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IEEE Transactions on energy Markets, Policy and Regulation 2024年第1期2卷 40-51页

作者： Ferrando, Robert Pagnier, Laurent Mieth, Robert Liang, Zhirui Dvorkin, Yury Bienstock, Daniel Chertkov, Michael University of Arizona Program in Applied Mathematics and Department of Mathematics TucsonAZ85721 United States Department of Industrial and Systems Engineering at Rutgers University PiscatawayNJ08854 United States Johns Hopkins University Department of Electrical and Computer Engineering BaltimoreMD21218-2625 United States Elec. and Comp. Eng. and Ralph o'Connor Sustainable Energy Institute Department of Civil and Systems Engineering Johns Hopkins University BaltimoreMD21218-2625 United States Columbia University IEOR New YorkNY10027 United States

This article addresses the challenge of efficiently recovering exact solutions to the optimal power flow problem in real-time electricity markets. The proposed solution, named Physics-Informed Market-Aware Active Set learning OPF (PIMA-AS-OPF), leverages physical constraints and market properties to ensure physical and economic feasibility of market-clearing outcomes. Specifically, PIMA-AS-OPF employs the active set learning technique and expands its capabilities to account for curtailment in load or renewable power generation, which is a common challenge in real-world power systems. The core of PIMA-AS-OPF is a fully-connected neural network that takes the net load and the system topology as input. The outputs of this neural network include active constraints such as saturated generators and transmission lines, as well as non-zero load shedding and wind curtailments. These outputs allow for reducing the original market-clearing optimization to a system of linear equations, which can be solved efficiently and yield both the dispatch decisions and the locational marginal prices (LMPs). The dispatch decisions and LMPs are then tested for their feasibility with respect to the requirements for efficient market-clearing results. The accuracy and scalability of the proposed method is tested on a realistic 1814-bus NYISO system with current and future renewable energy penetration levels. © 2023 IEEE.

关键词： Costs

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Efficient energy Scheduling for Microgrids Under Uncertainty

Efficient Energy Scheduling for Microgrids Under Uncertainty

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Yousif Ahmed Al-Wajih Md Shafiullah Mujahed M. Al-Dhaifallah Ammar Sonbul Control & Instrumentation Engineering KFUPM Dhahran Saudi Arabia Control & Instrumentation Engineering IRC for Sustainable Energy Systems (IRC-SES) KFUPM Dhahran Saudi Arabia Mawhiba Enrichment Research Program Riyadh Saudi Arabia

ISBN: (数字)9798350374131

ISBN: (纸本)9798350374148

This study aims to develop a strategy for scheduling energy in a community microgrid that considers electricity costs, loads, and climate uncertainties. These microgrids are a localized, self-sufficient energy network that can generate, store, and supply energy to a local community and can be managed by individual control systems or in alignment with the country's utility grid. The system proposed is interconnected with a utility grid, a solar photovoltaic (PV) plant, a wind generation system, a micro-turbine, an energy storage system (ESS), and a load. A flexible math-ematical problem is formulated and solved using an efficient meta-optimization method called the marine predator algorithm (MPA). The strategy considered uses intelligent management software to meet load demands efficiently while minimizing costs by enhancing the utilization of the resources.

关键词： Wind energy generation Transactive energy Renewable energy sources Uncertainty Costs Software algorithms Microgrids

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Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method

