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On the potential of vehicle-to-grid and second-life batteries to provide energy and material security | 10.1038/s41467-024-48554-0 | https://doi.org/10.1038/s41467-024-48554-0 | Nature Communications | 2,024 | Aguilar Lopez, F.; Lauinger, D.; Vuille, F.; Müller, D. | AbstractThe global energy transition relies increasingly on lithium-ion batteries for electric transportation and renewable energy integration. Given the highly concentrated supply chain of battery materials, importing regions have a strategic imperative to reduce their reliance on battery material imports through, e.g., battery recycling or reuse. We investigate the potential of vehicle-to-grid and second-life batteries to reduce resource use by displacing new stationary batteries dedicated to | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Optimization & Control | |
Grid-like entorhinal representation of an abstract value space during prospective decision making | 10.1038/s41467-024-45127-z | https://doi.org/10.1038/s41467-024-45127-z | Nature Communications | 2,024 | Nitsch, A.; Garvert, M.; Bellmund, J.; Schuck, N.; Doeller, C. | Abstract
How valuable a choice option is often changes over time, making the prediction of value changes an important challenge for decision making. Prior studies identified a cognitive map in the hippocampal-entorhinal system that encodes relationships between states and enables prediction of future states, but does not inherently convey value during prospective decision making. In this fMRI study, participants predicted changing values of choice options in a sequence, forming | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
The value of long-duration energy storage under various grid conditions in a zero-emissions future | 10.1038/s41467-024-53274-6 | https://doi.org/10.1038/s41467-024-53274-6 | Nature Communications | 2,024 | Staadecker, M.; Szinai, J.; Sánchez-Pérez, P.; Kurtz, S.; Hidalgo-Gonzalez, P. | Abstract
Long-duration energy storage (LDES) is a key resource in enabling zero-emissions electricity grids but its role within different types of grids is not well understood. Using the Switch capacity expansion model, we model a zero-emissions Western Interconnect with high geographical resolution to understand the value of LDES under 39 scenarios with different generation mixes, transmission expansion, storage costs, and storage mandates. We find that a) | CrossRef | DigiEnergy | Renewable Energy Simulation Tools | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Electric vehicle battery chemistry affects supply chain disruption vulnerabilities | 10.1038/s41467-024-46418-1 | https://doi.org/10.1038/s41467-024-46418-1 | Nature Communications | 2,024 | Cheng, A.; Fuchs, E.; Karplus, V.; Michalek, J. | Abstract
We examine the relationship between electric vehicle battery chemistry and supply chain disruption vulnerability for four critical minerals: lithium, cobalt, nickel, and manganese. We compare the nickel manganese cobalt (NMC) and lithium iron phosphate (LFP) cathode chemistries by (1) mapping the supply chains for these four materials, (2) calculating a vulnerability index for each cathode chemistry for various focal countries and (3) using network flow optimization to bound u | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Optimization & Control | |
Offshore wind and wave energy can reduce total installed capacity required in zero-emissions grids | 10.1038/s41467-024-50040-6 | https://doi.org/10.1038/s41467-024-50040-6 | Nature Communications | 2,024 | Gonzalez, N.; Serna-Torre, P.; Sánchez-Pérez, P.; Davidson, R.; Murray, B. | Abstract
As the world races to decarbonize power systems to mitigate climate change, the body of research analyzing paths to zero emissions electricity grids has substantially grown. Although studies typically include commercially available technologies, few of them consider offshore wind and wave energy as contenders in future zero-emissions grids. Here, we model with high geographic resolution both offshore wind and wave energy as independent technologies with the possibility | CrossRef | DigiEnergy | Renewable Energy Resource Mapping | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Optimal blade pitch control for enhanced vertical-axis wind turbine performance | 10.1038/s41467-024-46988-0 | https://doi.org/10.1038/s41467-024-46988-0 | Nature Communications | 2,024 | Le Fouest, S.; Mulleners, K. | Abstract
Vertical-axis wind turbines are great candidates to enable wind power extraction in urban and off-shore applications. Currently, concerns around turbine efficiency and structural integrity limit their industrial deployment. Flow control can mitigate these concerns. Here, we experimentally demonstrate the potential of individual blade pitching as a control strategy and explain the flow physics that yields the performance enhancement. We perform automated experiments usi | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Effect of adaptive cruise control on fuel consumption in real-world driving conditions | 10.1038/s41467-024-54066-8 | https://doi.org/10.1038/s41467-024-54066-8 | Nature Communications | 2,024 | Moawad, A.; Zebiak, M.; Han, J.; Karbowski, D.; Zhang, Y. | Abstract
This paper presents a comprehensive analysis of the impact of adaptive cruise control on energy consumption in real-world driving conditions based on a natural experiment: a large-scale observational dataset of driving data from a diverse fleet of vehicles and drivers. The analysis is conducted at two different fidelity levels: (1) a macroscopic trip-level benefit estimate that compares trips with and without cruise control in a counterfactual way using statistical met | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
The role of electric grid research in addressing climate change | 10.1038/s41558-024-02092-1 | https://doi.org/10.1038/s41558-024-02092-1 | Nature Climate Change | 2,024 | Xie, L.; Majumder, S.; Huang, T.; Zhang, Q.; Chang, P. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
The role of advanced nuclear reactors and fuel cycles in a future energy system | 10.1093/pnasnexus/pgae030 | https://doi.org/10.1093/pnasnexus/pgae030 | npj Clean Energy | 2,024 | Kornecki, K.; Wise, C. | Abstract
Nuclear power has been an important part of the US electricity system since the 1950s and continues to be a major source of low-carbon electricity today. Despite having low emissions, high grid reliability, and an excellent track record of safety, nuclear power also demands significant time and upfront capital to deploy, can struggle to compete economically with other generation sources, has intrinsic proliferation risk by relying on fissile material for fuel, and generat | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Storm and tidal interactions control sediment exchange in mixed-energy coastal systems | 10.1093/pnasnexus/pgae042 | https://doi.org/10.1093/pnasnexus/pgae042 | npj Clean Energy | 2,024 | Georgiou, I.; FitzGerald, D.; Hanegan, K. | Abstract
