UEXdo/OpenDataHub huggingface dataset:
Early engagement and co-benefits strengthen cities’ climate commitments
Authors: O’Garra, T.; Kuz, V.; Deneault, A.; Orr, C.; Chan, S.
Journal: Nature Cities (2024)

AbstractCities can lead the way in tackling climate change through robust climate actions (that is, measures taken to limit climate change or its impacts). However, escalating crises due to pandemics, conflict and climate change pose challenges to ambitious and sustained city climate action. Here we use global data on 793 cities from the Carbon Disclosure Project 2021 platform to assess how the COVID-19 crisis has affected cities’ reported climate commitments and actions and the factors associat
Open data for energy networks: introducing DAVE—a data fusion tool for automated network generation
Authors: Banze, T.; Kneiske, T.
Journal: Scientific Reports (2024)

Abstract
                  Developing a sustainable energy system for the future requires new ways of planning and operating energy infrastructure. A large part of this involves suitable network models. Real network data is not available for research without restrictions since energy networks are part of the critical infrastructure. Using open datasets and expert rules to generate non-restricted models is one solution to this. This paper introduces open data for energy networks generated by the
Optimising the manufacturing of a β-Ti alloy produced via direct energy deposition using small dataset machine learning
Authors: Brooke, R.; Qiu, D.; Le, T.; Gibson, M.; Zhang, D.
Journal: Scientific Reports (2024)

Abstract
                  
                    Successful additive manufacturing involves the optimisation of numerous process parameters that significantly influence product quality and manufacturing success. One commonly used criteria based on a collection of parameters is the global energy distribution (GED). This parameter encapsulates the energy input onto the surface of a build, and is a function of the laser power, laser scanning speed and laser spot size. This study uses machine learnin
Analytical and experimental analysis of concrete temperature and energy considering open-air environmental variations
Authors: Yang, W.; Li, P.; Zhuo, L.; Pang, M.; Xie, H.
Journal: Scientific Reports (2024)

AbstractLongwave radiation is an important open-air environmental factor that can significantly affect the temperature of concrete, but it has often been ignored in the temperature analysis of open-air concrete structures. In this article, an improved analytical model of concrete temperature was proposed by considering solar radiation, thermal convection, thermal conduction and especially longwave radiation. Temperature monitoring of an open-air concrete block was carried out to verify the propo
Numerical study on solar photovoltaic/thermal system with tesla valve
Authors: Du, S.; Zou, J.; Zheng, X.; Ye, X.; Yang, H.
Journal: Scientific Reports (2024)

AbstractIn recent years, photovoltaic/thermal (PV/T) systems have played a crucial role in reducing energy consumption and environmental degradation, nonetheless, the low energy conversion efficiency presents a considerable obstacle for PV/T systems. Therefore, improving heat conversion efficiency is essential to enhance energy efficiency. In this paper, the PV/T system with the Tesla valve is proposed to solve this problem. Firstly, the cooling effect is simulated and analyzed in the system wit
Leveraging opposition-based learning for solar photovoltaic model parameter estimation with exponential distribution optimization algorithm
Authors: Kullampalayam Murugaiyan, N.; Chandrasekaran, K.; Manoharan, P.; Derebew, B.
Journal: Scientific Reports (2024)

AbstractGiven the multi-model and nonlinear characteristics of photovoltaic (PV) models, parameter extraction presents a challenging problem. This challenge is exacerbated by the propensity of conventional algorithms to get trapped in local optima due to the complex nature of the problem. Accurate parameter estimation, nonetheless, is crucial due to its significant impact on the PV system’s performance, influencing both current and energy production. While traditional methods have provided reaso
Energy efficient and sustainable design of a multi-story building based on embodied energy and cost
Authors: Qing, Z.; Li Na, Z.
Journal: Scientific Reports (2024)

AbstractSustainable multi-story building designs are gaining increasing attention in light of the green development of the building industry. Recently, many studies have been conducted to determine the optimized embodied energy considering size of structural members and materials strength using a single objective function. In this context, the current study adopted a multi-objective function based on cost and Embodied Energy (EE) for the sustainable design of the entire multi-story building. A B
Optimization of building integrated energy scheduling using an improved genetic whale algorithm
Authors: Wei, L.; An, G.
Journal: Scientific Reports (2024)

