基于机会约束规划的风–火–蓄联合系统优化调度

Optimal Scheduling of Combined Wind-thermo-storage System Based on Chance Constrained Programming

针对由于风电的间歇性和波动性而导致的大量风能成为弃风从而极大地降低风电消纳的问题,首先根据日前调度周期内风电预测功率平均值建立抽水蓄能机组的运行状态模型;其次,利用置信水平分别对风蓄联合机组的并网功率以及抽水蓄能机组的抽水功率和发电功率进行约束,以风蓄联合机组的最大经济效益和风火蓄联合系统的最小成本为目标,构建基于可信性理论机会约束规划的风火蓄经济优化调度模型;然后将改进惯性权重后的粒子群算法和随机模拟技术相结合并应用在模型求解步骤中。仿真结果表明,所构建的优化调度模型能减小风电上网功率的间歇性和波动性,减少弃风量和增加风电上网经济效益,并减小整体系统的投资运行成本。

Intermittency and volatility of wind power may lead to curtailment of wind power,becoming a serious problem for wind power accommodation.Firstly,this paper establishes a operating state model of pumped-storage unit based on forecasted average wind power in a day-to-day scheduling period.Secondly,confidence level is used to constrain the grid-connected power of combined wind-storage unit and pumping or generating power of pumped-storage unit,considering the relevant constraints of wind turbine to predict generated power.Based on the maximum economic benefit of the wind-storage unit and the minimum cost of the combined system of wind,thermal and storage,a optimal model of wind-thermo-storage economy based on credibility theory and chance-constrained planning is constructed.Then,the improved particle swarm optimization(PSO)and stochastic simulation techniques are combined and applied to the model to improve convergence speed and accuracy of the algorithm.Simulation shows that the optimized scheduling model constructed in this paper can reduce impact of intermittency and volatility of wind power and the amount of abandoned wind,and increase economic benefit of integrated wind power.It also reduces coat of investment and operation of overall system.