Energy nexus最新文献

{"title":"Assessment and analysis of development risks under uncertainty: The impact of disruptive technologies on renewable energy development","authors":"Ibrahim Alrashdi ,&nbsp;Ahmed M. Ali ,&nbsp;Karam M. Sallam ,&nbsp;Mohamed Abdel-Basset","doi":"10.1016/j.nexus.2025.100371","DOIUrl":"10.1016/j.nexus.2025.100371","url":null,"abstract":"<div><div>Renewable energy (RE) is gaining great attention nowadays, as opposed to traditional energy, such as fossil fuels, which have various negative impacts and issues. RE faces multiple risks and challenges, so these risks need to be evaluated and mitigated such as technical risks, environmental risks, security risks, policy risks, and technological risks. This study proposed a multi-criteria decision-making (MCDM) method for assessing RE risks. The MCDM method is integrated with neutrosophic sets (NSs) to deal with inconsistent data in the evaluation process. Two MCDM methods are used in this study: Entropy and Ranking of Alternatives with Weights of Criterion (RAWEC). The neutrosophic entropy is used to compute the criteria weight, and the neutrosophic RAWEC method ranks the alternatives. This study applied the proposed method to two case studies. In the first case study, the RE risks are ranked. In the second case study, various strategies are proposed by blockchain, artificial intelligence (AI), the Internet of Things (IoT), big data, and zero-trust to reduce RE risks. There are six main factors; 31 sub-factors and 19 risks are used in the first case study, and 19 factors and 20 strategies are used in the second case study. The sensitivity analysis was conducted to show the stability of the rank. The proposed methodology was compared with MCDM methods such as neutrosophic TOPSIS, neutrosophic VIKOR, and fuzzy CoCoSo. The results show various proposed strategies can reduce RE risks.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100371"},"PeriodicalIF":8.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143454176","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diverse pathways to decarbonization: cluster-specific impacts of energy sources on CO2 emissions in the European Union","authors":"Jana Chovancová ,&nbsp;Igor Petruška ,&nbsp;Ugur Korkut Pata ,&nbsp;Peter Adamišin","doi":"10.1016/j.nexus.2025.100367","DOIUrl":"10.1016/j.nexus.2025.100367","url":null,"abstract":"<div><div>This study examines the relationship between different energy sources and CO₂ emissions across European Union (EU) countries through a regression clustering panel data analysis. Using a dataset from 2011 to 2022, we identify distinct country clusters and analyse the impact of energy sources, including gas, coal, oil, wind, biofuels, solar, hydro and nuclear, on CO₂ emissions within these clusters. The regression cluster analysis reveals significant differences in the impact of these energy sources on emissions across the EU. In particular, gas, coal and oil all have positive and significant coefficients, with coal having the largest impact on CO₂ emissions across all clusters. Conversely, biofuel shows a consistently negative and significant effect, indicating its potential to reduce CO₂ emissions. Wind shows mixed behaviour, with both positive and negative significance in certain clusters, highlighting the complexity of integrating wind energy into existing infrastructures. Coefficients of determination R² for individual clusters ranges from 0.9818 to 0.9940, indicating the high reliability of the models. The variables Solar, Hydro and Nuclear show the least significant coefficients. These findings underscore the need for tailored energy policies that consider the specific conditions of each country cluster in order to achieve an effective transition away from fossil fuels and maximise the benefits of renewable energy sources. This study provides critical insights for policymakers aiming to meet climate change targets and underlines the urgent need for strategic energy and climate change policies aligned with the unique characteristics of each EU country cluster to facilitate a successful energy transition.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100367"},"PeriodicalIF":8.