Research

29 pages, 4504 KiB

Open AccessArticle

Global Sensitivity Analysis Applied to Train Traffic Rescheduling: A Comparative Study

by Soha Saad, Florence Ossart, Jean Bigeon, Etienne Sourdille and Harold Gance

Energies 2021, 14(19), 6420; https://0-doi-org.brum.beds.ac.uk/10.3390/en14196420 - 08 Oct 2021

Cited by 1 | Viewed by 1566

The adjustment of rail traffic in the event of an electrical infrastructure disruption presents an important decision-making process for the smooth operation of the network. Railway systems are complex, and their analysis relies on expensive simulations, which makes incident management difficult. This paper [...] Read more.

The adjustment of rail traffic in the event of an electrical infrastructure disruption presents an important decision-making process for the smooth operation of the network. Railway systems are complex, and their analysis relies on expensive simulations, which makes incident management difficult. This paper proposes the use of sensitivity analysis in order to evaluate the influence of different traffic adjustment actions (e.g., spacing between trains and speed reduction) on the train supply voltage, which must never drop below the critical value prescribed by technical standards. Three global sensitivity analysis methods dedicated to black box, multivariate, nonlinear models are considered: generalized Sobol indices, energy distance-based indices, and regional sensitivity analysis. The three methods are applied to a simple traffic rescheduling test case and give similar results, but at different costs. Regional sensitivity analysis appears to be the most suitable method for the present application: it is easy to implement, rather fast, and accounts for constraints on the system output (a key feature for electrical incident management). The application of this method to a test case representative of a real rescheduling problem shows that it provides the information needed by the traffic manager to reschedule traffic in an efficient way. The same type of approach can be used for any power system optimization problem with the same characteristics. Full article

(This article belongs to the Special Issue Simulation and Optimization of Electrotechnical Systems)

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21 pages, 24067 KiB

Open AccessArticle

Approximation of Permanent Magnet Motor Flux Distribution by Partially Informed Neural Networks

by Marcin Jastrzębski and Jacek Kabziński

Energies 2021, 14(18), 5619; https://0-doi-org.brum.beds.ac.uk/10.3390/en14185619 - 07 Sep 2021

Viewed by 1383

Abstract

New results in the area of neural network modeling applied in electric drive automation are presented. Reliable models of permanent magnet motor flux as a function of current and rotor position are particularly useful in control synthesis—allowing one to minimize the losses, analyze [...] Read more.

New results in the area of neural network modeling applied in electric drive automation are presented. Reliable models of permanent magnet motor flux as a function of current and rotor position are particularly useful in control synthesis—allowing one to minimize the losses, analyze motor performance (torque ripples etc.) and to identify motor parameters—and may be used in the control loop to compensate flux and torque variations. The effectiveness of extreme learning machine (ELM) neural networks used for approximation of permanent magnet motor flux distribution is evaluated. Two original network modifications, using preliminary information about the modeled relationship, are introduced. It is demonstrated that the proposed networks preserve all appealing features of a standard ELM (such as the universal approximation property and extremely short learning time), but also decrease the number of parameters and deal with numerical problems typical for ELMs. It is demonstrated that the proposed modified ELMs are suitable for modeling motor flux versus position and current, especially for interior permanent magnet motors. The modeling methodology is presented. It is shown that the proposed approach produces more accurate models and provides greater robustness against learning data noise. The execution times obtained experimentally from well-known DSP boards are short enough to enable application of derived models in modern algorithms of electric drive control. Full article

(This article belongs to the Special Issue Simulation and Optimization of Electrotechnical Systems)

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19 pages, 835 KiB

Open AccessArticle

Optimal Location and Sizing of Energy Storage Systems in DC-Electrified Railway Lines Using a Coral Reefs Optimization Algorithm with Substrate Layers

by David Roch-Dupré, Carlos Camacho-Gómez, Asunción P. Cucala, Silvia Jiménez-Fernández, Álvaro López-López, Antonio Portilla-Figueras, Ramón R. Pecharromán, Antonio Fernández-Cardador and Sancho Salcedo-Sanz

Energies 2021, 14(16), 4753; https://0-doi-org.brum.beds.ac.uk/10.3390/en14164753 - 05 Aug 2021

Cited by 4 | Viewed by 1674

Abstract

This paper deals with the problem of finding the optimal location and sizing of Energy Storage Systems in DC-electrified railway lines. These devices increment the use of the regenerated energy produced by the trains in the braking phases, as they store the energy [...] Read more.

