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Advances in the Optimization and Control of Solar Integrated Energy Systems

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "A2: Solar Energy and Photovoltaic Systems".

Deadline for manuscript submissions: 25 August 2026 | Viewed by 1287

Special Issue Editors


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Guest Editor
Centro Mixto CIESOL, Universidad de Almería, 04120 Almería, Spain
Interests: process control; model predictive control; solar energy; biosystems; agriculture

E-Mail Website
Guest Editor
Centro Mixto CIESOL, Universidad de Almería, 04120 Almería, Spain
Interests: control engineering; model predictive control; solar energy; renewable energy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The global transition towards sustainable and low-carbon energy has placed solar-based technologies at the forefront of future energy systems. Solar thermal and photovoltaic plants, as well as hybrid solutions integrating storage, desalination, hydrogen, and biomass systems, have become essential for addressing today’s energy, water, and climate challenges. However, the inherent variability of solar resources, coupled with the increasing complexity of integrated multi-energy systems, poses significant challenges for reliable, efficient, and cost-effective operation. These challenges have accelerated the need for advanced optimization and control strategies capable of ensuring flexibility, resilience, and scalability across different applications and scales.

This Special Issue aims to present and disseminate the most recent advances in the optimization, modeling, and control of solar integrated energy systems. It will highlight theoretical developments, computational approaches, experimental validations, and real-world applications that contribute to improving energy efficiency, reducing costs, and enhancing the sustainability of solar-driven technologies. Both original research articles and comprehensive reviews are welcome, with contributions encouraged from a broad range of interdisciplinary fields.

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

  • Optimization and control of solar thermal, photovoltaic, and hybrid systems;
  • Solar-powered desalination, membrane distillation, and water–energy nexus solutions;
  • Hierarchical, predictive, adaptive, and classic control schemes for solar plants;
  • Integration of solar energy with storage, hydrogen, and biomass systems;
  • Multi-objective optimization for efficiency, cost, and environmental performance;
  • Modeling, simulation, and control of Concentrated Solar Thermal (CSP) systems at different scales;
  • Control-oriented approaches for uncertainty, intermittency, and fault tolerance;
  • Experimental validation and industrial applications of solar control strategies;
  • Digital twins, machine learning, and AI for solar system optimization and control.

Dr. Igor Mendes Lima Pataro
Dr. Juan D. Gil
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

  • solar energy systems
  • system optimization
  • model predictive control
  • adaptive control
  • multi-objective optimization
  • concentrated solar power
  • photovoltaics and hybrid systems
  • water–energy nexus
  • solar desalination
  • multi-objective optimization
  • digital twins and machine learning

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Published Papers (2 papers)

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Research

28 pages, 5280 KB  
Article
Case Study of a Photovoltaic (PV)-Powered, Battery-Integrated System in Cyprus
by Andreas Livera, Panagiotis Herodotou, Demetris Marangis, George Makrides and George E. Georghiou
Energies 2026, 19(10), 2402; https://doi.org/10.3390/en19102402 - 16 May 2026
Viewed by 365
Abstract
Despite the rapid expansion of photovoltaic (PV) installations over the past decade, challenges such as curtailments of renewable energy sources (RESs) and grid constraints continue to limit the capacity of Cyprus’ power system to accommodate higher solar penetration. In this context, grid reliability, [...] Read more.
Despite the rapid expansion of photovoltaic (PV) installations over the past decade, challenges such as curtailments of renewable energy sources (RESs) and grid constraints continue to limit the capacity of Cyprus’ power system to accommodate higher solar penetration. In this context, grid reliability, defined as the ability to maintain stable operation by balancing supply and demand, minimizing curtailment, and reducing stress on the island network, has emerged as a critical concern. The deployment of PV-plus-storage systems offers a viable solution to enhance grid reliability while alleviating operational constraints. This paper presents a real-world case study of the first commercially deployed grid-connected PV-powered, battery-integrated electric vehicle (EV) charging station in Cyprus. Commissioned in May 2025, the system integrates a 60.32 kWp rooftop PV array, a 100 kW/97 kWh battery energy storage system (BESS), and a 160 kW DC fast charger. A custom cloud-based energy management platform enables real-time monitoring, forecasting, and optimization under a zero-export scheme. High-resolution operational and weather data were collected between 15 May and 30 November 2025. Over this period, the integrated PV-battery system supplied 29% of the site’s total energy demand (self-sufficiency rate of 28.97%) and achieved a self-consumption rate of 98.69%. Such rates would not have been attainable with a pure PV system, given the depot’s evening-concentrated EV charging demand profile, which requires the BESS to time-shift daytime solar generation. The system reduced depot electricity costs by approximately 29%, generating €16,010 in savings and avoiding 26.47 tonnes of carbon dioxide (CO2) emissions compared to a grid-only baseline. Beyond site-level performance, the system contributed to grid stress reduction by absorbing excess PV generation that would otherwise have been curtailed/wasted. Operational insights indicate minimal temperature-related issues, highlight the importance of automated fault detection and alerting to minimize downtime, and demonstrate how periodic operation strategies can optimize system performance and mitigate curtailment in Cyprus’s isolated grid. Full article
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15 pages, 2505 KB  
Article
Comparative Analysis of Sampling Strategies for Solar Irradiance Signals and Their Implications in Discrete-Time Control Models
by Nicole Bastidas, Angelo Pozo, Elian Pasiche and Cristian Cuji
Energies 2026, 19(5), 1348; https://doi.org/10.3390/en19051348 - 6 Mar 2026
Viewed by 569
Abstract
This study compares uniform and stratified sampling strategies applied to hourly solar irradiance signals. The analysis examines how each approach affects signal reconstruction, anomaly detection, and dynamic PV modelling. Using PCHIP interpolation and error metrics such as RMSE and MAE, results show that [...] Read more.
This study compares uniform and stratified sampling strategies applied to hourly solar irradiance signals. The analysis examines how each approach affects signal reconstruction, anomaly detection, and dynamic PV modelling. Using PCHIP interpolation and error metrics such as RMSE and MAE, results show that uniform sampling yields lower global reconstruction error (26.64 W/m2 vs. 32.98 W/m2), while stratified sampling captures instantaneous peaks more accurately under high-variability conditions. Stratified sampling also improves anomaly identification due to its more representative temporal distribution. These findings highlight a practical trade-off between minimizing average error and preserving extreme events, providing guidance for PV estimation, forecasting, and discrete-time control applications. Full article
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