Energy nexus最新文献

{"title":"Potential of smart irrigation controllers for demand-side management of water distribution systems","authors":"Nathan T. Lunstad ,&nbsp;Robert B. Sowby","doi":"10.1016/j.nexus.2025.100458","DOIUrl":"10.1016/j.nexus.2025.100458","url":null,"abstract":"<div><div>As a demand-side management (DSM) tool, smart irrigation controllers (SICs) have the potential to help water utilities manage peak demands. With an EPANET hydraulic model we demonstrate that residential SICs can shift and shave peak demands for outdoor irrigation. A real pressurized irrigation system was modeled with demands on a Monday-Wednesday-Friday schedule (baseline scenario) compared to a Monday-Wednesday-Friday and Tuesday-Thursday-Saturday schedule (intervention scenario). With the intervention, the system has lower peak demand (49 % reduction) and improved pressures (9.5 % increase in nodes satisfying minimum pressure). Without intervention, costly capital facility improvements would be needed to maintain the same level of service. Literature suggests SIC can provide 15 % to 40 % water savings; a third scenario assuming 30 % conservation with SICs (intervention SIC scenario) would shift and shave demand (65 % reduction in peak demand) as well as deliver benefits in pressure management (10 % increase in nodes satisfying minimum pressure), energy use (28 % reduction in peak power and 13 % reduction in energy cost), and distribution capacity (9.5 % decrease in pipes with high velocity) relative to the baseline scenario. This is the first hydraulic model analysis to demonstrate the DSM effectiveness of SICs.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100458"},"PeriodicalIF":8.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144071754","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":"Harnessing urban biomass for energy and water production: an NSGA-II-based optimization approach","authors":"Parviz Heydari Nasab ,&nbsp;Ata Chitsaz ,&nbsp;Hiva Rashidzadeh ,&nbsp;Alireza Rostamzadeh Khosroshahi","doi":"10.1016/j.nexus.2025.100449","DOIUrl":"10.1016/j.nexus.2025.100449","url":null,"abstract":"<div><div>In this research, were propose a multiple-system that includes gasification for syngas and heat production, a Brayton cycle for power generation, and the utilization of waste heat from the turbine. This waste heat is used in a two-effect absorption refrigeration system to produce cooling and in a 24-step, multi-stage flash (MSF) desalination process to produce fresh water. A certain amount of natural gas is added as an auxiliary fuel to increase the calorific value of the syngas produced in the gasifier. The main driver is biomass from municipal solid waste due to its renewable nature and availability in all cities. This system is thermodynamically modeled using the Engineering Equation Solver (EES) software. It provides integrated analysis and investigation of the effects of energy, exergy, and the Levelized Cost Of Energy (LCOE) and Levelized Cost Of Exergy (LCOEx) in multi-objective optimization of multiple-systems to achieve maximum efficiency and minimum cost. It has been validated with similar papers. Finally, using objective functions, the (LCOE) and exergy efficiency has been optimized using MATLAB software with the Non-dominated Sorting Genetic Algorithm (NSGA II) method. The results indicate that the system achieves a net power Output of 18.756 MW, a heating capacity of 1.75 MW, a cooling capacity of 17.77 MW, and a freshwater production rate of 47.7 kg/s. The energy efficiency is calculated to be 73.51 %, with an exergy efficiency of 26.31%. The (LCOE) and (LCOEx) are 0.062 $/kWh and 0.236 $/kWh, respectively. The system is designed with a useful life of 25 years. Optimization results reveal that the optimal range for the (LCOE) is between 0.0566 and 0.0592 $/kWh, while the exergy efficiency ranges between 26.21 % and 28.09 %.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100449"},"PeriodicalIF":8.