AIMS Energy最新文献

{"title":"The role of techno-economic factors for net zero carbon emissions in Pakistan","authors":"Muhammad Amir Raza, M. M. Aman, A. G. Abro, Muhammad Shahid, D. Ara, Tufail Ahmed Waseer, M. Tunio, N. A. Tunio, S. Soomro, T. Jumani","doi":"10.3934/energy.2023013","DOIUrl":"https://doi.org/10.3934/energy.2023013","url":null,"abstract":"The Government of Pakistan has established clean energy transition goals in the national Alternative and Renewable Energy (ARE) Policy. The goal of this policy is to increase the 30% capacity of green energy in total energy mix by 2030. In this regard, the aim of this study is to develop a de-carbonization plan for achieving net zero emissions through the deployment of a green energy system for the period 2021 to 2040 by incorporating the ARE policy targets. The Low Emissions Analysis Platform (LEAP®) software is used for finding the unidirectional causality among gross domestic product, population within the country, energy demand, renewable energy production and CO2 emissions for Pakistan. The results revealed that energy production of 564.16 TWh is enough to meet the energy demand of 480.10 TWh with CO2 emissions of 22.19 million metric tons, having a population of 242.1 million people and GDP growth rate of 5.8%, in the year 2040 in Pakistan. The share of green energy production is 535.07 TWh, which can be utilized fully for meeting energy demand in the country, and almost zero emissions will produce till 2040. CO2 emissions produced by burning natural gas were 20.64 million metric tons in 2020, which then reduced to 3.25 million metric tons in 2040. CO2 emissions produced by burning furnace oil are also reduced from 4.19 million metric tons in 2020 to 2.06 million metric tons in 2040. CO2 emissions produced by burning coal were 24.85 million metric tons in 2020, which then reduced to 16.88 million metric tons in 2040. Energy demand is directly related to the population and GDP of the country, while renewable utilization is inversely proportional to carbon emissions. The declining trend of carbon emissions in Pakistan would help to achieve net zero emissions targets by mid-century. This technique would bring prosperity in the development of a clean, green and sustainable environment.","PeriodicalId":45696,"journal":{"name":"AIMS Energy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70229704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Modelling and development of sustainable energy systems","authors":"Muhammad Amir Raza, M. Aman, Abdul Ghani Abro, Muhammad Shahid, D. Ara, Tufail Ahmed Waseer, Mohsin Ali Tunio, Shakir Ali Soomro, Nadeem Ahmed Tunio, R. Haider","doi":"10.3934/energy.2023014","DOIUrl":"https://doi.org/10.3934/energy.2023014","url":null,"abstract":"Due to the recent climate change, organizations all over the globe are developing plans for reducing carbon emissions by developing clean energy technologies and energy efficient devices. However, the path for transition to green energy system is still unclear and in general, the representation of green energy supply for transition pathways is limited. Therefore, this study outlines a plan for getting Swedish energy sector completely carbon neutral by 2050. The approach can also be applicable to the majority of nations worldwide. Computer based simulations are performed on Energy PLAN software for making clean, green and sustainable energy system that can balance every component of entire energy system during the study period 2022 to 2050. This study takes into account the sustainable use of renewable sources for all economic sectors as well as the interchange of energy with nearby nations under the two scenarios. Additionally, the energy system works in tandem with other industries to create a fully carbon-free environment. The results revealed that, 50% de-carbonization is possible till 2035 and 100% de-carbonization is possible till 2050. This enables a discussion of how ambitious 10-year goals might serve as a first step toward the mid-century elimination of fossil fuels from the energy sector.","PeriodicalId":45696,"journal":{"name":"AIMS Energy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70229775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empirical assessment of drivers of electricity prices in East Africa: Panel data experience of Rwanda, Uganda, Tanzania, Burundi, and Kenya","authors":"Mburamatare Daniel, W. Gboney, Hakizimana Khan Jean de Dieu, Akumuntu Joseph, Fidèle Mutemberezi","doi":"10.3934/energy.2023001","DOIUrl":"https://doi.org/10.3934/energy.2023001","url":null,"abstract":"Sustainable electricity supply plays a key role in economic development. Cost recovery, profitability and affordability of electricity through power tariff regulation, have become a subject of conflict between private providers and regulators. Consequently, regulators need to balance the interests of all stakeholders. The objective of this study, is to measure to which extent, Electricity Net Consumption (EC), Electricity Net Generation (EG), electricity transmission and distribution losses (Losses), International Average Crude oil prices (FP), Consumer Price Index (CPI), Industry Value Added (IVA) could influence the Average Electricity Prices (EP) in East Africa, especially in Rwanda, Uganda, Tanzania, Burundi, and Kenya. The data are from World Bank Indicators and cover the period from 2000 to 2019. This study