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Energies
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Flexibility Regulation and Operational Optimization of New-Type Power Systems
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Flexibility Regulation and Operational Optimization of New-Type Power Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F1: Electrical Power System".

Deadline for manuscript submissions: closed (15 May 2026) | Viewed by 1731

Special Issue Editors

Dr. Honggang Fan

E-Mail Website
Guest Editor
State Key Laboratory of Hydroscience and Engineering, Department of Energy and Power Engineering, Tsinghua University, Beijing 100084, China
Interests: flexibility regulation; joint operation control of cascaded hydropower stations; engineering optimized scheduling; inverse problem computation
Dr. Tao Zhang

E-Mail Website
Guest Editor
Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education, School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing 100083, China
Interests: operational optimization of integrated energy system; virtual power plant; new- type energy planning

Special Issue Information

Dear Colleagues,

As the world moves towards sustainable development, traditional fossil-fuel-based power systems are giving way to new-type ones with high renewable energy penetration. However, renewable sources, such as wind and solar, are intermittent and volatile, causing power generation fluctuations that disrupt supply-demand balance, risking power quality and system stability. To tackle this, flexibility regulation allows the system to swiftly adjust generation, consumption, and storage in response to changes, accommodating renewable variability for a reliable power supply. Given the complexity of integrating multiple energy sources and advanced tech, it uses algorithms to optimize resource dispatch and management, minimizing costs and emissions while boosting reliability.

This Special Issue aims to present and disseminate the most recent advances related to the theory, design, modeling, and application control of all types of new-type power systems.

Topics of interest for publication include, but are not limited to, the following:

  • Computation intelligence in electrical engineering;
  • Distributed generation, fuel cells and renewable;
  • Energy systems and flexibility regulation;
  • Joint operation control of cascaded hydropower stations;
  • Engineering optimized scheduling;
  • Intelligent control systems;
  • Intelligent systems and approach;
  • Power system modeling, simulation and analysis;
  • Predictive control;
  • Operational optimization of integrated energy systems;
  • Virtual power plant;
  • New-type energy planning.

Dr. Honggang Fan
Dr. Tao Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Energies is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • operational optimization
  • integrated energy system
  • virtual power plant
  • new-type energy planning
  • flexibility regulation

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Published Papers (3 papers)