Storms can have devasting effects on shorelines, causing flooding and the destruction of property and infrastructure. As global warming and the frequency and magnitude of tropical storms increase, barrier islands comprising 10% of the world's coast may undergo significant change caused by beach erosion, loss of dunes, and formation of washovers and tidal inlets. Understanding how storms affect sediment transport at tidal inlets is an understudied subject that directly inf | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | Optimization & Control | |
Effective data-driven collective variables for free energy calculations from metadynamics of paths | 10.1093/pnasnexus/pgae159 | https://doi.org/10.1093/pnasnexus/pgae159 | npj Clean Energy | 2,024 | Müllender, L.; Rizzi, A.; Parrinello, M.; Carloni, P.; Mandelli, D. | Abstract
A variety of enhanced sampling (ES) methods predict multidimensional free energy landscapes associated with biological and other molecular processes as a function of a few selected collective variables (CVs). The accuracy of these methods is crucially dependent on the ability of the chosen CVs to capture the relevant slow degrees of freedom of the system. For complex processes, finding such CVs is the real challenge. Machine learning (ML) CVs offer, in principle, a soluti | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | AI & Deep Learning | |
Microphase iron particle growth promoted by solar wind implantation in lunar soils | 10.1093/pnasnexus/pgae450 | https://doi.org/10.1093/pnasnexus/pgae450 | npj Clean Energy | 2,024 | Lu, X.; Chen, J.; Cao, H.; Fu, X.; Zeng, X. | Abstract
Lunar soils record the history and spectral changes resulting from the space-weathering process. The solar wind and micrometeoroids are the main space-weathering agents leading to darkening (decreasing albedo) and reddening (increasing reflectance with longer wavelength) of visible and near-infrared spectra. Nevertheless, their relative contributions are not well constrained and understood. In this study, we examine the near-infrared spectral variation as a function of lu | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Forecasting & Prediction | |
Food–energy–water nexus optimization brings substantial reduction of urban resource consumption and greenhouse gas emissions | 10.1093/pnasnexus/pgae028 | https://doi.org/10.1093/pnasnexus/pgae028 | npj Clean Energy | 2,024 | Zhang, P.; Zhang, L.; Hao, Y.; Xu, M.; Pang, M. | Abstract
Urban sustainability is a key to achieving the UN sustainable development goals (SDGs). Secure and efficient provision of food, energy, and water (FEW) resources is a critical strategy for urban sustainability. While there has been extensive discussion on the positive effects of the FEW nexus on resource efficiency and climate impacts, measuring the extent to which such synergy can benefit urban sustainability remains challenging. Here, we have developed a systematic and | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Prioritizing social vulnerability in urban heat mitigation | 10.1093/pnasnexus/pgae360 | https://doi.org/10.1093/pnasnexus/pgae360 | npj Clean Energy | 2,024 | Fung, K.; Yang, Z.; Martilli, A.; Krayenhoff, E.; Niyogi, D. | Abstract
We utilized city-scale simulations to quantitatively compare the diverse urban overheating mitigation strategies, specifically tied to social vulnerability and their cooling efficacies during heatwaves. We enhanced the Weather Research and Forecasting model to encompass the urban tree effect and calculate the Universal Thermal Climate Index for assessing thermal comfort. Taking Houston, Texas, and United States as an example, the study reveals that equitably mitigating ur | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Forecasting & Prediction | |
Robust capital cost optimization of generation and multitimescale storage requirements for a 100% renewable Australian electricity grid | 10.1093/pnasnexus/pgae127 | https://doi.org/10.1093/pnasnexus/pgae127 | npj Clean Energy | 2,024 | Shaikh, R.; Vowles, D.; Dinovitser, A.; Allison, A.; Abbott, D. | Abstract
Transitioning from a fossil-fuel-dependent economy to one based on renewable energy requires significant investment and technological advancement. While wind and solar technologies provide lower cost electricity, enhanced energy storage and transmission infrastructure come at a cost for managing renewable intermittency. Energy storage systems vary in characteristics and costs, and future grids will incorporate multiple technologies, yet the optimal combination of storage | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Cocaine diminishes functional network robustness and destabilizes the energy landscape of neuronal activity in the medial prefrontal cortex | 10.1093/pnasnexus/pgae092 | https://doi.org/10.1093/pnasnexus/pgae092 | npj Clean Energy | 2,024 | Borzou, A.; Miller, S.; Hommel, J.; Schwarz, J. | Abstract
We present analysis of neuronal activity recordings from a subset of neurons in the medial prefrontal cortex of rats before and after the administration of cocaine. Using an underlying modern Hopfield model as a description for the neuronal network, combined with a machine learning approach, we compute the underlying functional connectivity of the neuronal network. We find that the functional connectivity changes after the administration of cocaine with both functional-ex | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | AI & Deep Learning | |
A biospecies-derived genomic DNA hybrid gel electrolyte for electrochemical energy storage | 10.1093/pnasnexus/pgae213 | https://doi.org/10.1093/pnasnexus/pgae213 | npj Clean Energy | 2,024 | Mitta, S.; Kim, J.; Rana, H.; Kokkiligadda, S.; Lim, Y. | Abstract
Intrinsic impediments, namely weak mechanical strength, low ionic conductivity, low electrochemical performance, and stability have largely inhibited beyond practical applications of hydrogels in electronic devices and remains as a significant challenge in the scientific world. Here, we report a biospecies-derived genomic DNA hybrid gel electrolyte with many synergistic effects, including robust mechanical properties (mechanical strength and elongation of 6.98 MPa and 997 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
China's progress in synergetic governance of climate change and multiple environmental issues | 10.1093/pnasnexus/pgae351 | https://doi.org/10.1093/pnasnexus/pgae351 | npj Clean Energy | 2,024 | Yang, J.; Zhao, Z.; Fang, W.; Ma, Z.; Liu, M. | Abstract
