A Decentralized Model for Coordinated Operation of Distribution Network and EV Aggregators

Mohiti, Maryam; Monsef, Hassan; Mazidi, Mohammadreza; Anvari‐Moghaddam, Amjad

doi:10.1109/eeeic.2018.8494429

Cited by 3 publications

(2 citation statements)

References 19 publications

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“…Sustainability 2022, 14, 15747 3 of 25 usage modeling [39], the coordinated operation of the distribution network and EV aggregators [40], and different frameworks introduced for the optimal design of EVs systems [41]. Remarkable efforts have been made around EVAs in recent years due to the positive effect of such aggregators in demand-side management.…”

Section: Literature Review and Detailed Discussionmentioning

confidence: 99%

An Updated Review and Outlook on Electric Vehicle Aggregators in Electric Energy Networks

2022

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Electric vehicles (EVs) are predicted to be highly integrated into future smart grids considering their significant role in achieving a safe environment and sustainable transportation. The charging/discharging flexibility of EVs, which can be aggregated by an agent, provides the opportunity of participating in the demand-side management of energy networks. The individual participation of consumers at the system level would not be possible for two main reasons: (i) In general, their individual capacity is below the required minimum to participate in power system markets, and (ii) the number of market participants would be large, and thus the volume of individual transactions would be difficult to manage. In order to facilitate the interactions between consumers and the power grid, an aggregation agent would be required. The EV aggregation area and their integration challenges and impacts on electricity markets and distribution networks is investigated in much research studies from different planning and operation points of view. This paper aims to provide a comprehensive review and outlook on EV aggregation models in electrical energy systems. The authors aim to study the main objectives and contributions of recent papers and investigate the proposed models in such areas in detail. In addition, this paper discusses the primary considerations and challenging issues of EV aggregators reported by various research studies. In addition, the proposed research outlines the future trends around electric vehicle aggregators and their role in electrical energy systems.

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Section: Literature Review and Detailed Discussionmentioning

confidence: 99%

An Updated Review and Outlook on Electric Vehicle Aggregators in Electric Energy Networks

2022

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“…The saddle point of the primal‐dual Lagrangian‐based methods could not always lead to the optimal solution, despite their more general structure [10]. The most well‐known distributed method over recent years is ADMM due to its flexible structure and advantage of convergence to the optimum point after finite iterations [11]. However, in this paper, a new approach based on the primal‐dual method of multipliers (PDMM) is suggested as a distributed optimization method.…”

Section: Introductionmentioning

confidence: 99%

A multi‐agent privacy‐preserving energy management framework for renewable networked microgrids

Tajalli

Kavousi‐Fard

Mardaneh

et al. 2023

IET Generation Trans & Dist

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This paper proposes a fully distributed scheme to solve the day‐ahead optimal power scheduling of networked microgrids in the presence of different renewable energy resources, such as photovoltaics and wind turbines, considering energy storage systems. The proposed method enables the optimization of the power scheduling problem through local computation of agents in the system and private communication between existing agents, without any centralized scheduling unit. In this paper, a cloud‐fog‐based framework is also introduced as a fast and economical infrastructure for the proposed distributed method. The suggested optimized energy framework proposes an area to regulate and update policies, detect misbehaving elements, and execute punishments centrally, while the general power scheduling problem is optimized in a distributed manner using the proposed method. The suggested cloud‐fog‐based method eliminates the need to invest in local databases and computing systems. The proposed scheme is examined on a small‐scale microgrid and also a larger test networked microgrid, including 4 microgrids and 15 areas in a 24‐h time period, to illustrate the scalability, convergence, and accuracy of the framework. The simulation results substantiate the fast and precise performance of the proposed framework for networked microgrids compared with other existing centralized and distributed methods.

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Energy management system for smart grid: An overview and key issues

2020

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Summary Energy crisis and the global impetus to “go green” have encouraged the integration of renewable energy resources, plug‐in electric vehicles, and energy storage systems to the grid. The presence of more than one energy source in the grid necessitates the need for an efficient energy management system to guide the flow of energy. Moreover, the variability and volatile nature of renewable energy sources, uncertainties associated with plug‐in electric vehicles, the electricity price, and the time‐varying load bring new challenges to the power engineers to achieve demand‐supply balance for stable operation of the power system. The energy management system can effectively coordinate the energy sharing/trading among all available energy resources, and supply loads economically in all the conditions for the reliable, secure, and efficient operation of the power system. This paper reviews the framework, objectives, architecture, benefits, and challenges of the energy management system with a comprehensive analysis of different stakeholders and participants involved in it. The review paper gives a critical analysis of the distributed energy resources behavior and different programs such as demand response, demand‐side management, and power quality management implemented in the energy management system. Different uncertainty quantification methods are also summarized. This review paper also presents a comparative and critical analysis of the main optimization techniques used to achieve different energy management system objectives while satisfying multiple constraints. Thus, the review offers numerous recommendations for research and development of the cutting‐edge optimized energy management system applicable for homes, buildings, industries, electric vehicles, and the whole community.

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A Decentralized Model for Coordinated Operation of Distribution Network and EV Aggregators

Cited by 3 publications

References 19 publications

An Updated Review and Outlook on Electric Vehicle Aggregators in Electric Energy Networks

An Updated Review and Outlook on Electric Vehicle Aggregators in Electric Energy Networks

A multi‐agent privacy‐preserving energy management framework for renewable networked microgrids

Energy management system for smart grid: An overview and key issues

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