Special Issue "Optimal Control of Hybrid Systems and Renewable Energies"

A special issue of Energies (ISSN 1996-1073). This special issue belongs to the section "Electrical Power and Energy System".

Deadline for manuscript submissions: 31 December 2019.

Special Issue Editors

Guest Editor
Prof. Dr. Michela Robba Website E-Mail
Department of Informatics, Bioengineering, Roborotics, and Systems Engineering, University of Genova, Italy
Phone: +39 3805105692
Interests: automatic control; optimal control; optimization; energy systems; smart grids
Guest Editor
Prof. Dr. Mansueto Rossi Website E-Mail
Department of Electrical, Electronics and Telecommunication Engineering and Naval Architecture, University of Genova, Italy
Phone: +39 3285423470
Interests: renewable and decentralized energy resources

Special Issue Information

Dear Colleagues,

International policies for sustainable development have led to an increase of distributed power production based on renewable resources. However, on the one hand, their intermittency may create problems for the electrical grid, and, on the other hand, they are costly. It is necessary to define new technological solutions that can reduce costs and new control strategies to optimally manage renewable resources and to integrate them into the new energy systems, which are more and more characterized by the close interaction between different energy vectors and their networks (thermal, electrical, etc.) and by a transition from a centralized structure to a decentralized one (both in terms of sources and controls).

The main aim of this Special Issue is to collect papers in the field of the optimal control of power and energy production from renewable resources (wind, PV, biomass, hydrogen, etc.). The specific topics of the Special Issue (but not limited to) are:

  • Modelling and control of wind turbines, PV and solar thermal plants, etc.;
  • Optimal control of hybrid systems (wind, hydrogen, fuel cells, hydro-electric plants, etc.);
  • Operational management of biomass-based power plants;
  • Optimization and control of energy systems;
  • Stochastic optimization;
  • Model predictive control;
  • Distributed optimization;
  • Optimal control of storage systems;
  • Modelling and control of flexible loads.

Prof. Dr. Michela Robba
Prof. Dr. Mansueto Rossi
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 papers will be 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 1800 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

  • optimal control
  • optimization
  • renewable resources
  • storage systems
  • power converters
  • wind
  • biomass
  • photovoltaics
  • solar thermal

Published Papers (5 papers)

