Applications of Agent-Based Methods in Multi-Energy Systems-A Systematic Literature Review

被引:16
作者
Yao, Ruiqiu [1 ]
Hu, Yukun [1 ]
Varga, Liz [1 ]
机构
[1] UCL, Dept Civil Environm & Geomatic Engn, London WC1E 6BT, England
基金
英国工程与自然科学研究理事会; 英国经济与社会研究理事会;
关键词
integrated energy system; multi-energy system; multi-agent system; agent-based modeling; systematic literature review; optimization; muti-agent reinforcement learning; ENERGY MANAGEMENT-SYSTEM; POWER ENGINEERING APPLICATIONS; MULTIAGENT SYSTEMS; DEMAND RESPONSE; SCHEDULING STRATEGY; LEARNING-METHOD; SMART GRIDS; ELECTRICITY; SIMULATION; OPERATION;
D O I
10.3390/en16052456
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The need for a greener and more sustainable energy system evokes a need for more extensive energy system transition research. The penetration of distributed energy resources and Internet of Things technologies facilitate energy system transition towards the next generation of energy system concepts. The next generation of energy system concepts include "integrated energy system", "multi-energy system", or "smart energy system". These concepts reveal that future energy systems can integrate multiple energy carriers with autonomous intelligent decision making. There are noticeable trends in using the agent-based method in research of energy systems, including multi-energy system transition simulation with agent-based modeling (ABM) and multi-energy system management with multi-agent system (MAS) modeling. The need for a comprehensive review of the applications of the agent-based method motivates this review article. Thus, this article aims to systematically review the ABM and MAS applications in multi-energy systems with publications from 2007 to the end of 2021. The articles were sorted into MAS and ABM applications based on the details of agent implementations. MAS application papers in building energy systems, district energy systems, and regional energy systems are reviewed with regard to energy carriers, agent control architecture, optimization algorithms, and agent development environments. ABM application papers in behavior simulation and policy-making are reviewed with regard to the agent decision-making details and model objectives. In addition, the potential future research directions in reinforcement learning implementation and agent control synchronization are highlighted. The review shows that the agent-based method has great potential to contribute to energy transition studies with its plug-and-play ability and distributed decision-making process.
引用
收藏
页数:36
相关论文
共 184 条
[1]   Agent Based Modelling and Simulation tools: A review of the state-of-art software [J].
Abar, Sameera ;
Theodoropoulos, Georgios K. ;
Lemarinier, Pierre ;
O'Hare, Gregory M. P. .
COMPUTER SCIENCE REVIEW, 2017, 24 :13-33
[2]   Computational intelligence techniques for HVAC systems: A review [J].
Ahmad, Muhammad Waseem ;
Mourshed, Monjur ;
Yuce, Baris ;
Rezgui, Yacine .
BUILDING SIMULATION, 2016, 9 (04) :359-398
[3]   Strategies for an Adaptive Control System to Improve Power Grid Resilience with Smart Buildings [J].
Ahrens, Mischa ;
Kern, Fabian ;
Schmeck, Hartmut .
ENERGIES, 2021, 14 (15)
[4]   Interactive decentralized operation with effective presence of renewable energies using multi-agent systems [J].
Alishavandi, Amir Mohammad ;
Moghaddas-Tafreshi, Seyed Masoud .
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2019, 112 :36-48
[5]   Modelling sustainable energy futures for the UK [J].
Allen, Peter ;
Varga, Liz .
FUTURES, 2014, 57 :28-40
[6]   A multi-agent based energy management solution for integrated buildings and microgrid system [J].
Anvari-Moghaddam, Amjad ;
Rahimi-Kian, Ashkan ;
Mirian, Maryam S. ;
Guerrero, Josep M. .
APPLIED ENERGY, 2017, 203 :41-56
[7]  
Anylogic, AnyLogic: Simulation Modeling Software Tools & Solutions for Business
[8]   Application of computable general equilibrium (CGE) to climate change mitigation policy: A systematic review [J].
Babatunde, Kazeem Alasinrin ;
Begum, Rawshan Ara ;
Said, Fathin Faizah .
RENEWABLE & SUSTAINABLE ENERGY REVIEWS, 2017, 78 :61-71
[9]   Energy and complexity: New ways forward [J].
Bale, Catherine S. E. ;
Varga, Liz ;
Foxon, Timothy J. .
APPLIED ENERGY, 2015, 138 :150-159
[10]   Transactive control of fast-acting demand response based on thermostatic loads in real-time retail electricity markets [J].
Behboodi, Sahand ;
Chassin, David P. ;
Djilali, Ned ;
Crawford, Curran .
APPLIED ENERGY, 2018, 210 :1310-1320