Multi-Agent Systems Applications in Energy Optimization Problems: A State-of-the-Art Review

Alfonso González-Briones, Fernando De La Prieta, Mohd Saberi Mohamad, Sigeru Omatu and Juan M. Corchado
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Alfonso González-Briones: BISITE Digital Innovation Hub, University of Salamanca, Edificio Multiusos I+D+i, 37007 Salamanca, Spain
Fernando De La Prieta: BISITE Digital Innovation Hub, University of Salamanca, Edificio Multiusos I+D+i, 37007 Salamanca, Spain
Mohd Saberi Mohamad: Institute For Artificial Intelligence and Big Data, Universiti Malaysia Kelantan, City Campus, Pengkalan Chepa, Kota Bharu 16100, Malaysia
Sigeru Omatu: Department of Electronics, Osaka Institute of Technology, Information and Communication, Faculty of Engineering, Osaka 535-8585, Japan
Juan M. Corchado: BISITE Digital Innovation Hub, University of Salamanca, Edificio Multiusos I+D+i, 37007 Salamanca, Spain

Energies, 2018, vol. 11, issue 8, 1-28

Abstract: This article reviews the state-of-the-art developments in Multi-Agent Systems (MASs) and their application to energy optimization problems. This methodology and related tools have contributed to changes in various paradigms used in energy optimization. Behavior and interactions between agents are key elements that must be understood in order to model energy optimization solutions that are robust, scalable and context-aware. The concept of MAS is introduced in this paper and it is compared with traditional approaches in the development of energy optimization solutions. The different types of agent-based architectures are described, the role played by the environment is analysed and we look at how MAS recognizes the characteristics of the environment to adapt to it. Moreover, it is discussed how MAS can be used as tools that simulate the results of different actions aimed at reducing energy consumption. Then, we look at MAS as a tool that makes it easy to model and simulate certain behaviors. This modeling and simulation is easily extrapolated to the energy field, and can even evolve further within this field by using the Internet of Things (IoT) paradigm. Therefore, we can argue that MAS is a widespread approach in the field of energy optimization and that it is commonly used due to its capacity for the communication, coordination, cooperation of agents and the robustness that this methodology gives in assigning different tasks to agents. Finally, this article considers how MASs can be used for various purposes, from capturing sensor data to decision-making. We propose some research perspectives on the development of electrical optimization solutions through their development using MASs. In conclusion, we argue that researchers in the field of energy optimization should use multi-agent systems at those junctures where it is necessary to model energy efficiency solutions that involve a wide range of factors, as well as context independence that they can achieve through the addition of new agents or agent organizations, enabling the development of energy-efficient solutions for smart cities and intelligent buildings.

Keywords: energy optimization; demand response; serious game; efficient decision-making process; multi-agent system (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

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