Arabian Journal for Science and Engineering, Год журнала: 2024, Номер 49(12), С. 16919 - 16939
Опубликована: Июль 14, 2024
Язык: Английский
Arabian Journal for Science and Engineering, Год журнала: 2024, Номер 49(12), С. 16919 - 16939
Опубликована: Июль 14, 2024
Язык: Английский
Journal of Energy Storage, Год журнала: 2023, Номер 69, С. 107981 - 107981
Опубликована: Июнь 16, 2023
Язык: Английский
Процитировано
169Journal of Energy Storage, Год журнала: 2023, Номер 78, С. 109888 - 109888
Опубликована: Дек. 14, 2023
Язык: Английский
Процитировано
132Sustainable Cities and Society, Год журнала: 2024, Номер 103, С. 105264 - 105264
Опубликована: Фев. 8, 2024
In this study, an intelligent and data-driven hierarchical energy management approach considering the optimal participation of renewable resources (RER), storage systems (ESSs) integrated demand response (IDR) programs execution based on wholesale retail market signals in multi-integrated system (MIES) structure is presented. The proposed objective function presented four levels, which include minimizing operating costs, environmental pollution risk reducing destructive effects cyberattacks such as false data injection (FDI). implemented central controller local multi-agent deep reinforcement learning method (MADRL). MADRL model formulated Markov decision process equations solved by soft actor-critic Q-learning algorithms two levels offline training online operation. different scenario results show operation cost reduction equivalent to 19.51%, 19.69%, cyber security 24%, 20.24%. has provided important step responding smart cities challenges requirements advantage fast response, high accuracy also computational time burden.
Язык: Английский
Процитировано
33Nature Reviews Electrical Engineering, Год журнала: 2024, Номер 1(3), С. 163 - 179
Опубликована: Фев. 9, 2024
Язык: Английский
Процитировано
28Electric Power Systems Research, Год журнала: 2023, Номер 225, С. 109856 - 109856
Опубликована: Сен. 15, 2023
Язык: Английский
Процитировано
42Energy Strategy Reviews, Год журнала: 2024, Номер 52, С. 101306 - 101306
Опубликована: Фев. 1, 2024
Energy management in Micro Grids (MG) has become increasingly difficult as stochastic Renewable Sources (RES) and Electric Vehicles (EV) have more prevalent. Even challenging is autonomous MG operation with RES since prompt frequency control required. We provide an innovative Management Strategy (EMS) for grid support this academic publication. By integrating EV storage, we seek to decrease reliance on the grid. The EMS consists of three execution phases: Ranking Recommendation (RER), Optimal Power Allocation (OPA) Fleet, Storage (OAES). aim slicing time smaller intervals update energy power scheduling shorter per changes are going system. period 24 h divided into 96 (t) storage requirements (kWh/t) estimated based load together necessary volume. employ approaches that frequently used communication channel allocation optimization accomplish OAES. With two objectives: minimum network loss plus voltage fluctuations, Multi-Objective Optimization Problem (MOOP) solved each 't' OAES Flow (OPF). Pareto-front calculate best amount from fleet 't'. data received fuzzy rule base third stage train intelligent Convolutional Neural Network (CNN), which rank output four decision variables inputs. main goals minimize battery degradation make most it support. aid a MATLAB-based simulation setup heterogeneous entities, primary goal examined put practice On-grid MG.
Язык: Английский
Процитировано
18Electric Power Systems Research, Год журнала: 2024, Номер 232, С. 110372 - 110372
Опубликована: Апрель 8, 2024
Язык: Английский
Процитировано
15Journal of Energy Storage, Год журнала: 2024, Номер 90, С. 111657 - 111657
Опубликована: Май 17, 2024
Язык: Английский
Процитировано
11Process Integration and Optimization for Sustainability, Год журнала: 2025, Номер unknown
Опубликована: Фев. 13, 2025
Язык: Английский
Процитировано
2Energy, Год журнала: 2023, Номер 286, С. 129435 - 129435
Опубликована: Ноя. 12, 2023
Язык: Английский
Процитировано
17