Abstract：Capacity allocation problem is one of key factor to influence the profitability of distributed energy system (DES) projects. This paper proposes a DES solutions that uses heat storage equipment to replace part of power equipments to reduce the capacity. The physical model and operation strategy of this system are transformed into mathematic model. A special heat and electricity loads are used as the calculation basis and the particle swarm optimization (PSO) is applied to calculate the capacities of power equipment and heat storage equipment with the maximum net present value as the goal. The result is validated by traversing method. It shows that the optimal capacity of power equipment is less than the maximum electricity load, and the system need to purchase electricity from power grid during the peak period of electrical load. However, most of time, the power unit has higher efficiency, because it works in rated condition or close to rated condition. The natural gas is expensive and it is uneconomical to burn gas for peak heating load. The optimal heat storage capacity configuration is to supplement the heating capacity in the cold period without gas combustion, only use heat storage equipment to meet the heating load demand exactly in freeze-up. That is, there is no configuration redundancy for heat storage equipment.
标题：基于粒子群算法的分布式能源系统容量优化配置
title:Optimization Allocation of Distributed Energy System Based on Particle Swarm Optimization Algorithm
作者：杨佳霖
authors:YANG Jialin
关键词：分布式能源,粒子群算法,容量配置优化,内燃机,储热,
keywords:distributed energy,particle swarm optimization algorithm,optimization allocation,internal-combustion engine,thermal energy storage,