This paper deals with the problem of finding the optimal location and sizing of Energy Storage Systems in DC-electrified railway lines. These devices increment the use of the regenerated energy produced by the trains in the braking phases, as they store the energy to later provide to the catenary the excess of regenerated energy, that otherwise would be lost in the rheostats. However, these infrastructures require a high initial investment that, in some cases, may question their profitability. We propose a multi-method ensemble meta-heuristic to obtain the optimal solution to the problem, with a high level of accuracy. Specifically, the Coral Reefs Optimization with Substrate Layers (CRO-SL) is proposed, an evolutionary-type approach able to run different search procedures within the same population. We will evaluate the performance of the CRO-SL in the problem, and we will show that it performs better than the best known existing meta-heuristics for this problem. Full article

(This article belongs to the Special Issue Simulation and Optimization of Electrotechnical Systems)

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16 pages, 3654 KiB

Open AccessArticle

Optimization and Coordination of Electric Vehicle Charging Process for Long-Distance Trips

by Jean Hassler, Zlatina Dimitrova, Marc Petit and Philippe Dessante

Energies 2021, 14(13), 4054; https://0-doi-org.brum.beds.ac.uk/10.3390/en14134054 - 05 Jul 2021

Cited by 7 | Viewed by 2603

Abstract

Battery electric vehicles offer many advantages in terms of performance and zero-emission pollutants, but their limited range for long-distance trips compromises their large-scale market penetration. The problem of range can be solved with a dense network of fast-charging stations and an increase in [...] Read more.

Battery electric vehicles offer many advantages in terms of performance and zero-emission pollutants, but their limited range for long-distance trips compromises their large-scale market penetration. The problem of range can be solved with a dense network of fast-charging stations and an increase in embedded battery capacity. Simultaneously, improvements in high-power charging point units offer range gains of hundreds of kilometers in a mere 20 min. One risk remains: The travel time depends on the availability of charging stations, which can drop during rush hours, due to long queues, or power grid constraints. These situations could significantly affect the user experience. In this paper, we presented an approach to coordinate EV charging station choices in the case of long-distance trips. This system relies on vehicle-to-infrastructure communications (V2X). The objective is to enhance the use of the infrastructure by improving the distribution of vehicles between the different charging stations, thus reducing waiting time. Our target is to build an efficient and easily deployable system. The performance of this system is compared to an uncoordinated situation and an offline optimization. We conducted a case study on a 550-km highway with heavy traffic. With this system, the results showed a 10% reduction in time spent in charging stations. Full article

(This article belongs to the Special Issue Simulation and Optimization of Electrotechnical Systems)

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25 pages, 5227 KiB

Open AccessArticle

Reliability Evaluation of Renewable Power Systems through Distribution Network Power Outage Modelling

by Fitsum Salehu Kebede, Jean-Christophe Olivier, Salvy Bourguet and Mohamed Machmoum

Energies 2021, 14(11), 3225; https://0-doi-org.brum.beds.ac.uk/10.3390/en14113225 - 31 May 2021

Cited by 11 | Viewed by 2528

Abstract

Intermittent power interruptions and blackouts with long outage durations are very common, especially on weak distribution grids such as in developing countries. This paper proposes a hybrid photovoltaic (PV)-battery-system sizing optimization through a genetic algorithm to address the reliability in fragile grids measured [...] Read more.

Intermittent power interruptions and blackouts with long outage durations are very common, especially on weak distribution grids such as in developing countries. This paper proposes a hybrid photovoltaic (PV)-battery-system sizing optimization through a genetic algorithm to address the reliability in fragile grids measured by the loss of power supply probability (LPSP) index. Recorded historical outage data from a real stochastic grid in Ethiopia and measured customer load is used. The resulting hybrid-system Pareto solutions give the flexibility for customers/power utilities to choose appropriate sizes based on the required reliability level. To evaluate the sizing solutions’ robustness, this work considers and compares grid outage modeling through two different approaches. The first is a Markov model, developed to be minimally implemented with limited outage data available. The second is a Weibull model, commonly used to describe extreme phenomena and failure analysis. It is more faithful in reproducing the dispersion of outage events. Using these models, the effectiveness and performance of the PV-battery system is verified on a large number of simulated outage scenarios, to estimate the real performance of the optimized design. It leads to a more accurate evaluation of the behavior of a renewable power system to a weak and unreliable electrical grid. Full article

(This article belongs to the Special Issue Simulation and Optimization of Electrotechnical Systems)

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16 pages, 1992 KiB

Open AccessArticle

Comparison of Tank and Battery Storages for Photovoltaic Water Pumping

by Camille Soenen, Vincent Reinbold, Simon Meunier, Judith A. Cherni, Arouna Darga, Philippe Dessante and Loïc Quéval

Energies 2021, 14(9), 2483; https://0-doi-org.brum.beds.ac.uk/10.3390/en14092483 - 27 Apr 2021

Cited by 14 | Viewed by 2653

Abstract

Photovoltaic water pumping systems (PVWPS) are a promising solution to improve domestic water access in low-income rural areas. It is challenging, however, to make them more affordable for the local communities. We develop here a comparative methodology to assess relevant features of both [...] Read more.