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143377312","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Predictive Modeling of soil salinity integrating remote sensing and soil variables: An ensembled deep learning approach","authors":"Sana Arshad ,&nbsp;Jamil Hasan Kazmi ,&nbsp;Endre Harsányi ,&nbsp;Farheen Nazli ,&nbsp;Waseem Hassan ,&nbsp;Saima Shaikh ,&nbsp;Main Al-Dalahmeh ,&nbsp;Safwan Mohammed","doi":"10.1016/j.nexus.2025.100374","DOIUrl":"10.1016/j.nexus.2025.100374","url":null,"abstract":"<div><div>Accurate predictions of soil salinity can significantly contribute to achieving the UN- Sustainable Development Goal (SDG-2) of ensuring ‘zero hunger.’ From this perspective, the current research aimed to predict soil electrical conductivity (EC) from remote sensing and soil data using advanced deep learning (DL) architectures. A total of 109 soil samples were analyzed for agricultural land use in the Middle Indus Basin of Pakistan. Seven salinity indices (SI-1 to SI-7) were derived from the 10m to 20m wavelength bands of Sentinel-2, along with vegetation and topographic covariates. Initially, Recursive Feature Elimination was implemented as a feature-selection method to select the most effective predictors. Subsequently, deep learning architectures, including a Feedforward Neural Network (FFNN), Recurrent Neural Network (RNN), and Long Short-Term Memory (LSTM), were employed to predict soil salinity. Research findings showed that EC ranged between 0.57dS/m to 11.5 dS/m in the study area. The evaluation metrics of the DL models revealed that a simple FFNN with three fully connected dense layers achieved the highest R² = 0.88 for model training. However, the ensemble of improved FFNN and LSTM outperformed with the highest R² and NSE = 0.84, and the lowest RMSE and MAE = 1.38 and 1.01, respectively, on the testing dataset. Optimized deep learning architectures with adjustments to the learning rate, dropout rate, and activation functions achieved the highest prediction accuracy with the lowest validation loss. Finally, SHapely Additive exPlanations (SHAP) revealed that elevation, pH, NDVI, SI-1, and SI-7 had highly significant impacts on EC predictions. This research provides insight into implementing advanced and interpretable DL architectures, supporting informed decision-making by agricultural stakeholders.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100374"},"PeriodicalIF":8.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143387124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of mineral nutrition and biopriming on crop performance, energetics, and the carbon footprint in rainfed castor bean (Ricinus communis L.)","authors":"Revappa Mohan Kumar ,&nbsp;Yamanura Madival ,&nbsp;Mahantesh Basangouda Nagangoudar ,&nbsp;Nagesha Narayanappa ,&nbsp;Gopalaswamy Ranganath ,&nbsp;Sugganahalli Channappa Ranganatha ,&nbsp;Venkatesh Paramesh ,&nbsp;Dinesh Jinger","doi":"10.1016/j.nexus.2025.100370","DOIUrl":"10.1016/j.nexus.2025.100370","url":null,"abstract":"<div><div>Suboptimal nutrition augmented by soil moisture stress adversely impacts crop performance in rainfed agriculture. At the same situation, conjunctive use of bioinoculants with mineral nutrients alleviates moisture stress and amplifies nutrient availability that improves the crop performance. With this background, a four-year fixed plot field experiment was conducted to determine the impact of mineral nutrition and biopriming on the productivity, economics, energetics, and carbon (C) footprint in rainfed castor. Three fertilizer rates and five bioinoculants were evaluated in a split-plot design with three replications. The result revealed that, application of recommended rate of fertilizer (RRF) recorded ∼22.13 % and 82.49 % higher yields than 75 % and 50 % RRF, respectively. The highest gross returns (₹ 80,412 ha^-1), net returns (₹ 50,511 ha^-1) and benefit-cost ratios (2.68) were also found higher with RRF. Likewise, plots applied with RRF even increased the seed oil content (50.9 %), oil productivity (722 kg ha^-1), and rain-water use efficiency (1.60 kg ha^-1 mm^-1). The plots treated with RRF required in 8.12–18.64 % higher energy input (12,275 MJ ha^-1) over 75 % and 50 % RRF, respectively. Furthermore, RRF appeared to be convincing by recording significantly highest C-outputs (1,582 kg CE ha⁻¹) and also other C quotients over its counterparts. Among the binoculants, seed priming with <em>Bacillus megaterium</em> and <em>Pseudomonas fluorescens</em> surpassed the productivity potential of other bioinoculants. Bioinoculants being energy diffident inputs they did not showed significant variation in energy input, while they showed significant variation in energy output. The energy output of castor bioprimed with <em>B. megaterium</em> (47,011 MJ ha^-1) surpassed the remaining bioinoculants. Again, <em>B. megaterium</em> recorded significantly lower C-footprint (0.22 kg CE kg castor seed yield⁻¹) while it displayed highest C-outputs (1,556 kg CE ha⁻¹), C-efficiencies (4.53 kg kg⁻¹ CE), net C-gains (1,278 kg CE ha⁻¹), and C-sustainability index (4.60). Consequently, the application of RRF, i.e.