AbstractRenewable energy generation has become the general trend with increasing environmental problems. However, the instability of renewable energy generation and the diversification of user demand are highlighted and the optimization of energy scheduling has become the key to solve the problem. This study introduces an energy scheduling optimization model tailored for building integrated energy systems, encompassing elements like gas turbines, wind and solar modules, ground source heat pumps,
Comparative analysis of direct coupling and MPPT control in standalone PV systems for solar energy optimization to meet sustainable building energy demands
Authors: Nataraj, C.; Karthikeyan, G.; Bharathi, G.; Duraikannan, S.
Journal: Scientific Reports (2024)

Abstract
                  Solar energy, a prominent renewable source, has reached an installed capacity of 71.78 GW in India. This research explored the load demands of the computer center at an engineering college in Tanjore, Tamil Nadu, India. The computer center at the engineering college has an annual energy requirement of 260,552 kWh/Year. Consequently, the research focused on the planning and implementation of a standalone photovoltaic (SAPV) system, assessing it against the institution's
Multiple objective energy optimization of a trade center building based on genetic algorithm using ecological materials
Authors: Kabiri, E.; Maftouni, N.
Journal: Scientific Reports (2024)

AbstractIt is crucial to optimize energy consumption in buildings while considering thermal comfort. The first step here involved an EnergyPlus simulation on a trade center building located in Tehran, Bandar Abbas, and Tabriz, Iran. A multi-objective optimization was then performed based on non-dominated sorting genetic algorithm II (NSGA-II) in jEPlus + EA to establish the building in the selected city where would benefit the most from implementing the radiant ceiling cooling system. Efforts we
Urban 3D building morphology and energy consumption: empirical evidence from 53 cities in China
Authors: Wang, Y.; Sun, G.; Wu, Y.; Rosenberg, M.
Journal: Scientific Reports (2024)

AbstractThe impact of building morphology on building energy consumption has been extensively studied. However, research on how 3D building morphology affects energy consumption at a macroscopic scale is lacking. In this study, we measured the mean building height (BH), mean building volume (BV), and mean European nearest neighbor distance (MENN) of the city to quantify the 3D building morphology. We then used a spatial regression model to analyze the quantitative impact of urban 3D building mor
Theoretical study of the synergic relationships between the design parameters in energy-saving building design
Authors: Huo, H.; Ji, Y.; Qin, Y.; Chen, C.; Yuan, T.
Journal: Scientific Reports (2024)

AbstractWith the rapid development of the economy, people have increasingly higher requirements for the comfort of living spaces, and the result is the sharp increase in building energy consumption. Several design parameters influence living space comfort and building energy efficiency. Since the same design standard can include different design parameter combinations, synergic relationships may exist between these criteria for one case. Identifying these synergic relationships requires an inver
Active learning-based machine learning approach for enhancing environmental sustainability in green building energy consumption
Authors: Mahmood, S.; Sun, H.; Ali Alhussan, A.; Iqbal, A.; El-kenawy, E.
Journal: Scientific Reports (2024)

AbstractGreen building (GB) techniques are essential for reducing energy waste in the construction sector, which accounts for almost 40% of global energy consumption. Despite their importance, challenges such as occupant behavior and energy management gaps often result in GBs consuming up to 2.5 times more energy than intended. To address this, Building Automation Systems (BAS) play a crucial role in enhancing energy efficiency. This research develops a predictive model for GB design using machi
Robust load-frequency control of islanded urban microgrid using 1PD-3DOF-PID controller including mobile EV energy storage
Authors: Davoudkhani, I.; Zare, P.; Abdelaziz, A.; Bajaj, M.; Tuka, M.
Journal: Scientific Reports (2024)

