Reserve Evaluation and Energy Management of Micro-grids in Joint Electricity Markets Based on Non-Intrusive Load Monitoring
Yuechuan Tao, Jing Qiu, Shuying Lai, Yunqi Wang, Xianzhuo Sun
Abstract
The heating, ventilation, and air-conditioning (HVAC) units are regarded as major demand response (DR) resources in micro-grids. However, due to privacy concerns and technical constraints, it is difficult for the system operator to obtain the complete information on each individual appliance. In this paper, we present a non-intrusive load monitoring (NILM) based framework for the operation strategy of the micro-grid in the joint energy, reserve, and regulation markets. The NILM technologies enable the operator to disaggregate the power of the HVAC units from the reading of the smart meters. Hence, the operation state of the appliances and the behavior of consumers can be studied without obtaining detailed data of each individual appliance. An advanced NILM algorithm is proposed, and the Coupled Generative Adversarial Networks (C-GAN) are utilized to enhance the generalizability of the trained model. Based on the NILM result, a novel method based on Hidden Markov Model (HMM) is proposed to evaluate the upward and downward reserve capacity of the HVAC units. The evaluated reserve capacity can help the operator better bid in the joint market based on the proposed optimization model. The proposed framework and methodology are verified through case studies. The simulation result reveals that with NILM, the market operator can save more energy consumption costs and load curtailment costs and earn more revenues in the joint market by selling excessive energy and providing ancillary services.