Energies

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20 pages, 5651 KiB

Open AccessArticle

Novel Fuzzy Control Energy Management Strategy for Fuel Cell Hybrid Electric Vehicles Considering State of Health

by Xiao Hu, Shikun Liu, Ke Song, Yuan Gao and Tong Zhang

Energies 2021, 14(20), 6481; https://doi.org/10.3390/en14206481 - 10 Oct 2021

Cited by 12 | Viewed by 2761

Due to the low efficiency and high pollution of conventional internal combustion engine vehicles, the fuel cell hybrid electric vehicles are expected to play a key role in the future of clean energy transportation attributed to the long driving range, short hydrogen refueling [...] Read more.

Due to the low efficiency and high pollution of conventional internal combustion engine vehicles, the fuel cell hybrid electric vehicles are expected to play a key role in the future of clean energy transportation attributed to the long driving range, short hydrogen refueling time and environmental advantages. The development of energy management strategies has an important impact on the economy and durability, but most strategies ignore the aging of fuel cells and the corresponding impact on hydrogen consumption. In this paper, a rule-based fuzzy control strategy is proposed based on the constructed data-driven online estimation model of fuel cell health. Then, a genetic algorithm is used to optimize this fuzzy controller, where the objective function is designed to consider both the economy and durability by combining the hydrogen consumption cost and the degradation cost characterized by the fuel cell health status. Considering that the rule-based strategy is more sensitive to operating conditions, this paper uses an artificial neural network for predictive control. The results are compared with those obtained from the genetic algorithm optimized fuzzy controller and are found to be very similar, where the prediction accuracy is assessed using MAPE, RMSE and 10-fold cross-validation. Experiments show that the developed strategy has a good generalization capability for variable driving cycles. Full article

(This article belongs to the Special Issue Renewables-Based Microgrids)

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23 pages, 58092 KiB

Open AccessArticle

Techno-Economic Analysis of a Fuzzy Logic Control Based Hybrid Renewable Energy System to Power a University Campus in Japan

by Tatsuya Hinokuma, Hooman Farzaneh and Ayas Shaqour

Energies 2021, 14(7), 1960; https://doi.org/10.3390/en14071960 - 1 Apr 2021

Cited by 19 | Viewed by 3686

Abstract

In order to reduce the load demand of buildings in Japan, this study proposes a grid-tied hybrid solar–wind–hydrogen system that is equipped with a maximum power point tracking (MPPT) system, using a fuzzy logic control (FLC) algorithm. Compared with the existing MPPTs, the [...] Read more.

In order to reduce the load demand of buildings in Japan, this study proposes a grid-tied hybrid solar–wind–hydrogen system that is equipped with a maximum power point tracking (MPPT) system, using a fuzzy logic control (FLC) algorithm. Compared with the existing MPPTs, the proposed MPPT provides rapid power control with small oscillations. The dynamic simulation of the proposed hybrid renewable energy system (HRES) was performed in MATLAB-Simulink, and the model results were validated using an experimental setup installed in the Chikushi campus, Kyushu University, Japan. The techno-economic analysis (TEA) of the proposed system was performed to estimate the optimal configuration of the proposed HRES, subject to satisfying the required annual load in the Chikushi campus. The results revealed a potential of 2% surplus power generation from the proposed HRES, using the FLC-based MPPT system, which can guarantee a lower levelized cost of electricity (LOCE) for the HRES and significant savings of 2.17 million yen per year. The TEA results show that reducing the cost of the solar system market will lead to a reduction in LCOE of the HRES in 2030. Full article

(This article belongs to the Special Issue Renewables-Based Microgrids)

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31 pages, 10680 KiB

Open AccessArticle

Design and Validation of Energy Management Strategy for Extended-Range Fuel Cell Electric Vehicle Using Bond Graph Method

by Ke Song, Yimin Wang, Cancan An, Hongjie Xu and Yuhang Ding

Energies 2021, 14(2), 380; https://doi.org/10.3390/en14020380 - 12 Jan 2021

Cited by 13 | Viewed by 3167

Abstract

In view of the aggravation of global pollution and greenhouse effects, fuel cell electric vehicles (FCEVs) have attracted increasing attention, owing to their ability to release zero emissions. Extended-range fuel cell vehicles (E-RFCEVs) are the most widely used type of fuel cell vehicles. [...] Read more.

