Two-Layer Control Framework and Aggregation Response Potential Evaluation of Air Conditioning Load Considering Multiple Factors


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Air conditioning load has become a crucial demand response resource in power systems. However, due to its diversity in types and decentralized integration, the dispatch center faces challenges in directly accessing its aggregated power and conducting scheduling control, limiting the full potential of its response. To address this issue, this paper proposes a dual-layer control framework that combines multiple types of resources, considering the aggregation response potential of air conditioning load, and integrates precise control into the scheduling process. In the day-ahead scheduling layer, an approximate aggregation model is used to determine the aggregated power of air conditioning load. Considering factors such as user thermal comfort, willingness, and controllability, an evaluation model for air conditioning load aggregation response potential is established. This model, combined with the response characteristics of fundamental flexible loads, constitutes a unified scheduling model, effectively leveraging the potential of various demand-side resources in system regulation. In the intra-day control layer, to tackle the power drop phenomenon in air conditioning groups during load reduction and temperature control strategy execution, a variable-state queuing model is introduced. By introducing preparation time, heterogeneous air conditioning clusters are grouped for controlled operation, ensuring that air conditioning load follows the scheduling plan. This enhances control precision and mitigates the impact of power drops on system operation. Lastly, based on simulation analysis of a simplified distribution network system, the results indicate that the proposed two-layer control framework can effectively harness and direct the utilization of air conditioning load response potential at the scheduling layer. At the control layer, it achieves precise control and mitigates the negative effects of power drops, demonstrating substantial practical value in engineering applications.
Air conditioning,Atmospheric modeling,Load modeling,Regulation,Mathematical models,Controllability,Water heating,Queueing analysis,Power systems,Demand response,Air conditioning load,aggregation model,response potential,status queuing,preparation time,packet control
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