Sustainable Cities and Society, Год журнала: 2023, Номер 101, С. 105166 - 105166
Опубликована: Дек. 27, 2023
Язык: Английский
Sustainable Cities and Society, Год журнала: 2023, Номер 101, С. 105166 - 105166
Опубликована: Дек. 27, 2023
Язык: Английский
Expert Systems with Applications, Год журнала: 2024, Номер 250, С. 123729 - 123729
Опубликована: Март 22, 2024
Язык: Английский
Процитировано
64Sustainable Cities and Society, Год журнала: 2023, Номер 99, С. 104908 - 104908
Опубликована: Сен. 10, 2023
Язык: Английский
Процитировано
37Energies, Год журнала: 2024, Номер 17(3), С. 715 - 715
Опубликована: Фев. 2, 2024
The increasing impact of climate change and rising occurrences natural disasters pose substantial threats to power systems. Strengthening resilience against these low-probability, high-impact events is crucial. proposition reconfiguring traditional systems into advanced networked microgrids (NMGs) emerges as a promising solution. Consequently, growing body research has focused on NMG-based techniques achieve more resilient system. This paper provides an updated, comprehensive review the literature, particularly emphasizing two main categories: microgrids’ configuration control. study explores key facets NMG configurations, covering formation, distribution, operational considerations. Additionally, it delves control features, examining their architecture, modes, schemes. Each aspect reviewed based problem modeling/formulation, constraints, objectives. examines findings highlights gaps, focusing elements such frequency voltage stability, reliability, costs associated with remote switches communication technologies, overall network. On that basis, unified problem-solving approach addressing both aspects stable reliable NMGs proposed. article concludes by outlining potential future trends, offering valuable insights for researchers in field.
Язык: Английский
Процитировано
14Sustainable Cities and Society, Год журнала: 2024, Номер 107, С. 105448 - 105448
Опубликована: Апрель 22, 2024
Язык: Английский
Процитировано
13Deleted Journal, Год журнала: 2025, Номер 7(3)
Опубликована: Фев. 25, 2025
Язык: Английский
Процитировано
1Applied Sciences, Год журнала: 2023, Номер 13(5), С. 2865 - 2865
Опубликована: Фев. 23, 2023
The multi-microgrid (MMG) system has attracted more and attention due to its low carbon emissions flexibility. This paper proposes a multi-agent reinforcement learning algorithm for real-time energy management of an MMG. In this problem, the MMG is connected distribution network (DN). operator (DSO) each microgrid (MG) are modeled as autonomous agents. Each agent makes decisions suit interests based on local information. decision-making problem multiple agents Markov game solved by prioritized deep deterministic policy gradient (PMADDPG), where only observation required make decisions, centralized training mechanism applied learn coordination strategy, experience replay (PER) strategy adopted improve efficiency. proposed method can deal with non-stationary problems in process partial observable execution stage, all trained deployed distributed manner real time. Simulation results show that according method, accelerated, optimal
Язык: Английский
Процитировано
12Environmental Science and Pollution Research, Год журнала: 2023, Номер 30(48), С. 105646 - 105664
Опубликована: Сен. 16, 2023
Язык: Английский
Процитировано
11Green Energy and Intelligent Transportation, Год журнала: 2025, Номер unknown, С. 100263 - 100263
Опубликована: Янв. 1, 2025
Язык: Английский
Процитировано
0Sustainable Cities and Society, Год журнала: 2023, Номер 95, С. 104589 - 104589
Опубликована: Апрель 14, 2023
Язык: Английский
Процитировано
10IET Renewable Power Generation, Год журнала: 2024, Номер 18(11), С. 1798 - 1818
Опубликована: Июль 9, 2024
Abstract The reliability‐oriented optimized sizing and placement of electric vehicle (EV) charging stations (EVCSs) has received less attention. In addition, the literature review shows that a research gap exists regarding clustering‐based method to optimize allocation DGs EVCSs, considering system uncertainties. This article tries fill such knowledge by proposing new EVs simultaneously, uncertainties EV behaviours stochastic renewable DGs. Developing model for using clustering algorithm is one essential contributions. uncertain parameters, e.g. loads based on owners’ (arrival time, departure driving distance) DGs, would be clustered. proposed could solve execution time challenges Monte Carlo simulation‐based approaches concern smart grids. simultaneously optimal protection equipment, another main contribution. IEEE 33‐bus test studied examine introduced method. Simulation results imply 1.45% accuracy improvement obtained compared available analytical ones, while its appropriate.
Язык: Английский
Процитировано
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