Open AccessDay-ahead sharing model of multi-integrated energy service providers based on source-load matching degree
Author(s) -
Weiting Xu,
Ruiguang Ma,
Chao Chen,
Wei Wang
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/766/1/012092
Subject(s) - computer science , matching (statistics) , photovoltaic system , energy (signal processing) , index (typography) , function (biology) , mathematical optimization , reliability engineering , simulation , engineering , electrical engineering , mathematics , statistics , evolutionary biology , world wide web , biology
The limited regulation capacity in the integrated energy community is a key factor restricting the development of the community-based integrated (distributed) energy system. Based on this, a model for optimal sharing of day-ahead energy in multi-communities considering the matching degree of source-load curves between communities is proposed. Firstly, the relationship between energy supply and multi-energy flow is analysed concretely in a single community. A mathematical model that includes electric vehicles and multiple energy conversion equipment is built, then, an objective function minimizing the cost of energy purchase, equipment operation and maintenance, and EV battery loss is established. Secondly, the comprehensive Spearman constant and Euclidean distance matching index based on photovoltaic and load data among the communities are considered to optimize the multi-community operation efficiency with the goal of minimizing the energy interaction cost. Finally, in a 3-community simulation system simulation, results show that the multi-energy sharing mode can effectively improve the overall economy of the system and the photovoltaic consumption capacity. The introduction of matching index also improves the energy transmission efficiency, verifying the rationality of the proposed model.