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Control and Optimization of Electrical Power and Energy Systems to Integrate More Renewable and Sustainable Energy Resources

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

Deadline for manuscript submissions: 5 September 2025 | Viewed by 5266

Special Issue Editors

Dr. Muhammad Numan

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, University College Dublin, D04 V1W8 Dublin, Ireland
Interests: power system operation optimization; network expansion planning; transmission network topologies; optimal integration of distributed energy resources
Dr. Arshad Nawaz

E-Mail Website
Guest Editor
School of Electrical Engineering, Shandong University, Jinan 250061, China
Interests: microgrid systems; distributed control; optimal energy management
Dr. Alireza Zakariazadeh

E-Mail Website
Guest Editor
School of Electrical and Electronic Engineering, University College Dublin, D04 V1W8 Dublin, Ireland
Interests: smart grids; demand response; electric vehicles; stochastic

Special Issue Information

Dear Colleagues,

Modern electrical power and energy systems are constantly evolving and becoming more complex and interesting every day. The global move towards decarbonization is encouraging growth in the sustainable energy sector. The making of great advances towards more sustainable, renewable, and distributed power generation comes with many new opportunities, as well as new challenges. Furthermore, many new technologies are now commercially available, such as programmable smart loads, electric vehicles, smart meters, and smart inverters. Energy storage systems, such as battery energy storage, compressed air storage, power storage bricks, and fuel cells, have come to the fore. All these new technologies are an interesting addition to modern power systems and provide new opportunities for flexible operation and demand management. To optimally involve all these new components and utilize renewable energy resources more effectively, the operation, control, and management methods employed must be updated. The control and optimization of modern electrical power and energy systems are modern challenges that require modern solutions. 

This Special Issue aims to present and disseminate the most recent advances in the control and optimization of electrical power and energy systems to integrate more renewable and sustainable energy resources. The areas focused on include control, theory, and modelling, optimization methods, renewable energy integration, demand management, energy trading, behaviour prediction, integrated energy systems, and applications.

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

  • Advanced Control Strategies for Renewable Integration:
    • Development of adaptive and robust control strategies for managing the variability and uncertainty of renewable energy sources;
    • Integration of distributed energy resources (DERs) and renewable energy systems into existing grid infrastructures with minimal disruption.
  • Optimization Techniques for Grid Operation and Planning:
    • Application of stochastic, robust, and convex optimization techniques to enhance grid planning, reliability, and resilience with high penetrations of renewables;
    • Optimization of energy storage systems placement and operation to maximize the benefits of renewable generation.
  • Demand Response and Load Management:
    • Innovative demand response strategies that leverage renewable generation patterns to meet grid demand effectively;
    • Consumer-centric load management techniques that encourage the use of renewable energy through dynamic pricing and incentives.
  • Energy Storage Integration and Management:
    • Control and optimization of hybrid energy storage systems to mitigate the intermittency of renewable energy sources;
    • Strategies for integrating energy storage into renewable energy systems for smoothing power output and enhancing grid stability.
  • Microgrids and Off-grid Solutions:
    • Control and optimization strategies for microgrids incorporating renewables to ensure reliable and efficient operation;
    • Solutions for off-grid and rural electrification using renewable energy sources, focusing on sustainability and access to clean energy.
  • Technological Innovations and Emerging Trends:
    • Exploration of emerging technologies such as blockchain for the secure and efficient management of transactions in systems with high renewable integration;
    • The role of artificial intelligence and machine learning in optimizing grid operation, renewable integration, and predictive maintenance.
  • Energy models and their use in optimizing future pathways for energy networks;
  • Integrated energy systems.

Additionally, please ensure that the summary aligns with the aims and scope of Energies: https://www.mdpi.com/journal/energies/about.

