Export file:


  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text


  • Citation Only
  • Citation and Abstract

A review on Multi-Agent system based energy management systems for micro grids

Department of Electrical Engineering, University of Moratuwa, Colombo, Sri Lanka

Topical Section: Smart Grids and Networks

Over the last century, there has been no significant change in the centrally controlled structure of electrical power grids. The economic and population growth throughout the planet increases the pressure on the power sector. Power electrical grid, as the main structure for power transmission has to reconsider its concepts. The flexible controlling of DER (Distributed Energy Resources) such as wind power, solar power, hydropower, wave power, geo-thermal power and biomass power has to be considered to overcome these challenges. The demand for electricity is steadily increasing and current centrally controlled structure is ill-suited to fulfill the modern complex power requirements. As a result the concepts like micro grids, smart grids, multi-energy systems, virtual power plants are emerging combined with new concepts like MAS (Multi-Agent Systems) and IoT (Internet of Things). They move our electrical power grid to a more decentralized, highly efficient energy management system. The objective of this paper is to discuss how multi-agent concept based energy management systems will behave for micro grids. The paper contributes a description of smart micro grids, MAS based Energy management systems and controlling of DER in micro grids, and future of power electrical grid structure with MAS.
  Article Metrics

Keywords Micro-grids; Multi-Agent systems; energy management; distributed energy resources; IoT

Citation: HVV Priyadarshana, MA Kalhan Sandaru, KTMU Hemapala, WDAS Wijayapala. A review on Multi-Agent system based energy management systems for micro grids. AIMS Energy, 2019, 7(6): 924-943. doi: 10.3934/energy.2019.6.924


