Multi Agent Based Energy Management System for Microgrids

Perera, M. K.; Disanayaka, R.U.I.; Kumara, E.M.C.S; Walisundara, W.M.C.S.B; Priyadarshana, H.V.V.; Ekanayake, E.M.A.G.N.C.; Hemapala, K.T.M.U.

doi:10.1109/piicon49524.2020.9113021

Cited by 10 publications

(4 citation statements)

References 15 publications

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“…Based on the load types in NGs, the MG loads (L MG ) are also made up of DC and AC loads, as expressed in the following Equation (19):…”

Section: Load Definitionmentioning

confidence: 99%

Sustainable Intelligent Energy Management System for Microgrid Using Multi-Agent Systems: A Case Study

Hamidi,

Raihani,

Bouattane

2023

Sustainability

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In this paper, a sustainable, intelligent energy management system for a microgrid based on a multi-agent system (MAS) is studied. The system is designed to address the challenges posed by the intermittence of renewable energy sources. Also, the system optimizes the use of available AC–DC renewable energy sources by utilizing load flexibility and the complementarity of renewable sources. To evaluate the effectiveness of this proposed multi-agent framework, a co-simulation using MATLAB and JADE platforms is conducted for a microgrid connected to the main grid. The results show that the proposed energy sharing system achieved over 82.34% of energy savings. This innovative solution has the potential to reduce the need for energy storage and improve energy efficiency while also reducing CO2 emissions. It offers a promising sustainable development solution for managing and controlling MG. The proposed system contributes to the development of sustainable energy systems based on artificial intelligence to meet the global goals.

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“…Based on the load types in NGs, the MG loads (L MG ) are also made up of DC and AC loads, as expressed in the following Equation (19):…”

Section: Load Definitionmentioning

confidence: 99%

Sustainable Intelligent Energy Management System for Microgrid Using Multi-Agent Systems: A Case Study

Hamidi,

Raihani,

Bouattane

2023

Sustainability

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“…MAS STRATEGY MAS comprises independent agents that perform autonomous actions to execute the assigned tasks. The MAS control scheme is designed to schedule sources and loads by considering the operation modes of the microgrid [41]. The MAS agents include the Source agent, grid agent and load agent.…”

Section: H Objective Functionmentioning

confidence: 99%

Decentralized Smart Energy Management in Hybrid Microgrids: Evaluating Operational Modes, Resources Optimization, and Environmental Impacts

Billah,

Yousif,

Numan

et al. 2023

IEEE Access

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Escalating energy demands and climate change challenges necessitate the adaptation of renewable-based microgrid systems in the energy sector. The proposed work employs a robust Multi Agent System (MAS) technique to achieve efficient and automated control of the hybrid microgrid operation. The hybrid microgrid system incorporates Renewable Energy Sources (RES), a diesel generator, and a battery storage system. The operation of the hybrid microgrid consists of three distinct modes: islanded, transition to grid, and grid-oriented mode. The system's performance is optimized by considering factors like climatic patterns, energy costs, connected source characteristics, and load demand. Different climatic scenarios are assessed for each mode of operation, where the best, extreme sunny, extreme cloudy, and worst climate conditions are considered for islanded mode; sunny and cloudy scenarios are considered for transition to grid mode as well as grid-feed and grid-tied modes are considered for grid-oriented operation of the microgrid. The simulation studies are performed using the MATLAB/Simulink R2021a environment. Furthermore, Particle Swarm Optimization (PSO) is implemented to optimize power allocation within the microgrid and enhance its cost-effectiveness. The optimization results demonstrate efficient utilization of available energy sources along with effective energy management facilitated by the MAS control system. The results emphasize the importance of adopting a MAS approach for achieving smart energy management through comprehensive analysis and integrating decentralized energy management techniques for optimal accommodation of distributed energy resources in hybrid microgrids.INDEX TERMS Renewable energy sources, particle swarm optimization, energy management system, multi agent system, microgrid. NOMENCLATURE RES Renewable energy sources. DER Distributed energy resources. PV Photovoltaic. MAS Multi agent system. PSO Particle swarm optimization. AI Artificial intelligence. MILP Mixed integer linear programming.The associate editor coordinating the review of this manuscript and approving it for publication was Xiwang Dong.

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“…A MAS Based on decentralized EMS for connecting MG using the java agent development environment (JADE) was proposed in [23]. The power sources adopted in the architecture are PV and WT sources.…”

Section: Introductionmentioning

confidence: 99%

A new modular nanogrid energy management system based on multi-agent architecture

Hamidi

Raihani

Youssfi

et al. 2022

IJPEDS

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The emergence of renewable energy sources with controllable loads gave the opportunity to the consumers to build their own Microgrids. However, the intermittence of renewable energy sources such as wind and photovoltaic leads to some challenges in terms of balancing generation and consumption. This paper aims to present a novel multi-agent model based intelligent control scheme to balance the home/building alternative current (AC)-direct current (DC) load demands and renewable energy sources. The new proposed scheme consists of a three-level hierarchical multi agent system based on cooperation, communication and interaction between intelligent agents to fulfill the load's requirements. Then, the proposed multi agent framework is simulated using four different nanogrids to prove its effectiveness using different temporal profiles for loads and generators. The proposed model is designed to be modular, so that it can be considered as a sample from a set of similar modules, assigned to different buildings to allow efficient energy sharing and balancing. The used approach in this concept is inspired from auto-similar systems, which is well suited and easy to implement on multi agent systems. A co-simulation in MATLAB and JAVA/JADE platforms has been performed regarding the production-consumption of the 24 hours baseline period.

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Multi Agent Based Energy Management System for Microgrids

Cited by 10 publications

References 15 publications

Sustainable Intelligent Energy Management System for Microgrid Using Multi-Agent Systems: A Case Study

Sustainable Intelligent Energy Management System for Microgrid Using Multi-Agent Systems: A Case Study

Decentralized Smart Energy Management in Hybrid Microgrids: Evaluating Operational Modes, Resources Optimization, and Environmental Impacts

A new modular nanogrid energy management system based on multi-agent architecture

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