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Renewable energy systems: Comparisons, challenges and barriers, sustainability indicators, and the contribution to UN sustainable development goals

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International Journal of Thermofluids 2023年 20卷

作者： Olabi, A.G. Elsaid, Khaled Obaideen, Khaled Abdelkareem, Mohammad Ali Rezk, Hegazy Wilberforce, Tabbi Maghrabie, Hussein M. Sayed, Enas Taha Dept. of Sustainable and Renewable Energy Engineering University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates Sustainable Energy & Power Systems Research Centre RISE University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates Mechanical Engineering and Design Aston University School of Engineering and Applied Science Aston Triangle Birmingham B4 7ET United Kingdom Chemical Engineering Program Texas A&M University at Qatar P.O. 23874 Doha Qatar Chemical Engineering Department Faculty of Engineering Minia University Elminia Egypt Department of Electrical Engineering College of Engineering in Wadi Alddawasir Prince Sattam bin Abdulaziz University Saudi Arabia Department of Mechanical Engineering Faculty of Engineering South Valley University Qena83521 Egypt

Because of the harsh environmental impacts of fossil fuels, price fluctuation, and resource limitation, renewable energy resources (RERs) are considered the ultimate solution to overcome these challenges. RERs are also abundant and environmentally friendly. It has been reported that the growth rates in renewable energy installations have increased by 8–9% annually since 2010, reaching a cumulative capacity of 2.9 TW by 2020 and exceeding the growth rate for fossil resources. In this work, the different RERs have been critically discussed in terms of their operation principles, advantages, disadvantages, and associated environmental impacts, focusing on wind and solar energies as the most deployed RERs. Barriers to the full deployment of RERs to replace fossil resources are discussed. Based on the discussion presented on RERs, the contribution of deploying RERs towards the achievement of the United Nations (UN) Sustainable Development Goals (SDGs) is also critically discussed. A total of 80 indicators have been identified for RERs' contribution toward the achievement of SDGs. © 2023 The Author(s)

关键词： Environmental impact

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Numerical simulation of heat pipes in different applications

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International Journal of Thermofluids 2022年 16卷

作者： Maghrabie, Hussein M. Olabi, A.G. Alami, Abdul Hai Radi, Muaz Al Zwayyed, Firas salamah, Tareq Wilberforce, Tabbi Abdelkareem, Mohammad Ali Department of Mechanical Engineering Faculty of Engineering South Valley University Qena83521 Egypt Sustainable Energy & Power Systems Research Centre RISE University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates Mechanical Engineering and Design Aston University School of Engineering and Applied Science Aston Triangle BirminghamB4 7ET United Kingdom Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates Faculty of Engineering Minia University Elminia Egypt

Nowadays heat pipes are considered to be popular passive heat transfer technologies due to their high thermal performance. The heat pipe is a superior heat transfer apparatus in which latent heat of vaporization is employed to transfer heat for an extended distance under a limited operating temperature difference. Numerical simulation of heat transfer devices is a principal step before implementing in real-life applications as many parameters can be tested in cost-and time-effective behaviors. The present study provides a review of the numerical simulations of various heat pipes in different applications such as cooling of electronic components, heating, ventilation, and air conditioning (HVAC), nuclear reactors, solar energy systems, electric vehicles, waste heat recovery systems, cryogenic, etc. Firstly, this work introduces a background about the main components of heat pipes such as an evacuated tube, wick, and working fluid. The fluid flow and thermal performance characteristics of heat pips are discussed, considering the optimum parameters. Finally, the critical challenges and recommendations for future work encountering the broad application of heat pipes are thoroughly studied. © 2022

关键词： Heat pipes

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Optimal Peak-Shaving Control Strategy Utilizing an Efficient Pv-Bes System for Dynamic Demand Response in Smart Malaysian Commercial Buildings

SSRN

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SSRN 2023年

作者： Hossain, Jahangir Saeed, Nagham Manojkumar, Rampelli Marzband, Mousa Abusorrah, Abdullah Universiti Teknikal Malaysia Faculty of Electrical Engineering Melaka76100 Malaysia University of West London School of Computing and Engineering LondonW5 5RF United Kingdom BVRIT HYDERABAD College of Engineering for Women Department of Electrical and Electronics Engineering Telangana Hyderabad500090 India Net Zero Industry Innovation Centre Teesside University Campus Masterplan MiddlesbroughTS1 3BA United Kingdom Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah21589 Saudi Arabia