Advancing the synergetic control of climate change and environmental crisis is crucial for achieving global sustainable development goals. This study evaluates synergetic governance levels over climate change and four environmental issues at the provincial level in China from 2009 to 2020. Our findings reveal significant progress in China's coordinated efforts to mitigate carbon emissions, reduce air pollutants, and conserve water resources. However, there remains room fo | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Catch the wind: Optimizing wind turbine power generation by addressing wind veer effects | 10.1093/pnasnexus/pgae480 | https://doi.org/10.1093/pnasnexus/pgae480 | npj Clean Energy | 2,024 | Gao, L.; Milliren, C.; Dasari, T.; Knoll, A.; Hong, J. | Abstract
Wind direction variability with height, known as “wind veer,” results in power losses for wind turbines (WTs) that rely on single-point wind measurements at the turbine nacelles. To address this challenge, we introduce a yaw control strategy designed to optimize turbine alignment by adjusting the yaw angle based on specific wind veer conditions, thereby boosting power generation efficiency. This strategy integrates modest yaw offset angles into the existing turbine contro | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Deciphering the variability in air-sea gas transfer due to sea state and wind history | 10.1093/pnasnexus/pgae389 | https://doi.org/10.1093/pnasnexus/pgae389 | npj Clean Energy | 2,024 | Yang, M.; Moffat, D.; Dong, Y.; Bidlot, J. | Abstract
Understanding processes driving air-sea gas transfer and being able to model both its mean and variability are critical for studies of climate and carbon cycle. The air-sea gas transfer velocity (K660) is almost universally parameterized as a function of wind speed in large scale models—an oversimplification that buries the mechanisms controlling K660 and neglects much natural variability. Sea state has long been speculated to affect gas transfer, but consistent relations | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Enhancing molecular oxygen activation by nitrogen-doped carbon encapsulating FeNi alloys with ultra-low Pt loading | 10.1093/pnasnexus/pgae594 | https://doi.org/10.1093/pnasnexus/pgae594 | npj Clean Energy | 2,024 | Zhu, D.; Huang, Y.; Shi, X.; Li, R.; Wang, Z. | Abstract
Modulating the electronic structure of noble metals via electronic metal–support interaction (EMSI) has been proven effectively for facilitating molecular oxygen activation and catalytic oxidation reactions. Nevertheless, the investigation of the fundamental mechanisms underlying activity enhancement has primarily focused on metal oxides as supports, especially in the catalytic degradation of volatile organic compounds. In this study, a novel Pt catalyst supported on nitr | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
An integrated experimental–modeling approach to identify key processes for carbon mineralization in fractured mafic and ultramafic rocks | 10.1093/pnasnexus/pgae388 | https://doi.org/10.1093/pnasnexus/pgae388 | npj Clean Energy | 2,024 | Neil, C.; Yang, Y.; Nisbet, H.; Iyare, U.; Boampong, L. | Abstract
Controlling atmospheric warming requires immediate reduction of carbon dioxide (CO2) emissions, as well as the active removal and sequestration of CO2 from current point sources. One promising proposed strategy to reduce atmospheric CO2 levels is geologic carbon sequestration (GCS), where CO2 is injected into the subsurface and reacts with the formation to precipitate carbonate minerals. Rapid mineralization has recently been reported for field tests in mafic and ultramaf | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Optimising the manufacturing of a β-Ti alloy produced via direct energy deposition using small dataset machine learning | 10.1038/s41598-024-57498-w | https://doi.org/10.1038/s41598-024-57498-w | Scientific Reports | 2,024 | Brooke, R.; Qiu, D.; Le, T.; Gibson, M.; Zhang, D. | 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 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | AI & Deep Learning | |
Leveraging opposition-based learning for solar photovoltaic model parameter estimation with exponential distribution optimization algorithm | 10.1038/s41598-023-50890-y | https://doi.org/10.1038/s41598-023-50890-y | Scientific Reports | 2,024 | Kullampalayam Murugaiyan, N.; Chandrasekaran, K.; Manoharan, P.; Derebew, B. | 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 | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | |
MPPT control of photovoltaic array based on improved marine predator algorithm under complex solar irradiance conditions | 10.1038/s41598-024-70811-x | https://doi.org/10.1038/s41598-024-70811-x | Scientific Reports | 2,024 | Zhang, H.; Wang, X.; Zhang, J.; Ge, Y.; Wang, L. | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | ||
Enhanced Whale optimization algorithms for parameter identification of solar photovoltaic cell models: a comparative study | 10.1038/s41598-024-67600-x | https://doi.org/10.1038/s41598-024-67600-x | Scientific Reports | 2,024 | Yang, S.; Xiong, G.; Fu, X.; Mirjalili, S.; Mohamed, A. | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | ||
An improved transient search optimization algorithm for building energy optimization and hybrid energy sizing applications | 10.1038/s41598-024-68239-4 | https://doi.org/10.1038/s41598-024-68239-4 | Scientific Reports | 2,024 | Jearsiripongkul, T.; Karbasforoushha, M.; Khajehzadeh, M.; Keawsawasvong, S.; Thongchom, C. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Optimization of building integrated energy scheduling using an improved genetic whale algorithm | 10.1038/s41598-024-52995-4 | https://doi.org/10.1038/s41598-024-52995-4 | Scientific Reports | 2,024 | Wei, L.; An, G. | 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, | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Comparative analysis of direct coupling and MPPT control in standalone PV systems for solar energy optimization to meet sustainable building energy demands | 10.1038/s41598-024-72606-6 | https://doi.org/10.1038/s41598-024-72606-6 | Scientific Reports | 2,024 | Nataraj, C.; Karthikeyan, G.; Bharathi, G.; Duraikannan, S. | 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 | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Forecasting & Prediction | |
Multiple objective energy optimization of a trade center building based on genetic algorithm using ecological materials | 10.1038/s41598-024-58515-8 | https://doi.org/10.1038/s41598-024-58515-8 | Scientific Reports | 2,024 | Kabiri, E.; Maftouni, N. | 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 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Active learning-based machine learning approach for enhancing environmental sustainability in green building energy consumption | 10.1038/s41598-024-70729-4 | https://doi.org/10.1038/s41598-024-70729-4 | Scientific Reports | 2,024 | Mahmood, S.; Sun, H.; Ali Alhussan, A.; Iqbal, A.; El-kenawy, E. | 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 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Demand Response & New Mobilities & Urban Planning | AI & Deep Learning | |
