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Advanced Control Strategies and Optimization for Renewable Energy Systems
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Advanced Control Strategies and Optimization for Renewable Energy Systems

A special issue of Applied System Innovation (ISSN 2571-5577).

Deadline for manuscript submissions: 20 February 2027 | Viewed by 8211

Editor

Dr. Mohsen Pourkiaei

E-Mail Website
Guest Editor
Air Quality and Particle Technology, Department of Civil, Environmental and Geomatic Engineering, Institute of Environmental Engineering, ETHZ, 8093 Zürich, Switzerland
Interests: environmental sciences; energy; systems engineering
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The integration of renewable energy sources into modern power systems plays a crucial role in ensuring global sustainable development. However, the intermittent and variable nature of renewables energy sources such as solar, wind, and tidal energy introduces significant challenges in terms of system stability, efficiency, and reliability. This Special Issue aims to gather cutting-edge research and recent advances in the field of optimization and control strategies for renewable energy and renewable energy-integrated systems.
We welcome original research articles, review papers, and innovative case studies that focus on optimization algorithms, intelligent control systems, real-time energy management, smart grid technologies, and hybrid renewable systems. Topics of interest also include predictive control, distributed energy resource management, machine/deep learning applications in control, energy storage optimization, and resilience strategies for power systems under high renewable deployment.
This Special Issue provides a platform for scholars and practitioners to present state-of-the-art developments and share knowledge that supports the transition toward clean and sustainable energy systems. We encourage submissions that bridge the gap between theory and real-world implementation, and particularly those that demonstrate tangible contributions to environmental quality and energy efficiency.
We look forward to your valuable contributions.

Dr. Mohsen Pourkiaei
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 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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied System Innovation is an international peer-reviewed open access monthly 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 1600 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

  • renewable energy systems
  • optimization algorithms
  • intelligent control strategies
  • energy management systems
  • sustainable development
  • smart grids
  • energy storage optimization
  • hybrid energy systems
  • machine/deep learning in control
  • predictive control
  • distributed energy resources
  • power system resilience

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Published Papers (7 papers)