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Joule 2024年第7期8卷 1958-1981页

作者： Maradesa, Adeleke Py, Baptiste Huang, Jake Lu, Yang Iurilli, Pietro Mrozinski, Aleksander Law, Ho Mei Wang, Yuhao Wang, Zilong Li, Jingwei Xu, Shengjun Meyer, Quentin Liu, Jiapeng Brivio, Claudio Gavrilyuk, Alexander Kobayashi, Kiyoshi Bertei, Antonio Williams, Nicholas J. Zhao, Chuan Danzer, Michael Zic, Mark Wu, Phillip Yrjänä, Ville Pereverzyev, Sergei Chen, Yuhui Weber, André Kalinin, Sergei V. Schmidt, Jan Philipp Tsur, Yoed Boukamp, Bernard A. Zhang, Qiang Gaberšček, Miran O'Hayre, Ryan Ciucci, Francesco Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Hong Kong Metallurgical and Materials Engineering Colorado School of Mines Golden80401 United States Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical Engineering Tsinghua University Beijing China Green Energy Storage Trento38123 Italy Department of Manufacturing and Production Engineering Faculty of Mechanical Engineering and Ship Technology Institute of Machine and Materials Technology Gdańsk University of Technology Gdańsk Poland Electrode Design for Electrochemical Energy Systems University of Bayreuth Bayreuth Germany School of Chemistry University of New South Wales Sydney Australia School of Advanced Energy Sun Yat-Sen University Shenzhen China Sustainable Energy Center CSEM Neuchâtel2002 Switzerland Interdisciplinary Faculty of Science and Engineering Shimane University Matsue Japan Centre for Electronic and Optical Materials National Institute for Materials Science Tsukuba Japan Department of Civil and Industrial Engineering University of Pisa Pisa Italy Department of Materials Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Department of Chemical Engineering Massachusetts Institute of Technology Cambridge02139 United States Electrical Energy Systems University of Bayreuth Bayreuth Germany Ruder Boskovic Institute Zagreb Croatia Department of Materials and Minerals Resources Engineering National Taipei University Taipei Taiwan Finland Johann Radon Institute for Computational and Applied Mathematics Linz Austria School of Science and Engineering Nanjing Tech. University Nanjing China Karlsruhe Germany Department of Materials Science and Engineering University of Tennessee KnoxvilleTN37996 United States Physical Science Division Pacific Northwest National Laboratory RichlandWA99354 United States Systems Engineering for Electrical Energy Storage University of B

Electrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric models, such as the distribution of relaxation times (DRT, also known as the distribution function of relaxation times, DFRT), have emerged as promising tools for EIS analysis. For example, the DRT can be used to generate equivalent circuit models, initialize regression parameters, provide a time-domain representation of EIS spectra, and identify electrochemical processes. However, mastering the DRT method poses challenges as it requires mathematical and programming proficiency, which may extend beyond experimentalists’ usual expertise. Post-inversion analysis of DRT data can be difficult, especially in accurately identifying electrochemical processes, leading to results that may not always meet expectations. This article examines non-parametric EIS analysis methods, outlining their strengths and limitations from theoretical, computational, and end-user perspectives, and provides guidelines for their future development. Moreover, insights from survey data emphasize the need to develop a large impedance database, akin to an impedance genome. In turn, software development should target one-click, fully automated DRT analysis for multidimensional EIS spectra interpretation, software validation, and reliability. Particularly, creating a collaborative ecosystem hinged on free software could promote innovation and catalyze the adoption of the DRT method throughout all fields that use impedance data. © 2024 Elsevier Inc.

关键词： Electrochemical impedance spectroscopy

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Photoresponse of Thermally Evaporated Copper Oxide-Based Solar Cells

Photoresponse of Thermally Evaporated Copper Oxide-Based Sol...

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Solar Conference (MENA-SC), Middle East and North Africa

作者： Abdul Hai Alami Mohamad Ayoub Adnan Alashkar Shamma Alasad Ayman Mdallal Siren Khuri Haya Aljaghoub Sustainable and Renewable Energy Engineering Department Sustainable Energy & Power Systems Research Centre University of Sharjah Sharjah United Arab Emirates Materials Science and Engineering PhD Program American University of Sharjah Sharjah United Arab Emirates Mechancial Engineering Department American University of Sharjah Sharjah United Arab Emirates Sustainable Energy & Power Systems Research Centre University of Sharjah Sharjah United Arab Emirates Industrial Engineering and Engineering Management Department University of Sharjah Sharjah United Arab Emirates

This study reports on the fabrication and characterization of a copper oxide (CuO)-based photoactive cell. Copper was thermally evaporated onto two substrates and post-treated using chemical and thermal treatments to obtain different semiconducting types of CuO. Absorption measurements were conducted to obtain the bandgaps of CuO, which were found to be 1.51 eV and 1.21 eV, for the chemically and thermally treated CuO, respectively. Finally, a chronoamperometry test was conducted to confirm the photoresponse of the cell, which showed a doubling of output current values under light conditions compared to dark conditions.

