Coordinated Energy Management of Networked Microgrids in Distribution Systems

Wang, Zhaoyu; Chen, Bokan; Wang, Jianhui; Begović, Miroslav; Chen, Chen

doi:10.1109/tsg.2014.2329846

Cited by 527 publications

(259 citation statements)

References 39 publications

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“…Agents in the higher levels are responsible for the decision-making regarding the complex tasks, while the lower-level agents are accommodated to simpler tasks. Some other applications of hierarchal agent-based systems for smart grid and microgrid simulation are discussed in [203][204][205][206][207][208][209].…”

Section: Microgrid and Smart Grid Simulationmentioning

confidence: 99%

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

et al. 2018

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This survey provides a comprehensive analysis on recent research related to optimization and simulation in the new paradigm of power systems, which embraces the so-called smart grid. We start by providing an overview of the recent research related to smart grid optimization. From the variety of challenges that arise in a smart grid context, we analyze with a significance importance the energy resource management problem since it is seen as one of the most complex and challenging in recent research. The survey also provides a discussion on the application of computational intelligence, with a strong emphasis on evolutionary computation techniques, to solve complex problems where traditional approaches usually fail. The last part of this survey is devoted to research on large-scale simulation towards applications in electricity markets and smart grids. The survey concludes that the study of the integration of distributed renewable generation, demand response, electric vehicles, or even aggregators in the electricity market is still very poor. Besides, adequate models and tools to address uncertainty in energy scheduling solutions are crucial to deal with new resources such as electric vehicles or renewable generation. Computational intelligence can provide a significant advantage over traditional tools to address these complex problems. In addition, supercomputers or parallelism opens a window to refine the application of these new techniques. However, such technologies and approaches still need to mature to be the preferred choice in the power systems field. In summary, this survey provides a full perspective on the evolution and complexity of power systems as well as advanced computational tools, such as computational intelligence and simulation, while motivating new research avenues to cover gaps that need to be addressed in the coming years.

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Section: Microgrid and Smart Grid Simulationmentioning

confidence: 99%

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

et al. 2018

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“…This triad is also valuable for organising research efforts shedding light into these challenges. Technological adaptation-oriented research has contributed with knowledge on the integration of electricity storage in distribution systems [37][38][39][40][41], integration of distributed generation sources from wind [42][43][44], solar [45][46][47][48][49], CHP [50][51][52], and micro-CHP [53][54][55][56], integration of EVs [57][58][59][60], integration of smart meters [61][62][63][64][65][66], implementation of DR [67][68][69][70][71], deployment of active distribution management systems [72][73][74][75][76], and advanced grid monitoring and control [77][78][79], as well as the use of artificial intelligence methods [80][81][82], and machine learning applicati...…”

Section: Electricity Distribution Adaptation To a Smarter And More Sumentioning

confidence: 99%

The challenging paradigm of interrelated energy systems towards a more sustainable future

Soares

Martins

Carvalho³

et al. 2018

Renewable and Sustainable Energy Reviews

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This paper brings together several contemporary topics in energy systems aiming to provide a literature review based reflection on how several interrelated energy systems can contribute together to a more sustainable world. Some directions are discussed, such as the improvement of the energy efficiency and environmental performance of the systems, the development of new technologies, the increase of the use of renewable energy sources, the promotion of holistic and multidisciplinary studies, and the implementation of new management rules and "eco-friendly and sustainable" oriented policies at different scales. The interrelations of the diverse energy systems are also discussed in order to address their main social-economic-environmental impacts. The subjects covered include the assessment of the electricity market and its main players (demand, supply, distribution), the evaluation of some urban systems (buildings, transportation, commuting), the analysis of the implementation of renewable energy cooperatives, the discussion of the diffusion of the electric vehicle and the importance of new bioenergy systems. This paper also presents relevant research carried out in the framework of both the Energy for Sustainability Initiative of the University of Coimbra and the Sustainable Energy Systems focus area of the MIT-Portugal Program. To conclude, several research topics that should be addressed in the near future are proposed.

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“…With the increase in MG installations, integrated operation strategies for multiple MGs have been presented in several studies [6][7][8][9][10][11]. In community MGs, an optimal economic operating method is introduced through hierarchical optimization in [7].…”

Section: Introductionmentioning

confidence: 99%

Distributed Coordination Control Strategy for a Multi-Microgrid Based on a Consensus Algorithm

Lee¹,

Choi²,

Lee

et al. 2017

Energies

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Microgrids (MGs) in which power generation and consumption occur locally have gained prominence, and MG demonstration tests have been widely carried out. In accordance with the increase in the number of MG installations, studies regarding the cooperative control of multiple MGs are proceeding in various forms. In this paper, the distributed control strategy of a multi-microgrid (MMG) is proposed. Distributed control is the method in which agents of the electric power facility autonomously control their facility through communication with the neighboring agents only. In this process, a consensus algorithm is utilized to obtain the global information required to control the overall system. In this distributed control strategy, a single MG is operated at an optimal economic point using the equality incremental cost constraints while maintaining the balance between the generation and demand. The control strategy of a MMG is that the flow of the point of common coupling (PCC) is maintained at a particular value needed by the utility and the internal change in power is distributed to the MGs according to their reserves. The proposed algorithm is verified in the MG level and the MMG level through a simulation model using PSCAD/EMTDC software in the C language.

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Coordinated Energy Management of Networked Microgrids in Distribution Systems

Cited by 527 publications

References 39 publications

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

Survey on Complex Optimization and Simulation for the New Power Systems Paradigm

The challenging paradigm of interrelated energy systems towards a more sustainable future

Distributed Coordination Control Strategy for a Multi-Microgrid Based on a Consensus Algorithm

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