Integrating Protection Constraints to a MEAN-Based Method for Service Restoration in Radial Distribution Systems

Vieira, Andrey R; Batista, Vitor S; Júnior, G. Cardoso; Vieira, Joao Paulo Abreu

doi:10.1016/j.epsr.2020.106851

Cited by 5 publications

(2 citation statements)

References 14 publications

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“…Widiputra et al [146] developed a novel restoration algorithm that uses discrete PSO to solve the clod load pick up and conservation voltage reduction problems in service restoration. Vieira et al [147] integrated the protection constraints in service restoration for a distributed power network by using the multi-objective evolutionary algorithm to enhance the protection efficiency of the device. Ma et al [148] proposed a three-level optimization problem to minimize the investment and load-shedding costs during extreme weather events, and applied the greedy searching algorithm to optimize the formulation proposed in a multi-study of scenarios.…”

Section: Restorationmentioning

confidence: 99%

Energy Management System in Microgrids: A Comprehensive Review

et al. 2021

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As promising solutions to various social and environmental issues, the generation and integration of renewable energy (RE) into microgrids (MGs) has recently increased due to the rapidly growing consumption of electric power. However, such integration can affect the stability and security of power systems due to its complexity and intermittency. Therefore, an optimal control approach is essential to ensure the efficiency, reliability, and quality of the delivered power. In addition, effective planning of policies for integrating MGs can help promote MG operations. However, outages may render these strategies inefficient and place the power system at risk. MGs are considered an ideal candidate for distributed power systems, given their capability to restore these systems rapidly after a physical or cyber-attack and create reliable protection systems. The energy management system (EMS) in an MG can operate controllable distributed energy resources and loads in real-time to generate a suitable short-term schedule for achieving some objectives. This paper presents a comprehensive review of MG elements, the different RE resources that comprise a hybrid system, and the various types of control, operating strategies, and goals in an EMS. A detailed explanation of the primary, secondary, and tertiary levels of MGs is also presented. This paper aims to contribute to the policies and regulations adopted by certain countries, their protection schemes, transactive markets, and load restoration in MGs.

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Section: Restorationmentioning

confidence: 99%

Energy Management System in Microgrids: A Comprehensive Review

et al. 2021

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“…Secondly, although various important technology developments and advancements, such as distributed generators (DG) [19], microgrids [20, 21], digital relay protection [22], mobile emergency generators [18], cooperation between dispatchers and maintenance crews [23], have been studied in distribution system restoration, there still exist many unsolved issues in the context of active distribution system (ADS). The challenge lies in the work flows of SR that is susceptible to management, distribution technology, and actual environment [24].…”

Section: Introductionmentioning

confidence: 99%

Incorporating public feedback in service restoration for electric distribution networks

Zhong

Wang

Xie

et al. 2023

IET Generation Trans & Dist

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Power outages in urban area carry heavy social and economic costs. Although social cost, especially public sentiment, is concerned by engineers and managers, it has been only qualitatively investigated without a rigorous model in the state-of-the-art research and practice of service restoration (SR) for a long time. To fill this gap, this paper investigates a hybrid model which takes public sentiment into consideration by quantifying public sentiment triggered by power outage. Furthermore, conventional SR method focused on the optimization model with ideal conditions, which leaves a large room for improvement in complex environment. To improve the robustness of the model, the authors propose a reinforcement learning framework to analyze emergency management process without prior rules. At each time step, the optimal decision can be made automatically by a learned model. The numerical simulations with modified IEEE 33-bus and IEEE 123-bus systems demonstrate the effectiveness of the proposed method.

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