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143946500","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":"Optimal sizing of a grid-connected DC microgrid for agricultural applications with water-energy management system considering battery cycle life","authors":"Mohammad Hossein Mokhtare,&nbsp;Ozan Keysan","doi":"10.1016/j.nexus.2025.100445","DOIUrl":"10.1016/j.nexus.2025.100445","url":null,"abstract":"<div><div>This paper presents an optimal sizing method for a DC microgrid topology commonly installed in agricultural farms. The microgrid comprises solar photovoltaic (PV) panels, a battery energy storage system (BESS), an electric water pump, an elevated water reservoir (WR), and a household electrical load. The sizing optimization procedure includes selecting a suitable PV array size and optimizing the WR and BESS capacities. For the technical evaluation of possible solutions, a water-energy management system (WEMS) is proposed. Water is treated as an independent demand. The irrigation regime is modeled on the basis of farmers’ experiential knowledge and a temperature constraint to avoid unnecessary evaporation due to irrigation in high temperatures. Moreover, the battery cycle and calendar lifetimes are integrated into the presented sizing method. A case study is conducted for an actual farm with real data. Comparative simulations with alternative topologies show that the PV-BESS-Grid microgrid with solar water pumping is the most techno-economically efficient topology. The target farm, while supplied only from the grid, has a levelized cost of energy (LCOE) equal to 401 $/MWh. However, the presented sizing method finds a DC agricultural microgrid configuration that provides energy with an LCOE of 223 $/MWh. This is a significant 44% decrease in the LCOE. With the optimal solution, around 77% of the energy needs of the farm are supplied from renewable solar energy. In addition, wasted solar energy decreases by 62.4% compared to a standalone solar pumping system. Sensitivity analysis is performed by varying critical parameters to observe the impacts on the optimal solution.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100445"},"PeriodicalIF":8.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143941262","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":"Impact of ozone nanobubble on water quality, gut microbiota, and growth performance of white leg shrimp (Penaeus vannamei) in an intensive indoor farming system","authors":"Phan Trong Binh ,&nbsp;Phan Thi Van ,&nbsp;Nguyen Huu Nghia ,&nbsp;Tong Tran Huy ,&nbsp;Le Thi May ,&nbsp;Sophie St-Hilaire ,&nbsp;Pham Thai Giang","doi":"10.1016/j.nexus.2025.100450","DOIUrl":"10.1016/j.nexus.2025.100450","url":null,"abstract":"<div><div>This study evaluated the effects of ozone nanobubbles (NB-O₃) on water quality, growth performance, survival rate, and gut microbiota in intensive indoor farming of white-leg shrimp (<em>Penaeus vannamei</em>). The experiment lasted 12 weeks and included two groups: (1) NB-O₃ treatment at 0.3 mg/L ozone concentration and (2) a control group without NB-O₃ treatment. Water quality parameters including temperature, dissolved oxygen (DO), pH, and Oxidation–Reduction Potential (ORP) were monitored daily. Weekly analyses were conducted for Chemical Oxygen Demand (COD), Biochemical Oxygen Demand after 5 days (BOD₅), Ammonia Nitrogen (NH₃-N), Nitrite Nitrogen (NO₂-N), and Vibrio counts. Shrimp weight was recorded weekly, while final biomass (FB), final body weight (FBW), survival rate (SR), feed conversion ratio (FCR), specific growth rate (SGR), and mean weekly weight gain (MWWG) were evaluated at the end of study. Gut microbiota samples were collected on days 1, 60, and 84. The results showed that NB-O₃ significantly reduced COD, total <em>Vibrio</em>, and NH₃-N levels compared to the control (<em>p</em> &lt; 0.05). Shrimp in the NB-O₃ group exhibited significantly higher weights from week 5 onwards (<em>p</em> &lt; 0.05), with improved FB, FBW, SGR, and MWWG compared to the control (<em>p</em> &lt; 0.05). However, SR and FCR were lower in the NB-O₃ group (<em>p</em> &lt; 0.05). Dominant gut microbiota phyla in NB-O₃-treated shrimp were Proteobacteria, Bacteroidota, and Acinobacteriota, with their proportions recorded as 72.27 %, 13.82 %, and 6.72 % on day 1; 60.75 %, 17.16 %, and 18.64 % on day 60; and 45.74 %, 40.25 %, and 8.44 % on day 84, respectively. Significant differences in alpha and beta diversity were observed between groups on days 1 and 60 (<em>p</em> &lt; 0.05). <em>Vibrio parahaemolyticus</em> density was lower in NB-O₃-treated shrimp (<em>p</em> &lt; 0.05). These findings demonstrate that NB-O₃ improves water quality, enhances shrimp growth performance, and effectively regulates <em>Vibrio</em> spp. in intensive indoor farming systems. To the best of our knowledge, this is the first study to report the effects of NB-O3 on shrimp gut microbiota.