Photovoltaic water pumping systems (PVWPS) are a promising solution to improve domestic water access in low-income rural areas. It is challenging, however, to make them more affordable for the local communities. We develop here a comparative methodology to assess relevant features of both widely employed PVWPS architecture with water tank storage, and hardly used PVWPS architecture with a battery bank instead of tank storage. The quantitative comparison is carried out through techno-economic optimization, with the goal of minimizing the life cycle cost of PVWPS with constraints on the satisfaction of the water demand of local inhabitants and on the groundwater resource sustainability. It is aimed to support decision-makers in selecting most appropriate storage for domestic water supply projects. We applied the methodology in the rural village of Gogma, Burkina Faso. Results indicate that the life-cycle cost of an optimized PVWPS with batteries is $24.1k while it is $31.1k if a tank is used instead. Moreover, reduced impact on groundwater resources and greater modularity to adapt to evolving water demand is noted if using batteries. However, as batteries must be replaced regularly and recycled adequately, PVWPS’ financial accessibility could increase only if sustainable and efficient operation, maintenance, and recycling facilities for batteries were present or developed locally. Full article

(This article belongs to the Special Issue Simulation and Optimization of Electrotechnical Systems)

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24 pages, 2626 KiB

Open AccessArticle

Comparison of Cycle Reduction and Model Reduction Strategies for the Design Optimization of Hybrid Powertrains on Driving Cycles

by Adham Kaloun, Stéphane Brisset, Maxime Ogier, Mariam Ahmed and Robin Vincent

Energies 2021, 14(4), 948; https://0-doi-org.brum.beds.ac.uk/10.3390/en14040948 - 11 Feb 2021

Cited by 4 | Viewed by 1638

Abstract

Decision-making is a crucial and difficult step in the design process of complex systems such as the hybrid powertrain. Finding an optimal solution requires the system feedback. This can be, depending on the granularity of the models at the component level, highly time-consuming. [...] Read more.

Decision-making is a crucial and difficult step in the design process of complex systems such as the hybrid powertrain. Finding an optimal solution requires the system feedback. This can be, depending on the granularity of the models at the component level, highly time-consuming. This is even more true when the system’s performance is determined by its control. In fact, various possibilities can be selected to deliver the required torque to the wheels during a driving cycle. In this work, two different design strategies are proposed to minimize the fuel consumption and the cost of the hybrid powertrain. Both strategies adopt the iterative framework which allows for the separation of the powertrain design problem and its control while leading to system optimality. The first approach is based on model reduction, while the second approach relies on improved cycle reduction techniques. They are then applied to a parallel hybrid vehicle case study, leading to important cost reduction in reasonable delays and are compared using different metrics. Full article

(This article belongs to the Special Issue Simulation and Optimization of Electrotechnical Systems)

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14 pages, 6849 KiB

Open AccessArticle

The Use of Hypergeometric Functions in Hysteresis Modeling

by Dejana Herceg, Krzysztof Chwastek and Đorđe Herceg

Energies 2020, 13(24), 6500; https://0-doi-org.brum.beds.ac.uk/10.3390/en13246500 - 09 Dec 2020

Cited by 4 | Viewed by 2093

Abstract

Accurate hysteresis models are necessary for modeling of magnetic components of devices such as transformers and motors. This study presents a hysteresis model with a convenient analytical form, based on hypergeometric functions with one free parameter, built upon a class of parameterized curves. [...] Read more.

Accurate hysteresis models are necessary for modeling of magnetic components of devices such as transformers and motors. This study presents a hysteresis model with a convenient analytical form, based on hypergeometric functions with one free parameter, built upon a class of parameterized curves. The aim of this work is to explore suitability of the presented model for describing major and minor loops, as well as to demonstrate improved agreement between experimental and modeled hysteresis loops. The procedure for generating first order reversal curves is also discussed. The added parameter, introduced into the model, controls the shape of the model curve, especially near saturation. It can be adjusted to provide better agreement between measured and model curves. The model parameters are nonlinearly dependent; therefore, they are determined in a nonlinear curve fitting procedure. The choice of the initial approximation and a suitable set of constraints for the optimization procedure are discussed. The inverse of the model function, required to generate first order reversal curves, cannot be obtained in analytical form. The procedure to calculate the inverse numerically is presented. Performance of the model is demonstrated and verified on experimental data obtained from measurements on construction steel sheets and grain-oriented electrical steel samples. Full article

(This article belongs to the Special Issue Simulation and Optimization of Electrotechnical Systems)

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