<em>,</em> 40–40–20 kg N-P₂O₅-K₂O ha^-1, along with the biopriming of <em>B.megaterium</em> appeared to be promising in enhancing productivity, economic returns, and resource use efficiency besides optimizing energy flow and C footprint in rainfed castor bean cultivation.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100370"},"PeriodicalIF":8.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143403193","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging technologies in water desalination: A review and future outlook","authors":"Anwur Alenezi ,&nbsp;Yousef Alabaiadly","doi":"10.1016/j.nexus.2025.100373","DOIUrl":"10.1016/j.nexus.2025.100373","url":null,"abstract":"<div><div>This review analyses emerging desalination technologies that offer sustainable solutions to global water scarcity and address unresolved issues. This study examines solar electrochemical distillation (SED), integrated solar capacitive deionisation (SCDI) and capacitive deionisation hybrid systems (CDI-HS), solar-powered passive desalination (SPPD), membrane distillation (MD), and forward osmosis (FO). A comprehensive literature review evaluates recent research and advancements in each technology. From each study, the authors extracted key characteristics, including the year of publication, research methods, data collection techniques, and the direction or strength of the research outcomes. Each study in this review serves as a unit of analysis, with the literature forming a database to interpret trends and draw conclusions about emerging desalination technologies. Key challenges were identified, and recommendations for future studies proposed, based on existing data and experimental findings. The review's findings underscore the need to address unresolved issues in desalination technologies to enhance their efficiency, scalability, and sustainability. Implementing the recommended research strategies could optimise these technologies, ensuring a reliable and sustainable supply of fresh water. Continued innovation, supported by targeted research and robust policy frameworks, is essential to mitigate global water scarcity and ensure water security for future generations.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100373"},"PeriodicalIF":8.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143402681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A systematic literature review on combined seawater desalination and reverse electrodialysis: Evaluating its technological readiness and potential for full-commercialization","authors":"Marijn T. van Geet,&nbsp;Janina Fuchs","doi":"10.1016/j.nexus.2025.100362","DOIUrl":"10.1016/j.nexus.2025.100362","url":null,"abstract":"<div><div>Combined seawater desalination and reverse electrodialysis technology has emerged as an eco-innovation that holds great promise to enhance the economic and environmental performance of the desalination industry. However, despite its apparent benefits and increased academic interest, reverse electrodialysis is, to date, not commonly used in combination with desalination. Using a technological readiness perspective, the current study evaluates its technological maturity and potential to achieve full commercialization. Based on a structured literature review including 70 recent publications on the topic, the current study identified four main techno-economic barriers that stand in the way of this eco-innovation progressing to wide-scale adoption: (1) a low power density and energy efficiency; (2) a high levelized cost of energy; (3) technological immaturity; and (4) a lack of competitiveness. The technological immaturity of combined seawater desalination and reverse electrodialysis technology is one of the prime reasons for the low power density and energy efficiency, which in turn has a causal relationship with the high costs associated with the technology. Additionally, the high costs may contribute to the lack of competitiveness. It is concluded that these main barriers might cause the eco-innovation to fall victim to the so-called \"Valley of Death,\" a funding gap between the proof of concept within academia and the adoption of the technology by the industry on a commercial scale. These findings have implications for future policy initiatives and investment decisions that aim to decarbonize and lessen the desalination industry's environmental impact.