  • 1. Otuoze AO, Mustafa MW, Larik RM (2018) Smart grids security challenges: Classification by sources of threats. J Electr Syst Inf Technol 5: 468-483.
  • 2. Gungor VC, Sahin D, Kocak T, et al. (2011) Smart grid technologies: Communication technologies and standards. IEEE Trans Ind Inf 7: 529-539.    
  • 3. Brinkerink M, Deane P, Collins S, et al. (2018) Developing a global interconnected power system model. Global Energy Interconnect 1: 330-343.
  • 4. Takeda S, Sakurai S, Yamamoto Y, et al. (2016) Limitation of fusion power plant installation on future power grids under the effect of renewable and nuclear power sources. Fusion Eng Des 109-111: 1754-1758.    
  • 5. Liu W, Li N, Jiang Z, et al. (2018) Smart Micro-grid system with Wind/PV/Battery. Energy Procedia 152: 1212-1217.    
  • 6. Hirsch A, Parag Y, Guerrero J (2018) Microgrids: A review of technologies, key drivers, and outstanding issues. Renewable Sustainable Energy Rev 90: 402-411.    
  • 7. Adefarati T, Bansal RC (2019) Economic and environmental analysis of a cogeneration power system with the incorporation of renewable energy resources. Energy Procedia 158: 803-808.
  • 8. Rafik M, Bahnasse A, Khiat A, et al. (2019) Towards a smart energy sharing in micro smart grid adopting SDN approach. Proc Comput Sci 151: 717-724.    
  • 9. Sha A, Aiello M (2018) Topological considerations on decentralized energy exchange in the smart grid. Proc Comput Sci 130: 720-727.    
  • 10. Olivares DE, Mehrizi-Sani A, Etemadi AH, et al. (2014) Trends in microgrid control. IEEE Trans Smart Grid 5: 1905-1919.    
  • 11. Ton DT, Smith MA (2012) The U.S. department of energy's microgrid initiative. Electr J 25: 84-94.
  • 12. Chen MR, Zeng GQ, Dai YX, et al. (2018) Fractional-Order model predictive frequency control of an islanded microgrid. Energies 12: 84.    
  • 13. Sahoo AK, Abhitharan KP, Kalaivani A, et al. (2015) Feasibility study of microgrid installation in an educational institution with grid uncertainty. Proc Comput Scie 70: 550-557.    
  • 14. Choudhary P, Srivastava RK (2019) Sustainability perspectives-A review for solar photovoltaic trends and growth opportunities. J Cleaner Prod 227: 589-612.    
  • 15. Marzband M, Moghaddam MM, Akorede MF, et al. (2016) Adaptive load shedding scheme for frequency stability enhancement in microgrids. Electr Power Syst Res 140: 78-86.    
  • 16. Zhang Y, Lundblad A, Campana PE, et al. (2017) Battery sizing and rule-based operation of grid-connected photovoltaic-battery system: A case study in Sweden. Energy Convers Manage 133: 249-263.    
  • 17. Andri I, Pinaa A, Ferrãoa P, et al. (2018) Renewable energy integration with Mini/Microgrids, REM 2018, 29-30 September 2018, Rhodes, Greece A Unified Energy Bus Based Multi-energy Flow Modelin Method of Integrated Energy System; 2019.
  • 18. Wang F, Zhu Y, Yan J (2018) Performance of solar PV micro-grid systems: A comparison study. Energy Procedia 145: 570-575.    
  • 19. Vernet A, Khayesi JNO, George V, et al. (2019) How does energy matter? Rural electrification, entrepreneurship, and community development in Kenya. Energy Policy 126: 88-98.
  • 20. Derrouazin A, Mekkakia-Maaza N, Taleb R, et al. (2014) Low cost hybrid energiess smart management system applied for Micro-grids. Energy Procedia 50: 729-737.    
  • 21. Lewandowska-Bernat A, Desideri U (2017) Sustainable mini-grid. Energy Procedia 142: 3008-3013.    
  • 22. Averyt K, Huber-Lee A, Macknick J, et al. (2011) Freshwater use by US power plants: A report of the energy and water in a warming world initiative.
  • 23. Meldrum J, Nettles-Anderson S, Heath G, et al. (2013) Life cycle water use for electricity generation: A review and harmonization of literature estimates. Environ Res Lett 8.
  • 24. Zhu X, Han XQ, Qin WP, et al. (2015) Past, today and future development of micro-grids in China. Renewable Sustainable Energy Rev 42: 1453-1463.    
  • 25. Lopes JP, Moreira C, Resende F (2005) Microgrids blackstart and islanding operation in Proc. 15th PSCC. Liege, Belgium.
  • 26. Hatziargyriou ND, Meliopoulos APS (2002). Distributed energy sources: Technical challenges. 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings. 1012: 1017-1022.
  • 27. Hegazy YG, Chikhani AY (2003) Intention islanding of distributed generation for reliability enhancement, 208-213.
  • 28. Arulampalam A, Barnes M, Engler A, et al. (2004) Control of power electronic interfaces in distributed generation microgrids. Int J Electron 91: 503-523.    
  • 29. Katiraei F, Iravani MR, Lehn PW (2005) Micro-grid autonomous operation during and subsequent to islanding process. IEEE Trans Power Delivery 20: 248-257.    