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All-Electric Ship On-Board Continuous sustainable H2 Generation from Aluminum Scrap and Seawater

All-Electric Ship On-Board Continuous Sustainable H2 Generat...

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2023 IEEE Electric Ship Technologies Symposium, ESTS 2023

作者： Taher, Dhyogo M. Balmant, Wellington Och, Stephan H. Pitz, Diogo B. Venter, Giuliana S. Filho, Lucio C. Martins, Lauber S. Vargas, Jose V. C. Ordonez, Juan C. Federal University of Paraná Ufpr Graduate Program in Mechanical Engineering Sustainable Energy Research and Development Center PR Curitiba81531-980 Brazil Maringá State University Uem Department of Chemical Engineering PR Maringá87020-900 Brazil Advent Health University Ahu Department of Health and Biomedical Sciences OrlandoFL32803 United States Center for Advanced Power Systems and Energy Sustainability Center Florida State University Fsu Department of Mechanical Engineering TallahasseeFL32310 United States

ISBN: (纸本)9781665465151

A mathematical model of a sustainable H2 generation reactor that utilizes aluminum and seawater is introduced. Conservation of species and the kinetics of the H2 production reaction from aluminum and seawater allowed for obtaining the process transient response in a batch reactor. Continuous steady state production was assessed by adding a balance of energy, allowing for reactants inlet mass flow rates, and calculating the outlet H2 mass flow (generation) rate. The theoretical H2 production curve data showed good quantitative and qualitative agreement with experimental data. The validated mathematical model was then used to optimize the continuous reactor. The maximum was sharp, since an 85% variation between the maximum and the smallest H2 generation rate value as a function of the inlet NaOH solution volumetric flow rate tested range was verified. Such fundamental result stresses the importance of operating the system at the optimal condition, no matter how complex the actual reactor design may be. Since aluminum is inexpensive, abundant, and fully recyclable, in situ sustainable H2 production could allow for fuel cell stacks to become all electric ships (AES) power sources. © 2023 IEEE.

关键词： Aluminum

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Mapping Radionuclide Concentrations in the Uae Using a Gaussian Process Machine Learning Approach

SSRN

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SSRN 2024年

作者： Khuwaileh, Bassam A. Almomani, Belal El-Sayed, Samar Ajaj, Rahaf Akram, Yumna Nuclear Engineering Program Department of Mechanical and Nuclear Engineering University of Sharjah Sharjah27272 United Arab Emirates Nuclear Energy System Simulation and Safety Research Group Sustainable Energy & Power Systems Research Centre RISE University of Sharjah 27272 United Arab Emirates College of Health Science Abu Dhabi University Abu Dhabi United Arab Emirates

This study introduces a machine learning approach for mapping soil radionuclide concentrations in the UAE using Gaussian Process (GP) regression. Aimed at enhancing environmental monitoring and public health, the approach utilizes soil samples from across the UAE to create a radiation map (covering Ra-226, Th-232, and K-40 isotopes). GP regression, known for its proficiency in spatial data interpolation, predicts radionuclide levels in areas without direct testing. This method is adept at managing the non-linear spatial complexities inherent in geographic data, offering both a qualitative and quantitative understanding beneficial for decision-making and further sampling strategies. The results reveal the GP model's capacity to accurately reflect geographic variances in isotopic concentrations, with RMSE values of 13%, 14%, and 22% for Ra-226, Th-232, and K-40, respectively. The model's success in learning the geographical variations of the concentrations showcases its potential to guide future research by identifying areas of increased radioactivity risk. © 2024, The Authors. All rights reserved.

