基于置信间隙决策的综合能源系统鲁棒优化调度

Robust Optimal Dispatching of Integrated Energy System Based on Confidence Gap Decision

为实现具有鲁棒性的综合能源系统优化调度,该文通过将高斯混合概率模型置信区间与信息间隙决策理论(information gap decision theory,IGDT)的鲁棒思想结合起来,提出新的基于鲁棒驱动的置信间隙决策理论,并以㶲效率最大和运行成本最低为优化目标,构建基于置信间隙决策的综合能源系统多目标鲁棒优化调度模型;然后根据不确定性理论将模型中的机会约束转化为等效确定性约束;并设计一种新型的自适应谐波混叠多目标复合微分进化算法对模型进行高效求解。所提出的置信间隙决策模型不仅可降低常规鲁棒决策的保守性,同时也克服IGDT模型中不确定集合的粗略性和目标偏差因子的主观性,从而可实现更为合理而准确的不确定性优化调度。最后,通过算例分析验证所提方法的有效性和优越性。

In order to achieve the robust optimal dispatching of integrated energy system,a new confidence gap decision(CGD)theory based on robust driving was proposed in this paper by combining the confidence interval of Gaussian mixed probability model with the robust idea of information gap decision theory(IGDT).Considering the comprehensive optimization objectives of maximizing exergy efficiency and minimizing operating cost,a multi-objective robust optimization dispatching model of integrated energy system based on CGD was established.Moreover,the chance constraints in CGD model were transformed into equivalent deterministic constraints according to uncertainty theory,and a new adaptive harmonic aliasing multi-objective compound differential evolution algorithm was designed to solve the model efficiently.The proposed CGD model can not only reduce the conservativeness of conventional robust decision,but also overcomes the roughness of uncertain set and the subjectivity of objective deviation factor in IGDT model,so that a more reasonable and accurate uncertainty optimization dispatching could be achieved.Finally,the effectiveness and superiority of the proposed method are verified by example analysis.