AbstractElectricity generation in Islanded Urban Microgrids (IUMG) now relies heavily on a diverse range of Renewable Energy Sources (RES). However, the dependable utilization of these sources hinges upon efficient Electrical Energy Storage Systems (EESs). As the intermittent nature of RES output and the low inertia of IUMGs often lead to significant frequency fluctuations, the role of EESs becomes pivotal. While these storage systems effectively mitigate frequency deviations, their high costs a
Determinants of household adoption of clean energy with its rural–urban disparities in Bangladesh
Authors: Haq, I.; Khan, M.; Chakma, S.; Hossain, M.; Sarkar, S.
Journal: Scientific Reports (2024)

AbstractThis study aims to investigate factors influencing the adoption of clean energy among households in Bangladesh, using Blinder-Oaxaca decomposition and extended probit regression model with data from the 2019 Bangladesh multiple indicator cluster survey. Small households, primarily Muslim and urban dwellers, who speak the Bengali language and are Internet and mobile users, were likelier to adopt cleaner fuels than their counterparts. On the contrary, households residing in the Barisal, Kh
Research on coupling optimization of carbon emissions and carbon leakage in international construction projects
Authors: Zhou, Z.; Wang, Y.; Alcalá, J.; Yepes, V.
Journal: Scientific Reports (2024)

AbstractDue to the rapid economic development of globalization and the intensification of economic and trade exchanges, cross-international and regional carbon emissions have become increasingly severe. Governments worldwide establish laws and regulations to protect their countries' environmental impact. Therefore, selecting robustness evaluation models and metrics is an urgent research topic. This article proves the reliability and scientific of the assessment data through literature coupling e
Studying tourism development and its impact on carbon emissions
Authors: Zhao, X.; Li, T.; Duan, X.
Journal: Scientific Reports (2024)

AbstractAnalyzing the influence of tourism on carbon emission has significant implications for promoting the sustainable development of tourism. Based on the panel data of 31 tourist cities in China from 2005 to 2022, this study utilizes a structural equation model to explore the carbon reduction effect of tourism development and its influencing mechanism. The results show that: (1) The overall carbon emission efficiency of tourism cities first decreased and then increased, rised to a peak of 0.
The trajectory of carbon emissions and terrestrial carbon sinks at the provincial level in China
Authors: Hu, Y.; Li, Y.; Zhang, H.; Liu, X.; Zheng, Y.
Journal: Scientific Reports (2024)

Abstract
                  
                    Global greenhouse gas emission, major factor driving climate change, has been increasing since nineteenth century. STIRPAT and CEVSA models were performed to estimate the carbon emission peaks and terrestrial ecosystem carbon sinks at the provincial level in China, respectively. Utilizing the growth characteristics and the peak time criteria for the period 1997–2019, the patterns of energy consumption and CO
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Digital inclusive finance, green technological innovation, and carbon emissions from a spatial perspective
Authors: Lu, Y.; Xia, Z.
Journal: Scientific Reports (2024)

AbstractBased on the panel data of 276 prefecture-level cities in China from 2011 to 2020, this study explores the impact of digital inclusive finance (DIF) on carbon emissions and the intrinsic mechanism of green technological innovation from a spatial perspective by constructing a spatial econometric model, a mediating effect model, and a threshold model. The results show that DIF significantly inhibits carbon emissions, exhibiting a spatial spillover effect. The transmission mechanism from a
Determinants and their spatial heterogeneity of carbon emissions in resource-based cities, China
Authors: Guo, C.; Yu, J.
Journal: Scientific Reports (2024)

AbstractGlobal climate change associated with increased carbon emissions has become a global concern. Resource-based cities, by estimations, have emerged as major contributors to carbon emissions, accounting for approximately one-third of the national total. This underscores their pivotal role in the pursuit of carbon neutrality goals. Despite this, resource-based cities have long been neglected in current climate change mitigation policy discussions. Accordingly, using exploratory spatial data
Reshaping the energy landscape of Crete through renewable energy valleys
Authors: Skaloumpakas, P.; Sarmas, E.; Rachmanidis, M.; Marinakis, V.
Journal: Scientific Reports (2024)