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Research

Jump to: Review

29 pages, 4836 KB  
Article
Investigating the Use of Large-Diameter Earth–Air Heat Exchangers to Achieve Office Building Cooling Self-Sufficiency
by Rogério Duarte, Amândio Rebola and Luís Coelho
Appl. Syst. Innov. 2026, 9(8), 160; https://doi.org/10.3390/asi9080160 - 28 Jul 2026
Viewed by 433
Abstract
Standalone use of EAHEs for room cooling is a passive and nature-based alternative to air conditioning technology that can be used to mitigate the increase in electricity and GWP-refrigerant consumption associated with cooling in buildings. EAHEs replacing air conditioning is documented in the [...] Read more.
Standalone use of EAHEs for room cooling is a passive and nature-based alternative to air conditioning technology that can be used to mitigate the increase in electricity and GWP-refrigerant consumption associated with cooling in buildings. EAHEs replacing air conditioning is documented in the technical and research literature. However, for office-room cooling, EAHEs are mostly employed as a support to air conditioning systems for precooling outdoor air. The larger cooling loads and the stricter design conditions commonly used in the sizing of office rooms prevent the most commonly investigated EAHE typologies from operating effectively in standalone cooling mode. To assess the feasibility of alternative typologies, such as large-diameter EAHEs, tools that are capable of modeling the complexity of the coupled heat and moisture transfer between air and soil are particularly valuable. For detailed assessments, researchers typically turn to advanced commercial tools; however, developments in free and open-source scientific programming languages that combine symbolic computation packages with efficient numerical solvers of partial differential equations allow analyses at reduced cost that are comparable to those from commercial tools. This paper shows how one such programming language can be used to study the coupled heat and moisture transfer problem in EAHEs. Starting from the symbolic form of the mathematical problem, the numerical implementation is described and validated with monitoring data from an existing large-diameter EAHE. Using the validated computational model, the paper proceeds to study the sensitivity of load removal in EAHEs operating in standalone and precooling cooling modes, highlighting fundamental differences between both operating modes, identifying the most relevant design parameters and providing guidance on the conditions under which an EAHE enables self-sufficient cooling of office buildings. The results show how, for a hot and dry climate, standalone EAHEs with large diameters (∼1 m), buried at depths larger than 3 m, allow the removal of up to 20 kWh/m2 of room sensible cooling loads, a level that is consistent with the cooling demand of low-energy office buildings. Full article
(This article belongs to the Special Issue Advanced Control Strategies and Optimization for Renewable Energy Systems)
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22 pages, 3043 KB  
Article
Integrated Multi-Scenario OPF-Based Economic Dispatch for Grid-Connected Microgrids Considering Bidirectional Power Flow and Technical Constraints
by Katherine Cabana-Jiménez, Vladimir Sousa Santos, John E. Candelo-Becerra, Zaid García Sánchez and Fredy E. Hoyos
Appl. Syst. Innov. 2026, 9(7), 135; https://doi.org/10.3390/asi9070135 - 26 Jun 2026
Viewed by 995
Abstract
Economic dispatch in grid-connected microgrids is challenged by the variability of renewable generation, the uncertainty of demand, and the need to simultaneously satisfy technical and economic constraints under different operating conditions. This study proposes an integrated predictive economic dispatch strategy for power grids [...] Read more.
Economic dispatch in grid-connected microgrids is challenged by the variability of renewable generation, the uncertainty of demand, and the need to simultaneously satisfy technical and economic constraints under different operating conditions. This study proposes an integrated predictive economic dispatch strategy for power grids with interconnected microgrids, structured as a unified optimization framework. The approach integrates nodal electrical modeling, Optimal Power Flow (OPF)-based optimization, multi-scenario analysis, and post-optimization feasibility verification based on performance indicators within a single decision-support structure. The methodology is applied to a modified 14-node power grid interconnected with a microgrid, where simulations are conducted under three representative load scenarios (100%, 70%, and 40%) and two operational configurations (hybrid and renewable-only), enabling a comprehensive assessment of system behavior. Results show that the hybrid configuration consistently outperforms the renewable-only case, achieving loss reductions of up to 7.3 MW, increases in spinning reserve exceeding 50 MW, and a transition from net power import to export of approximately 50 MW under high demand. Additionally, the microgrid plays an active operational role, dynamically switching between import and export modes based on load levels and the generation mix. The proposed framework enables identification of operationally efficient and technically feasible configurations by incorporating bidirectional power exchange, electrical constraints, and reserve requirements. The main contribution lies in integrating technical, operational, and interaction variables within a single deterministic Optimal Power Flow (OPF)-based assessment scheme to support decision-making in interconnected microgrid-based power grids. Full article
(This article belongs to the Special Issue Advanced Control Strategies and Optimization for Renewable Energy Systems)
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15 pages, 1946 KB  
Article
A Theoretical Study on Coordinated Control Strategy of VSG for Transient Power Angle Stability and Fault Current Limiting
by Sheng Li and Shihao Gu
Appl. Syst. Innov. 2026, 9(6), 109; https://doi.org/10.3390/asi9060109 - 27 May 2026
Viewed by 426
Abstract
Virtual synchronous generators (VSGs) are prone to transient power angle instability and short-circuit current overshoot under symmetrical short-circuit grid faults. To address the limitation that existing transient control strategies fail to simultaneously guarantee power angle stability and fault current limiting, a coordinated control [...] Read more.