Reducing peak demand on the utility grid is advantageous for both grid operatorsReducing peak demand on the utility grid is advantageous for both grid operators and consumers. However, accomplishing this without compromising human comfort poses a challenge. This study proposes the implementation of a grid-connected, energy-efficient solar photovoltaic (PV) and battery energy storage (BES) system for the purpose of peak shaving. An optimal rule-based control strategy is employed, taking into account day-ahead PV power and load demand predictions, along with a limit on the daily load profile, specifically for C1 tariff in Malaysian Commercial Buildings. The peak shaving control strategy determines the optimal schedules for battery charging and discharging in advance, aiming to minimize peak demand effectively. To regulate the corresponding demand for the day, a root-finding algorithm is employed to determine the optimal demand limit, in conjunction with the formulated rule-based peak-shaving control strategy. The results demonstrate significant reductions in energy consumption and peak demand for different load profiles. Specifically, a reduction of 19.02%, 20.9%, 4.72%, and 0% in energy consumption, and 42.46%, 49.82%, 40.44%, and 33.1% in peak demand are achieved for case studies (CS) 1, 2, 3, and 4, respectively. © 2023, The Authors. All rights reserved.

关键词： Energy management systems

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Multi-objective IGDT-based scheduling of low-carbon multi-energy microgrids integrated with hydrogen refueling stations and electric vehicle parking lots

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Sustainable Cities and Society 2021年 74卷

作者： Mansour-Saatloo, Amin Ebadi, Ramin Mirzaei, Mohammad Amin Zare, Kazem Mohammadi-Ivatloo, Behnam Marzband, Mousa Anvari-Moghaddam, Amjad Faculty of Electrical and Computer Engineering University of Tabriz Tabriz Iran Department of Electrical Engineering Sahand University of Technology Tabriz Iran Northumbria University Electrical Power and Control Systems Research Group Ellison PlaceNewcastle upon TyneNE1 8ST United Kingdom Aalborg University Aalborg9220 Denmark Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah Saudi Arabia

There is little room for doubt that distributed generation systems including renewable energy, microgrids (MGs), combined heat and power (CHP) units and storage systems have been of particular importance in sustaining low-carbon and cost-effective operations due to the tremendous increase in greenhouse gas emissions in recent years. Additionally, hydrogen-based power technologies have earned a great deal of publicity that hydrogen can serve as a zero-emission fuel for electrical power and thermal energy production. In this regard, the current paper proposes an optimal energy management strategy for a combined hydrogen, heat, and power MG (CHHP-MG) with hydrogen fueling stations (HFSs) for hydrogen vehicles (HVs), electric vehicle parking lots (EVPLs) and fuel cell micro-CHP (FC-MCHP) units to meet power and heat requirements. In order to reduce the regular operating expense, the presented CHHP-MG could also communicate with both electricity and hydrogen markets. In addition, to compensate for the associated heat and hydrogen requirements, power-to-X technologies such as the power to heat (P2HT) and power to hydrogen (P2H) are integrated. In order to improve flexibility and build a low carbon MG, multi-energy storage (MES) system along with heat and power demand response (HPDR) programs will be taken into consideration. As the uncertainties associated with the predicted wind and photovoltaic power have a major impact on the energy management of the CHHP-MG, a multi-objective information gap decision theory (IGDT)-based robust approach is applied as an effective non-probabilistic modeling technique for handling such uncertainties. The empirical results show that the proposed model can efficiently handle the uncertainties and reduce the overall operation cost by 76.35%. © 2021 Elsevier Ltd

关键词： Energy management

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Three-layer joint distributionally robust chance-constrained framework for optimal day-ahead scheduling of e-mobility ecosystem

arXiv

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arXiv 2021年

作者： Tookanlou, Mahsa Bagheri Kani, Seyyed Ali Pourmousavi Marzband, Mousa Faculty of Engineering and Environment Department of Maths Physics and Electrical Engineering Northumbria University Newcastle United Kingdom School of Electrical and Electronic Engineering University of Adelaide Australia Faculty of Engineering and Environment Department of Maths Physics and Electrical Engineering Northumbria University Newcastle United Kingdom Center of Research Excellence in Renewable Energy and Power Systems King Abdulaziz University Jeddah Saudi Arabia