Developing the hybrid BIM-BEM and jellyfish search optimization system for optimizing energy consumption and building installation costs | 10.1038/s41598-024-68021-6 | https://doi.org/10.1038/s41598-024-68021-6 | Scientific Reports | 2,024 | Luong, D.; Truong, N.; Ngo, N.; Nguyen, N. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Urban Water-Energy consumption Prediction Influenced by Climate Change utilizing an innovative deep learning method | 10.1038/s41598-024-81836-7 | https://doi.org/10.1038/s41598-024-81836-7 | Scientific Reports | 2,024 | Wang, D.; Zhang, Y.; Yousefi, N. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | ||
Robust load-frequency control of islanded urban microgrid using 1PD-3DOF-PID controller including mobile EV energy storage | 10.1038/s41598-024-64794-y | https://doi.org/10.1038/s41598-024-64794-y | Scientific Reports | 2,024 | Davoudkhani, I.; Zare, P.; Abdelaziz, A.; Bajaj, M.; Tuka, M. | 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 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | Forecasting & Prediction | |
Research on coupling optimization of carbon emissions and carbon leakage in international construction projects | 10.1038/s41598-024-59531-4 | https://doi.org/10.1038/s41598-024-59531-4 | Scientific Reports | 2,024 | Zhou, Z.; Wang, Y.; Alcalá, J.; Yepes, V. | 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 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
A rule-based energy management system for hybrid renewable energy sources with battery bank optimized by genetic algorithm optimization | 10.1038/s41598-024-54333-0 | https://doi.org/10.1038/s41598-024-54333-0 | Scientific Reports | 2,024 | Jamal, S.; Pasupuleti, J.; Ekanayake, J. | 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 | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Forecasting & Prediction | |
A novel advanced hybrid fuzzy MPPT controllers for renewable energy systems | 10.1038/s41598-024-72060-4 | https://doi.org/10.1038/s41598-024-72060-4 | Scientific Reports | 2,024 | Rafi Kiran, S.; Alsaif, F. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Forecasting for electricity demand utilizing enhanced inception-V4 using improved Osprey optimization | 10.1038/s41598-024-81487-8 | https://doi.org/10.1038/s41598-024-81487-8 | Scientific Reports | 2,024 | Chen, S.; Fang, X.; Khayatnezhad, M. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | ||
Optimization clearing strategy for multi-region electricity-heat market considering shared energy storage and integrated demand response | 10.1038/s41598-024-72397-w | https://doi.org/10.1038/s41598-024-72397-w | Scientific Reports | 2,024 | Chen, S.; Ye, Z.; Meng, Y. | CrossRef | FLEXERGY | Demand Response | Demand Response & New Mobilities & Urban Planning | Optimization & Control | ||
Deep learning-based forecasting of electricity consumption | 10.1038/s41598-024-56602-4 | https://doi.org/10.1038/s41598-024-56602-4 | Scientific Reports | 2,024 | Qureshi, M.; Arbab, M.; Rehman, S. | 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 | CrossRef | FLEXERGY | Smart Home & EMS | Demand Response & New Mobilities & Urban Planning | Forecasting & Prediction | |
Estimating the energy consumption for residential buildings in semiarid and arid desert climate using artificial intelligence | 10.1038/s41598-024-63843-w | https://doi.org/10.1038/s41598-024-63843-w | Scientific Reports | 2,024 | Wefki, H.; Khallaf, R.; Ebid, A. | 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, | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | AI & Deep Learning | |
Deep learning-driven hybrid model for short-term load forecasting and smart grid information management | 10.1038/s41598-024-63262-x | https://doi.org/10.1038/s41598-024-63262-x | Scientific Reports | 2,024 | Wen, X.; Liao, J.; Niu, Q.; Shen, N.; Bao, Y. | 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 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
Construction of power network security risk assessment model based on LSA-SVM algorithm in the background of smart grid | 10.1038/s41598-024-59473-x | https://doi.org/10.1038/s41598-024-59473-x | Scientific Reports | 2,024 | Qi, H.; Zhu, W.; Ye, M.; Hu, Y.; Wang, Y. | 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 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Machine learning optimization for hybrid electric vehicle charging in renewable microgrids | 10.1038/s41598-024-63775-5 | https://doi.org/10.1038/s41598-024-63775-5 | Scientific Reports | 2,024 | Hassan, M. | 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 | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Electric vehicle path optimization research based on charging and switching methods under V2G | 10.1038/s41598-024-81449-0 | https://doi.org/10.1038/s41598-024-81449-0 | Scientific Reports | 2,024 | Liu, H.; Zhang, A. | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Optimization & Control | ||
Managing grid impacts from increased electric vehicle adoption in African cities | 10.1038/s41598-024-75039-3 | https://doi.org/10.1038/s41598-024-75039-3 | Scientific Reports | 2,024 | Lukuyu, J.; Shirley, R.; Taneja, J. | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Optimization & Control | ||
Power consumption prediction for electric vehicle charging stations and forecasting income | 10.1038/s41598-024-56507-2 | https://doi.org/10.1038/s41598-024-56507-2 | Scientific Reports | 2,024 | Akshay, K.; Grace, G.; Gunasekaran, K.; Samikannu, R. | 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 | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Forecasting & Prediction | |
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 | 10.1038/s41598-024-55271-7 | https://doi.org/10.1038/s41598-024-55271-7 | Scientific Reports | 2,024 | Benbouhenni, H.; Yessef, M.; Colak, I.; Bizon, N.; Kotb, H. | 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 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Continuous input current buck DC/DC converter for small-size wind energy systems featuring current sensorless MPPT control | 10.1038/s41598-023-50692-2 | https://doi.org/10.1038/s41598-023-50692-2 | Scientific Reports | 2,024 | Zakzouk, N. | 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 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Effective dynamic energy management algorithm for grid-interactive microgrid with hybrid energy storage system | 10.1038/s41598-024-70599-w | https://doi.org/10.1038/s41598-024-70599-w | Scientific Reports | 2,024 | Kamagaté, Y.; Shah, H. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | Optimization & Control | ||