adopts a three-stage approach, consisting of panel unit root tests, panel cointegration tests and estimating the long run cointegration relationship of the variables in a panel context. We applied four different panel unit root tests including ADF-Fisher Chi-square, Levin, Lin and Chu (LLC); PP-Fisher Chi-square, and Im, Pesaran, and Shin, (IPS). The results reveal that the variables are non-stationary at \"level\", stationary at first-differences and integrated with order one denoted as I(1). The Pedroni, Kao and Johansen Fisher co-integration tests were performed. This study uses full modified ordinary least squares (FMOLS) and dynamic ordinary least squares (DOLS) to estimate the long run relationship among the variables. We find that the increase in EG, FP, and CPI increase the Average Electricity Prices (EP); while the increase in Losses, EC, and IVA decreases EP. Therefore, we recommend the promotion of long-term investment policies in renewable sources and efficient policies to reduce technical and commercial losses. In addition, this study suggests that appropriate policies related to subsidized electricity prices would, however, prevent adverse effects related to inefficient over-consumption of electricity.","PeriodicalId":45696,"journal":{"name":"AIMS Energy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70229817","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preventive control method for stable operation of proton exchange membrane fuel-cell stacks","authors":"Yuto Tsuzuki, Y. Akimoto, K. Okajima","doi":"10.3934/energy.2023004","DOIUrl":"https://doi.org/10.3934/energy.2023004","url":null,"abstract":"Flooding and dry-out are major drawback issues in proton exchange membrane fuel cells (PEMFC), which necessitate adequate prevention control techniques. In a fuel-cell stack, as flooding and dry-out occur on the inlet and outlet sides, respectively, both faults can exist simultaneously. Therefore, the timely detection of these two contradictory faults is crucial for implementing timely control measures. In this study, we propose a preventive control method that detects the fault signs early for more effective prevention. The proposed method uses a curve-fitting method, which uses overpotential as the control index. As the control index can be obtained by measuring the current, voltage, and temperature, the evaluation can be performed quickly, making it easy to implement in a PEMFC system. Under a single fault, the stack output power, hydrogen consumption, and power efficiency of the proposed preventive control method and the previous study on flooding were compared. The results showed that our preventive control method could detect flooding sooner and was superior in stack output power, hydrogen consumption, and power generation compared to the fault control method. Under conditions of mixed flooding and dry-out, both flooding and dry-out were detected using the overpotential as the control index. Thus, because the proposed method initiates control measures before the fault progresses, it is possible to ensure the continued stable operation of the fuel cells.","PeriodicalId":45696,"journal":{"name":"AIMS Energy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70229887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prediction of the equivalent circulation density using machine learning algorithms based on real-time data","authors":"Abdelrahman Kandil, S. Khaled, T. Elfakharany","doi":"10.3934/energy.2023023","DOIUrl":"https://doi.org/10.3934/energy.2023023","url":null,"abstract":"Equivalent circulation density (ECD) is one of the most important parameters that should be considered while designing drilling programs. With increasing the wells' deep, offshore hydrocarbon extraction, the costly daily rate of downhole measurements, operating restrictions, and the fluctuations in the global market prices, it is necessary to reduce the non-productive time and costs associated with hole problems resulting from ignoring and incorrect evaluation of ECD. Therefore, optimizing ECD and selecting the best drilling parameters are curial tasks in such operations. The main objective of this work is to predict ECD using three machine learning algorithms: an artificial neural network (ANN) with a Levenberg-Marquardt backpropagation algorithm, a K neighbors regressor (knn), and a passive aggressive regressor (par). These models are based on 14 critical operation parameters that have been provided by downhole sensors during drilling operations such as annular pressure, annular temperature, and rate of penetration, etc. In the study, 4663 data points were selected and included, where 80% to 85% of the data set has been used for training and validation according to the algorithm, and the remaining data points were reserved for testing. In addition, several statistical tests were used to evaluate the accuracy of the models, including root mean square error (RMSE), correlation coefficient (R2), and mean squared error (MSE). The results of the developed models show various consistencies and accuracy, while the ANN shows a high accuracy with an R2 of nearly 0.999 for the training, validation, and testing, as well as the overall of them. The RMSE is 0.000211, 0.000253, 0.00293, and 0.00315 for overall, training, validation, and testing, respectively. This work expands the use of artificial intelligence in the gas and oil industry. The developed