Dr. Muhammad Numan
Dr. Arshad Nawaz
Dr. Alireza Zakariazadeh
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

  • electrical power systems
  • integrated energy systems
  • optimization and planning
  • operation and control
  • system management
  • energy modelling
  • energy systems
  • energy storage

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Published Papers (4 papers)

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Research

20 pages, 5100 KiB  
Article
Leveraging Seawater Thermal Energy Storage and Heat Pumps for Coupling Electricity and Urban Heating: A Techno-Economic Analysis
by Timur Abbiasov, Aldo Bischi, Manfredi Gangi, Andrea Baccioli, Paolo Santi and Carlo Ratti
Energies 2025, 18(7), 1869; https://doi.org/10.3390/en18071869 - 7 Apr 2025
Viewed by 284
Abstract
This paper presents an economic assessment of seawater thermal energy storage (TES) integrated with industrial heat pumps to couple renewable electricity generation with urban district heating networks. Using Amsterdam as a case study, we develop a techno-economic model leveraging real-world data on electricity [...] Read more.
This paper presents an economic assessment of seawater thermal energy storage (TES) integrated with industrial heat pumps to couple renewable electricity generation with urban district heating networks. Using Amsterdam as a case study, we develop a techno-economic model leveraging real-world data on electricity prices, heat demand, and system costs. Our findings show that large-scale TES using seawater as a storage medium significantly enhances district heating economics through energy arbitrage and operational flexibility. The optimal configuration yields a net present value (NPV) of EUR 466 million over 30 years and a payback period under 6 years. Thermal storage increases NPV by 17% compared to systems without storage, while within-day load shifting further boosts economic value by 23%. Accurate demand and price forecasting is critical, as forecasting errors can reduce NPV by 13.7%. The proposed system is scalable and well suited for coastal cities, offering a sustainable, space-efficient solution for urban decarbonization and addressing renewable energy overproduction. Full article
(This article belongs to the Special Issue Control and Optimization of Electrical Power and Energy Systems to Integrate More Renewable and Sustainable Energy Resources)
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19 pages, 583 KiB  
Article
Control Conditions for Equal Power Sharing in Multi-Area Power Systems for Resilience Against False Data Injection Attacks
by Zahoor Ahmed, Muhammad Nasir, Deema Mohammed Alsekait, Muhammad Zohaib Hassan Shah, Diaa Salama AbdElminaam and Furqan Ahmad
Energies 2024, 17(22), 5757; https://doi.org/10.3390/en17225757 - 18 Nov 2024
Cited by 1 | Viewed by 705
Abstract
Power cyber–physical systems such as multi-area power systems (MAPSs) have gained considerable attention due to their integration of power electronics with wireless communications technologies. Incorporating a communication setup enhances the sustainability, reliability, and efficiency of these systems. Amidst these exceptional benefits, such systems’ [...] Read more.
Power cyber–physical systems such as multi-area power systems (MAPSs) have gained considerable attention due to their integration of power electronics with wireless communications technologies. Incorporating a communication setup enhances the sustainability, reliability, and efficiency of these systems. Amidst these exceptional benefits, such systems’ distributed nature invites various cyber-attacks. This work focuses on the equal power sharing of MAPSs in the event of false data injection (FDI) attacks. The proposed work uses a sliding mode control (SMC) mechanism to ensure timely detection of challenges such as FDI attacks and load change, making MAPSs reliable and secure. First, a SMC-based strategy is deployed to enable the detection and isolation of compromised participants in MAPS operations to achieve equal power sharing. Second, time-varying FDI attacks on MAPSs are formulated and demonstrate their impact on equal power sharing. Third, a robust adaptive sliding mode observer is used to accurately assess the state of the MAPS to handle state errors robustly and automatically adjust parameters for identifying FDI attacks and load changes. Lastly, simulation results are presented to explain the useful ability of the suggested method. Full article
(This article belongs to the Special Issue Control and Optimization of Electrical Power and Energy Systems to Integrate More Renewable and Sustainable Energy Resources)
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27 pages, 4101 KiB  
Article
Designing a Dispatch Engine for Hybrid Renewable Power Stations Using a Mixed-Integer Linear Programming Technique
by Myada Shadoul, Rashid Al Abri, Hassan Yousef and Abdullah Al Shereiqi
Energies 2024, 17(13), 3281; https://doi.org/10.3390/en17133281 - 4 Jul 2024
Viewed by 1652
Abstract