关键词： Machine learning

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Towards Robust and Scalable Dispatch Modeling of Long-Duration energy Storage

arXiv

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arXiv 2024年

作者： Guerra, Omar J. Dalvi, Sourabh Thatte, Amogh A. Cowiestoll, Brady Jorgenson, Jennie Hodge, Bri-Mathias National Renewable Energy Laboratory 15013 Denver West Parkway GoldenCO80401 United States Colorado School of Mines Advanced Energy Systems Graduate Program 1500 Illinois Street GoldenCO80401 United States Renewable and Sustainable Energy Institute University of Colorado BoulderCO80309 United States Department of Electrical Computer & Energy Engineering University of Colorado BoulderCO80309 United States

energy storage technologies, including short-duration, long-duration, and seasonal storage, are seen as technologies that can facilitate the integration of larger shares of variable renewable energy, such as wind and solar photovoltaics, in power systems. However, despite recent advances in the techno-economic modeling of energy storage (particularly for short-duration applications), the operation and economics of long-duration energy storage are still incomplete in power systems modeling platforms. For instance, existing modeling approaches for long-duration storage are often based either on an oversimplified representation of power system operations or limited representation of storage technologies, e.g., evaluation of only a single application. This manuscript presents an overview of the challenges of modeling long-duration energy storage technologies, as well as a discussion regarding the capabilities and limitations of existing approaches. We used two test power systems with high shares of both solar photovoltaics- and wind (70% - 90% annual variable renewable energy shares) to assess long-duration energy storage dispatch approaches. Our results estimate that better dispatch modeling of long-duration energy storage could increase the associated operational value by 4% - 14% and increase the standard capacity credit by 14% - 34%. Thus, a better long-duration energy storage dispatch could represent significant cost saving opportunities for electric utilities and system operators. In addition, existing long-duration dispatch modeling approaches were tested in terms of both improved system value (e.g., based on production cost and standard capacity credit) and scalability (e.g., based on central processing unit time and peak memory usage). Both copper plate and nodal representations of the power system were considered. Although the end volume target dispatch approach, i.e., based on mid-term scheduling, showed promising performance in terms of both improved system

关键词： Scalability

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Water management and conductivity studies in novel polymer zirconium-based membranes for PEM fuel cells

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Case Studies in Chemical and Environmental engineering 2025年 11.0卷

作者： Ahmed, Tallah Magdi Al Othman, Amani Shamayleh, Abdulrahim Tawalbeh, Muhammad Engineering Systems Management Graduate Program American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Department of Chemical and Biological Engineering American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Energy Water and Sustainable Environment Research Center American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Department of Industrial Engineering American University of Sharjah PO. Box 26666 Sharjah United Arab Emirates Sustainable and Renewable Energy Engineering Department University of Sharjah PO. Box 27272 Sharjah United Arab Emirates Sustainable Energy & Power Systems Research Centre RISE University of Sharjah P.O. Box 27272 Sharjah United Arab Emirates

Proton exchange membrane fuel cells (PEMFCs) are among the promising alternatives for clean energy generation, especially when hydrogen is the fuel used. Their operation is still faced with several challenges, and one of them is water accumulation in the cathode compartment. If PEMFCs are operated at temperatures above the boiling point of water, a significant obstacle would be eliminated due to the formation of water in the vapor phase. This prevents water from accumulating in the liquid phase which causes flooding. Therefore, this work aims to develop a novel composite membrane based on zirconium silicate (ZrSiO₄) and Polyvinylidene fluoride (PVDF) for such high-temperature operation. The composite membrane was synthesized using solution casting, and its structural and chemical properties were characterized using thermogravimetric analysis (TGA), Fourier-transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) techniques. The ZrSiO₄/PVDF membrane demonstrated a maximum proton conductivity of 2.14 × 10⁻³ S/cm at room temperature with 8 wt% ZrSiO₄, along with a water uptake value of 43.85 %. Consequently, when tested above the boiling point of water, the membrane exhibited a high conductivity of 2.13 × 10⁻³ S/cm at 105 °C. The results suggest the suitability of such zirconium silicate-based composite membranes for fuel cell applications operating above the boiling point of water. © 2024 The Author(s)

关键词： Composite membranes PEM fuel cells Proton conduction PVDF Water management Zirconium silicate

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The Role of Interconnected Island Networks for Decarbonising Power Sector in Large Archipelago Nation

