A multi-agent based distributed energy management scheme for smart grid applications

被引:58
作者
Radhakrishnan, Bharat Menon [1 ]
Srinivasan, Dipti [1 ]
机构
[1] Natl Univ Singapore, Dept Elect & Comp Engn, Singapore 117548, Singapore
关键词
Active grid control; Cost model; Energy management systems; Electricity markets; Multi-agent systems; Smart grids; GREENHOUSE-GAS EMISSIONS; OPTIMIZATION; SYSTEM;
D O I
10.1016/j.energy.2016.02.117
中图分类号
O414.1 [热力学];
学科分类号
摘要
A multi-agent system based distributed EMS (energy management system) is proposed in this paper to perform optimal energy allocation and management for grids comprising of renewables, storage and distributed generation. The reliable and efficient operation of smart grids is slackened due to the presence of intermittent renewables. As the load demand and renewables are uncertain throughout the day, an energy management system is essential to ensure grid stability and achieve reductions in operation costs and CO2 emissions. The main objectives of the proposed algorithm is to maintain power balance in the system and to ensure long cycle life for storage units by controlling their SOC (state of charge). The proposed EMS scheme is tested and validated on a practical test system, which replicates a small-scale smart grid with a variety of distributed sources, storage devices, loads, power electronic converters, and SCADA (supervisory control and data acquisition) system. This system is also connected to the utility grid and the power exchange is controlled with the help of a battery system through a fuzzy based decision making framework. The proposed algorithm is also extensively verified and tested using a series of sensitivity analyses and benchmarking with existing algorithms. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:192 / 204
页数:13
相关论文
共 50 条
  • [21] Decentralised dispatch of distributed energy resources in smart grids via multi-agent coalition formation
    Ye, Dayong
    Zhang, Minjie
    Sutanto, Danny
    JOURNAL OF PARALLEL AND DISTRIBUTED COMPUTING, 2015, 83 : 30 - 43
  • [22] Heuristic Multi-Agent Control for Energy Management of Microgrids with Distributed Energy Sources
    Ali, Zunaib
    Putrus, Ghanim
    Marzband, Mousa
    Tookanlou, Mahsa Bagheri
    Saleem, Komal
    Ray, Pravat Kumar
    Subudhi, Bidyadhar
    2021 56TH INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE (UPEC 2021): POWERING NET ZERO EMISSIONS, 2021,
  • [23] Adaptive Multi-agent System for Smart Grid Regulation with Norms and Incentives
    Rubio, Thiago R. P. M.
    Cardoso, Henrique Lopes
    Oliveira, Eugenio
    TECHNOLOGICAL INNOVATION FOR CYBER-PHYSICAL SYSTEMS, 2016, 470 : 315 - 322
  • [24] Multi-Agent System Architecture for Smart Home Energy Management and Optimization
    Asare-Bediako, B.
    Kling, W. L.
    Ribeiro, P. F.
    2013 4TH IEEE/PES INNOVATIVE SMART GRID TECHNOLOGIES EUROPE (ISGT EUROPE), 2013,
  • [25] Multi-Agent approach for Power System in a Smart Grid Protection Context
    Abedini, Reza
    Pinto, Tiago
    Morais, Hugo
    Vale, Zita
    2013 IEEE GRENOBLE POWERTECH (POWERTECH), 2013,
  • [26] A review of the applications of multi-agent reinforcement learning in smart factories
    Bahrpeyma, Fouad
    Reichelt, Dirk
    FRONTIERS IN ROBOTICS AND AI, 2022, 9
  • [27] Multi-agent microgrid energy management based on deep learning forecaster
    Afrasiabi, Mousa
    Mohammadi, Mohammad
    Rastegar, Mohammad
    Kargarian, Amin
    ENERGY, 2019, 186
  • [28] Multi-Agent Based Smart Grid Management and Simulation: Situation Awareness and Learning in a Test Bed with Simulated and Real Installations and Players
    Morais, Hugo
    Vale, Zita
    Pinto, Tiago
    Gomes, Luis
    Fernandes, Filipe
    Oliveira, Pedro
    Ramos, Carlos
    2013 IEEE POWER AND ENERGY SOCIETY GENERAL MEETING (PES), 2013,
  • [29] Distributed energy management of multi-area integrated energy system based on multi-agent deep reinforcement learning
    Ding, Lifu
    Cui, Youkai
    Yan, Gangfeng
    Huang, Yaojia
    Fan, Zhen
    INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS, 2024, 157
  • [30] Optimal Distributed Dispatch of Smart Multi-Agent Energy Hubs Based on Consensus Algorithm Considering Lossy Communication Network and Uncertainty
    Eladl, Abdelfattah A.
    El-Afifi, Magda I.
    El-Saadawi, Magdi M.
    Sedhom, Bishoy E.
    CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2025, 11 (01): : 352 - 364