A review on multi-agent systems in microgrid applications

Kulasekera, Asitha L.; Gopura, R. A. R. C.; Hemapala, K.T.M.U.; Perera, N.

doi:10.1109/iset-india.2011.6145377

Cited by 47 publications

(13 citation statements)

References 42 publications

(53 reference statements)

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“…In both these studies the multi-agent control system was able to learn occupancy trends and optimize building energy demand. MAS have also gained popularity in other fields of energy as well, a review on MAS applied on microgrid systems can be found in (Kulasekera et al 2011).…”

Section: Discussionmentioning

confidence: 99%

Computational intelligence techniques for HVAC systems: A review

et al. 2016

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Buildings are responsible for 40% of global energy use and contribute towards 30% of the total CO 2 emissions. The drive to reduce energy use and associated greenhouse gas emissions from buildings has acted as a catalyst in the development of advanced computational methods for energy efficient design, management and control of buildings and systems. Heating, ventilation and air-conditioning (HVAC) systems are the major source of energy consumption in buildings and ideal candidates for substantial reductions in energy demand. Significant advances have been made in the past decades on the application of computational intelligence (CI) techniques for HVAC design, control, management, optimization, and fault detection and diagnosis. This article presents a comprehensive and critical review on the theory and applications of CI techniques for prediction, optimization, control and diagnosis of HVAC systems. The analysis of trends reveals that the minimisation of energy consumption was the key optimization objective in the reviewed research, closely followed by the optimization of thermal comfort, indoor air quality and occupant preferences.Hardcoded Matlab program was the most widely used simulation tool, followed by TRNSYS, EnergyPlus, DOE-2, HVACSim+ and ESP-r. Metaheuristic algorithms were the preferred CI method for solving HVAC related problems and in particular genetic algorithms were applied in most of the studies. Despite the low number of studies focussing on multi-agent systems (MAS), as compared to the other CI techniques, interest in the technique is increasing due to their ability of dividing and conquering an HVAC optimization problem with enhanced overall performance. The paper also identifies prospective future advancements and research directions.

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Section: Discussionmentioning

confidence: 99%

Computational intelligence techniques for HVAC systems: A review

et al. 2016

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“…The concept of MAS has been wide applied to various problems in microgrid research, such as power management [12], distributed optimization [13], active power and reactive power control [14]. Existing MAS based applications in power systems are usually rule-based and lacked rigorous stability analysis.…”

Section: Introductionmentioning

confidence: 99%

“…Multi-agent system (MAS) is one of the most popular distributed control approaches in literature [11]- [14]. The concept of MAS has been wide applied to various problems in microgrid research, such as power management [12], distributed optimization [13], active power and reactive power control [14].…”

Section: Introductionmentioning

confidence: 99%

Distributed Subgradient-Based Coordination of Multiple Renewable Generators in a Microgrid

Zhang

Liu

et al. 2014

IEEE Trans. Power Syst.

103

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Abstract-For a microgrid with high renewable energy penetration to work autonomously, it must maintain its own supply-demand balance of active power. Maximum peak power tracking algorithms, which emphasize high renewable energy utilization, may cause a supply-demand imbalance when the available renewable generation is more than demanded, especially for autonomous microgrids. Currently, droop control is one of the most popular decentralized methods for sharing active and reactive loads among the distributed generators. However, conventional droop control methods suffer from slow and oscillating dynamic response and steady state deviations. To overcome these problems, this paper proposes a distributed subgradient-based solution to coordinate the operations of different types of distributed renewable generators in a microgrid. By controlling the utilization levels of renewable generators, the supply-demand balance can be well maintained and the system dynamic performance can be significantly improved. Simulation results demonstrate the effectiveness of the proposed control solution.

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“…Some researchers such as [23][24][25][26][27][28][29][30] have proposed frameworks and guidelines for the design, modeling and development of MAS with a correct view on how they should act, interact, socialize and pursue the goal, which is the power management solution of their power system. It is not intended to classify solutions in the microgrids as in [31][32][33] and for MAS as presented at [34][35][36].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Framework for Energy Management System of a Smart Microgrid Using Multiagent Systems

et al. 2018

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This paper presents a framework to analyze the problem of real-time management of Smart Grids. For this purpose, the energy management is integrated with the power system through a telecommunication system. The use of Multiagent Systems (MAS) leads the proposed algorithm to find the best-integrated solution, taking into consideration the operating scenario and the system characteristics. With this framework it was possible to evaluate the design of the energy management and the impact of the algorithm developed in the MAS. In the same way, the data sent from the power system to be used for energy management have a direct impact on his behavior. The proposed framework is tested with the help of a microgrid, so the results may be replicated.

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A review on multi-agent systems in microgrid applications

Cited by 47 publications

References 42 publications

Computational intelligence techniques for HVAC systems: A review

Computational intelligence techniques for HVAC systems: A review

Distributed Subgradient-Based Coordination of Multiple Renewable Generators in a Microgrid

Real-Time Framework for Energy Management System of a Smart Microgrid Using Multiagent Systems

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