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Research

Open AccessArticle
A Comparison of the Dynamic Performance of Conventional and Ternary Pumped Storage Hydro
Energies 2019, 12(18), 3513; https://doi.org/10.3390/en12183513 - 12 Sep 2019
Abstract
With decreasing costs of renewable energy harvesting devices, penetration of solar panels and wind turbines have increased manifold. Under such high levels of penetration, coping with increased intermittency and unpredictability and maintaining power system resiliency under reduced inertia conditions has become a critical [...] Read more.
With decreasing costs of renewable energy harvesting devices, penetration of solar panels and wind turbines have increased manifold. Under such high levels of penetration, coping with increased intermittency and unpredictability and maintaining power system resiliency under reduced inertia conditions has become a critical issue. Pumped storage hydro (PSH) is the most matured and economic form of storage that can serve the purpose of capacity for over 4 to 8 h. However, to increase network inertia and add required flexibility to low inertia power systems, significant paradigm shifting modifications have been engineered to result in the development of Ternary PSH (TPSH). In this paper a test system to consider governor interaction is constructed. The dynamic models of conventional PSH (CPSH) and TPSH are constructed and integrated to the test system to examine the effect of CPSH and TPSH in the hydraulic short circuit (TPSH-HSC). The ability and the effect of mode change (from pump to turbine) without the loss synchronism of TPSH has also been examined. Results display the superior capability and effect of TPSH with its HSC capability to contribute to frequency regulation during pumping mode and the effect of rapid mode change, as compared to its primitive alternative, CPSH. Full article
(This article belongs to the Special Issue Optimal Control of Hybrid Systems and Renewable Energies)
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Open AccessArticle
A Feedback Control Loop Optimisation Methodology for Floating Offshore Wind Turbines
Energies 2019, 12(18), 3490; https://doi.org/10.3390/en12183490 - 10 Sep 2019
Abstract
Wind turbines usually present several feedback control loops to improve or counteract some specific performance or behaviour of the system. It is common to find these multiple feedback control loops in Floating Offshore Wind Turbines where the system perferformance is highly influenced by [...] Read more.
Wind turbines usually present several feedback control loops to improve or counteract some specific performance or behaviour of the system. It is common to find these multiple feedback control loops in Floating Offshore Wind Turbines where the system perferformance is highly influenced by the platform dynamics. This is the case of the Aerodynamic Platform Stabiliser and Wave Rejection feedback control loops which are complementaries to the conventional generator speed PI control loop when it is working in an above rated wind speed region. The multiple feedback control loops sometimes can be tedious to manually improve the initial tuning. Therefore, this article presents a novel optimisation methodology based on the Monte Carlo method to automatically improve the manually tuned multiple feedback control loops. Damage Equivalent Loads are quantified for minimising the cost function and automatically update the control parameters. The preliminary results presented here show the potential of this novel optimisation methodology to improve the mechanical fatigue loads of the desired components whereas maintaining the overall performance of the wind turbine system. This methodology provides a good balance between the computational complexity and result effectiveness. The study is carried out with the fully coupled non-linear NREL 5-MW wind turbine model mounted on the ITI Energy’s barge and the FASTv8 code. Full article
(This article belongs to the Special Issue Optimal Control of Hybrid Systems and Renewable Energies)
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Open AccessArticle
Control of Hybrid Diesel/PV/Battery/Ultra-Capacitor Systems for Future Shipboard Microgrids
Energies 2019, 12(18), 3460; https://doi.org/10.3390/en12183460 - 07 Sep 2019
Abstract
In recent times, concerns over fossil fuel consumption and severe environmental pollution have grabbed attention in marine vessels. The fast development in solar technology and the significant reduction in cost over the past decade have allowed the integration of solar technology in marine [...] Read more.
In recent times, concerns over fossil fuel consumption and severe environmental pollution have grabbed attention in marine vessels. The fast development in solar technology and the significant reduction in cost over the past decade have allowed the integration of solar technology in marine vessels. However, the highly intermittent nature of photovoltaic (PV) modules might cause instability in shipboard microgrids. Moreover, the penetration is much more in the case of utilizing PV panels on ships due to the continuous movement. This paper, therefore, presents a frequency sharing approach to smooth the effect of the highly intermittent nature of PV panels integrated with the shipboard microgrids. A hybrid system based on an ultra-capacitor and a lithium-ion battery is developed such that high power and short term fluctuations are catered by an ultra-capacitor, whereas long duration and high energy density fluctuations are catered by the lithium-ion battery. Further, in order to cater for the fluctuations caused by weather or variation in sea states, a battery energy storage system (BESS) is utilized in parallel to the dc-link capacitor using a buck-boost converter. Hence, to verify the dynamic behavior of the proposed approach, the model is designed in MATLAB/SIMULINK. The simulation results illustrate that the proposed model helps to smooth the fluctuations and to stabilize the DC bus voltage. Full article
(This article belongs to the Special Issue Optimal Control of Hybrid Systems and Renewable Energies)
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Open AccessArticle
Hybrid Nonlinear MPC of a Solar Cooling Plant
Energies 2019, 12(14), 2723; https://doi.org/10.3390/en12142723 - 16 Jul 2019
Abstract
Solar energy for cooling systems has been widely used to fulfill the growing air conditioning demand. The advantage of this approach is based on the fact that the need of air conditioning is usually well correlated to solar radiation. These kinds of plants [...] Read more.
Solar energy for cooling systems has been widely used to fulfill the growing air conditioning demand. The advantage of this approach is based on the fact that the need of air conditioning is usually well correlated to solar radiation. These kinds of plants can work in different operation modes resulting on a hybrid system. The control approaches designed for this kind of plant have usually a twofold goal: (a) regulating the outlet temperature of the solar collector field and (b) choosing the operation mode. Since the operation mode is defined by a set of valve positions (discrete variables), the overall control problem is a nonlinear optimization problem which involves discrete and continuous variables. This problems are difficult to solve within the normal sampling times for control purposes (around 20–30 s). In this paper, a two layer control strategy is proposed. The first layer is a nonlinear model predictive controller for regulating the outlet temperature of the solar field. The second layer is a fuzzy algorithm which selects the adequate operation mode for the plant taken into account the operation conditions. The control strategy is tested on a model of the plant showing a proper performance. Full article
(This article belongs to the Special Issue Optimal Control of Hybrid Systems and Renewable Energies)
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Open AccessArticle
A Firefly Algorithm Optimization-Based Equivalent Consumption Minimization Strategy for Fuel Cell Hybrid Light Rail Vehicle
Energies 2019, 12(14), 2665; https://doi.org/10.3390/en12142665 - 11 Jul 2019
Abstract
To coordinate multiple power sources properly, this paper presents an optimal control strategy for a fuel cell/battery/supercapacitor light rail vehicle. The proposed strategy, which uses the firefly algorithm to optimize the equivalent consumption minimization strategy, improves the drawback that the conventional equivalent consumption [...] Read more.
To coordinate multiple power sources properly, this paper presents an optimal control strategy for a fuel cell/battery/supercapacitor light rail vehicle. The proposed strategy, which uses the firefly algorithm to optimize the equivalent consumption minimization strategy, improves the drawback that the conventional equivalent consumption minimization strategy takes insufficient account of the global performance for the vehicle. Moreover, the strategy considers the difference between the two sets of optimized variables. The optimization objective is to minimize the daily operating cost of the vehicle, which includes the total fuel consumption, initial investment, and cycling costs of power sources. The selected case study is a 100% low-floor light rail vehicle. The advantages of the proposed strategy are investigated by comparison with the operating mode control, firefly algorithm-based operating mode control, and equivalent consumption minimization strategy. In contrast to other methods, the proposed strategy shows cost reductions of up to 39.62% (from operating mode control), 18.28% (from firefly algorithm-based operating mode control), and 13.81% (from equivalent consumption minimization strategy). In addition, the proposed strategy can reduce fuel consumption and increase the efficiency of the fuel cell system. Full article
(This article belongs to the Special Issue Optimal Control of Hybrid Systems and Renewable Energies)
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