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Research on Operation Optimization of Integrated Energy Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "F5: Artificial Intelligence and Smart Energy".

Deadline for manuscript submissions: 10 November 2025 | Viewed by 467

Special Issue Editor


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Guest Editor
Research and Innovation Centre Pro-Akademia, 95-050 Konstantynów Łódzki, Poland
Interests: energy efficiency; big data analytics; smart grids; energy systems; decarbonisation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Increased demand for sustainable energy technologies has brought integrated energy systems (IESs) to the forefront of modern energy research. These systems, which combine various forms of energy generation, storage, and distribution, are critical for enhancing the reliability, resilience, and overall performance of energy conversion and use. The complexity of IESs, with their intertwined electrical, thermal, and, sometimes, chemical processes, presents unique challenges in operation optimization, demanding innovative approaches and methodologies.

This Special Issue will showcase the latest research advancements in operation optimization for integrated energy systems. We will gather cutting-edge contributions that address the multifaceted challenges associated with optimizing the performance, efficiency, and sustainability of IESs in various contexts, including urban environments, industrial applications, and renewable energy integration.

Potential paper topics include, but are not limited to, the following:

  • Optimization algorithms and methodologies for IES operation;
  • Integration of renewable energy sources into IESs;
  • Demand-side management and its impact on IES optimization;
  • Energy storage solutions within IESs and their operational strategies;
  • Economic dispatch and unit commitment in IESs;
  • Multi-energy flow modeling and optimization;
  • Advanced control strategies for the real-time optimization of IESs;
  • Decentralized and distributed optimization approaches for IES;
  • Uncertainty management in IES operation optimization;
  • Case studies of IESs in urban, industrial, or rural settings;
  • Smart grids and their interaction with IES;
  • Artificial intelligence and machine learning applications in IES optimization;
  • Lifecycle analysis and sustainability assessments in IES operation.

We invite researchers and practitioners from academia, industry, and governmental bodies to contribute to this Special Issue by submitting original research, reviews, or case studies that advance the knowledge and practice of operation optimization in integrated energy systems.

We look forward to receiving your submissions and increasing our collective understanding of and technological progress in this critical area of energy research.

Dr. Maksymilian Kochanski
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

  • multi-energy flow management
  • renewable energy integration
  • smart grid control strategies
  • decentralized energy optimization

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Published Papers (1 paper)

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Research

18 pages, 1239 KiB  
Article
Optimized Demand Side Management for Refrigeration: Modeling and Case Study Insights from Kenya
by Josephine Nakato Kakande, Godiana Hagile Philipo and Stefan Krauter
Energies 2025, 18(13), 3258; https://doi.org/10.3390/en18133258 - 21 Jun 2025
Viewed by 228
Abstract
According to the International Institute of Refrigeration (IIR), 20% of worldwide electricity consumption is for refrigeration, with domestic refrigeration appliances comprising a fifth of this demand. As the uptake of renewable energy sources for on-grid and isolated electricity supply increases, the need for [...] Read more.
According to the International Institute of Refrigeration (IIR), 20% of worldwide electricity consumption is for refrigeration, with domestic refrigeration appliances comprising a fifth of this demand. As the uptake of renewable energy sources for on-grid and isolated electricity supply increases, the need for mechanisms to match demand and supply better and increase power system flexibility has led to enhanced attention on demand-side management (DSM) practices to boost technology, infrastructure, and market efficiencies. Refrigeration requirements will continue to rise with development and climate change. In this work, particle swarm optimization (PSO) is used to evaluate energy saving and load factor improvement possibilities for refrigeration devices at a site in Kenya, using a combination of DSM load shifting and strategic conservation, and based on appliance temperature evolution measurements. Refrigeration energy savings of up to 18% are obtained, and the load factor is reduced. Modeling is done for a hybrid system with grid, solar PV, and battery, showing a marginal increase in solar energy supply to the load relative to the no DSM case, while the grid portion of the load supply reduces by almost 25% for DSM relative to No DSM. Full article
(This article belongs to the Special Issue Research on Operation Optimization of Integrated Energy Systems)
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