A high number of electric vehicles (EVs) in the transportation sector necessitates an advanced scheduling framework for e-mobility ecosystem operation as a whole in order to overcome range anxiety and create a viable business model for charging stations (CSs). The framework must account for the stochastic nature of all stakeholders’ operations, including EV drivers, CSs, and retailers and their mutual interactions. In this paper, a three-layer joint distributionally robust chance-constrained (DRCC) model is proposed to plan grid-to-vehicle (G2V) and vehicle-to-grid (V2G) operation in day-ahead for e-mobility ecosystems. The proposed stochastic model does not rely on a specific probability distribution for stochastic parameters. To solve the problem, an iterative process is proposed using joint DRCC formulation. To achieve computational tractability, the exact reformulation is implemented for double-sided and single-sided chance constraints (CCs). Furthermore, the impact of temporal correlation of uncertain PV generation on CSs operation is considered. A simulation study is carried out for an ecosystem of three retailers, nine CSs, and 600 EVs based on real data from San Francisco, the USA. The simulation results show the necessity and applicability of such a scheduling method for the e-mobility ecosystem in an uncertain environment, e.g., by reducing the number of unique EVs that failed to reach their destination from 272 to 61. © 2021, CC BY-NC-SA.

关键词： Solar cells

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A comparative assessment of the power generation via S-shape and M-shape PV system and its impact on a residential consumer

Franklin Open

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Franklin Open 2023年 5卷

作者： Huang, Yongyi Howlader, Harun Or Rashid Hemeida, Ashraf Mohamed Narayanan, K. Masrur, Hasan Khalid, Muhammad Mikhaylov, Alexey Senjyu, Tomonobu Faculty of Engineering University of the Ryukyus 1 Senbaru Okinawa 903-0213 Japan Hawai‘i Natural Energy Institute Research Corporation of The University of Hawaii Hawaii 96822 HI United States Electrical Engineering Department Faculty of Energy Engineering Aswan University Aswan 81528 Egypt Department of Electrical and Electronic Engineering SASTRA Deemed University Thanjavur 613401 India Interdisciplinary Research Center for Smart Mobility and Logistics King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Financial University under the Government of the Russian Federation Moscow 124167 Russian Federation Electrical Engineering Department and Center for Renewable Energy and Power Systems King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia

This paper compares the differences in power generation and resident experience between S-shape and M-shape photovoltaic (PV) systems at the same location with the same number of modules. First, the sky anisotropy model (Hay-Davies-Klucher-Reindl, HDKR) is used to simulate solar irradiance (direct, diffuse, and reflection radiation) received by solar modules based on the laws of movement between the Earth and the Sun in the solar system. Next, the annual output power of two different PV system arrangements is calculated based on the solar irradiation received. Furthermore, because the solar module receives three types of solar radiation, interference is added to each of the three parts one by one to simulate shadows cast by moving objects such as birds, leaves, or clouds. Subsequently, off-grid and grid-connected power consumption models are established, and two different photovoltaic power generation systems are used at the power generation end. Lastly, the photovoltaic systems were tested based on residents’ electricity consumption habits, considering both off-grid and grid-connected households. Among them, the grid-connected model adopts the Particle Swarm Optimization (PSO) algorithm to generate an intelligent and flexible power consumption strategy. The results, based on data from Naha, Japan, show that with the same number of modules, the M-shape arrangement generates less annual power than the S-shape. In summer, though, the M-shape can generate more power, and the two structures have similar immunity to disturbances. The S-shape and M-shape have little difference in the power consumption experience. However, the general applicability of these results to other regions remains uncertain, and further testing is needed to account for environmental variations. © 2023 The Authors

关键词： HDKR M-shape PV arrangement PSO Sky anisotropic model Smart house PV system Solar irradiance

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Optimizing the Homogeneity and Efficiency of A Solid Oxide Electrolysis Cell Based on Multiphysics Simulation and Data-Driven Surrogate Model

SSRN

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SSRN 2022年

作者： Chi, Yingtian Yokoo, Kentaro Nakajima, Hironori Ito, Kohei Lin, Jin Song, Yonghua State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100087 China Department of Hydrogen Energy Systems Graduate School of Engineering Kyushu University Fukuoka Japan Department of Mechanical Engineering Faculty of Engineering Kyushu University Fukuoka Japan Tsinghua-Sichuan Energy Internet Research Institute Chengdu610213 China State Key Laboratory of Internet of Things for Smart City University of Macau 999078 China

