Topic Editors

School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
Prof. Dr. Qijun Deng
School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
College of Information Science and Engineering, Northeastern University, Shenyang 110819, China

Advances in Planning, Operation, Control/Protection, and Market of New Power Energy System

Abstract submission deadline
30 April 2026
Manuscript submission deadline
30 June 2026
Viewed by
2137

Topic Information

Dear Colleagues,

New power energy systems are composed of multiple interconnected energy supplies and consumption networks, such as power grids, oil and gas networks (including natural gas/hydrogen networks), cold and hot networks, transportation networks (including highway/railway/shipping/aviation, etc.), and communication/information networks (including data centers, supercomputing centers, etc.). Their key characteristic is that each energy-related network has a respective source, network, load, and storage in corresponding energy form, and there is a bidirectional coupling of energy flow and information flow between the primary energy network and the secondary communication/information network.

All energy networks are coordinated, scheduled, and controlled/protected by the communication/information network. Each individual energy network and multi-energy system's overall energy network, as well as each communication/information network, have their own planning, operation, control/protection, and market trading, with the goal of achieving balance, security, stability, efficiency, and low-carbon environmental protection during system operations under different time scales. This topic focuses on the innovative methods, key technologies, and applications in the planning, operation, control/protection, and marketing of new power energy systems, involving the integration of multiple disciplines and application areas such as electrical engineering, power engineering, transportation engineering, control engineering, communication engineering, computer science (including artificial intelligence), and mathematics (including network science, optimization theory, etc.). The scope of submissions includes, but is not limited to, the following:

  1. Planning methods and key technologies for new power energy systems;
  2. Operation methods and key technologies of new power energy systems;
  3. Control/protection methods and key technologies for new power energy systems;
  4. Progress in market mechanisms and clearing methods for new power energy systems.

Prof. Dr. Tao Lin
Prof. Dr. Qijun Deng
Dr. Xue Cui
Dr. Bowen Zhou
Topic Editors

Keywords

  • electric power systems
  • oil and gas systems
  • hydrogen transmission
  • power systems
  • transportation systems
  • communication and information systems
  • planning
  • operation
  • control
  • protection
  • energy-carbon market

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Applied Sciences
applsci
2.5 5.5 2011 19.8 Days CHF 2400 Submit
Electronics
electronics
2.6 6.1 2012 16.8 Days CHF 2400 Submit
Energies
energies
3.2 7.3 2008 16.2 Days CHF 2600 Submit
Mathematics
mathematics
2.2 4.6 2013 18.4 Days CHF 2600 Submit
Sustainability
sustainability
3.3 7.7 2009 19.3 Days CHF 2400 Submit

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Published Papers (3 papers)