ANN model is more flexible in response to challenges, reduces dependence on humans, and thus, reduces the chance of human omission, as well as increasing the efficiency of operations.","PeriodicalId":45696,"journal":{"name":"AIMS Energy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70230443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analytical assessment of the filed results on the PV system connectors performance under operating temperature","authors":"Mebarek Lahbib, M. Boussaid, H. Moungar, A. Tahri","doi":"10.3934/energy.2023029","DOIUrl":"https://doi.org/10.3934/energy.2023029","url":null,"abstract":"In this study, we will shed light on the aggressive effect of a blowing sandstorm in the presence of high temperatures on the photovoltaic inter-module connectors in a solar station located in the desert environment of southwestern Algeria. After a short period of operation, it is observed that the MC4 connectors, which tighten the interconnection between the photovoltaic modules, are completely faulty because of sand grains carried away by a wind blowing at an average annual speed, which exceeds 6 m/s. Then, we analyzed and evaluated the connector failure to propose an appropriate solution. We checked the variations of the intrinsic temperatures of each connector employing the thermocouple for the three cases of operating temperatures, as well as the current measurement flowing through each connector, to calculate the powers dissipated in each branch of the circuit. Finally, this experimental work shows that a loss of power reaches almost 10% from the nominal power of the typical case. The proposed solution for this problem is to cover the connectors with an impervious plastic cover.","PeriodicalId":45696,"journal":{"name":"AIMS Energy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70230599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Remaining useful life indirect prediction of lithium-ion batteries using CNN-BiGRU fusion model and TPE optimization","authors":"Xiaoyu Zheng, Dewang Chen, Yusheng Wang, Liping Zhuang","doi":"10.3934/energy.2023043","DOIUrl":"https://doi.org/10.3934/energy.2023043","url":null,"abstract":"<abstract><p>The performance of lithium-ion batteries declines rapidly over time, inducing anxiety in their usage. Ascertaining the capacity of these batteries is difficult to measure directly during online remaining useful life (RUL) prediction, and a single deep learning model falls short of accuracy and applicability in RUL predictive analysis. Hence, this study proposes a lithium-ion battery RUL indirect prediction model, fusing convolutional neural networks and bidirectional gated recurrent units (CNN-BiGRU). The analysis of characteristic parameters of battery life status reveals the selection of pressure discharge time, average discharge voltage and average temperature as health factors of lithium-ion batteries. Following this, a CNN-BiGRU model for lithium-ion battery RUL indirect prediction is established, and the Tree-structured Parzen Estimator (TPE) adaptive hyperparameter optimization method is used for CNN-BiGRU model hyperparameter optimization. Overall, comparison experiments on single-model and other fusion models demonstrate our proposed model's superiority in the prediction of RUL in terms of stability and accuracy.</p> </abstract>","PeriodicalId":45696,"journal":{"name":"AIMS Energy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135650021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Building-integrated photovoltaic (BIPV) systems: A science mapping approach","authors":"Eliseo Zarate-Perez, Juan Grados, Santiago Rubiños, Herbert Grados-Espinoza, Jacob Astocondor-Villar","doi":"10.3934/energy.2023052","DOIUrl":"https://doi.org/10.3934/energy.2023052","url":null,"abstract":"<abstract> <p>Solar energy is one of the most important renewable energy sources due to its wide availability and applicability. One way to use this resource is by building-integrated photovoltaics (BIPV). Therefore, it is essential to develop a scientific map of BIPV systems and a comprehensive review of the scientific literature that identifies future research directions. For that reason, the bibliometric research methodology enables the quantification and evaluation of the performance, quality and influence of the generated maps and their elements. In this regard, an analysis of the scientific production related to BIPV, indexed from 2001 to 2022, was carried out using the Scopus database. This was done using a scientific mapping approach via the SciMAT tool to analyze the co-occurrence of terms through clustering techniques. The BIPV was integrated with the themes of buildings, investments, numerical models, office buildings, photovoltaic modules, roofs, solar cells and zero-energy buildings. As photovoltaic technology progresses, the production of flexible PV elements is increasing in lieu of silicon substrate-based PV elements, and this is of current scientific interest. The evaluations of BIPVs in various climatic contexts are encouraging in warm and sunny climates. BIPVs demonstrated high-energy generation, while in temperate climates, BIPV windows exhibited a reduction in heating and cooling loads, indicating notable efficiency. Despite significant benefits, BIPVs face challenges such as upfront costs, integration complexities and durability concerns. Therefore, silicon solar cells are considered a cross-cutting theme within the BIPV research field. It is highlighted that this study provides a comprehensive scientific mapping and critical review of the literature in the field of BIPV systems. This bibliometric analysis not only quantifies the performance and quality of the generated maps but also identifies key thematic areas that have evolved.