文献类型：会议论文

英文题名：Analysis of probabilistic energy flow for integrated electricity and heat systems considering source-load uncertainty

作者：Liu, Taihao[1]; Song, Yunzhong[1,2,3]; Xiao, Huimin[4]; Wang, Fuzhong[1,2,3]

第一作者：Liu, Taihao

机构：[1] School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, 454003, China; [2] Henan International Joint Laboratory of Direct Drive and General of Intelligent Equipment, Zhengzhou, China; [3] Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment, Zhengzhou, China; [4] School of Computer and Information Engineering, Henan University of Economics and Law, Zhengzhou, China

第一机构：School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, 454003, China

通讯机构：[1]School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo, 454003, China

会议论文集：Proceedings of 2023 Chinese Intelligent Systems Conference - Volume II

会议日期：October 14, 2023 - October 15, 2023

会议地点：Ningbo, China

语种：英文

外文关键词：Electric loads - Intelligent systems - Monte Carlo methods - Uncertainty analysis

摘要：Building the integrated energy system has become a major strategy for the country to achieve energy transformation and sustainable development. Aiming at the source-load uncertainty in the actual operation of integrated electricity and heat systems (IEHS), a probabilistic energy flow calculation method for IEHS considering source-load uncertainty based on discrete solution is proposed. Firstly, the models of power system, thermal system, coupling element and source-load uncertainty are established respectively. Then, on the basis of steady-state energy flow, the uncertainty of electric, heating load and photovoltaic and wind power output is considered, and Monte Carlo simulation (MCS) method is used to calculate the probabilistic energy flow for IEHS. The effectiveness of the proposed method is verified by a case, and it is explained that IEHS can be operated more safely by adjusting the capacity of heat pump (HP). ? The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.