SSRN

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SSRN 2023年

作者： Reyseliani, Nadhilah Pratama, Yoga Wienda Shafira, Alya Nurul Dowell, Niall Mac Kammen, Daniel M. Purwanto, Widodo Wahyu Sustainable Energy Systems and Policy Research Cluster Universitas Indonesia Depok16424 Indonesia Chemical Engineering Department Faculty of Engineering Universitas Indonesia Depok16424 Indonesia Master Program in Energy Systems Engineering Faculty of Engineering Universitas Indonesia Depok16424 Indonesia Centre for Environmental Policy Imperial College London South Kensington LondonSW7 1NA United Kingdom Schlossplatz 1 Laxenburg2361 Austria Renewable and Appropriate Energy Laboratory and Energy and Resources Group University of California BerkeleyCA94720 United States

The reality in modelling the power system transition of an archipelagic country lies in the substantial investment required for interisland transmission lines and the uneven distribution of electricity demand. Approximately 72–75% of Indonesia's electricity demand is centered on Java, where the substantial population density constrains the land availability for renewable energy. Therefore, the spatial aspect in modelling Indonesian power system becomes important. This study assessed the differences in the decarbonisation of the Indonesian power system using single- and multi-region optimisation models and compared the isolated and interconnected power systems using the Integrated MARKAL–EFOM System (TIMES) Indonesia. The findings indicated that the isolated multi-region approach exhibited lower penetration of renewable energy compared to the single-region approach. Introducing interconnected power system enhanced the renewable energy mix by 2.5 times, reduced the overall system cost, CO2 storage capacity, and coal consumption by building 115 GW of interisland grid and importing 62% of electricity in Java from Sumatra, Kalimantan, and NT, which resulting in more distributed investment. However, due to the considerable distance, an interconnected power system is not considered a cost-effective solution for Papua, Sulawesi, and Maluku. Decarbonisation under coal phase-out plan helps reduce the interisland transmission system by 8.3%. © 2023, The Authors. All rights reserved.

关键词： Cost effectiveness

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Diesel/Biodiesel/Biogas Mixtures Driven Compression Ignition Internal Combustion Engines Constructal Design

SSRN

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SSRN 2024年

作者： Arcanjo, S. Vargas, José Viriato Coelho Ordonez, J.C. Och, S.H. Balmant, W. Mariano, A.B. Kava, V.M. Department of Mechanical Engineering Graduate Program in Mechanical Engineering PGMEC andSustainableEnergyResearch&DevelopmentCenter NPDEAS FederalUniversityofParaná UFPR CP 19011 PR Curitiba81531–980 Brazil Department of Mechanical Engineering Energy and Sustainability Center Center for Advanced Power Systems Florida State University FSU TallahasseeFL32310–6046 United States Department of Electrical Engineering Sustainable Energy Research & Development Center NPDEAS Federal University of Paraná UFPR CP 19011 PR Curitiba81531–980 Brazil Department of Genetics Sustainable Energy Research & Development Center NPDEAS Federal University of Paraná UFPR CP 19011 PR Curitiba81531–980 Brazil

This paper introduces a first and second law based transient mathematical model for 4-stroke compression ignition internal combustion engines (CI-ICE) driven by diesel/biodiesel/biogas mixtures to allow for the maximization of system performance. In this way, the CI-ICE morphology that provides easier access to the currents that flow through it is sought, according to constructal law. The total entropy generated in the CI-ICE cycle was calculated by adding the entropy generation in all strokes. An optimization problem was formulated based on the variation of operating and geometric parameters, and the objective functions were the effective and 2nd law efficiencies, and , as well as the destroyed exergy fraction, . The optimal ranges found for the bore-stroke, compression and conrod-crank ratios were;, and in which with for D100 (pure diesel), and with for B50D25NG25 (biodiesel/diesel/natural gas blend). The maxima and minimum found were sharp, since and varied up to 71% and 69% in comparison to their maximum values, respectively, and up to 45% in comparison to its minimum value within the adopted ranges of variation of the optimized parameters. Such large variations stress the importance of considering the optimized CI-ICE morphology in actual design, i.e., CI-ICE constructal design. © 2024, The Authors. All rights reserved.

关键词： Entropy

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