AbstractRenewable energy valleys (REVs) represent a transformative concept poised to reshape global energy landscapes. These comprehensive ecosystems transition regions from conventional energy sources to sustainable, self-reliant hubs for renewable energy generation, distribution, and consumption. At their core, REVs integrate advanced information and communication technology (ICT), interoperable digital solutions, social innovation processes, and economically viable business models. They offer
A rule-based energy management system for hybrid renewable energy sources with battery bank optimized by genetic algorithm optimization
Authors: Jamal, S.; Pasupuleti, J.; Ekanayake, J.
Journal: Scientific Reports (2024)

AbstractA Nanogrid (NG) model is described as a power distribution system that integrates Hybrid Renewable Energy Sources (HRESs) and Energy Storage Systems (ESSs) into the primary grid. However, this process is affected by several factors, like load variability, market pricing, and the intermittent nature of Wind Turbines (WTs) and Photovoltaic (PV) systems. Hence, other researchers in the past have used a few optimization-based processes to improve the development of Energy Management Systems
Deep learning-based forecasting of electricity consumption
Authors: Qureshi, M.; Arbab, M.; Rehman, S.
Journal: Scientific Reports (2024)

AbstractBuilding energy management systems (BEMS) are integrated computerized systems that track and manage the energy use of many pieces of building-related machinery and equipment, including lighting, power systems, and HVAC systems. Modern buildings must have BEMSs in order to reduce energy usage while maintaining comfort. Not only for energy-saving purposes, BEMS is essential in enhancing the quality of the energy supply, which helps to gain a better understanding of how energy is used and t
Estimating the energy consumption for residential buildings in semiarid and arid desert climate using artificial intelligence
Authors: Wefki, H.; Khallaf, R.; Ebid, A.
Journal: Scientific Reports (2024)

AbstractThis research aims to develop predictive models to estimate building energy accurately. Three commonly used artificial intelligence techniques were chosen to develop a new building energy estimation model. The chosen techniques are Genetic Programming (GP), Artificial Neural Network (ANN), and Evolutionary Polynomial Regression (EPR). Sixteen energy efficiency measures were collected and used in designing and evaluating the proposed models, which include building dimensions, orientation,
Limited increases in Arctic offshore oil and gas production with climate change and the implications for energy markets
Authors: Zhang, Y.; Msangi, S.; Edmonds, J.; Waldhoff, S.
Journal: Scientific Reports (2024)

AbstractClimate change impacts on sea ice thickness is opening access to offshore Arctic resources. The degree to which these resources are exploited will depend on sea-ice conditions, technology costs, international energy markets, and the regulatory environment. We use an integrated human-Earth system model, GCAM, to explore the effects of spatial–temporal patterns of sea-ice loss under climate change on future Arctic offshore oil and gas extraction, considering interactions with global energy
Deep learning-driven hybrid model for short-term load forecasting and smart grid information management
Authors: Wen, X.; Liao, J.; Niu, Q.; Shen, N.; Bao, Y.
Journal: Scientific Reports (2024)

AbstractAccurate power load forecasting is crucial for the sustainable operation of smart grids. However, the complexity and uncertainty of load, along with the large-scale and high-dimensional energy information, present challenges in handling intricate dynamic features and long-term dependencies. This paper proposes a computational approach to address these challenges in short-term power load forecasting and energy information management, with the goal of accurately predicting future load dema
Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid
Authors: Qi, H.; Zhu, W.; Ye, M.; Hu, Y.; Wang, Y.
Journal: Scientific Reports (2024)

AbstractDue to theintricate and interdependent nature of the smart grid, it has encountered an increasing number of security threats in recent years. Currently, conventional security measures such as firewalls, intrusion detection, and malicious detection technologies offer specific protection based on their unique perspectives. However, as the types and concealment of attacksincrease, these measures struggle to detect them promptly and respond accordingly. In order to meet the social demand for
Machine learning optimization for hybrid electric vehicle charging in renewable microgrids
Authors: Hassan, M.
Journal: Scientific Reports (2024)

AbstractRenewable microgrids enhance security, reliability, and power quality in power systems by integrating solar and wind sources, reducing greenhouse gas emissions. This paper proposes a machine learning approach, leveraging Gaussian Process (GP) and Krill Herd Algorithm (KHA), for energy management in renewable microgrids with a reconfigurable structure based on remote switching of tie and sectionalizing. The method utilizes Gaussian Process (GP) for modeling hybrid electric vehicle (HEV) c
Power consumption prediction for electric vehicle charging stations and forecasting income
Authors: Akshay, K.; Grace, G.; Gunasekaran, K.; Samikannu, R.
Journal: Scientific Reports (2024)

