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Energies
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Optimization and Control of New Energy Systems
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Optimization and Control of New Energy Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A1: Smart Grids and Microgrids".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 9050

Special Issue Editors

Prof. Dr. Wei Yao

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Interests: power system stability analysis and control; renewable energy; HVDC and DC Grid; application of artificial intelligence in smart grid
Prof. Dr. Bo Yang

E-Mail Website
Guest Editor
Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China
Interests: intelligent optimization and control of new energy and energy storage systems; application of artificial intelligence in smart grid
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Lin Jiang

E-Mail Website
Guest Editor
Department of Electrical Engineering and Electronics, University of Liverpool, Liverpool L69 3GJ, UK
Interests: smart grid control and dynamic; renewable energy and electronics; advanced control and applications in energy system
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Chuan-Ke Zhang

E-Mail Website
Guest Editor
School of Automation, China University of Geosciences, Wuhan 430074, China
Interests: power system stability analysis and control; robust control
Prof. Dr. Chao Duan

E-Mail Website
Guest Editor
Department of Physics and Astronomy, Northwestern University, Evanston, IL 60208, USA
Interests: power system stability analysis; control and optimization
Dr. Yaxing Ren

E-Mail Website
Guest Editor
WMG, University of Warwick, Coventry, CV4 7AL, UK
Interests: intellegent control, system design and analysis and hardware; implementation of grid-connected renewable power generation, battery mangement

Special Issue Information

Dear Colleagues,

In recent years, challenges in the field of energy have become increasingly stringent and complex in terms of the consumption of primary resources and of pollutant emissions. In terms of energy, scientific and technical paradigms had to focus on changing toward a more intricate reality. With the rapid development of various renewable energies (e.g., wind and solar energies) and advanced energy storage technologies, the current energy structure and power generation modes have achieved dramatical transformations. Traditional power systems that mainly consists of fossil energy have experienced dramatical transformations. The proposed "New Power System" concept aims to construct a clean, low-carbon, safe, and efficient modern energy system, which takes renewable energy as the basis and fossil energy as a supplement.

Due to the inherent strong randomness and uncertainty characteristics of renewable energy, it is difficult yet crucial to undertake some advanced techniques in modern power systems with large-scale renewable energy integration to ensure the power generation output can be optimized and controlled on demand. Hence, the exploitation and implementation of various advanced optimization and control techniques is extremely critical for economic and efficient operation, including frequency regulation, voltage support, converter control, parameter/state identification and estimation, MPPT design, planning and dispatching, power and load forecast, and so on. Therefore, the exploitation and application of various advanced techniques to deal with the optimization and control of new energy systems are imperative.

This Special Issue aims to make an effective contribution to highlight all solutions, methodologies, approaches, and tools to collect first-class research along this direction, focusing on the most recent investigations and studies on optimization and control strategies for new power system. Researchers and experts worldwide are invited to submit high-quality original research papers and review articles on the following potential topics.

Potential topics aims at covering themes including but not limited to:

  • Modelling and simulation of renewable energy systems;
  • Operation planning and control of energy storage systems;
  • Application of optimization techniques such as meta-heuristic algorithms, reinforcement learning, and neural networks to energy systems and grids;
  • Control strategies such as fuzzy logic control, sliding-mode control, feedback control, perturbation/disturbance observer-based control, H-infinity control, and backstepping control for energy systems and grids;
  • Approaches for the optimized design of architectures and sizing of energy systems and grids;
  • Solutions and techniques for energy generation, conversion, distribution, storage, and use (e.g., renewable energy generation, energy storage systems, etc.).

Prof. Dr. Wei Yao
Prof. Dr. Bo Yang
Prof. Dr. Lin Jiang
Prof. Dr. Chuan-Ke Zhang
Prof. Dr. Chao Duan
Dr. Yaxing Ren
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 100 words) can be sent to the Editorial Office for announcement on this website.

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

  • new power system
  • renewable energy
  • energy storage
  • optimization
  • control

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Published Papers (4 papers)

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Editorial

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4 pages, 205 KiB  
Editorial
Optimization and Control of New Power Systems under the Dual Carbon Goals: Key Issues, Advanced Techniques, and Perspectives
by Bo Yang, Yulin Li, Wei Yao, Lin Jiang, Chuanke Zhang, Chao Duan and Yaxing Ren
Energies 2023, 16(9), 3904; https://doi.org/10.3390/en16093904 - 5 May 2023
Cited by 9 | Viewed by 2016
Abstract
Production and consumption as a result of human demand for energy are increasing with each passing day as populations grow [...] Full article
(This article belongs to the Special Issue Optimization and Control of New Energy Systems)