  • 30. Lopes JP, Moreira CL, Madureira AG (2006) Defining control strategies for MicroGrids islanded operation. IEEE Trans Power Syst 21: 916-924.    
  • 31. Abuelnasr M, El-Khattam W, Helal I (2018) Examining the influence of micro-grids topologies on optimal energy management systems decisions using genetic algorithm. Ain Shams Eng J 9: 2807-2814.    
  • 32. Mellouk L, Aaroud A, Benhaddou D, et al. (2015) Overview of mathematical methods for energy management optimization in smart grids. 2015 3rd International Renewable and Sustainable Energy Conference (IRSEC).
  • 33. van Ackooij W, De Boeck J, Detienne B, et al. (2018) Optimizing power generation in the presence of micro-grids. Eur J Oper Res 271: 450-461.    
  • 34. Kanchev H, Lu D, Colas F, et al. (2011) Energy management and power planning of a microgrid with a PV-based active generator for smart grid applications. IEEE Trans Ind Electron 58: 4583-4592.    
  • 35. Wu H, Liu X, Ding M (2014) Dynamic economic dispatch of a microgrid: Mathematical models and solution algorithm. Int J Electr Power Energy Syst 63: 336-346.    
  • 36. Ding M, Zhang Y, Mao M, et al. (2009) Steady model and operation optimization for microgrids under centralized control. Autom of Electr Power Syst.
  • 37. Koltsaklis NE, Giannakakis M, Georgiadis MC (2018) Optimal energy planning and scheduling of microgrids. Chem Eng Res Design 131: 318-332.    
  • 38. Ma T, Wu J, Hao L, et al. (2018) The optimal structure planning and energy management strategies of smart multi energy systems. Energy 160: 122-141.    
  • 39. Wu X, Cao W, Wang D, et al. (2019) A Multi-Objective optimization dispatch method for microgrid energy management considering the power loss of converters. Energies 12.
  • 40. Raju L, Morais AA, Rathnakumar R, et al. (2017) Micro-grid grid outage management using multi agent systems. Energy Procedia 117: 112-119.    
  • 41. Lin H, Wang Q, Wang Y, et al. (2017) A multi-agent based optimization architecture for energy hub operation. Energy Procedia 142: 2158-2164.    
  • 42. Ormandjieva O, Bentahar J, Huang J, et al. (2015) Modelling multi-agent systems with category theory. Procedia Comput Sci52: 538-545.
  • 43. Fu J, Wang J (2014) Adaptive coordinated tracking of multi-agent systems with quantized information. Syst Control Lett 74: 115-125.    
  • 44. González-Pardo A, Varona P, Camacho D, et al. (2012) Communication by identity discrimination in bio-inspired multi-agent systems. Concurr Comput: Pract Exper 24: 589-603.    
  • 45. Li S, Du H, Lin X (2011) Finite-time consensus algorithm for multi-agent systems with double-integrator dynamics. Automatica 47: 1706-1712.    
  • 46. Angeli D, Bliman P (2005) Extension of a result by Moreau on stability of leaderless multi-agent systems. Proceedings of the 44th IEEE Conference on Decision and Control, 759-764.
  • 47. Zhao Y, Wen G, Duan Z, et al. (2013) A new Observer-Type consensus protocol for linear Multi-Agent dynamical systems. Asian J Control 15: 571-582.    
  • 48. Zhang DM, Meng L, Wang XG, et al. (2013) Linear quadratic regulator control of multi-agent systems. Optim Control Appl Methods 36: 45-59.
  • 49. Li Z, Ren W, Liu X, et al. (2013) Consensus of Multi-Agent systems with general linear and lipschitz nonlinear dynamics using distributed adaptive protocols. IEEE Trans Autom Control 58: 1786-1791    
  • 50. Du H, He Y, Cheng Y (2014) Finite-Time synchronization of a class of Second-Order nonlinear Multi-Agent systems using output feedback control. IEEE Trans Circuits Syst I: Regular Papers 61: 1778-1788.    
  • 51. Gao L, Liao X, Li H, et al. (2016) Event-Triggered control for Multi-Agent systems with general directed topology and time delays. Asian J Control 18: 945-953.    
  • 52. Guo G, Ding L, Han QL (2014) A distributed event-triggered transmission strategy for sampled-data consensus of multi-agent systems. Automatica 50: 1489-1496.    
  • 53. Li H, Ming C, Shen S, et al. (2014) Event-triggered control for multi-agent systems with randomly occurring nonlinear dynamics and time-varying delay. J Franklin Inst 351: 2582-2599.    
  • 54. Liu Z, You X, Yang H, et al. (2015) Leader-following consensus of heterogeneous multi-agent systems with packet dropout. Int J Control, Autom Syst 13: 1067-1075.    
  • 55. Olfati-Saber R, Murray RM (2004) Consensus problems in networks of agents with switching topology and time-delays. IEEE Trans Autom Control 49: 1520-1533    
  • 56. Liu B, Su H, Li R, et al. (2014) Switching controllability of discrete-time multi-agent systems with multiple leaders and time-delays. Appl Math Comput 228: 571-588.
