Decentralized Demand Management Based on Alternating Direction Method of Multipliers Algorithm for Industrial Park with CHP Units and Thermal Storage

作     者：Jingdong Wei Yao Zhang Jianxue Wang Lei Wu Peiqi Zhao Zhengting Jiang Jingdong Wei;Yao Zhang;Jianxue Wang;Lei Wu;Peiqi Zhao;Zhengting Jiang

作者机构：School of Electrical EngineeringXi’an Jiaotong UniversityXi’anChina Electrical and Computer Engineering DepartmentStevens Institute of TechnologyHobokenUSA 

出 版 物：《Journal of Modern Power Systems and Clean Energy》 (现代电力系统与清洁能源学报（英文）)

年 卷 期：2022年第10卷第1期

页      面：120-130页

核心收录：

学科分类：080802[工学-电力系统及其自动化] 0808[工学-电气工程] 08[工学] 

基　　金：This work was supported by the National Key R&D Program of China(No.2018YFB0905000) the Science and Technology Project of State Grid Corporation of China(No.SGTJDK00DWJS1800232) 

主　　题：Alternating direction method of multipliers(ADMM) combined heat and power(CHP)unit demand management industrial park integrated demand response(IDR) thermal storage 

摘      要：This paper proposes a decentralized demand management approach to reduce the energy bill of industrial park and improve its economic gains.A demand management model for industrial park considering the integrated demand response of combined heat and power(CHP)units and thermal storage is firstly ***,by increasing the electricity outputs of CHP units during peak-load periods,not only the peak demand charge but also the energy charge can be *** thermal storage can efficiently utilize the waste heat provided by CHP units and further increase the flexibility of CHP *** heat dissipation of thermal storage,thermal delay effect,and heat losses of heat pipelines are considered for ensuring reliable solutions to the industrial *** proposed model is formulated as a multi-period alternating current(AC)optimal power flow problem via the second-order conic programming *** alternating direction method of multipliers(ADMM)algorithm is used to compute the proposed demand management model in a distributed manner,which can protect private data of all participants while achieving solutions with high *** case studies validate the effectiveness of the proposed demand management approach in reducing peak demand charge,and the performance of the ADMM-based decentralized computation algorithm in deriving the same optimal results of demand management as the centralized approach is also validated.