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Research

22 pages, 1502 KB  
Article
Optimal Joint Scheduling and Forecasting of Photovoltaic and Wind Power Generation Based on Transformer-BiLSTM
by Wei Luo, Liyuan Zhu, Defa Cao, Wei Wu, Yi Yang, Jiamin Zhang and Long Wang
Energies 2026, 19(7), 1651; https://doi.org/10.3390/en19071651 - 27 Mar 2026
Viewed by 436
Abstract
Addressing the challenge of coordinated dispatch between wind/solar and thermal power in new energy grids, this research proposes a thermal power unit output prediction method based on a Transformer-BiLSTM hybrid deep learning model. First, a simulated annealing algorithm optimizes the output configuration of [...] Read more.
Addressing the challenge of coordinated dispatch between wind/solar and thermal power in new energy grids, this research proposes a thermal power unit output prediction method based on a Transformer-BiLSTM hybrid deep learning model. First, a simulated annealing algorithm optimizes the output configuration of solar thermal power plants to mitigate fluctuations in wind and solar combined generation. An ant colony-greedy algorithm is then integrated to determine the optimal dispatch data for thermal power units, constructing a high-quality training dataset under physical constraints. In the model design, a bidirectional long short-term memory network captures short-term temporal features, while the Transformer’s multi-head self-attention mechanism models long-term dependencies. The model innovatively incorporates the learnable positional encoding to enhance temporal awareness. Experimental results demonstrate accurate predictions, with the power constraint mechanism effectively correcting over-limit forecasts. This ensures 98.7% of predictions during low-load periods comply with unit technical specifications. Compared to existing methods, this model avoids data limitations and manual feature engineering bottlenecks through the end-to-end wind–solar–thermal mapping, providing a high-precision solution for dispatch decisions in renewable-dominated grids. Full article
(This article belongs to the Special Issue Flexibility Regulation and Operational Optimization of New-Type Power Systems)
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25 pages, 2729 KB  
Article
Restoration of Distribution Network Power Flow Solutions Considering the Conservatism Impact of the Feasible Region from the Convex Inner Approximation Method
by Zirong Chen, Yonghong Huang, Xingyu Liu, Shijia Zang and Junjun Xu
Energies 2026, 19(3), 609; https://doi.org/10.3390/en19030609 - 24 Jan 2026
Viewed by 441
Abstract
Under the “Dual Carbon” strategy, high-penetration integration of distributed generators (DG) into distribution networks has triggered bidirectional power flow and reactive power-voltage violations. This phenomenon undermines the accuracy guarantee of conventional relaxation models (represented by second-order cone programming, SOCP), causing solutions to deviate [...] Read more.
Under the “Dual Carbon” strategy, high-penetration integration of distributed generators (DG) into distribution networks has triggered bidirectional power flow and reactive power-voltage violations. This phenomenon undermines the accuracy guarantee of conventional relaxation models (represented by second-order cone programming, SOCP), causing solutions to deviate from the AC power flow feasible region. Notably, ensuring solution feasibility becomes particularly crucial in engineering practice. To address this problem, this paper proposes a collaborative optimization framework integrating convex inner approximation (CIA) theory and a solution recovery algorithm. First, a system relaxation model is constructed using CIA, which strictly enforces ACPF constraints while preserving the computational efficiency of convex optimization. Second, aiming at the conservatism drawback introduced by the CIA method, an admissible region correction strategy based on Stochastic Gradient Descent is designed to narrow the dual gap of the solution. Furthermore, a multi-objective optimization framework is established, incorporating voltage security, operational economy, and renewable energy accommodation rate. Finally, simulations on the IEEE 33/69/118-bus systems demonstrate that the proposed method outperforms the traditional SOCP approach in the 24 h sequential optimization, reducing voltage deviation by 22.6%, power loss by 24.7%, and solution time by 45.4%. Compared with the CIA method, it improves the DG utilization rate by 30.5%. The proposed method exhibits superior generality compared to conventional approaches. Within the upper limit range of network penetration (approximately 60%), it addresses the issue of conservative power output of DG, thereby effectively promoting the utilization of renewable energy. Full article
(This article belongs to the Special Issue Flexibility Regulation and Operational Optimization of New-Type Power Systems)
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22 pages, 3247 KB  
Article
Capacity Optimization and Rolling Scheduling of Offshore Multi-Energy Coupling Systems
by Honggang Fan, Yan Liu, Cui Wang and Wankun Wang
Energies 2026, 19(2), 447; https://doi.org/10.3390/en19020447 - 16 Jan 2026
Viewed by 479
Abstract
Increasing penetration of offshore renewable energy has highlighted the challenges posed by strong intermittency, output uncertainty, and insufficient utilization of marine energy resources. To address these issues, this study investigates an offshore multi-energy coupling system integrating wind, photovoltaic, tidal, and wave energy with [...] Read more.
Increasing penetration of offshore renewable energy has highlighted the challenges posed by strong intermittency, output uncertainty, and insufficient utilization of marine energy resources. To address these issues, this study investigates an offshore multi-energy coupling system integrating wind, photovoltaic, tidal, and wave energy with flexible loads such as seawater desalination and hydrogen production. A coordinated two-stage optimization framework is proposed. In the planning stage, a joint operation–planning capacity configuration model is formulated to minimize the annualized system cost while determining the optimal sizes of generation units and energy storage. In the operational stage, a multi-time-scale rolling scheduling model combining day-ahead and intra-day optimization is developed to dynamically mitigate renewable output fluctuations and enhance system flexibility. Case studies verify that the proposed framework significantly improves renewable energy utilization, reducing the curtailment rate to 0.7%, while achieving stable and cost-effective operation. The results demonstrate the effectiveness of coordinated planning and rolling scheduling for future offshore integrated energy systems. Full article
(This article belongs to the Special Issue Flexibility Regulation and Operational Optimization of New-Type Power Systems)
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