激励条件下的大规模空调负荷聚合集群优化策略

Optimization strategies for large scale air conditioning load aggregation clusters under incentive conditions

中文关键词: 大规模空调  空调负荷集群  负荷聚合商  用户激励

英文关键词: large scale air conditioning  air conditioning load cluster  load aggregator  user incentives

中文摘要:

      为提高大规模空调负荷聚合精度、提升空调集群可调节潜力，提出了激励条件下的大规模空调负荷聚合集群优化策略。首先建立了大规模空调负荷聚合架构，然后建立单体的二阶空调等值热力参数模型，同时基于蒙特卡洛方法对不同区域的空调负荷进行二次聚合，建立用户满意度与激励水平之间的关系。在此基础上，以实际空调聚合功率与缺口负荷之间的标准差最小、空调负荷聚合商补偿费用最少为优化目标，采用粒子群算法进行求解，最后通过算例说明了本文所提策略的有效性。

英文摘要:

      In order to improve the accuracy of large-scale air conditioning load aggregation and enhance the adjustable potential of air conditioning clusters,an optimization strategy for large-scale air conditioning load aggregation clusters under incentive conditions is proposed.Firstly,a large-scale air conditioning load aggregation architecture is established. Secondly,a second-order equivalent thermal parameter model for individual air conditioners is established,and the air conditioning loads in different regions are secondary aggregated based on the Monte Carlo method. Meanwhile,the relationship between user satisfaction and incentive levels is established. On this basis,optimization objective is to minimize the standard deviation between actual air conditioning aggregated power and the gap load,and to minimize the compensation cost for the air conditioning load aggregator. Particle swarm optimization algorithm is used to solve the problem. Finally,effectiveness of the proposed strategy is demonstrated through numerical examples.