Optimal scheduling model using the IGDT method for park integrated energy systems considering P2G–CCS and cloud energy storage | 10.1038/s41598-024-68292-z | https://doi.org/10.1038/s41598-024-68292-z | Scientific Reports | 2,024 | Wang, L.; Cheng, J.; Luo, X. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Digital finance reduces urban carbon footprint pressure in 277 Chinese cities | 10.1038/s41598-024-67315-z | https://doi.org/10.1038/s41598-024-67315-z | Scientific Reports | 2,024 | Dong, Z.; Yao, S. | 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 | CrossRef | EnergiTrade | Urban Carbon Footprint | Carbon Trading & New Business Models | Forecasting & Prediction | |
Short-term multi-energy consumption forecasting for integrated energy system based on interactive multi-scale convolutional module | 10.1038/s41598-024-72103-w | https://doi.org/10.1038/s41598-024-72103-w | Scientific Reports | 2,024 | Liu, F.; Huang, Y.; Wang, Y.; Xia, E.; Qureshi, H. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | ||
Blockchain-based energy consumption approaches in IoT | 10.1038/s41598-024-77792-x | https://doi.org/10.1038/s41598-024-77792-x | Scientific Reports | 2,024 | Habibullah, S.; Alam, S.; Ghosh, S.; Dey, A.; De, A. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Demand Response & IoT | ||
Optimization scheduling of microgrid comprehensive demand response load considering user satisfaction | 10.1038/s41598-024-66492-1 | https://doi.org/10.1038/s41598-024-66492-1 | Scientific Reports | 2,024 | Wang, C.; Li, X. | AbstractThe original load control model of microgrid based on demand response lacks the factors of incentive demand response, the overall satisfaction of users is low, the degree of demand response is low, the Time Of Use (TOU) price of peak-valley filling capacity is weak, and the peak-valley difference of load curve is large. Regarding the limitations of the current microgrid demand response model, this study further optimizes the flexible load control strategy and proposes a two-objective opt | CrossRef | FLEXERGY | Demand Response | Demand Response & New Mobilities & Urban Planning | Forecasting & Prediction | |
A Multi-Layer Techno-Economic-Environmental Energy Management Optimization in Cooperative Multi-Microgrids with Demand Response Program and Uncertainties Consideration | 10.1038/s41598-024-72706-3 | https://doi.org/10.1038/s41598-024-72706-3 | Scientific Reports | 2,024 | Alamir, N.; Kamel, S.; Megahed, T.; Hori, M.; Abdelkader, S. | AbstractThis paper presents a multi-layer, multi-objective (MLMO) optimization model for techno-economic-environmental energy management in cooperative multi-Microgrids (MMGs) that incorporates a Demand Response Program (DRP). The proposed MLMO approach simultaneously optimizes operating costs, MMG operator benefits, environmental emissions, and MMG dependency. This paper proposed a new hybrid ε-lexicography–weighted-sum that eliminates the need to normalize or scalarize objectives. The first la | CrossRef | FLEXERGY | Demand Response | Demand Response & New Mobilities & Urban Planning | Optimization & Control | |
Optimizing demand response and load balancing in smart EV charging networks using AI integrated blockchain framework | 10.1038/s41598-024-82257-2 | https://doi.org/10.1038/s41598-024-82257-2 | Scientific Reports | 2,024 | Singh, A.; Kumar, R.; Madhavi, K.; Alsaif, F.; Bajaj, M. | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Forecasting & Prediction | ||
The evolving long tail at the edge of the grid: Benefits and concerns | 10.1016/j.joule.2024.04.005 | https://doi.org/10.1016/j.joule.2024.04.005 | Joule | 2,024 | Parag, Y.; Zemah-Shamir, S.; Shaviv, E.; Teschner, N. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Foundation models for the electric power grid | 10.1016/j.joule.2024.11.002 | https://doi.org/10.1016/j.joule.2024.11.002 | Joule | 2,024 | Hamann, H.; Gjorgiev, B.; Brunschwiler, T.; Martins, L.; Puech, A. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
An empirical agent-based model of consumer co-adoption of low-carbon technologies to inform energy policy | 10.1016/j.crsus.2024.100268 | https://doi.org/10.1016/j.crsus.2024.100268 | Cell Reports Sustainability | 2,024 | van der Kam, M.; Lagomarsino, M.; Azar, E.; Hahnel, U.; Parra, D. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Demand Response & IoT | ||
Seasonal hydrogen energy storage sizing: Two-stage economic-safety optimization for integrated energy systems in northwest China | 10.1016/j.isci.2024.110691 | https://doi.org/10.1016/j.isci.2024.110691 | iScience | 2,024 | Li, L.; Sun, Y.; Han, Y.; Chen, W. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Many-objective bi-level energy scheduling method for integrated energy stations based on power allocation strategy | 10.1016/j.isci.2024.109305 | https://doi.org/10.1016/j.isci.2024.109305 | iScience | 2,024 | Liao, X.; Ma, J.; Yin, B.; Qian, B.; Lei, R. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
On the optimization of the interconnection of photovoltaic modules integrated in vehicles | 10.1016/j.isci.2024.110089 | https://doi.org/10.1016/j.isci.2024.110089 | iScience | 2,024 | Macías, J.; Herrero, R.; San José, L.; Núñez, R.; Antón, I. | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | ||
Batteries or hydrogen or both for grid electricity storage upon full electrification of 145 countries with wind-water-solar? | 10.1016/j.isci.2024.108988 | https://doi.org/10.1016/j.isci.2024.108988 | iScience | 2,024 | Jacobson, M. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Optimization & Control | ||
Optimal scheduling of electricity and hydrogen integrated energy system considering multiple uncertainties | 10.1016/j.isci.2024.109654 | https://doi.org/10.1016/j.isci.2024.109654 | iScience | 2,024 | Chang, P.; Li, C.; Zhu, Q.; Zhu, T.; Shi, J. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
The carbon footprint of predicting CO2 storage capacity in metal-organic frameworks within neural networks | 10.1016/j.isci.2024.109644 | https://doi.org/10.1016/j.isci.2024.109644 | iScience | 2,024 | Korolev, V.; Mitrofanov, A. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | AI & Deep Learning | ||
Enhancing the European power system resilience with a recommendation system for voluntary demand response | 10.1016/j.isci.2024.111430 | https://doi.org/10.1016/j.isci.2024.111430 | iScience | 2,024 | Silva, C.; Bessa, R.; Andrade, J.; Coelho, F.; Costa, R. | CrossRef | FLEXERGY | Demand Response | Demand Response & New Mobilities & Urban Planning | Demand Response & IoT | ||
PM
<sub>2.5</sub>
