Optimal Allocation of Shared Energy Storage Capacity Considering Source-Load Interconnection in Multiple Distribution Transformer Areas DOI
Xin Zhang,

Chenming Sun,

Hui Meng

et al.

Published: Dec. 13, 2024

Language: Английский

China's Energy System Building Toward an Era of Resilience: How Green Fintech Can Empower? DOI Creative Commons
Yarong Shi, Bo Yang

International Review of Economics & Finance, Journal Year: 2025, Volume and Issue: unknown, P. 103876 - 103876

Published: Jan. 1, 2025

Language: Английский

Citations

4

Shared energy storage-multi-microgrid operation strategy based on multi-stage robust optimization DOI

Tana Siqin,

Shan He,

Bing Hu

et al.

Journal of Energy Storage, Journal Year: 2024, Volume and Issue: 97, P. 112785 - 112785

Published: July 13, 2024

Language: Английский

Citations

11

Multi-objective configuration optimization model of shared energy storage on the power side DOI
Jicheng Liu, Yanan Song

Journal of Energy Storage, Journal Year: 2025, Volume and Issue: 114, P. 115706 - 115706

Published: Feb. 10, 2025

Language: Английский

Citations

1

Advancing Power Systems with Renewable Energy and Intelligent Technologies: A Comprehensive Review on Grid Transformation and Integration DOI Open Access
Muhammed Cavus

Electronics, Journal Year: 2025, Volume and Issue: 14(6), P. 1159 - 1159

Published: March 15, 2025

The global energy landscape is witnessing a transformational shift brought about by the adoption of renewable technologies along with power system modernisation. Distributed generation (DG), smart grids (SGs), microgrids (MGs), and advanced storage systems (AESSs) are key enablers sustainable resilient future. This review deepens analysis fulminating change in systems, detailing growth wind solar integration, next-generation high-voltage direct current (HVDC) transmission systems. Moreover, we address important aspects such as monitoring, protection, control, dynamic modelling distribution metering infrastructure (AMI) development. Emphasis laid on involvement artificial intelligence (AI) techniques optimised grid operation, voltage stability, integration lifetime resources islanding hosting capacities. paper reviews advancements their applications, enabling identification opportunities challenges to be addressed toward achieving modern, intelligent, efficient infrastructure. It wraps up perspective future research paths well discussion potential hybrid models that integrate AI machine learning (ML) distributed (DESs) improve grid’s resilience sustainability.

Language: Английский

Citations

1

Review of Modelling and Optimal Control Strategy for Virtual Energy Storage DOI Creative Commons
Bowen Zhou, Yichen Jiang, Yanhui Zhang

et al.

IET Generation Transmission & Distribution, Journal Year: 2025, Volume and Issue: 19(1)

Published: Jan. 1, 2025

ABSTRACT VES is a method of balancing the energy power system with other equipment or scheduling strategies, particularly respect to controllable loads, owing end‐user electrification. This paper summarises connotations, classifications, and typical modelling applications for users. Thereafter, methods, characteristics, specific operation cases five types VESs are introduced, including electric vehicles, buildings, cold storage, industrial production hydrogen storage. Furthermore, storage capacity planning, strategy, control strategy VESS realised through optimal strategies. Finally, in conjunction demand response, development prospects strategies discussed improve economic environmental benefits microgrids.

Language: Английский

Citations

0

Coordinated Optimal Dispatch of Distribution Grids and P2P Energy Trading Markets DOI Creative Commons
Jing Deng,

Fawu He,

Qingbin Zeng

et al.

Energy Science & Engineering, Journal Year: 2025, Volume and Issue: unknown

Published: March 24, 2025

ABSTRACT With the increasing integration of distributed renewable energy, traditional power users are evolving into prosumers capable both generation and consumption. However, their decentralized nature poses challenges in resource coordination. This study proposes a bi‐level optimization framework for distribution networks integrating peer‐to‐peer (P2P) energy trading shared storage. The upper‐level model minimizes system operator (DSO) operational costs, including network losses storage management, while ensuring voltage stability. lower‐level enables to maximize P2P market profits through adaptive load adjustments utilization. To address nonlinear, high‐dimensional challenges, an improved Convex‐Soft Actor‐Critic (C‐SAC) algorithm is developed, combining deep reinforcement learning with convex achieve privacy‐preserving Case studies on IEEE 33‐node demonstrate that increases prosumer by 56.9%, reduces DSO costs 23.6%, lowers 21.5% compared non‐cooperative scenarios. capacity requirements 20% 14.1%, respectively. C‐SAC outperforms methods (DDPG, SAC) convergence speed economic metrics, showing scalability across larger systems (IEEE 69/118 nodes). work provides model‐free solution renewable‐rich networks, balancing efficiency security.

Language: Английский

Citations

0

Two-stage optimization configuration of shared energy storage for multi-distributed photovoltaic clusters in rural distribution networks considering self-consumption and self-sufficiency DOI

K. Kang,

Heping Jia, Hongxun Hui

et al.

Applied Energy, Journal Year: 2025, Volume and Issue: 394, P. 126174 - 126174

Published: May 24, 2025

Language: Английский

Citations

0

AADMM based shared energy storage planning for resilience improvement of renewable energy stations DOI Creative Commons

Long Zhi Zhao,

Jinping Zhang,

Qingquan Lv

et al.

Frontiers in Energy Research, Journal Year: 2024, Volume and Issue: 12

Published: Sept. 10, 2024

The exponential proliferation of renewable energy has resulted in a significant mismatch between power supply and demand, especially during extreme events. This incongruity presents challenges efficiently harnessing enhancing the resilience grid. To address this issue, paper proposes shared storage (SES) planning based on adaptive alternating direction method multipliers (AADMM). objective is to fully leverage SES, enhance local consumption level energy, ensure grid resilience, reduce operational costs. First, effective utilization SES while minimizing initial investment construction costs, model for formulated. Secondly, maximize benefits multiple prosumers within station, profit maximization established. Lastly, guarantee privacy security multi-prosumers optimizing computational efficiency, distributed computing AADMM developed. results example show that proposed can not only cost 47.96 CNY, but also increase self-sufficiency rate by 21.86%. In addition, compared with traditional optimization, number iterations increased 47.05%, efficiency 54.67%. market prices have great impact trading, pricing operation park considered our current research. case, future research aims consider how price reasonably so as realize stable participation each subject market.

Language: Английский

Citations

0

Safety Assessment for Intelligent Distribution Networks in Multiple Scenarios DOI
Rui Li, Ming Wang, Yang Zhao

et al.

2022 IEEE 17th Conference on Industrial Electronics and Applications (ICIEA), Journal Year: 2024, Volume and Issue: unknown, P. 1 - 5

Published: Aug. 5, 2024

Language: Английский

Citations

0

Optimal Allocation of Shared Energy Storage Capacity Considering Source-Load Interconnection in Multiple Distribution Transformer Areas DOI
Xin Zhang,

Chenming Sun,

Hui Meng

et al.

Published: Dec. 13, 2024

Language: Английский

Citations

0