Research

Jump to: Editorial

21 pages, 5263 KiB  
Article
Intelligent Digital Twin Modelling for Hybrid PV-SOFC Power Generation System
by Zhimin Guo, Zhiyuan Ye, Pengcheng Ni, Can Cao, Xiaozhao Wei, Jian Zhao and Xing He
Energies 2023, 16(6), 2806; https://doi.org/10.3390/en16062806 - 17 Mar 2023
Cited by 8 | Viewed by 2573
Abstract
Hydrogen (H2) energy is an ideal non-polluting renewable energy and can achieve long-term energy storage, which can effectively regulate the intermittence and seasonal fluctuation of solar energy. Solid oxide fuel cells (SOFC) can generate electricity from H2 with only outputs [...] Read more.
Hydrogen (H2) energy is an ideal non-polluting renewable energy and can achieve long-term energy storage, which can effectively regulate the intermittence and seasonal fluctuation of solar energy. Solid oxide fuel cells (SOFC) can generate electricity from H2 with only outputs of water, waste heat, and almost no pollution. To solve the power generation instability and discontinuity of solar photovoltaic (PV) systems, a hybrid PV-SOFC power generation system has become one feasible solution. The “digital twin”, which integrates physical systems and information technology, offers a new view to deal with the current problems encountered during smart energy development. In particular, an accurate and reliable system model is the basis for achieving this vision. As core components, the reliable modelling of the PV cells and fuel cells (FCs) is crucial to the whole hybrid PV-SOFC power generation system’s optimal and reliable operation, which is based on the reliable identification of unknown model parameters. Hence, in this study, an artificial rabbits optimization (ARO)-based parameter identification strategy was proposed for the accurate modelling of PV cells and SOFCs, which was then validated on the PV double diode model (DDM) and SOFC electrochemical model under various operation scenarios. The simulation results demonstrated that ARO shows a more desirable performance in optimization accuracy and stability compared to other algorithms. For instance, the root mean square error (RMSE) obtained by ARO are 1.81% and 13.11% smaller than that obtained by ABC and WOA algorithms under the DDM of a PV cell. Meanwhile, for SOFC electrochemical model parameter identification under the 5 kW cell stack dataset, the RMSE obtained by ARO was only 2.72% and 4.88% to that of PSO for the (1 atm, 1173 K) and (3 atm, 1273 K) conditions, respectively. By establishing a digital twin model for PV cells and SOFCs, intelligent operation and management of both can be further achieved. Full article
(This article belongs to the Special Issue Optimization and Control of New Energy Systems)
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17 pages, 6701 KiB  
Article
Cooperative Game-Based Collaborative Optimal Regulation-Assisted Digital Twins for Wide-Area Distributed Energy
by Pengcheng Ni, Zhiyuan Ye, Can Cao, Zhimin Guo, Jian Zhao and Xing He
Energies 2023, 16(6), 2598; https://doi.org/10.3390/en16062598 - 9 Mar 2023
Cited by 3 | Viewed by 1597
Abstract
With the wide use of renewable energy sources and the requirement for energy storage technology, the field of power systems is facing the need for further technological innovation. This paper proposes a wide-area distributed energy model based on digital twins. This model was [...] Read more.
With the wide use of renewable energy sources and the requirement for energy storage technology, the field of power systems is facing the need for further technological innovation. This paper proposes a wide-area distributed energy model based on digital twins. This model was constructed to more fully optimize the coordination of wide-area distributed energy in order to rationally deploy and utilize new energy units. Moreover, the minimization of the power deviation between the dispatch command and the actual power regulation output was also taken into account. In contrast to previous dispatch research, the cooperative game co-optimization algorithm was applied to this model, enabling a distributed approach that can quickly obtain a high-quality power command scheduling scheme. Finally, the simulation and comparison experiments using this algorithm with the wide-area distributed energy (WDE) model showed that it had the advantages of significantly reducing the tracking error, average error, and total error and effectively improving the tracking accuracy. The proposed method can help reduce total power deviations by about 61.1%, 55.7%, 53.1%, and 74.8%. Full article
(This article belongs to the Special Issue Optimization and Control of New Energy Systems)
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12 pages, 1097 KiB  
Article
Equivalent Model of Photovoltaic Power Station Considering Different Generation Units’ Fault Current Contributions
by Sumei Liu, Hao Zhang, Peng Zhang, Zhongqing Li and Zepeng Wang
Energies 2022, 15(1), 229; https://doi.org/10.3390/en15010229 - 30 Dec 2021
Cited by 5 | Viewed by 1843
Abstract
The fault current calculation model of photovoltaic (PV) power stations is usually treated as a capacity weighted equivalent model of a single PV generation unit (PVGU). However, in the same PV power station, different PVGUs have various fault current characteristics. As a result, [...] Read more.
The fault current calculation model of photovoltaic (PV) power stations is usually treated as a capacity weighted equivalent model of a single PV generation unit (PVGU). However, in the same PV power station, different PVGUs have various fault current characteristics. As a result, there are significant differences in fault current characteristics between a PVGU and a PV power station. It means that the existing capacity weighted equivalent model cannot be used for accurately describing the fault current contributions from a practical PV power station. In this paper, the fault behaviors of the PVGUs located at different access points of a PV power station are firstly analyzed. The difference in PVGUs’ fault current contributions is identified and reflected with the activation states of current limiters that are employed for PV inverters. The activation states are represented by a theoretical expression so as to distinguish the PVGUs’ fault contributions. Further, based on the proposed theoretical expression, a novel algorithm is developed for sorting all PVGUs included in a PV power station. The multi-machine calculation model is deduced in order to exactly express the fault current contribution from a PV station. Finally, some simulation tests are conducted. The tested results verify the effectiveness of the proposed calculation model. It can provide support for calculating the protection setting of power grid connected with large-scale PV stations. Full article
(This article belongs to the Special Issue Optimization and Control of New Energy Systems)
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