In view of the aggravation of global pollution and greenhouse effects, fuel cell electric vehicles (FCEVs) have attracted increasing attention, owing to their ability to release zero emissions. Extended-range fuel cell vehicles (E-RFCEVs) are the most widely used type of fuel cell vehicles. The powertrain system of E-RFCEV is relatively complex. Bond graph theory was used to model the important parts of the E-RFCEV powertrain system: Battery, motor, fuel cell, DC/DC, vehicle, and driver. In order to verify the control effect of energy management strategy (EMS) in a real-time state, bond graph theory was applied to hardware-in-the-loop (HiL) development. An HiL simulation test-bed based on the bond graph model was built, and the HiL simulation verification of the energy management strategy was completed. Based on the comparison to a power-following EMS, it was found that fuzzy logic EMS is more adaptive to vehicle driving conditions. This study aimed to apply bond graph theory to HiL simulations to verify that bond graph modeling is applicable to complex systems. Full article

(This article belongs to the Special Issue Renewables-Based Microgrids)

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16 pages, 1686 KiB

Open AccessArticle

Can Green Hydrogen Production Be Economically Viable under Current Market Conditions

by David Jure Jovan and Gregor Dolanc

Energies 2020, 13(24), 6599; https://doi.org/10.3390/en13246599 - 14 Dec 2020

Cited by 103 | Viewed by 12491

Abstract

This paper discusses the potential of green hydrogen production in a case study of a Slovenian hydro power plant. To assess the feasibility and eligibility of hydrogen production at the power plant, we present an overview of current hydrogen prices and the costs [...] Read more.

This paper discusses the potential of green hydrogen production in a case study of a Slovenian hydro power plant. To assess the feasibility and eligibility of hydrogen production at the power plant, we present an overview of current hydrogen prices and the costs of the power-to-gas system for green hydrogen production. After defining the production cost for hydrogen at the case study hydro power plant, we elaborate on the profitability of hydrogen production over electricity. As hydrogen can be used as a sustainable energy vector in industry, heating, mobility, and the electro energetic sectors, we discuss the current competitiveness of hydrogen in the heating and transport sectors. Considering the current prices of different fuels, it is shown that hydrogen can be competitive in the transport sector if it is unencumbered by various environmental taxes. The second part of the paper deals with hydrogen production in the context of secondary control ancillary service provided by a case study power plant. Namely, hydrogen can be produced during the time period when there is no demand for extra electric power within a secondary control ancillary service, and thus the economics of power plant operation can be improved. Full article

(This article belongs to the Special Issue Renewables-Based Microgrids)

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21 pages, 6344 KiB

Open AccessArticle

Online Prediction of Vehicular Fuel Cell Residual Lifetime Based on Adaptive Extended Kalman Filter

by Ke Song, Yimin Wang, Xiao Hu and Jing Cao

Energies 2020, 13(23), 6244; https://doi.org/10.3390/en13236244 - 26 Nov 2020

Cited by 13 | Viewed by 2244

Abstract

The limited lifetime of proton exchange membrane fuel cell (PEMFC) inhibits the further development of the fuel cell industry. Prediction is one of the most effective means for managing the lifetime of a fuel cell because it can assist in the implementation of [...] Read more.

The limited lifetime of proton exchange membrane fuel cell (PEMFC) inhibits the further development of the fuel cell industry. Prediction is one of the most effective means for managing the lifetime of a fuel cell because it can assist in the implementation of mitigation actions before a vehicular fuel cell fails by estimating the residual lifetime. Therefore, this study aimed to develop a PEMFC lifetime prediction method for online applications. This paper presents the online prediction method developed for the residual lifetime of a vehicular fuel cell, which utilises data processing with an adaptive extended Kalman filter and a prediction formula. The formula considers different operating conditions and the external environment, which is in accord with the actual operating conditions of fuel cell vehicles. This method realises the online prediction of the residual lifetime of a vehicular fuel cell by updating weight coefficients for the operating conditions and environmental factors. This prediction method was validated and analysed using a simulation. The influences of key parameters on the stability and prediction accuracy of the algorithm were evaluated. The prediction method proposed in this paper can provide a reference for studies on fuel cell lifetime prediction. Full article

(This article belongs to the Special Issue Renewables-Based Microgrids)

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13 pages, 1263 KiB

Open AccessArticle

Source Diagnosis of Solid Oxide Fuel Cell System Oscillation Based on Data Driven

by Xiaowei Fu, Yanlin Liu and Xi Li

Energies 2020, 13(16), 4069; https://doi.org/10.3390/en13164069 - 6 Aug 2020

Cited by 5 | Viewed by 2861

Abstract

The solid oxide fuel cell (SOFC) is a new energy technology that has the advantages of low emissions and high efficiency. However, oscillation and propagation often occur during the power generation of the system, which causes system performance degradation and reduced service life. [...] Read more.

