考虑用户调节行为多样性的空调负荷聚合商日前调度策略

Day ahead scheduling strategy for air conditioning load aggregators considering user regulation behavior diversity

空调负荷作为重要的柔性负荷资源之一,通过负荷聚合商参与电网调控,对改善夏季电网的负荷特性具有重要意义。然而聚合商通过分组控制方式无法最大化地利用空调的可调潜力,并且对用户舒适度有一定影响。从负荷聚合商的角度出发,对用户空调负荷分别采用温度设定值控制,以保持用户调节行为的多样性。在最大化挖掘负荷可调潜力的同时保证用户舒适度,提出了一种基于用户空调负荷温度控制的负荷聚合商日前调度双层优化模型。模型上层以负荷聚合商利益最大为优化目标,下层考虑用户舒适度差异以用户整体不舒适度水平最小为优化目标。采用粒子群整数规划算法进行求解获得单台空调设备设定温度的调节量。通过仿真验证表明,所提日前调度策略可以在给电网提供一定削峰能力的同时,充分挖掘空调负荷的可调潜力,保证负荷聚合商获得最大化利益并且用户舒适度水平更高。

As one of the important flexible load resources,air conditioning participates in power grid regulation through load aggregators.This is of significance in improving the load characteristics of a power grid in summer.However,aggregators cannot maximize the adjustable potential of air conditioning through group control,and it has a certain impact on user comfort.From the point of view of load aggregators,the temperature setting values are used to control the user air conditioning load in order to maintain the diversity of user regulation behavior.In order to maximize the potential of load adjustment while ensuring user comfort,a two-level optimization model of day ahead scheduling for load aggregators based on user air conditioning load temperature control is proposed.The upper layer of the model takes the maximum benefit of the load aggregator as the optimization objective,and the lower layer considers the difference of user comfort and the minimum level of overall user discomfort as the optimization objective.The particle swarm integer programming algorithm is used to obtain the adjustment of the set temperature of a single piece of air conditioning equipment.The simulation results show that the day ahead scheduling strategy can provide certain peak clipping capability to the power grid while fully tapping the adjustable potential of the air-conditioning load to ensure that the load aggregator obtains the maximum benefit and the user comfort level is higher.