基于差分进化算法的分布式能源系统 多目标优化

为了避免传统分布式冷热电三联供系统设计中偏离实际工况、负荷率偏低、效率低下等问题，本文以某商务区为对象，将分布式能源系统设备容量的最优化问题转化为以年总成本和年排放量综合最低的多目标数学模型，在对比多种常见智能算法后，选择具有强大全局巡优能力的差分进化算法进行求解，获得优化配置方案。分布式能源系统设备类型较多，且影响因素繁杂，各种设备的容量配置是整个系统运行效益好坏的关键。计算结果表明，与冷热电分供能系统进行对比，通过差分进化算法进行最优化配置后的分布式能源系统具有显著的优越性和可行性，系统结构设计、能源价格，均会对系统最优化结果产生影响。

Multi-Objective Optimization Based on Differential Evolution Algorithm for Distributed Energy System

In order to avoid deviating from actual conditions, low load rate and inefficiency in the design of traditional distributed CCHP system, this paper takes a business district as an object, transforms the optimization problem of equipment capacity of distributed energy system into a multi-objective mathematical model with the lowest comprehensive annual total cost and annual emissions. After comparing several common intelligent algorithms, it chooses a powerful and complete model. Differential Evolutionary Algorithms (DEA) with local patrol capability were used to solve the problem and obtain the optimal allocation scheme. There are many types of equipment in distributed energy system, and the influencing factors are complex. The capacity allocation of various equipment is the key to the operation efficiency of the whole system. The calculation results show that the distributed energy system optimized by differential evolution algorithm has remarkable advantages and feasibility compared with the cold, heat and power supply system. The system structure design and energy price will have an impact on the system optimization results.