Virtual synchronous generators (VSGs) are prone to transient power angle instability and short-circuit current overshoot under symmetrical short-circuit grid faults. To address the limitation that existing transient control strategies fail to simultaneously guarantee power angle stability and fault current limiting, a coordinated control strategy combining dynamic active power reference regulation and adaptive virtual impedance is designed. Specifically, the active power reference is dynamically adjusted in accordance with the voltage sag magnitude at the point of common coupling (PCC), which effectively narrows the acceleration area of the virtual rotor and maintains the transient power angle near its rated value to prevent the risk of system loss of synchronism. On this basis, an adaptive virtual impedance control scheme is designed to accurately calculate and implement the optimal current-limiting impedance on demand, confining the steady-state fault current within the allowable threshold. Finally, the effectiveness of the designed strategy is verified on the Matlab/Simulink simulation platform. Simulation results demonstrate that the designed strategy achieves the coordination between transient power angle stability and fault current limiting, thus improving the operational stability of the VSG grid-connected system under symmetrical short-circuit grid faults. Full article
(This article belongs to the Special Issue Advanced Control Strategies and Optimization for Renewable Energy Systems)
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19 pages, 358 KB  
Article
Enhancing Solar Cell Performance: Atan-Sinc Optimization Algorithm for Precise Parameter Extraction in the Three-Diode Model
by Diego Fernando Muñoz-Torres, Oscar Danilo Montoya, Jesús C. Hernández, Walter Gil-González and Luis Fernando Grisales-Noreña
Appl. Syst. Innov. 2026, 9(1), 26; https://doi.org/10.3390/asi9010026 - 22 Jan 2026
Cited by 1 | Viewed by 817
Abstract
This study focuses on estimating the nine parameters of the three-diode model (3DM) for photovoltaic (PV) cells by integrating the Atan-Sinc Optimization Algorithm (ASOA) with the Newton–Raphson (NR) method. The ASOA, a population-based metaheuristic approach inspired by the behaviors of the Sech and [...] Read more.
This study focuses on estimating the nine parameters of the three-diode model (3DM) for photovoltaic (PV) cells by integrating the Atan-Sinc Optimization Algorithm (ASOA) with the Newton–Raphson (NR) method. The ASOA, a population-based metaheuristic approach inspired by the behaviors of the Sech and Tanh functions, systematically generates candidate solutions for the complete set of parameters in the 3DM. For each of these solutions, the NR method is employed to solve the transcendental equation governing the solar cell model, facilitating a precise evaluation of the associated objective function. To guide the parameter estimation process, experimental current-voltage (I-V) and voltage-power (V-P) curves are utilized. The robustness of the proposed methodology is validated through studies on both monocrystalline and polycrystalline solar cells. Computational results reveal that the ASOA effectively navigates the parameter space, while the NR method provides accurate evaluations, resulting in reliable and precise parameter estimations. All numerical validations were conducted using MATLAB software, version 2024b. Full article
(This article belongs to the Special Issue Advanced Control Strategies and Optimization for Renewable Energy Systems)
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33 pages, 493 KB  
Article
Heterogeneous Graph Neural Network with Local and Global Message Passing for AC-Optimal Power Flow Solutions
by Aihui Wen, Bao Wen, Jining Li and Jin Xu
Appl. Syst. Innov. 2026, 9(1), 18; https://doi.org/10.3390/asi9010018 - 5 Jan 2026
Cited by 4 | Viewed by 2179
Abstract
The AC Optimal Power Flow (AC-OPF) problem remains a major computational bottleneck for real-time power system operation. Conventional solvers are accurate but time-consuming, while Graph Neural Networks (GNNs) offer faster approximations yet struggle to capture long-range dependencies and handle topological variations. To address [...] Read more.
The AC Optimal Power Flow (AC-OPF) problem remains a major computational bottleneck for real-time power system operation. Conventional solvers are accurate but time-consuming, while Graph Neural Networks (GNNs) offer faster approximations yet struggle to capture long-range dependencies and handle topological variations. To address these limitations, we propose a Heterogeneous Graph Transformer with bus-centric Local–Global Message Passing (LG-HGNN). The model performs type-specific local message passing over heterogeneous power graphs and applies a global Transformer only on bus nodes to capture system-wide correlations efficiently. Effective-resistance positional encodings and resistance-biased attention enhance electrical awareness, whereas bounded decoders and physics-informed regularization preserve operational feasibility. Experiments on IEEE 14-, 30-, and 118-bus systems show that LG-HGNN achieves near-optimal results within a few percent of the AC-OPF optimum and generalizes to thousands of unseen N-1 contingency topologies without retraining. Compared with interior-point solvers, it attains up to 190× speedup before power-flow correction and over 10× afterward on GOC 2000-bus systems, providing a scalable and physically consistent surrogate for real-time AC-OPF. Full article
(This article belongs to the Special Issue Advanced Control Strategies and Optimization for Renewable Energy Systems)
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16 pages, 3072 KB  
Article
Voltage Strength Assessment of Sending/Receiving Systems with a High Proportion of New Energy and HVDC
by Biyang Wang, Yu Kou, Dehai Zhang, Qinglei Zhang, Haibo Li, Zongxiang Lu and Ying Qiao
Appl. Syst. Innov. 2025, 8(5), 120; https://doi.org/10.3390/asi8050120 - 25 Aug 2025
Cited by 1 | Viewed by 1508
Abstract
The significant increase in renewable energy sources and HVDC transmission has resulted in a substantial reduction in power system stability, thereby giving rise to a growing concern regarding the safety and stability of the voltage and frequency of DC power systems. A survey [...] Read more.
The significant increase in renewable energy sources and HVDC transmission has resulted in a substantial reduction in power system stability, thereby giving rise to a growing concern regarding the safety and stability of the voltage and frequency of DC power systems. A survey of the extant literature pertaining to both DC outgoing systems and new energy power systems reveals a preponderance of studies that employ the short-circuit ratio or multi-site short-circuit ratio as a metric for strength evaluation. However, it is evident that there is an absence of a universally applicable and comprehensive strength definition index for new energy and DC-accessed sending/receiving systems. Thus, the present paper puts forward a novel voltage stiffness-based strength evaluation index for new energy and DC-accessed sending/receiving systems and provides a qualitative analysis from the perspective of static voltage stability support. The static stability limit and transient overvoltage limit correspond to impedance ratios of 1 and 2.56, respectively. The findings demonstrate the efficacy of the proposed index in accurately gauging the strength of the sending system. The index’s versatility is further highlighted by its wide applicability in the sending/receiving systems of new energy and HVDC access. Full article
(This article belongs to the Special Issue Advanced Control Strategies and Optimization for Renewable Energy Systems)
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Review

