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Modeling, Scheduling, Optimising, and Control of Power Grids and Integrated Energy Systems

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

Deadline for manuscript submissions: 25 December 2025 | Viewed by 840

Special Issue Editor


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Guest Editor
School of Electrical Engineering Computing and Mathematical Sciences, Curtin University, Bentley, WA 6102, Australia
Interests: integration of renewable energy resources; microgrids; power system planning and operation; electric vehicles; application of power electronics to power systems
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Special Issue Information

Dear Colleagues,

Modern power grids are evolving rapidly, with the significant integration of renewable energy sources, advanced power electronics, and digital technologies. While these advancements provide enhanced flexibility and control, they also introduce challenges such as intermittency, volatility, and operational uncertainty. Integrated energy systems (IESs) are critical to the ongoing energy transition, offering innovative pathways to enhance renewable energy integration, improve energy efficiency, and ensure sustainable operation. These systems are pivotal in addressing rising global energy demands and achieving environmental goals in line with international agreements. IESs, virtual power plants (VPPs), and microgrid systems form a hybrid paradigm requiring innovative modeling, scheduling, optimization, and control approaches.

The adoption of hydrogen as a clean energy carrier and advancements in energy storage technologies are reshaping both power grids and IESs. These innovations, coupled with digital twin technologies, machine learning, and artificial intelligence (AI) applications, drive new methodologies for efficient operation, demand response, and fault prediction. However, the complexity of coupling multi-energy systems and managing large-scale renewable energy integration necessitates robust solutions to ensure reliability and sustainability.

This Special Issue invites high-quality manuscripts on topics including, but not limited to:

  • Integration of renewable energy systems;
  • Modeling and optimization of integrated energy systems;
  • Digital twin technologies for power grids and energy systems;
  • Virtual power plants and microgrids;
  • Advanced scheduling strategies for multi-energy coordination;
  • Modeling and control of energy storage systems;
  • Fuel cell technologies, electrolyzers, and power-to-hydrogen systems;
  • Demand response models and smart community applications;
  • Case studies on practical applications in power grids and energy systems.

This Special Issue seeks to foster a deeper comprehension of the challenges and opportunities within modern power systems and integrated energy infrastructures through a detailed exploration of these themes. It aims to provide innovative frameworks and actionable strategies for the effective modeling, efficient scheduling, and optimized operation of power grids and integrated energy systems, addressing critical areas such as reliability, sustainability, and advanced coordination of multi-energy systems.

Dr. Ehsan Pashajavid
Guest Editor

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

  • decarbonization
  • renewable energy integration
  • integrated energy system
  • modeling, scheduling, and optimization
  • digital twins and machine learning
  • virtual power systems and microgrids
  • energy storage systems
  • power to hydrogen
  • power quality and reliability
  • grid compatibility
  • multi-energy systems

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Published Papers (2 papers)

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Research

16 pages, 7989 KB  
Article
Model-Free Predictive Control of Inverter Based on Ultra-Local Model and Adaptive Super-Twisting Sliding Mode Observer
by Wensheng Luo, Zejian Shu, Ruifang Zhang, Jose I. Leon, Abraham M. Alcaide and Leopoldo G. Franquelo
Energies 2025, 18(17), 4570; https://doi.org/10.3390/en18174570 - 28 Aug 2025
Viewed by 269
Abstract
Model predictive control (MPC) is significantly affected by parameter mismatch in inverter applications, whereas model-free predictive control (MFPC) avoids parameter dependence through the ultra-local model (ULM). However, the traditional MFPC based on the algebraic method needs to store historical data for multiple cycles, [...] Read more.
Model predictive control (MPC) is significantly affected by parameter mismatch in inverter applications, whereas model-free predictive control (MFPC) avoids parameter dependence through the ultra-local model (ULM). However, the traditional MFPC based on the algebraic method needs to store historical data for multiple cycles, which results in a sluggish dynamic response. To address the above problems, this paper proposes a model-free predictive control method based on the ultra-local model and an adaptive super-twisting sliding mode observer (ASTSMO). Firstly, the effect of parameter mismatch on the current prediction error of conventional MPC is analyzed through theoretical analysis, and a first-order ultra-local model of the inverter is established to enhance robustness against parameter variations. Secondly, a super-twisting sliding mode observer with adaptive gain is designed to estimate the unknown dynamic terms in the ultra-local model in real time. Finally, the superiority of the proposed method is verified through comparative validation against conventional MPC and the algebraic-based MFPC. Simulation results demonstrate that the proposed method can significantly enhance robustness against parameter variations and shorten the settling time during dynamic transients. Full article
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22 pages, 4263 KB  
Article
An Approach to Enhance the Controlled Switching of Circuit Breakers Equipped with Preinsertion Resistors for Power Capacitor Banks
by Ricardo T. Lima, Aurélio L. M. Coelho, Giovani B. Vitor and Philippe A. V. D. Liz
Energies 2025, 18(16), 4356; https://doi.org/10.3390/en18164356 - 15 Aug 2025
Viewed by 319
Abstract
The controlled switching of capacitor banks when properly parameterized brings significant benefits to the bank, circuit breaker, and adjacent equipment by significantly reducing the levels of inrush currents. This article explores and analyzes the waveforms from a circuit breaker equipped with both preinsertion [...] Read more.
The controlled switching of capacitor banks when properly parameterized brings significant benefits to the bank, circuit breaker, and adjacent equipment by significantly reducing the levels of inrush currents. This article explores and analyzes the waveforms from a circuit breaker equipped with both preinsertion resistors (PIR) and a controlled switching device (CSD), proposing a dynamic approach to determine the better closing times for both the PIR and the main contact of the circuit breaker, thereby reducing inrush current levels and improving system performance and reliability. The study employs a computational tool to identify the circuit breaker’s contacts insertion points, presenting important information such as the best closing instant for the main contact, the determination of preinsertion time, and maximum inrush current peak. The waveforms used in the study originate from both a real power shunt capacitor bank from a Brazilian substation and simulations modeled using the Alternative Transient Program (ATP). This dynamic approach not only reduces inrush current levels, but also contributes to increasing the useful life of the capacitor bank elements, the circuit breaker itself, and neighboring equipment. Full article
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