exposure disparities persist despite strict vehicle emissions controls in California | 10.1126/sciadv.adn8544 | https://doi.org/10.1126/sciadv.adn8544 | Science Advances | 2,024 | Koolik, L.; Alvarado, Á.; Budahn, A.; Plummer, L.; Marshall, J. |
As policymakers increasingly focus on environmental justice, a key question is whether emissions reductions aimed at addressing air quality or climate change can also ameliorate persistent air pollution exposure disparities. We examine evidence from California’s aggressive vehicle emissions control policy from 2000 to 2019. We find a 65% reduction in modeled statewide average exposure to PM
2.5
from on-road vehicles, yet for people of | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Physics-guided deep learning for skillful wind-wave modeling | 10.1126/sciadv.adr3559 | https://doi.org/10.1126/sciadv.adr3559 | Science Advances | 2,024 | Wang, X.; Jiang, H. | Modeling sea surface wind-waves is crucial for both scientific research and engineering applications. Nowadays, the most accurate wave models are based on numerical methods, which primarily concern the wave spectrum evolution by solving wave action balance partial differential equations. These methods are computationally expensive and limited by incomplete physical representations of wave spectral evolution. Here, we present a deep learning–based wave model trained using observation-merged wave | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | AI & Deep Learning | |
Nonsynchronous rotation of icy moon ice shells: The thermal wind perspective | 10.1126/sciadv.adk2277 | https://doi.org/10.1126/sciadv.adk2277 | Science Advances | 2,024 | Kang, W. | The ice shells of icy satellites have been hypothesized to undergo nonsynchronous rotation (NSR) under the influence of tidal torques and/or ocean currents. In this work, the author proposes that the thermal wind relationship can be combined with geostrophic turbulence theory to predict ocean stress onto the ice shell inside the tangent cylinder. High-resolution numerical simulations validate the prediction within a factor of 2. For the prediction to be valid, the rotation effect must dominate ( | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
CO
<sub>2</sub>
capture, geological storage, and mineralization using biobased biodegradable chelating agents and seawater | 10.1126/sciadv.adq0515 | https://doi.org/10.1126/sciadv.adq0515 | Science Advances | 2,024 | Wang, J.; Sekiai, R.; Tamura, R.; Watanabe, N. |
Geological storage and mineralization of CO
2
in mafic/ultramafic reservoirs faces challenges including limited effective porosity, permeability, and rock reactivity; difficulties in using seawater for CO
2
capture; and uncontrolled carbonation. This study introduces a CO
2
capture, storage, and mineralization approach with the utilization of biobased biodegradable chelating agents and seawater. An acidic chelat | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Olivine alteration and the loss of Mars’ early atmospheric carbon | 10.1126/sciadv.adm8443 | https://doi.org/10.1126/sciadv.adm8443 | Science Advances | 2,024 | Murray, J.; Jagoutz, O. |
The early Martian atmosphere had 0.25 to 4 bar of CO
2
but thinned rapidly around 3.5 billion years ago. The fate of that carbon remains poorly constrained. The hydrothermal alteration of ultramafic rocks, rich in Fe(II) and Mg, forms both abiotic methane, serpentine, and high-surface-area smectite clays. Given the abundance of ultramafic rocks and smectite in the Martian upper crust and the growing evidence of organic carbon in Martian sedimentary rocks, we | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Demand Response & IoT | |
A crowdsourced dataset of aerial images with annotated solar photovoltaic arrays and installation metadata | 10.1038/s41597-023-01951-4 | https://doi.org/10.1038/s41597-023-01951-4 | Scientific Data | 2,023 | Kasmi, G.; Saint-Drenan, Y.; Trebosc, D.; Jolivet, R.; Leloux, J. | AbstractPhotovoltaic (PV) energy generation plays a crucial role in the energy transition. Small-scale, rooftop PV installations are deployed at an unprecedented pace, and their safe integration into the grid requires up-to-date, high-quality information. Overhead imagery is increasingly being used to improve the knowledge of rooftop PV installations with machine learning models capable of automatically mapping these installations. However, these models cannot be reliably transferred from one re | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Solar active region magnetogram image dataset for studies of space weather | 10.1038/s41597-023-02628-8 | https://doi.org/10.1038/s41597-023-02628-8 | Scientific Data | 2,023 | Boucheron, L.; Vincent, T.; Grajeda, J.; Wuest, E. | AbstractIn this dataset we provide a comprehensive collection of line-of-sight (LOS) solar photospheric magnetograms (images quantifying the strength of the photospheric magnetic field) from the National Aeronautics and Space Administration’s (NASA’s) Solar Dynamics Observatory (SDO). The dataset incorporates data from three sources and provides SDO Helioseismic and Magnetic Imager (HMI) magnetograms of solar active regions (regions of large magnetic flux, generally the source of eruptive events | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Forecasting & Prediction | |
A benchmark dataset for binary segmentation and quantification of dust emissions from unsealed roads | 10.1038/s41597-022-01918-x | https://doi.org/10.1038/s41597-022-01918-x | Scientific Data | 2,023 | De Silva, A.; Ranasinghe, R.; Sounthararajah, A.; Haghighi, H.; Kodikara, J. | AbstractThe generation of reference data for machine learning models is challenging for dust emissions due to perpetually dynamic environmental conditions. We generated a new vision dataset with the goal of advancing semantic segmentation to identify and quantify vehicle-induced dust clouds from images. We conducted field experiments on 10 unsealed road segments with different types of road surface materials in varying climatic conditions to capture vehicle-induced road dust. A direct single-len | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | AI & Deep Learning | |
A Dataset for Electricity Market Studies on Western and Northeastern Power Grids in the United States | 10.1038/s41597-023-02448-w | https://doi.org/10.1038/s41597-023-02448-w | Scientific Data | 2,023 | Zhang, Q.; Li, F. | AbstractEfficient electricity market operations and cost-effective electricity generations are fundamental to a low-carbon energy future. The Western Electricity Coordinating Council (WECC) and Northeast Power Coordinating Council (NPCC) systems were built to provide efficient electrical grid simulation solutions for their respective U.S. regions. Data reuse for electricity economic studies remains a challenge due to the lack of credible and realistic economic data. This paper delivers a compreh | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | Optimization & Control | |
