基于灰熵关联择优的含不确定性预算调节策略的微电网鲁棒调度

摘要

With the minimal operation cost,environmental cost and renewable energy fluctuations as objective,a dispatch model of microgrid is established,which takes the grey entropy relation degree as its evaluation criterion of optimal solutions.Aiming at the uncertainties of wind and photovoltaic power,uncertainty sets with predicted values as the center are constructed and the dispatch model is improved by robust optimum theory.Aiming at the problem that energy storage system easily reaches its limits in dispatch process,a strategy is proposed to estimate the uncertainty budget based on the operation state of energy storage.Examples are solved by the improved differential evolution algorithm,which adopts cloud model to increase its local search capability and chaos algorithm to improve its global search ability.The simulative results verify the feasibility of the proposed model and algorithm.The superiority of robust dispatch model is analyzed from aspects of the change of Pareto frontier and the characteristic values of optimal solution sets.The influences of uncertainty budget values in different scenarios on the dispatch of microgrid are discussed to verify that the uncertainty budget regulation strategy can effectively prevent the energy storage system from reaching its upper and lower limits,which further improves the robustness of the microgrid dispatch.%以运行成本、环境成本和可再生能源波动最小为目标,建立了以灰熵关联度为最优解评价标准的微电网调度模型.针对风光发电的不确定性,构造以预测值为中心的不确定性集,引入鲁棒优化理论改进调度模型.针对储能系统在调度过程中可能过早到达其限值的问题,提出了一种通过储能运行状态来估计风光发电不确定性预算的策略.采用改进微分进化算法对算例进行求解,该算法结合云模型增强其局部搜索能力,依据混沌算法提升其全局搜索能力.仿真结果验证了模型和算法的可行性,从Pareto前沿的变化与最优解集的特征值两方面分析了鲁棒调度模型的优越性;讨论了在不同场景下不确定性预算值对微电网调度的影响,并验证了不确定性预算调节策略能更有效地防止储能系统到达储能上下限,从而进一步提高微电网调度的鲁棒性.