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100362"},"PeriodicalIF":8.0,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143372179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An investigation of solar photovoltaic systems for potable water and lighting in socially and economically disadvantaged coastal regions","authors":"Kazi Meharajul Kabir ,&nbsp;M.A. Matin ,&nbsp;N. Amin","doi":"10.1016/j.nexus.2025.100361","DOIUrl":"10.1016/j.nexus.2025.100361","url":null,"abstract":"<div><div>Bangladesh faces ongoing challenges in providing reliable electricity and clean drinking water, particularly in underprivileged coastal and rural areas. This study presents a low-cost, renewable energy-based system to address these issues, focusing on brackish water purification and nighttime lighting. The coastal zone, rich in solar, wind, and biomass resources, was selected for system design, optimization, and implementation. Simulations show that a solar and biomass hybrid energy system is cost-effective, providing water at $0.021/liter and electricity at $0.14/kWh. However, the high installation costs and need for expert maintenance limit the practicality of biomass for widespread use. Wind energy also proved ineffective in this region. Consequently, a solar photovoltaic (PV) system was identified as the most viable alternative, with costs of $0.022/liter for water and $0.17/kWh for energy. Laboratory testing confirmed that the system's purified water meets international water quality standards, producing potable water at just $0.002/liter, which is much cheaper than bottled water production, which costs $0.009/liter in Bangladesh. This research provides a sustainable solution for Bangladesh's underprivileged communities, contributing to long-term water and energy security.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100361"},"PeriodicalIF":8.0,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimization of performance under off-design conditions for dual-pressure organic Rankine cycle with hot source splitting","authors":"Shiqi Wang ,&nbsp;Zhongyuan Yuan ,&nbsp;Kim Tiow Ooi ,&nbsp;Xiangyu Chang ,&nbsp;Nanyang Yu","doi":"10.1016/j.nexus.2025.100360","DOIUrl":"10.1016/j.nexus.2025.100360","url":null,"abstract":"<div><div>The Dual-Pressure Organic Rankine Cycle system, integrated with Hot Source Splitting (DORC-HSS), demonstrates enhanced performance by optimizing heat matching. A primary challenge in deploying the DORC-HSS system lies in its off-design performance, particularly when faced with varying conditions of heat and cold sources. By using the first law of thermodynamics and the logarithmic mean temperature difference method, the MATLAB model of the system is established, and the net output power is optimized by particle swarm optimization. Our analysis reveals that in optimal off-design scenarios, the working fluid exits each loop preheater nearing a saturated liquid state. The increase in hot water flow rate leads to a decrease in the superheat degree in the high-pressure loop. Conversely, the working fluid at the expander inlet in the low-pressure loop consistently maintains a saturated vapor state. Furthermore, a 20.0% increase in optimal output power is observed for every 5 °C rise in hot water inlet temperature, and a 12.2% increase for every 20 kg/s increment in hot water flow rate. The highest thermal and exergy efficiencies achieved are 8.54% and 49.98%, respectively. A reduction of 1 °C in cooling water temperature corresponds to a 3.5% increase in output power. When the cooling water inlet temperature is 17 °C, the highest thermal and exergy efficiencies are 8.0% and 52.3%. The optimal hot water split ratio ranges from 67% to 79%. This optimization method can be used for any waste heat recovery system using DORC-HSS. Industries can approach control targets, ensuring the safe operation and translating into meaningful energy savings and lower operating costs. The economic benefits from such enhancements could shorten the payback period for DORC-HSS installations.