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30 pages, 15647 KB  
Review
Artificial Intelligence and Metaheuristic Optimization Strategies for Renewable Microgrid Sizing and Design: A Scoping Review
by Eliseo Zarate-Perez, Cesar Santos-Mejía, Enrique Rosales-Asensio and Pedro Cabrera
Appl. Syst. Innov. 2026, 9(8), 165; https://doi.org/10.3390/asi9080165 - 4 Aug 2026
Viewed by 471
Abstract
Optimal sizing and design of renewable microgrids and hybrid renewable energy systems require balancing renewable resource variability, demand uncertainty, storage operation, reliability, and techno-economic constraints. Artificial intelligence and metaheuristic optimization strategies have been increasingly used to address these challenges; however, the evidence remains [...] Read more.
Optimal sizing and design of renewable microgrids and hybrid renewable energy systems require balancing renewable resource variability, demand uncertainty, storage operation, reliability, and techno-economic constraints. Artificial intelligence and metaheuristic optimization strategies have been increasingly used to address these challenges; however, the evidence remains methodologically heterogeneous. This scoping review maps the literature on artificial intelligence, learning-based, metaheuristic, heuristic, and optimization-based strategies for renewable microgrid sizing and design. The review followed PRISMA-ScR guidelines. Searches were conducted in Scopus and the Web of Science Core Collection for research articles published between 2009 and March 2026. A total of 69 studies were included. Metaheuristics dominated the field, appearing in 63 studies, with particle swarm optimization and genetic algorithm-based strategies as the most frequent methodological families. Artificial intelligence and learning-based strategies were mainly used to support forecasting, surrogate modeling, uncertainty handling, and energy management. The most recurrent configurations involved photovoltaic, wind, and battery storage systems, often with diesel backup in stand-alone or off-grid contexts. The literature is strongly oriented toward metaheuristic sizing of PV–wind–battery microgrids, with emerging integration of AI-assisted prediction and decision-support strategies. Future studies should address reproducibility, uncertainty modeling, real-world validation, degradation assessment, explainability, and scalability. Full article
(This article belongs to the Special Issue Advanced Control Strategies and Optimization for Renewable Energy Systems)
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