Interactive Technology of Electrothermal Collaborative System Considering Demand Response Scenario

• Published in: 2022 8th International Conference on Control Science and Systems Engineering (ICCSSE) pp. 154 - 158
• Main Authors: Chen, Tao, Yao, YunTing, Wang, Chao liang, Li, Lei, Liu, Wei, Wei, YinWu
• Format: Conference Proceeding
• Language: English
• Published: IEEE 14.07.2022
• Subjects: Collaboration; Demand response; demand response interaction; Electric potential; Electrothermal collaborative system; load model; neural network; Neural networks; potential prediction; Prediction algorithms; Predictive models; Regulation
• DOI: 10.1109/ICCSSE55346.2022.10079732

Energy construction in typical regions is an important measure to realize energy reform. It is necessary to achieve clean and low-carbon utilization of energy, implement coal reduction and substitution, and encourage the construction of comprehensive energy projects coordinated by multiple energy sources such as electricity, heat, cold and gas. Considering the residents' participation in the demand response interaction in the electrothermal collaborative system, this paper first constructs the demand response interaction framework under the scenario of electrothermal collaborative system, then completes the modeling of the main equipment of residents' users, and finally uses the neural network algorithm to predict the demand response potential based on Residents' power consumption behavior, so as to improve the efficiency of users' participation in demand response in the electrothermal collaborative system.