Energy flow matrix modeling and optimal operation analysis of multi energy systems based on graph theory
- 1. Electric Power Research Institute of China, Haidian District, Beijing 100085 (China)
- 2. School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044 (China)
Description
Highlights: • A set of new definitions are proposed to build the directed graph of energy flows. • Propose a novel matrix modeling method to facilitate computerized modeling of multi energy systems. • Propose an optimal operation model based on energy flow matrix modeling method. • Optimal operation strategies of different multi energy systems are discussed. -- Abstract: Multi energy system (MES) is considered an efficient pattern to satisfy diverse energy demands of consumers and improve the energy utilization efficiency. A novel matrix modeling method based on graph theory is proposed to model the steady state energy flows of MES. Firstly, a set of new definitions are proposed to build the directed graph of the energy flows of MES including renewable energy, energy storage and demand response. Secondly, the matrices to describe the topology and energy conversion characteristics of MES are presented. Then the energy flow equations matrix modeling processes are demonstrated. Besides, an input data structure of the MES is suggested to facilitate computerized modeling. Based on this, an optimal operation model in matrix form is proposed to minimize the MES daily operation cost. Then optimal operation problems of multi energy systems with different structures are investigated with the novel modeling method. Simulation results show that the modeling method is effective and feasible to describe the energy flows of MESs with different structures including renewable energy, energy storage and demand response. Comparisons of various costs of case 1, case 2 and case 3 indicate that the renewable energy and energy storage can decrease the power cost of case 3 by 17.65% and 6.45%, respectively. Furthermore, comparisons of case 4 and case 3 show that demand response can reduce the power cost of case 4 by 21.91%.
Availability note (English)
Available from http://dx.doi.org/10.1016/j.applthermaleng.2018.10.022Additional details
Identifiers
- DOI
- 10.1016/j.applthermaleng.2018.10.022;
- PII
- S1359431118322087;
Publishing Information
- Journal Title
- Applied Thermal Engineering
- Journal Volume
- 146
- Journal Page Range
- p. 648-663
- ISSN
- 1359-4311
- CODEN
- ATENFT
INIS
- Country of Publication
- United Kingdom
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 54125378
- Subject category
- S42: ENGINEERING;
- Descriptors DEI
- COMPUTERIZED SIMULATION; ENERGY CONSUMPTION; ENERGY CONVERSION; ENERGY DEMAND; ENERGY LEVELS; ENERGY STORAGE; ENERGY SYSTEMS; GRAPH THEORY; MATRICES; STEADY-STATE CONDITIONS; TOPOLOGY
- Descriptors DEC
- CONVERSION; DEMAND; MATHEMATICS; SIMULATION; STORAGE
Optional Information
- Copyright
- Copyright (c) 2018 Elsevier Ltd. All rights reserved.