风电-光伏-光热联合发电系统的模糊多目标优化模型

为实现以风光为代表的高比例新能源在电力系统中的友好并网,集成风电场、光伏电站和光热电站为多电源系统,提出风电-光伏-光热联合发电系统的模糊多目标优化模型。利用含储热光热电站良好的可调度性与可控性,为系统提供旋转备用与爬坡支撑,削减风光出力随机性与不确定性,从而实现其削峰填谷功能。以系统并网效益最大和输出功率方差最小为目标建立优化模型,通过定义目标隶属度函数将确定性模型模糊化,并采用最大满意度指标法将多目标优化模型转化为单目标优化模型,利用基于差分进化的粒子群DE-PSO(particle swarm optimization based on differential evolution)算法进行求解。算例系统仿真结果表明:模糊多目标优化能充分利用光热电站优势实现整体运行效果最优,从而验证了所提优化运行模型的可行性和有效性。

Fuzzy Multi-objective Optimization Model of Wind-PV-CSP Hybrid Power Generation System

To realize the friendly integration of high proportion of new energy represented by wind and photovoltaic (PV) into the power system, wind farm, PV power station and concentrating solar power (CSP) plant are combined as a multi-power supply system, and a fuzzy multi-objective optimization model of wind-PV-CSP hybrid power generation system is proposed. The CSP plant with thermal storage has satisfying schedulability and controllability, and it can provide rotating standby and climbing support, and reduce the randomness and uncertainty in wind and PV output, thus realizing its peak-shaving function. An optimization model is built, which considers the maximum grid-connection benefit and minimum variance of output power. The deterministic model is fuzzified by defining a objective membership function, and the multi-objective optimization model is transformed into a single-objective one using the maximum satisfaction index method, which is further solved by the particle swarm optimization based on differential evolution (DE-PSO) algorithm. The simulation results of an example system show that the fuzzy multi-objective optimization can make full use of the advantages of the CSP plant to achieve the overall optimal operation effect, thereby verifying the feasibility and effectiveness of the proposed optimal operation model.