</p> </abstract>","PeriodicalId":45696,"journal":{"name":"AIMS Energy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135704317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Techno-economic analysis of battery storage systems and hydrogen-based storage systems as an alternative to grid expansion in the medium voltage grid in Germany","authors":"Franz Teske, Jan Schubert, Adrian Fehrle, Felix Funk, J. Franke","doi":"10.3934/energy.2023019","DOIUrl":"https://doi.org/10.3934/energy.2023019","url":null,"abstract":"The decentralization of the energy system in Germany is leading to enormous investments in grid expansion, as the current regulation creates an obligation to expand the power grid to eliminate bottlenecks. Meanwhile, opportunities to leverage grid-friendly control of storage systems are neglected to alleviate the need for investment. For this reason, it is necessary to investigate intelligent alternatives to grid expansion, such as storage systems, to efficiently integrate distributed technologies into the power system and reduce the need for grid expansion. In this work, two representative configurations of a medium voltage grid in Germany are developed for the years 2022 and 2050, and different storage systems are compared economically with the grid expansion in a model-based simulation. Hydrogen storage and battery storage were chosen as storage systems. The results show that grid expansion is the least expensive option if only the grid expansion costs are included in the analysis. However, if additional uses for the storage systems are considered, the battery storage systems are more economical. While in the scenario for 2050 the grid expansion causes costs of approx. 56,000 EUR per year, revenues of at least 58,000 EUR per year can be achieved via the revenue opportunities of the battery storage, representing a 3.5% margin. Heat extraction, arbitrage trading, and avoidance of grid expansion in superimposed grid levels were integrated as additional revenue streams/sources. A robust data basis and cost degressions were assumed for the simulations to generate meaningful results. Overall, hydrogen storage systems are economically inferior to battery storage systems and grid expansion for this use case. The results demonstrate the complexity of analyzing the trade-offs in terms of storage as an alternative to grid expansion as well as the opportunities presented using battery storage instead.","PeriodicalId":45696,"journal":{"name":"AIMS Energy","volume":null,"pages":null},"PeriodicalIF":1.8,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70230380","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review on peak shaving techniques for smart grids","authors":"Syed Sabir Hussain Rizvi, Krishna Teerth Chaturvedi, Mohan Lal Kolhe","doi":"10.3934/energy.2023036","DOIUrl":"https://doi.org/10.3934/energy.2023036","url":null,"abstract":"<abstract> <p>Peak shaving techniques have become increasingly important for managing peak demand and improving the reliability, efficiency, and resilience of modern power systems. In this review paper, we examine different peak shaving strategies for smart grids, including battery energy storage systems, nuclear and battery storage power plants, hybrid energy storage systems, photovoltaic system installations, the real-time scheduling of household appliances, repurposed electric vehicle batteries, uni- and bi-directional electric vehicle charging, the demand response, the time-of-use pricing, load shedding systems, distributed generation systems and energy-efficient management. We analyze the potential of each strategy to reduce peak demand and shift energy consumption to off-peak hours, as well as identify the key themes critical to the success of peak shaving for smart grids, including effective coordination and communication, data analytics and predictive modeling and clear policy and regulatory frameworks. Our review highlights the diverse range of innovative technologies and techniques available to utilities and power system operators and it emphasizes the need for continued research and development in emerging areas such as blockchain technology and artificial intelligence. Overall, the implementation of peak shaving strategies represents a significant step toward a more sustainable, reliable and efficient power system. By leveraging the latest technologies and techniques available, utilities and power system operators can better manage peak demand, integrate renewable energy sources, and create a more reliable and secure grid for the future. By discussing cutting-edge technologies and methods to effectively manage peak demand and incorporate renewable energy sources, this review paper emphasizes the significance of peak shaving strategies for smart grids as a crucial pathway towards realizing a more sustainable, dependable and efficient power system.</p> </abstract>","PeriodicalId":45696,"journal":{"name":"AIMS Energy","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135355937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}