空间耦合粒子群优化算法及峰谷电价下IES-CCHP区域联合调度

综合能源系统中电力、天然气和热力系统之间的交互影响具有一定的相关性。考虑能源间转换关系以及系统对分时电价的响应,以最小化购售电计划交易成本、燃料成本和排放污染气体所产生的环境成本为目标,建立峰谷电价下冷热电联供(CCHP)系统区域联合环保经济调度模型。为解决粒子群优化算法求解模型时存在的优化效率低、易陷入局部最优、计算结果随机性强等问题,提出一种空间耦合粒子群优化算法。在粒子寻优多维参数空间上,通过引入耦合协调数学模型将各维参数有效耦合,从而使所有参数从总体上同时趋向最优解。仿真结果表明,相比经典粒子群优化算法和改进粒子群优化算法,空间耦合粒子群优化算法有较强的全局搜索能力和更可靠的优化计算结果;所提CCHP系统的联合调度模型能有效促进能源的高效利用、电力的经济调度和节能减排。

SC-PSO algorithm and IES-CCHP regional joint dispatch with TOU price

Since the interactions among electric power, gas and thermal system in IES(Integrated Energy System) appear certain interdependency, a regional joint environmental-economic dispatch model is established for the CCHP(Combined Cold Heat and Power) system with TOU(Time-Of-Use) electricity price, which considers the energy transform among different sources and the system response to TOU price, and takes the minimum total cost as its object, including electricity purchase/sale cost, fuel cost and environmental cost due to pollutant emission. Aiming at the low efficiency, local optimum and random calculative results of PSO(Particle Swarm Optimization) algorithm, the SC-PSO(Space-Coupling PSO) algorithm is proposed, which introduces the coupled coordination math model to the multi-dimensional parameter space of PSO algorithm to effectively couple the parameters in different dimensions for the global optimum of all parameters at the same time. Simulative results show that, compared with classic PSO algorithm and improved PSO algorithm, SC-PSO algorithm has better global searching ability and more reliable optimization results; the proposed joint dispatch model for CCHP system is effective in high-efficient energy-source utilization, economic power dispatch and pollutant emission reduction.