Practical demand response potential evaluation of air-conditioning loads for aggregated customers

Abstract

The evaluation of demand response (DR) potential is of vital significance for evaluating the possible power reduction, forming constraints for optimal economic dispatching, and targeting appropriate customers effectively. To improve the applicability and reliability of DR of air conditioning loads (ACLs), this paper presents a novel approach of the DR potential for aggregated customers, considering both the performance of physical response and incentive effect. For physics-based part, in order to better reveal the multi-uncertainties and various conditions, a load decomposition methodology is proposed, which non-intrusively disaggregates the whole energy usage into baseload and ACLs. Subsequently, a segment analysis methodology, including a modified regression method and a PSO iteration method, are developed for the static and dynamic parameter estimation, respectively. For incentive-based part, the electricity elasticity of both the electricity price and incentive are considered to calculate the load difference after changes of electricity price and incentive, which better consider the actual response willingness and capacity of customers. Furthermore, case studies based on low voltage distribution area in Jiangsu province, China validate a better performance of accuracy and robustness using the proposed methods, which are further applied to DR implementation and the results strongly prove that much difference (a maximum of more than 400 kW) appears resulting from different operational conditions and DR strategies. By comparison, the practical DR potential is much affected by the incentive, rather than the physics, which mainly stimulates the customers’ intention. And the equilibrium can be achieved by choosing the optimal incentive price to stimulate greater potential and save the cost simultaneously.