The solid oxide fuel cell (SOFC) is a new energy technology that has the advantages of low emissions and high efficiency. However, oscillation and propagation often occur during the power generation of the system, which causes system performance degradation and reduced service life. To determine the root cause of multi-loop oscillation in an SOFC system, a data-driven diagnostic method is proposed in this paper. In our method, kernel principal component analysis (KPCA) and transfer entropy were applied to the system oscillation fault location. First, based on the KPCA method and the Oscillation Significance Index (OSI) of the system process variable, the process variables that were most affected by the oscillations were selected. Then, transfer entropy was used to quantitatively analyze the causal relationship between the oscillation variables and the oscillation propagation path, which determined the root cause of the oscillation. Finally, Granger causality (GC) analysis was used to verify the correctness of our method. The experimental results show that the proposed method can accurately and effectively locate the root cause of the SOFC system’s oscillation. Full article

(This article belongs to the Special Issue Renewables-Based Microgrids)

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Graphical abstract

15 pages, 2731 KiB

Open AccessFeature PaperArticle

Self-Sufficient and Islanded-Oriented Design of a Reversible Solid Oxide Cell-Based Renewable Microgrid

by Marco Sorrentino, Antonio Adamo and Gianmarco Nappi

Energies 2019, 12(17), 3224; https://doi.org/10.3390/en12173224 - 21 Aug 2019

Cited by 12 | Viewed by 2889

Abstract

This article presents the development of a constrained optimization algorithm, whose scope is to support the preliminary design of a renewable microgrid, integrating solar panels and wind turbines with reversible solid oxide cells. The motivations behind this research activity lie in the increasing [...] Read more.

This article presents the development of a constrained optimization algorithm, whose scope is to support the preliminary design of a renewable microgrid, integrating solar panels and wind turbines with reversible solid oxide cells. The motivations behind this research activity lie in the increasing interest in renewable-based production and on-site storage of hydrogen, and its aim is to help this energy vector spread worldwide and in as many industrial and residential sectors as possible within a reasonably short timeframe. To this end, suitable models were developed by referring to the most relevant literature and by introducing some specific simplifying assumptions. Such an approach allowed the setting-up of a multi-variable constrained optimization task, whose outcomes correspond to the most techno-economic effective plant configuration with respect to assigned design criteria. The optimum solution was particularly sought via the generalized reduced gradient method, aimed at determining renewable plants sizes under the constraint that the final stored hydrogen level is brought back to the initial value after one year. The results highlight that an interesting payback time of about 10 years can be attained, while guaranteeing that the optimal configuration holds promising resiliency and islanded-use capabilities (such as almost weekly self-sufficiency) via smart over-the-year charge-sustaining management of the designed hydrogen storage tank. In this way, it was possible to simultaneously address, via the specific optimization problem formulation, the interconnected needs of optimally designing system components in terms of installed power, and the proper management of the reversible solid oxide cell unit. Full article

(This article belongs to the Special Issue Renewables-Based Microgrids)

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22 pages, 2783 KiB

Open AccessArticle

How Hybridization of Energy Storage Technologies Can Provide Additional Flexibility and Competitiveness to Microgrids in the Context of Developing Countries

by Linda Barelli, Gianni Bidini, Paolo Cherubini, Andrea Micangeli, Dario Pelosi and Carlo Tacconelli

Energies 2019, 12(16), 3138; https://doi.org/10.3390/en12163138 - 15 Aug 2019

Cited by 25 | Viewed by 4691

Abstract

Hybrid microgrids, integrating renewable energy sources and energy storage, are key in extending energy access in the remote areas of developing countries, in a sustainably way and in providing a good quality of service. Their extensive development faces a financing gap, having a [...] Read more.

Hybrid microgrids, integrating renewable energy sources and energy storage, are key in extending energy access in the remote areas of developing countries, in a sustainably way and in providing a good quality of service. Their extensive development faces a financing gap, having a high capital expenditure (CAPEX) also due to high storage costs. In the present work, a case study of a Ugandan microgrid was used to compare various battery technologies employed on their own and in a combination with a flywheel, in terms of their durability and the overall levelized cost of energy (LCOE) of the plant. Simulations show how hybrid storage configurations result in a lower LCOE for the current load profile of the microgrid and even more so for two reference residential and industrial load scenarios, suggesting this would remain the best solution even accounting for future socio-economic development. The resulting LCOE for hybrid storage configurations is lower than the average values reported for microgrid projects and represents a promising solution to speed up the development of such electrification initiatives. Full article

(This article belongs to the Special Issue Renewables-Based Microgrids)

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