy complementary system proposes a power supply ratio optimization model,which takes the energy load,heat load,cold load and other energy requirements in the local multi energy complementary system as constraints,with a minimum investment payback period.The model maximizes the net present value of the investment,maximizes the internal rate of return of the project as the target,and then solves the model through the particle swarm optimization algorithm.The simulation results show that the local power supply ratio optimization method described in this paper can effectively improve energy efficiency and reduce total system cost while meeting various energy requirements in the park.