基于信息间隙决策理论的微电网多目标鲁棒优化调度

Multi-Objective Robust Optimal Scheduling of Micro Grid Based on IGDT

针对预测技术难以准确获取实际的可再生能源出力和负荷大小,其随机性影响微电网控制策略及用户经济性的问题,基于含光伏系统、储能系统和负荷的并网型微电网,考虑分时电价和需量管理,以用户日电费成本最低为目标函数,建立一种需量管理捆绑峰谷套利的微电网日前优化调度模型。基于该模型,计及光伏出力和负荷的波动性,提出基于信息间隙决策理论(Information Gap Decision Theory,IGDT)的微电网多目标鲁棒优化调度模型,制订具有鲁棒性的调度方案,并研究预设目标成本与光伏出力及负荷波动区间的定量关系。利用ε-约束方法刻画多目标问题的Pareto有效前沿,运用模糊满意度理论确定Pareto解集中的折中解,为运行人员提供合理的鲁棒决策方案。通过对某工业微电网进行仿真,并与蒙特卡洛法对比分析,验证了所建模型的可行性和有效性。

It is difficult to accurately obtain the renewable energy output and load based on the prediction technology. The randomness has a profound impact on the control strategy of micro-grid and the economy of users. For the grid connected micro-grid with photovoltaic system, energy storage system and load, a micro-grid day-ahead optimal scheduling model with demand management and bundled with peak-valley arbitrage is established, the objective function of which is the lowest daily electricity payment. Based on this model, taking into account the fluctuation of photovoltaic output and load, a multiobjective robust optimal scheduling model of micro-grid based on information gap decision theory(IGDT) is proposed to provide robust strategies, and study the quantitative relationship between preset target cost and photovoltaic output and load fluctuation range. The ε-constraint method is proposed to depict Pareto efficient frontier of multi-objective problem. Besides,the fuzzy satisfaction theory is used to determine the compromise solution of Pareto solution set, which provides a reasonable decision-making basis for operators. Compared with Monte Carlo method, simulation results on the micro-grid in an industrial park verify that the proposed model is feasible and effective.