Hybrid power plants have recently emerged as reliable and flexible electricity generation stations by combining multiple renewable energy sources, energy storage systems (ESS), and fossil-based output. However, the effective operation of the hybrid power plants to ensure continuous energy dispatch under challenging conditions [...] Read more.
Hybrid power plants have recently emerged as reliable and flexible electricity generation stations by combining multiple renewable energy sources, energy storage systems (ESS), and fossil-based output. However, the effective operation of the hybrid power plants to ensure continuous energy dispatch under challenging conditions is a complex task. This paper proposes a dispatch engine (DE) based on mixed-integer linear programming (MILP) for the planning and management of hybrid power plants. To maintain the committed electricity output, the dispatch engine will provide schedules for operation over extended time periods as well as monitor and reschedule the operation in real time. Through precise prediction of the load and the photovoltaic (PV) and wind power outputs, the proposed approach guarantees optimum scheduling. The precise predictions of the load, PV, and wind power levels are achieved by employing a predictor of the Feed-Forward Neural Network (FFNN) type. With such a dispatch engine, the operational costs of the hybrid power plants and the use of diesel generators (DGs) are both minimized. A case study is carried out to assess the feasibility of the proposed dispatch engine. Real-time measurement data pertaining to load and the wind and PV power outputs are obtained from different locations in the Sultanate of Oman. The real-time data are utilized to predict the future levels of power output from PV and from the wind farm over the course of 24 h. The predicted power levels are then used in combination with a PV–Wind–DG–ESS–Grid hybrid plant to evaluate the performance of the proposed dispatch engine. The proposed approach is implemented and simulated using MATLAB. The results of the simulation reveal the proposed FFNN’s powerful forecasting abilities. In addition, the results demonstrate that adopting the proposed DE can minimize the use of DG units and reduce a plant’s running expenses. Full article
(This article belongs to the Special Issue Control and Optimization of Electrical Power and Energy Systems to Integrate More Renewable and Sustainable Energy Resources)
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20 pages, 6407 KiB  
Article
A Stabilization Control Strategy for Wind Energy Storage Microgrid Based on Improved Virtual Synchronous Generator
by Jingguang Huang, Xinyuan Lin, Jiahang Sun and Huixin Xu
Energies 2024, 17(11), 2567; https://doi.org/10.3390/en17112567 - 26 May 2024
Cited by 3 | Viewed by 1510
Abstract
In high-penetration renewable-energy grid systems, conventional virtual synchronous generator (VSG) control faces a number of challenges, especially the difficulty of maintaining synchronization during grid voltage drops. This difficulty may lead to current overloads and equipment disconnections, and it has an impact on the [...] Read more.
In high-penetration renewable-energy grid systems, conventional virtual synchronous generator (VSG) control faces a number of challenges, especially the difficulty of maintaining synchronization during grid voltage drops. This difficulty may lead to current overloads and equipment disconnections, and it has an impact on the security and reliability of the system, as well as limiting the dynamic reactive power support capability of the system. To solve this problem, in this study, a wind–solar hybrid power generation system is designed with a battery energy storage device connected on the DC side, and proposes a low voltage ride-through (LVRT) control strategy for the grid-connected inverter based on an improved VSG. The control strategy employs an integrated current limiting technique combining virtual impedance and vector current limiting to ensure that the VSG exhibits good dynamic power support characteristics during symmetrical faults by adjusting the setpoint value of reactive power. At the same time, it maintains the synchronization and power angle stability of the VSG itself to achieve the goal of LVRT. Simulation results show that the proposed control strategy can effectively suppress the renewable power fluctuations (about 30% reduction in fluctuations compared to the conventional strategy) and ensure the safe and reliable operation of the renewable energy sources and VSGs during grid-side faults. In addition, it provides a given reactive power support and stable grid voltage control (voltage dips reduced by about 20%), which significantly enhances the LVRT capability of the hybrid wind–solar-storage generation system. Full article
(This article belongs to the Special Issue Control and Optimization of Electrical Power and Energy Systems to Integrate More Renewable and Sustainable Energy Resources)
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