A synthetic dataset of Danish residential electricity prosumers | 10.1038/s41597-023-02271-3 | https://doi.org/10.1038/s41597-023-02271-3 | Scientific Data | 2,023 | Yuan, R.; Pourmousavi, S.; Soong, W.; Black, A.; Liisberg, J. | AbstractConventional residential electricity consumers are becoming prosumers who not only consume electricity but also produce it. This shift is expected to occur over the next few decades at a large scale, and it presents numerous uncertainties and risks for the operation, planning, investment, and viable business models of the electricity grid. To prepare for this shift, researchers, utilities, policymakers, and emerging businesses require a comprehensive understanding of future prosumers’ el | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
A 21-year dataset (2000–2020) of gap-free global daily surface soil moisture at 1-km grid resolution | 10.1038/s41597-023-01991-w | https://doi.org/10.1038/s41597-023-01991-w | Scientific Data | 2,023 | Zheng, C.; Jia, L.; Zhao, T. | AbstractGlobal soil moisture estimates from current satellite missions are suffering from inherent discontinuous observations and coarse spatial resolution, which limit applications especially at the fine spatial scale. This study developed a dataset of global gap-free surface soil moisture (SSM) at daily 1-km resolution from 2000 to 2020. This is achieved based on the European Space Agency - Climate Change Initiative (ESA-CCI) SSM combined product at 0.25° resolution. Firstly, an operational ga | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Positron emission tomography dataset of [11C]carbon dioxide storage in coal for geo-sequestration application | 10.1038/s41597-023-02754-3 | https://doi.org/10.1038/s41597-023-02754-3 | Scientific Data | 2,023 | Jing, Y.; Kumaran, A.; Stimson, D.; Mardon, K.; Najdovski, L. | AbstractPositron Emission Tomography (PET) imaging has demonstrated its capability in providing time-lapse fluid flow visualisation for improving the understanding of flow properties of geologic media. To investigate the process of CO2 geo-sequestration using PET imaging technology, [11C]CO2 is the most optimal and direct radiotracer. However, it has not been extensively used due to the short half-life of Carbon-11 (20.4 minutes). In this work, a novel laboratory protocol is developed to use [11 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Demand Response & IoT | |
Taking control of energy as a solar prosumer | 10.1038/s41560-022-01174-8 | https://doi.org/10.1038/s41560-022-01174-8 | Nature Energy | 2,023 | Middlemiss, L. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Optimization & Control | ||
Emissions savings from equitable energy demand reduction | 10.1038/s41560-023-01283-y | https://doi.org/10.1038/s41560-023-01283-y | Nature Energy | 2,023 | Büchs, M.; Cass, N.; Mullen, C.; Lucas, K.; Ivanova, D. | AbstractEnergy demand reduction (EDR) will be required to reach climate targets in the Global North. To be compatible with just transitions principles, EDR needs to be equitable. Equitable EDR may involve targeting high energy users while ensuring the satisfaction of needs for all, which could require increasing consumption of low users. Emissions impacts of equitable EDR approaches have not yet been assessed. This Article finds that capping energy use of the top quintile of consumers across 27 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | Demand Response & IoT | |
A global model of hourly space heating and cooling demand at multiple spatial scales | 10.1038/s41560-023-01341-5 | https://doi.org/10.1038/s41560-023-01341-5 | Nature Energy | 2,023 | Staffell, I.; Pfenninger, S.; Johnson, N. | Abstract
Accurate modelling of the weather’s temporal and spatial impacts on building energy demand is critical to decarbonizing energy systems. Here we introduce a customizable model for hourly heating and cooling demand applicable globally at all spatial scales. We validate against demand from ~5,000 buildings and 43 regions across four continents. The model requires limited data inputs and shows better agreement with measured demand than existing models. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
Rail-based mobile energy storage as a grid-reliability solution for climate extremes | 10.1038/s41560-023-01284-x | https://doi.org/10.1038/s41560-023-01284-x | Nature Energy | 2,023 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |||
Leveraging rail-based mobile energy storage to increase grid reliability in the face of climate uncertainty | 10.1038/s41560-023-01276-x | https://doi.org/10.1038/s41560-023-01276-x | Nature Energy | 2,023 | Moraski, J.; Popovich, N.; Phadke, A. | Abstract
Maintaining reliability is increasingly challenging for electric grids as they endure more frequent extreme weather events and utilize more intermittent generation. Exploration of alternative reliability approaches is needed to effectively address these emerging issues. Here we examine the potential to use the US rail system as a nationwide backup transmission grid over which containerized batteries, or rail-based mobile energy storage (RMES), are shared among regions | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
International relations theory on grid communities and international politics in a green world | 10.1038/s41560-023-01363-z | https://doi.org/10.1038/s41560-023-01363-z | Nature Energy | 2,023 | Smith Stegen, K. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Local and utility-wide cost allocations for a more equitable wildfire-resilient distribution grid | 10.1038/s41560-023-01306-8 | https://doi.org/10.1038/s41560-023-01306-8 | Nature Energy | 2,023 | Wang, Z.; Wara, M.; Majumdar, A.; Rajagopal, R. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