Inhomogeneous current and temperature distributions are harmful to the durability of the solid oxide electrolysis cell (SOEC). Segmented SOEC experiments reveal that a high steam utilization, which is favorable for system efficiency, leads to local steam starvation and enhanced the inhomogeneity. It is necessary to consider inhomogeneity and efficiency jointly in optimization studies. Three-dimensional (3D) multiphysics models can simulate the inhomogeneity in a reliable manner, but they are unsuitable for optimization due to the high computational cost. This study proposes a method that combines segmented SOEC experiments, multiphysics simulation, and artificial intelligence to optimize the inhomogeneity and efficiency of SOEC. A 3D cell model is first built and verified by segmented SOEC experiments. Then, fast neural network surrogate models are built from the simulation data and integrated into a multi-objective optimization problem. Its solutions form a Pareto front reflecting the conflicting relationships among different objectives. It is found that the down-stream current is 60%-65% of the up-stream current when the steam utilization is 0.7. To increase the steam utilization to 0.8, the down-stream current further drops to 50%-60% of the up-stream current. The Pareto fronts enable system operators to achieve a balance between efficiency and inhomogeneity. © 2022, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Optimizing the Homogeneity and Efficiency of an SOEC Based on Multiphysics Simulation and Data-driven Surrogate Model

arXiv

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arXiv 2022年

Inhomogeneous current and temperature distributions are harmful to the durability of the solid oxide electrolysis cell (SOEC). Segmented SOEC experiments reveal that a high steam utilization, which is favorable for system efficiency, leads to local steam starvation and enhanced the inhomogeneity. It is necessary to consider inhomogeneity and efficiency jointly in optimization studies. Three-dimensional (3D) multiphysics models validated with experiments can simulate the inhomogeneity in a reliable manner, but they are unsuitable for optimization due to the high computational cost. This study proposes a method that combines segmented SOEC experiments, multiphysics simulation, and artificial intelligence to optimize the inhomogeneity and efficiency of SOEC jointly. A 3D cell model is first built and verified by segmented SOEC experiments. Then, fast neural network surrogate models are built from the simulation data and integrated into a multi-objective optimization problem. Its solutions form a Pareto front reflecting the conflicting relationships among different objectives. It is found that the down-stream current is 60%-65% of the up-stream current when the steam utilization is 0.7. To increase the steam utilization to 0.8, the down-stream current will further drop to 50%-60% of the up-stream current. The Pareto fronts enable system operators to achieve a balance between efficiency and inhomogeneity. Copyright © 2022, The Authors. All rights reserved.

关键词： Multiobjective optimization

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Lifetime estimation of operational aged transformers with new fuzzy logic algorithms

Lifetime estimation of operational aged transformers with ne...

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22nd International Symposium on High Voltage engineering (ISH 2021)

作者： S. Schreiter T. Kinkeldey H. Lohmeye P. Werle T. Münster HTWK Leipzig Leipzig University of Applied Science Faculty of Electrical Engineering and Information TechnologyDepartment of Electric Power Systems Leibniz Universität Hannover Institute of Electric Power Systems Division of High Voltage Engineering and Asset Management Schering-Institute Hannover Germany Hitachi ABB Power Grids Transformer Service Centre Halle Oil lab Halle Germany

The ongoing aging of transformers in the power supply networks represents an increasing technical and financial risk for operators. Therefore, the knowledge of the aging condition of the asset is of elementary interest in order to be able to plan replacement and exchange measures in a time- and cost-optimized manner. Since the end of life of transformers is determined by the aging of the solid insulation, the DP value is considered to be an indicator of the aging of the entire asset. However, this can only be determined directly by paper sampling with the active part accessible, which limits its practicality. Therefore, in the past, the paper condition was estimated by means of furan derivatives. Another approach is to estimate the DP value using computer-aided methods based on other insulating oil characteristics. In this paper, the results of both estimation methods are compared with the actual DP values of real transformers to investigate the validity of this new approach. Additionally the measured furan concentration will be compared to the measured DP value from more than 50 operationally aged transformers.

关键词： fuzzy logic insulating oils power transformer insulation

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ON MODELLING AND SIZING A SUPERCAPACITOR ENERGY STORAGE FOR power SYSTEM FREQUENCY CONTROL

ON MODELLING AND SIZING A SUPERCAPACITOR ENERGY STORAGE FOR ...

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The 12th Mediterranean Conference on power Generation, Transmission, Distribution and Energy Conversion (MEDpower 2020)

作者： M. Krpan I. Kuzle Department of Energy and Power Systems Faculty of Electrical Engineering and Computing University of Zagreb Zagreb Croatia

In this paper, we explore the issues of modelling and sizing of a supercapacitor ESS (SESS) for power system frequency control. We give an overview of different supercapacitor models used in literature. We present a simple method for sizing a SESS taking into account a realistic supercapacitor model, calculate the energy yield and voltage profile, and give insight into supercapacitor characteristics that may cause issues if not modelled adequately.

关键词： supercapacitors power system control frequency control

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