AbstractElectric vehicles (EVs) are the future of the automobile industry, as they produce zero emissions and address environmental and health concerns caused by traditional fuel-poared vehicles. As more people shift towards EVs, the demand for power consumption forecasting is increasing to manage the charging stations effectively. Predicting power consumption can help optimize operations, prevent grid overloading, and power outages, and assist companies in estimating the number of charging stat
Research on the interaction between energy consumption and power battery life during electric vehicle acceleration
Authors: Liu, Q.; Zhang, Z.; Zhang, J.
Journal: Scientific Reports (2024)

AbstractMost studies on the acceleration process of electric vehicle focus on reducing energy consumption, but do not consider the impact of the power battery discharge current and its change rate on the battery life. Therefore, this paper studied the interaction between electric vehicle energy consumption and power battery capacity attenuation during acceleration. First, a power battery life model for electric vehicle under driving conditions is established, and the percentage of battery capaci
Wind energy resource assessment and wind turbine selection analysis for sustainable energy production
Authors: Spiru, P.; Simona, P.
Journal: Scientific Reports (2024)

AbstractThe objective of this study is to perform an analysis to determine the most suitable type of wind turbine that can be installed at a specific location for electricity generation, using annual measurements of wind characteristics and meteorological parameters. Wind potential analysis has shown that the analyzed location is suitable for the development of a wind farm. The analysis was carried out for six different types of wind turbines, with a power ranging from 1.5 to 3.0 MW and a hub he
Dynamic performance of rotor-side nonlinear control technique for doubly-fed multi-rotor wind energy based on improved super-twisting algorithms under variable wind speed
Authors: Benbouhenni, H.; Yessef, M.; Colak, I.; Bizon, N.; Kotb, H.
Journal: Scientific Reports (2024)

AbstractThe paper proposes a nonlinear controller called dual super-twisting sliding mode command (DSTSMC) for controlling and regulating the rotor side converter (RSC) of multi-rotor wind power systems that use doubly-fed induction generators. It was proposed that this controller be developed as an alternative to the direct power control (DPC), which makes use of a pulse width modulation (PWM) strategy to regulate the RSC's functioning. Overcoming the power/current quality issue with the propos
Continuous input current buck DC/DC converter for small-size wind energy systems featuring current sensorless MPPT control
Authors: Zakzouk, N.
Journal: Scientific Reports (2024)

AbstractFor decentralized electrification in remote areas, small-sized wind energy systems (WESs) are considered sustainable and affordable solution when employing an efficient, small-sized component converter integrated with a less-sophisticated, cost-effective MPPT controller. Unfortunately, using a conventional buck DC/DC converter as a MPP tracker suffer from input current discontinuity. The latter results in high ripples in the tracked rectified wind power which reduces the captured power a
Modelling the wind potential energy for metallurgical sector in Albania
Authors: Dhoska, K.; Bebi, E.; Markja, I.; Milo, P.; Sita, E.
Journal: Scientific Reports (2024)

AbstractThe metallurgical industry, in the context of the global energy crisis and the new European green deal, needs urgent investments on energy and resource efficiency. The metallurgical sector, which includes the production of different metals is an energy-intensive industry that requires large amounts of energy for various processes such as smelting, refining, and casting. One of the largest consumptions of energy in Albania comes from the metallurgical sector during the production of iron,
Digital finance reduces urban carbon footprint pressure in 277 Chinese cities
Authors: Dong, Z.; Yao, S.
Journal: Scientific Reports (2024)

AbstractAs global warming's impact on humanity surpasses initial predictions, numerous countries confront heightened risks associated with escalating urban carbon footprints. Concurrently, digital finance has flourished, propelled by advancements in digital technology. This convergence underscores the urgency of exploring digital finance's role in mitigating urban carbon footprint pressures. This study analyzes data spanning 277 Chinese cities from 2011 to 2020, yielding several key findings: Fi