  • 57. Khan MW, Wang J, Ma M, et al. (2019) Optimal energy management and control aspects of distributed microgrid using multi-agent systems. Sustainable Cities and Soc 44: 855-870.    
  • 58. Wu Z, Gu W (2009) Active power and frequency control of islanded microgrid based on multi-agent technology. Electr Power Autom Equip 29: 57-61.
  • 59. Kantamneni A, Brown LE, Parker G, et al. (2015) Survey of multi-agent systems for microgrid control. Eng Appl Artif Intell 45: 192-203.    
  • 60. Mehta R, Menon Radhakrishnan B, Srinivasan D, et al. (2014) Market based multi-agent control of microgrid. 2014 IEEE Ninth International Conference on Intelligent Sensors, Sensor Networks and Information Processing.
  • 61. Colson CM, Nehrir MH (2009) A review of challenges to real-time power management of microgrids. 2009 IEEE Power & Energy Society General Meeting.
  • 62. Akkermans H, Ygge F (2011) Decentralized markets versus central control: A comparative study. J Artif Intell Res 11: 301-333.
  • 63. Wang L, Wang Z, Yang R (2012) Intelligent multiagent control system for energy and comfort management in smart and sustainable buildings. IEEE Trans Smart Grid 3: 605-617.    
  • 64. Dou C, Jin S, Jiang G, et al. (2009) Multi-Agent based control framework for microgrids. 2009 Asia-Pacific Power and Energy Engineering Conference.
  • 65. Funabashi T, Fujita G, Koyanagi K, et al. (2006) Field tests of a microgrid control system. Proceedings of the 41st International Universities Power Engineering Conference.
  • 66. Kim H, Kinoshita T (2009) Multiagent system for microgrid operation based on power market environment. INTELEC 2009-31st International Telecommunications Energy Conference.
  • 67. Duan R, Deconinck G (2010) Multi-agent model and interoperability of a market mechanism of the smart grids. 2010 IEEE/IFIP Network Operations and Management Symposium Workshops.
  • 68. Funabashi T, Tanabe T, Nagata T, et al. (2008) An autonomous agent for reliable operation of power market and systems including microgrids. 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies, 173-177.
  • 69. Logenthiran T, Srinivasan D, Khambadkone AM, et al. (2010) Scalable multi-agent system (MAS) for operation of a microgrid in islanded mode. 2010 Joint International Conference on Power Electronics, Drives and Energy Systems & 2010 Power India, 1-6.
  • 70. Xu Y, Zhang L, Wang Z (2009) Research on service restoration for large area blackout of distribution system with distributed generators. 2009 International Conference on Sustainable Power Generation and Supply, 1-6.
  • 71. Li XD, Xu YQ, Zhang L (2009) Distribution service restoration with DGs based on multi-agent immune algorithm. 2009 2nd International Conference on Power Electronics and Intelligent Transportation System (PEITS), 1-4.
  • 72. Mancarella P (2014) MES (multi-energy systems): An overview of concepts and evaluation models. Energy 65: 1-17.    
  • 73. Radziszewska W, Nahorski Z, Parol M, et al. (2014) Intelligent Computations in an Agent-Based Prosumer-Type Electric Microgrid Control System. In: Kóczy LT, Pozna CR, Kacprzyk J, editors. Issues and Challenges of Intelligent Systems and Computational Intelligence. Cham: Springer International Publishing, 293-312.
  • 74. Nouvel R, Kaden R, Bahu J-M, et al. (2015) Genesis of the CityGML Energy ADE.
  • 75. Hussain A, Aslam M, Arif SM (2016) N-version programming-based protection scheme for microgrids: A multi-agent system based approach. Sustainable Energy, Grids Networks 6: 35-45.    
  • 76. Han Y, Zhang K, Li H, et al. (2017) MAS-based distributed coordinated control and optimization in microgrid and microgrid clusters: A comprehensive overview. IEEE Trans Power Electron 33: 6488-6508.
  • 77. Khan MW, Wang J (2017) The research on multi-agent system for microgrid control and optimization. Renewable Sustainable Energy Rev 80: 1399-1411.    
  • 78. Ju L, Zhang Q, Tan Z, et al. (2018) Multi-agent-system-based coupling control optimization model for micro-grid group intelligent scheduling considering autonomy-cooperative operation strategy. Energy 157: 1035-1052.    
  • 79. Mishra S, Bordin C, Tomasgard A, et al. (2019) A multi-agent system approach for optimal microgrid expansion planning under uncertainty. Int J Electr Power Energy Syst 109: 696-709.
  • 80. Davarzani S, Granell R, Taylor GA, et al. (2019) Implementation of a novel multi-agent system for demand response management in low-voltage distribution networks. Appl Energy 253: 113516.    


Reader Comments

your name: *   your email: *  

© 2019 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Copyright © AIMS Press All Rights Reserved