基于优先级队列的居民需求响应策略自趋优方法

Self-optimization method of resident demand responsestrategy based on priority queue

居民负荷是电网季节性尖峰负荷的重要构成之一,具有巨大的需求响应(DR)潜力,但其随机性和分散性也限制了其灵活参与DR互动的能力。针对居民负荷的特点及其响应行为的不确定性,文中以负荷曲线特征、历史DR参与情况和响应程度为参数建立居民负荷模型,并以实际居民数据集为依据辨识分布参数。此外,文中提出一种基于历史响应效果形成优先级队列的方法,并在此基础上建立居民DR成本模型,以成本最小化为目标得出最优居民DR策略,从而在精确达成负荷削减目标的前提下合理控制DR成本。优先级队列在多次DR事件中逐次更新修正,实现响应策略自趋优。最后通过算例验证了提出的居民负荷模型及居民DR策略自趋优方法的有效性。

Resident load is one of the important components of seasonal peak load and has huge demand response(DR)potential.But its randomness and decentralization limit the ability to flexibly participate in DR interactions.In view of the characteristics of resident load and the uncertainty of response behavior,the resident load model is established with the characteristics of load curve,historical DR participation and response degree as parameters.And the distribution parameters are identified through actual resident data sets.Furthermore,a method of forming a priority queue based on historical response effects is proposed.On this basis,the resident DR cost model is established,and the optimal resident DR strategy is obtained with the goal of cost minimization,so that the DR cost can be reasonably controlled under the premise of accurately achieving the load reduction target.The priority queue is updated and corrected successively in multiple DR events to realize automatic optimization of response strategies.Finally,the calculation example verifies the effectiveness of the proposed resident load model and the resident DR strategy self-optimization method.