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100450"},"PeriodicalIF":8.0,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143929589","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":"Microcredit and household energy consumption: Exploring the impact of The Kredit Usaha Rakyat (KUR) program in Indonesia","authors":"Diana Setyawati ,&nbsp;Djoni Hartono","doi":"10.1016/j.nexus.2025.100446","DOIUrl":"10.1016/j.nexus.2025.100446","url":null,"abstract":"<div><div>Energy constraints significantly impact household welfare and the quality of life. Developing countries, such as Indonesia, continue to face challenges in meeting household energy needs. This study investigates the impact of microcredit access on Indonesian households' energy consumption. Understanding this relationship is essential for insights into how microcredit can affect energy use in the context of developing countries. Using data from 2019 (pre-pandemic) and 2021 (during the pandemic), this study uniquely bridges a gap in the literature by analyzing both pre-pandemic and pandemic periods. This offers novel insights into how microcredit programs respond to dynamic economic conditions. We employ the two-stage least squares (2SLS) method with instrumental variables to address potential causality issues. Our findings reveal a positive relationship between access to microcredit and household energy consumption expenditures. By comparing pre-pandemic and pandemic periods, the study highlights how economic conditions affect the effectiveness of microcredit programs. Moreover, regional analysis reveals variations in the impact of microcredit across Indonesia. This study contributes to understanding how microcredit programs affect household energy consumption, taking into account economic conditions and spatial effects. Our findings offer policy implications for enhancing household energy consumption through microcredit programs. Policymakers should consider regional needs and evolving economic conditions to optimize the effectiveness of microcredit programs.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100446"},"PeriodicalIF":8.0,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143932041","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":"Integrated DDPG-PSO energy management systems for enhanced battery cycling and efficient grid utilization","authors":"Oladimeji Ibrahim ,&nbsp;Mohd Junaidi Abdul Aziz ,&nbsp;Razman Ayop ,&nbsp;Wen Yao Low ,&nbsp;Nor Zaihar Yahaya ,&nbsp;Ahmed Tijjani Dahiru ,&nbsp;Temitope Ibrahim Amosa ,&nbsp;Shehu Lukman Ayinla","doi":"10.1016/j.nexus.2025.100448","DOIUrl":"10.1016/j.nexus.2025.100448","url":null,"abstract":"<div><div>Effective energy management is crucial in hybrid energy systems for optimal resource utilization and cost savings. This study integrates Deep Deterministic Policy Gradient (DDPG) with Particle Swarm Optimization (PSO) to enhance exploration and exploitation in the optimization process, aiming to improve energy resource utilization and reduce costs in hybrid energy systems. The integrated DDPG-PSO approach leverages DDPG's reinforcement learning and PSO's global search capabilities to enhance optimization solution quality. The PSO optimizes the DDPG actor-network parameters, providing a strong initial policy. DDPG then fine-tunes these parameters by interacting with the energy system, making decisions on battery scheduling and grid usage to maximize cost rewards. The results show that the integrated DDPG-PSO EMS outperforms the traditional DDPG in terms of battery scheduling and grid utilization efficiency. Cost evaluations under critical peak tariffs indicate that both EMS algorithms achieved a 34 % cost saving compared to a grid-only system. Under differential grid tariffs, the proposed DDPG-PSO approach achieved a 28 % cost reduction, outperforming the standalone DDPG, which achieved a 25 % saving. Notably, the DDPG-PSO effectively reduced overall grid dependency, yielding a total operational cost of $665.19, compared to $780.70 for the DDPG. resenting a 14.8 % reduction. The battery charge/discharge profiles further highlight the advantages of the DDPG-PSO strategy. It demonstrated more stable and efficient energy flow behavior, characterized by shallow cycling and partial discharges sustained over several hours. In contrast, the DDPG exhibited more aggressive deep cycling, fluctuating frequently between minimum and maximum charge levels. This improved energy flow management by DDPG-PSO not only reduces wear on the battery system but also promotes long-term sustainability and reliability in hybrid energy management.