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23 pages, 2742 KB  
Article
Optimal Bidding Framework for Integrated Renewable-Storage Plant in High-Dimensional Real-Time Markets
by Yuhao Song, Shaowei Huang, Laijun Chen, Sen Cui and Shengwei Mei
Sustainability 2025, 17(18), 8159; https://doi.org/10.3390/su17188159 - 10 Sep 2025
Viewed by 272
Abstract
With the development of electricity spot markets, the integrated renewable-storage plant (IRSP) has emerged as a crucial entity in real-time energy markets due to its flexible regulation capability. However, traditional methods face computational inefficiency in high-dimensional bidding scenarios caused by expansive decision spaces, [...] Read more.
With the development of electricity spot markets, the integrated renewable-storage plant (IRSP) has emerged as a crucial entity in real-time energy markets due to its flexible regulation capability. However, traditional methods face computational inefficiency in high-dimensional bidding scenarios caused by expansive decision spaces, limiting online generation of multi-segment optimal quotation curves. This paper proposes a policy migration-based optimization framework for high-dimensional IRSP bidding: First, a real-time market clearing model with IRSP participation and an operational constraint-integrated bidding model are established. Second, we rigorously prove the monotonic mapping relationship between the cleared output and the real-time locational marginal price (LMP) under the market clearing condition and establish mathematical foundations for migrating the self-dispatch policy to the quotation curve based on value function concavity theory. Finally, a generalized inverse construction method is proposed to decompose the high-dimensional quotation curve optimization into optimal power response subproblems within price parameter space, substantially reducing decision space dimensionality. The case study validates the framework effectiveness through performance evaluation of policy migration for a wind-dual energy storage plant, demonstrating that the proposed method achieves 90% of the ideal revenue with a 5% prediction error and enables reinforcement learning algorithms to increase their performance from 65.1% to 84.2% of the optimal revenue. The research provides theoretical support for resolving the “dimensionality–efficiency–revenue” dilemma in high-dimensional bidding and expands policy possibilities for IRSP participation in real-time markets. Full article
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18 pages, 5778 KB  
Article
Hierarchical Switching Control Strategy for Smart Power-Exchange Station in Honeycomb Distribution Network
by Xiangkun Meng, Wenyao Sun, Yi Zhao, Xiaoyi Qian and Yan Zhang
Sustainability 2025, 17(17), 7998; https://doi.org/10.3390/su17177998 - 5 Sep 2025
Viewed by 901
Abstract
The Honeycomb Distribution Network is a new distribution network architecture that utilizes the Smart Power-Exchange Station (SPES) to enable power interconnection and mutual assistance among multiple microgrids/distribution units, thereby supporting high-proportion integration of distributed renewable energy and promoting a sustainable energy transition. To [...] Read more.
The Honeycomb Distribution Network is a new distribution network architecture that utilizes the Smart Power-Exchange Station (SPES) to enable power interconnection and mutual assistance among multiple microgrids/distribution units, thereby supporting high-proportion integration of distributed renewable energy and promoting a sustainable energy transition. To promote the continuous and reliable operation of the Honeycomb Distribution Network, this paper proposes a Hierarchical Switching Control Strategy to address the issues of DC bus voltage (Udc) fluctuation in the SPES of the Honeycomb Distribution Network, as well as the state of charge (SOC) and charging/discharging power limitation of the energy storage module (ESM). The strategy consists of the system decision-making layer and the converter control layer. The system decision-making layer selects the main converter through the importance degree of each distribution unit and determines the control strategy of each converter through the operation state of the ESM’s SOC. The converter control layer restricts the ESM’s input/output active power—this ensures the ESM’s SOC and input/output active power stay within the power boundary. Additionally, it combines the Flexible Virtual Inertia Adaptive (FVIA) control method to suppress Udc fluctuations and improve the response speed of the ESM converter’s input/output active power. A simulation model built in MATLAB/Simulink is used to verify the proposed control strategy, and the results demonstrate that the strategy can not only effectively reduce Udc deviation and make the ESM’s input/output power reach the stable value faster, but also effectively avoid the ESM entering the unstable operation area. Full article
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23 pages, 4283 KB  
Article
Charging Incentive Design with Minimum Price Guarantee for Battery Energy Storage Systems to Mitigate Grid Congestion
by Yujiro Tanno, Akihisa Kaneko, Yu Fujimoto, Yasuhiro Hayashi, Yuji Hanai and Hideo Koseki
Energies 2025, 18(11), 2840; https://doi.org/10.3390/en18112840 - 29 May 2025
Viewed by 516
Abstract
The large-scale integration of renewable energy sources (RESs) has raised concerns regarding grid congestion in Japan. Battery energy storage systems (BESSs) can mitigate congestion by adjusting charging schedules; however, BESS owners basically prioritize market arbitrage, which may not be aligned with congestion mitigation. [...] Read more.
The large-scale integration of renewable energy sources (RESs) has raised concerns regarding grid congestion in Japan. Battery energy storage systems (BESSs) can mitigate congestion by adjusting charging schedules; however, BESS owners basically prioritize market arbitrage, which may not be aligned with congestion mitigation. This paper proposes a charging incentive design to guide arbitrage-oriented BESS charging toward time periods that are effective for grid congestion mitigation. The system operator predicts congested hours and ensures that BESS owners can purchase electricity at the lowest daily market price. This design intends to shift the BESS charging time towards congestion periods. Because market prices tend to decline during congestion periods, the proposed method reduces the operator’s financial burden while encouraging congestion-mitigating charging behavior. Numerical simulations using a simplified Japanese east-side power system model demonstrate that the proposed method reduced the congestion mitigation costs by 3.86% and curtailed the RES output by 3.89%, compared to using no incentive method (current operation in Japan). Furthermore, additional payments to BESS owners accounted for only around 7% of the resulting cost savings, indicating that the proposed method achieved lower overall system operating costs. Full article
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