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100360"},"PeriodicalIF":8.0,"publicationDate":"2025-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective inexact optimization of the biomass supply chain from an energy-land-carbon nexus perspective","authors":"Zhanxiang Fang ,&nbsp;Mengmeng Wang ,&nbsp;Ling Ji ,&nbsp;Yulei Xie ,&nbsp;Jiliang Zhen","doi":"10.1016/j.nexus.2024.100358","DOIUrl":"10.1016/j.nexus.2024.100358","url":null,"abstract":"<div><div>It is attractive and advantageous to utilize marginal land to support regional biomass energy development and improve energy security. In this study, an integrated and comprehensive decision-making framework is proposed to support the strategic planning and tactical management of regional biomass supply networks from an energy-land-carbon nexus perspective. It combines a multi-objective fuzzy chance-constraint programming model with spatial analysis of marginal land and multi-criteria assessment of biorefinery sites. The model is verified through a case study of a major agricultural region, Shandong Province in China. Local agricultural residues remain a key feedstock for bioethanol production. The results highlight the importance of considering the multi-objective tradeoffs and the intricate resource and environmental nexus for stakeholders to achieve sustainability in real practice. A cost-minimization objective drives the construction of large-scale biomass plants to enhance efficiency. An emissions-minimization goal favors smaller, decentralized plants to reduce transport distances and improve local land use. Maximizing social welfare promotes marginal land development, creating more employment opportunities. Decision-makers' management goals, risk preferences, and external fluctuations significantly influence the spatial planning of bioethanol supply chains, marginal land utilization, and operational strategies. Overall, the proposed methodology offers decision-makers an effective tool for achieving optimal decisions while accounting for complex system interdependencies, conflicting objectives, and uncertainties.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100358"},"PeriodicalIF":8.0,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143177881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Waste heat recovery of a combined internal combustion engine and inverse brayton cycle for hydrogen and freshwater outputs: 4E optimization and comparison","authors":"Mohammad Zoghi,&nbsp;Nasser Hosseinzadeh,&nbsp;Saleh Gharaie,&nbsp;Ali Zare","doi":"10.1016/j.nexus.2024.100356","DOIUrl":"10.1016/j.nexus.2024.100356","url":null,"abstract":"<div><div>In power plants, internal combustion engines (ICEs) continue to serve as a prevalent source of power generation. Despite advancements in ICE performance over the past decade, significant amounts of energy are still wasted through exhaust gases and jacket cooling water. In this study, advanced waste heat recovery technologies are explored to enhance the overall efficiency of ICE power plants. Initially, an inverse Brayton cycle (IBC) is employed for exhaust gas energy recovery in a 500 kW ICE. Subsequently, waste energy in the heat rejection stage of the IBC and the exhausted gas from the compressor is recovered using a thermoelectric generator (TEG) and an absorption chiller. Additionally, the extra electricity generated by the TEG is directed to a proton exchange membrane electrolyzer and a reverse osmosis desalination unit, producing hydrogen and potable water as additional outputs. Furthermore, energy from the jacket cooling water is recovered in a hot water unit. The 4E (energy, exergy, exergy-economic, and environmental) performance of the two configurations is compared by sensitivity analysis and design optimization. Exergy efficiency and unit cost of product (UCOP) are obtained as 36.09% and 58.303 $/GJ for the stand-alone engine. They are calculated at 39.62% and 64.553 $/GJ and 43.05% and 62.06 $/GJ for Configurations 1 and 2, respectively, in the optimum mode. In this case, Configuration 2 leads to the highest efficiency, and while the UCOP of Configuration 2 is better than that of Configuration 1, the stand-alone engine has the best value of UCOP. This suggests that converting a stand-alone engine to an integrated system with multiple useful outputs is a feasible and beneficial strategy for improving power plant efficiency and sustainability. Furthermore, in the optimum mode and for Configuration 2, improvements of 1.36% and 1.49% are reported for exergy efficiency and UCOP in comparison with the base case mode.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"17 ","pages":"Article 100356"},"PeriodicalIF":8.0,"publicationDate":"2024-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143179506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}