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100448"},"PeriodicalIF":8.0,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144084020","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":"Energy resilience enhancement against grid outages for a zero-emission hotel building via optimal energy management of onshore and offshore energy storages","authors":"Haojie Luo ,&nbsp;Sunliang Cao","doi":"10.1016/j.nexus.2025.100431","DOIUrl":"10.1016/j.nexus.2025.100431","url":null,"abstract":"<div><div>Increasing integration of renewable energy into building systems necessitates enhanced flexibility and resilience to maintain stability under dynamic grid conditions and unexpected outages. Existing research inadequately addresses energy flexibility for demand response and resilience during outages, underutilises hybrid mobile/stationary electrical/mechanical energy storage, and overlooks ocean-based renewable energy potential. To bridge these gaps, this study develops an advanced energy management system leveraging building batteries, electric vehicles, and wave energy converter reservoirs to improve flexibility and resilience in a net-zero energy building. Scenario-based analyses demonstrate that coordinated activation of sources outperforms single-source strategies. Coordinated control increased the flexibility index to 192.67% (1.93 times incentives), reducing costs to 80.66%; prioritisation further boosted flexibility to 199.89% and lowered costs to 79.52%. Resilience was enhanced by integrated wave energy converters, which enabled strategic energy storage/release, elevating from approximately 83% to over 99%, nearly eliminating CO₂ emissions and diesel backup reliance. Coordinating flexibility sources mitigates power shortages and reduces energy lag, strengthening system flexibility and outage resilience. The study’s originality lies in pioneering hybrid storage integration for dual flexibility-resilience objectives, novel utilisation of wave energy converters as demand-responsive assets, and efficient control strategies addressing profit maximisation and outage recovery. This research provides practical implications for reducing fossil fuel reliance and ensuring stable operations during grid disturbances, particularly applicable to coastal urban areas with ocean energy potential and electric vehicle adoption, offering a replicable model for net-zero transitions. This work bridges critical gaps in flexibility source coordination and ocean energy utilisation, advancing resilient, grid-interactive smart buildings.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100431"},"PeriodicalIF":8.0,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143932040","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":"Asymmetric behavior of average temperature and rainfall on rice production in Bangladesh","authors":"Md. Mamun Miah ,&nbsp;Md. Golam Kibria ,&nbsp;Nazhat Nury Aspy ,&nbsp;Kabir Hossain","doi":"10.1016/j.nexus.2025.100429","DOIUrl":"10.1016/j.nexus.2025.100429","url":null,"abstract":"<div><div>In light of today's scenario of global food security, developing economies need to meticulously monitor both the immediate and future influence of climate change on agricultural operations, as well as the possibility of perpetual adaptation. Regarding this issue, this inquiry aims to identify the asymmetrical behaviors of average temperature and rainfall on Bangladesh's rice yield. After assessing data from 1985 to 2021, the NARDL affirms that, although changes in average temperature hurt long-term yields of rice, they stimulate short-term production. In the short term, rainfall shocks, whether positive or negative, significantly boost rice yield, but in the long run, they have no significant influence. Conversely, carbon dioxide emissions have negative effects on rice output in the long run. Using fertilizer for longer periods augments rice yield in the long and short term. As part of policy suggestions, the government should compensate organic fertilizer users and stimulate sustainable behaviors to control average temperature and carbon dioxide emissions in Bangladesh.