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Fractal Fract
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Advances in Fractional-Order Control and Optimization for Sustainable Energy Systems
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Advances in Fractional-Order Control and Optimization for Sustainable Energy Systems

A special issue of Fractal and Fractional (ISSN 2504-3110). This special issue belongs to the section "Engineering".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 1659

Special Issue Editors

Dr. Jiuwu Hui

E-Mail Website
Guest Editor
Department of Building Environment and Energy Engineering, The Hong Kong Polytechnic University, Hong Kong, China
Interests: fractional-order control; fractional calculus; robust control; adaptive control; nonlinear systems; stability analysis; real-time applications
Dr. Aldo Jonathan Muñoz-Vazquez

E-Mail Website
Guest Editor
Department of Computer, Electrical & Software Engineering, Embry-Riddle Aeronautical University, Prescott, AZ 86301-3720, USA
Interests: fractional calculus; nonlinear systems; robotics; fuzzy logics; neural networks; control theory; integral equations; robotics and autonomous systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Fractional-order control and design techniques have emerged as powerful tools for advancing sustainable energy systems, offering enhanced performance, robustness, and flexibility in modeling and controlling complex renewable energy dynamics. Unlike traditional integer-order controllers, fractional-order controllers leverage fractional calculus to better capture the memory effects, nonlinearities, and distributed characteristics inherent in green energy technologies. This Special Issue will highlight cutting-edge developments in fractional-order control theory and its transformative applications in sustainable energy systems. Fractional-order methods provide critical advantages for renewable energy integration and optimization: Precision modeling of renewable resources: Fractional-order systems accurately characterize the complex dynamics of solar irradiance, wind patterns, and energy storage behaviors.

  • Robust grid integration: Fractional controllers enhance stability in power networks with high renewable penetration, mitigating intermittency challenges.
  • Optimal energy conversion: Advanced control schemes maximize efficiency in photovoltaic systems, wind turbines, and hybrid renewable plants.
  • Intelligent storage management: Fractional-order algorithms optimize battery performance and lifespan in energy storage systems.
Key application areas include:
  • Smart renewable generation: Fractional MPPT control for solar/wind systems, fault-tolerant operation
  • Grid-scale energy storage: Fractional control of battery arrays, supercapacitors, and hybrid storage systems
  • Microgrid coordination: Stability enhancement and power quality improvement using fractional strategies
  • Sustainable transportation: Energy management in EV charging networks and vehicle-to-grid systems
  • Green hydrogen systems: Fractional control of electrolyzers and fuel cell systems.

We invite contributions addressing these critical challenges through fractional-order approaches. Topics of interest include, but are not limited to:

  • Fractional-order modeling of renewable energy resources
  • Advanced control designs for wind/solar/hydrogen systems
  • Stability analysis of renewable-rich power networks
  • AI-enhanced fractional control for smart grids
  • Energy storage optimization using fractional calculus
  • Sustainable transportation energy management
  • Microgrid and distributed energy resource control
  • Real-world implementations and case studies.

Dr. Jiuwu Hui
Dr. Aldo Jonathan Muñoz-Vazquez
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. Fractal and Fractional 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 2700 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

  • fractional-order control
  • fractional calculus
  • robust control
  • adaptive control
  • nonlinear systems
  • stability analysis
  • real-time applications

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Published Papers (1 paper)

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Research

43 pages, 10093 KB  
Article
A Novel Red-Billed Blue Magpie Optimizer Tuned Adaptive Fractional-Order for Hybrid PV-TEG Systems Green Energy Harvesting-Based MPPT Algorithms
by Al-Wesabi Ibrahim, Abdullrahman A. Al-Shamma’a, Jiazhu Xu, Danhu Li, Hassan M. Hussein Farh and Khaled Alwesabi
Fractal Fract. 2025, 9(11), 704; https://doi.org/10.3390/fractalfract9110704 - 31 Oct 2025
Cited by 4 | Viewed by 1235
Abstract
Hybrid PV-TEG systems can harvest both solar electrical and thermoelectric power, but their operating point drifts with irradiance, temperature gradients, partial shading, and load changes—often yielding multi-peak P-V characteristics. Conventional MPPT (e.g., P&O) and fixed-structure integer-order PID struggle to remain fast, stable, and [...] Read more.
Hybrid PV-TEG systems can harvest both solar electrical and thermoelectric power, but their operating point drifts with irradiance, temperature gradients, partial shading, and load changes—often yielding multi-peak P-V characteristics. Conventional MPPT (e.g., P&O) and fixed-structure integer-order PID struggle to remain fast, stable, and globally optimal in these conditions. To address fast, robust tracking in these conditions, we propose an adaptive fractional-order PID (FOPID) MPPT whose parameters (Kp, Ki, Kd, λ, μ) are auto-tuned by the red-billed blue magpie optimizer (RBBMO). RBBMO is used offline to set the controller’s search ranges and weighting; the adaptive law then refines the gains online from the measured ΔV, ΔI slope error to maximize the hybrid PV-TEG output. The method is validated in MATLAB R2024b/Simulink 2024b, on a boost-converter–interfaced PV-TEG using five testbeds: (i) start-up/search, (ii) stepwise irradiance, (iii) partial shading with multiple local peaks, (iv) load steps, and (v) field-measured irradiance/temperature from Shanxi Province for spring/summer/autumn/winter. Compared with AOS, PSO, MFO, SSA, GHO, RSA, AOA, and P&O, the proposed tracker is consistently the fastest and most energy-efficient: 0.06 s to reach 95% MPP and 0.12 s settling at start-up with 1950 W·s harvested (vs. 1910 W·s AOS, 1880 W·s PSO, 200 W·s P&O). Under stepwise irradiance, it delivers 0.95–0.98 kJ at t = 1 s and under partial shading, 1.95–2.00 kJ, both with ±1% steady ripple. Daily field energies reach 0.88 × 10−3, 2.95 × 10−3, 2.90 × 10−3, 1.55 × 10−3 kWh in spring–winter, outperforming the best baselines by 3–10% and P&O by 20–30%. Robustness tests show only 2.74% power derating across 0–40 °C and low variability (Δvmax typically ≤ 1–1.5%), confirming rapid, low-ripple tracking with superior energy yield. Finally, the RBBMO-tuned adaptive FOPID offers a superior efficiency–stability trade-off and robust GMPP tracking across all five cases, with modest computational overhead. Full article
(This article belongs to the Special Issue Advances in Fractional-Order Control and Optimization for Sustainable Energy Systems)
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