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100429"},"PeriodicalIF":8.0,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143899328","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":"Dynamics of urban consumption and resulting impacts on ecological footprint: A longitudinal study of Khulna, Bangladesh","authors":"Syed Riad Morshed ,&nbsp;Reshma Afroz Rimi","doi":"10.1016/j.nexus.2025.100427","DOIUrl":"10.1016/j.nexus.2025.100427","url":null,"abstract":"<div><div>This study investigated the ecological impact of citizen consumption in Khulna, the third-largest city in Bangladesh, focusing on five primary sources of carbon emissions: food consumption, shelter-related activities, mobility, goods consumption, and services. Utilizing Landsat 5 and 8 imageries, the research tracked land use changes over two decades. To estimate the carbon footprint, about 651 sample data were collected through a questionnaire survey. Biocapacity data was obtained using supervised image classification techniques in ArcGIS, with calculations conducted for 2002, 2007, 2012, 2017, and 2022 to identify trends. Results revealed that Khulna City Corporation emits approximately 0.76 million tons of carbon annually, translating to 0.209 global hectares per person. The largest emission contributors were shelter-related activities and food consumption, accounting for 41.35 % and 39.41 % of total emissions, respectively. The city's ecological footprint was 0.209 global hectares per capita, with a biocapacity of 0.076, resulting in an ecological deficit of 0.134 global hectares per person, indicating that the ecological demand exceeds the biocapacity by 2.7 times. Over the past two decades, Khulna's biocapacity declined by 0.026 global hectares per capita, from 0.1028 in 2002 to 0.076 in 2022. Overall study provides a framework for assessing consumer level carbon footprint focusing on SDGs 11 and 13 which will help policymakers, urban planners and environmentalists in strategic planning to reduce carbon footprint and increasing environmental sustainability.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100427"},"PeriodicalIF":8.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143901913","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":"Toward Sustainable Campus Energy Management: A Comprehensive Review of Energy Management, Predictive Algorithms, and Recommendations","authors":"Noor Islam Jasim ,&nbsp;Saraswathy Shamini Gunasekaran ,&nbsp;Nouar AlDahoul ,&nbsp;Ali Najah Ahmed ,&nbsp;Ahmed El-Shafie ,&nbsp;Mohsen Sherif ,&nbsp;Moamin A Mahmoud","doi":"10.1016/j.nexus.2025.100435","DOIUrl":"10.1016/j.nexus.2025.100435","url":null,"abstract":"<div><div>Rapid growth and challenges are likely to be experienced by energy generation, delivery, and consumption in the upcoming years, which in turn affect the economic and environmental perspectives. University buildings account for a significant portion of global energy consumption and associated CO₂ emissions, and this is expected to rise substantially in the near future. Unawareness of energy efficiency in academic buildings results in weak sustainability financially and environmentally. This paper aims to review the existing studies related to energy management, efficiency, prediction, and recommendations in university buildings. Various works and algorithms were discussed addressing the challenges and limitations in the existing systems, and proposing insights as an attempt to fill the gap in this significant research domain. Additionally, the limitations of current systems, which offer only short-term solutions, become evident over time. These systems are ineffective in the long run as they lack predictive capabilities that could guide users toward predefined savings goals, actions, recommendations, or established energy standards. The paper states that to facilitate energy efficiency and manage consumption, it is important to extract patterns of energy consumption by data modelling and predictive algorithms to achieve the ultimate goal of consumption recommending and advising. This data driven decisions can support the reduction of energy load which helps in having more sustainable infrastructure and ensures less economic and financial expansion. Practically, the main objective is to support universities to save energy, reduce electricity bills, and maintain people comfort. This paper is beneficial to researchers that have interests to conduct future studies related to energy efficiency, management, prediction, and recommendations. This review study proposes a significant solution for smart buildings that fulfils energy efficiency with minimal cost and efforts.</div></div>","PeriodicalId":93548,"journal":{"name":"Energy nexus","volume":"18 ","pages":"Article 100435"},"PeriodicalIF":8.0,"publicationDate":"2025-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143946501","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}