A phenazine-based high-capacity and high-stability electrochemical CO2 capture cell with coupled electricity storage | 10.1038/s41560-023-01347-z | https://doi.org/10.1038/s41560-023-01347-z | Nature Energy | 2,023 | Pang, S.; Jin, S.; Yang, F.; Alberts, M.; Li, L. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Stability follows efficiency based on the analysis of a large perovskite solar cells ageing dataset | 10.1038/s41467-023-40585-3 | https://doi.org/10.1038/s41467-023-40585-3 | Nature Communications | 2,023 | Hartono, N.; Köbler, H.; Graniero, P.; Khenkin, M.; Schlatmann, R. | AbstractWhile perovskite solar cells have reached competitive efficiency values during the last decade, stability issues remain a critical challenge to be addressed for pushing this technology towards commercialisation. In this study, we analyse a large homogeneous dataset of Maximum Power Point Tracking (MPPT) operational ageing data that we collected with a custom-built High-throughput Ageing System in the past 3 years. In total, 2,245 MPPT ageing curves are analysed which were obtained under | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Creating complex protocells and prototissues using simple DNA building blocks | 10.1038/s41467-023-36875-5 | https://doi.org/10.1038/s41467-023-36875-5 | Nature Communications | 2,023 | Arulkumaran, N.; Singer, M.; Howorka, S.; Burns, J. | AbstractBuilding synthetic protocells and prototissues hinges on the formation of biomimetic skeletal frameworks. Recreating the complexity of cytoskeletal and exoskeletal fibers, with their widely varying dimensions, cellular locations and functions, represents a major material hurdle and intellectual challenge which is compounded by the additional demand of using simple building blocks to ease fabrication and control. Here we harness simplicity to create complexity by assembling structural fra | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Global green hydrogen-based steel opportunities surrounding high quality renewable energy and iron ore deposits | 10.1038/s41467-023-38123-2 | https://doi.org/10.1038/s41467-023-38123-2 | Nature Communications | 2,023 | Devlin, A.; Kossen, J.; Goldie-Jones, H.; Yang, A. | AbstractThe steel sector currently accounts for 7% of global energy-related CO2 emissions and requires deep reform to disconnect from fossil fuels. Here, we investigate the market competitiveness of one of the widely considered decarbonisation routes for primary steel production: green hydrogen-based direct reduction of iron ore followed by electric arc furnace steelmaking. Through analysing over 300 locations by combined use of optimisation and machine learning, we show that competitive renewab | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | AI & Deep Learning | |
The asymmetric effects of climate risk on higher-moment connectedness among carbon, energy and metals markets | 10.1038/s41467-023-42925-9 | https://doi.org/10.1038/s41467-023-42925-9 | Nature Communications | 2,023 | Zhou, Y.; Wu, S.; Liu, Z.; Rognone, L. | AbstractClimate change affects price fluctuations in the carbon, energy and metals markets through physical and transition risks. Climate physical risk is mainly caused by extreme weather, natural disasters and other events caused by climate change, whereas climate transition risk mainly results from the gradual switchover to a low-carbon economy. Given that the connectedness between financial markets may be affected by various factors such as extreme events and economic transformation, understa | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | Forecasting & Prediction | |
Geospatial mapping of distribution grid with machine learning and publicly-accessible multi-modal data | 10.1038/s41467-023-39647-3 | https://doi.org/10.1038/s41467-023-39647-3 | Nature Communications | 2,023 | Wang, Z.; Majumdar, A.; Rajagopal, R. | AbstractDetailed and location-aware distribution grid information is a prerequisite for various power system applications such as renewable energy integration, wildfire risk assessment, and infrastructure planning. However, a generalizable and scalable approach to obtain such information is still lacking. In this work, we develop a machine-learning-based framework to map both overhead and underground distribution grids using widely-available multi-modal data including street view images, road ne | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Mental search of concepts is supported by egocentric vector representations and restructured grid maps | 10.1038/s41467-023-43831-w | https://doi.org/10.1038/s41467-023-43831-w | Nature Communications | 2,023 | Viganò, S.; Bayramova, R.; Doeller, C.; Bottini, R. | Abstract
The human hippocampal-entorhinal system is known to represent both spatial locations and abstract concepts in memory in the form of allocentric cognitive maps. Using fMRI, we show that the human parietal cortex evokes complementary egocentric representations in conceptual spaces during goal-directed mental search, akin to those observable during physical navigation to determine where a goal is located relative to oneself (e.g., to our left or to our right). Concurrentl | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Grid integration feasibility and investment planning of offshore wind power under carbon-neutral transition in China | 10.1038/s41467-023-37536-3 | https://doi.org/10.1038/s41467-023-37536-3 | Nature Communications | 2,023 | Guo, X.; Chen, X.; Chen, X.; Sherman, P.; Wen, J. | AbstractOffshore wind power, with accelerated declining levelized costs, is emerging as a critical building-block to fully decarbonize the world’s largest CO2 emitter, China. However, system integration barriers as well as system balancing costs have not been quantified yet. Here we develop a bottom-up model to test the grid accommodation capabilities and design the optimal investment plans for offshore wind power considering resource distributions, hourly power system simulations, and transmiss | CrossRef | DigiEnergy | Renewable Energy Resource Mapping | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Electric vehicle batteries alone could satisfy short-term grid storage demand by as early as 2030 | 10.1038/s41467-022-35393-0 | https://doi.org/10.1038/s41467-022-35393-0 | Nature Communications | 2,023 | Xu, C.; Behrens, P.; Gasper, P.; Smith, K.; Hu, M. | AbstractThe energy transition will require a rapid deployment of renewable energy (RE) and electric vehicles (EVs) where other transit modes are unavailable. EV batteries could complement RE generation by providing short-term grid services. However, estimating the market opportunity requires an understanding of many socio-technical parameters and constraints. We quantify the global EV battery capacity available for grid storage using an integrated model incorporating future EV battery deployment | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Optimization & Control | |
Incentive based emergency demand response effectively reduces peak load during heatwave without harm to vulnerable groups | 10.1038/s41467-023-41970-8 | https://doi.org/10.1038/s41467-023-41970-8 | Nature Communications | 2,023 | Wang, Z.; Lu, B.; Wang, B.; Qiu, Y.; Shi, H. | Abstract
The incentive-based emergency demand response measure serves as an important regulatory tool during energy system operations. However, whether people will sacrifice comfort to respond to it during heatwave and what the effect on heat vulnerable populations will be are still unclear. A large-scale emergency demand response pilot involving 205,129 households was conducted in southwestern China during continuous extreme high temperatures in summer. We found that the incen | CrossRef | FLEXERGY | Demand Response | Demand Response & New Mobilities & Urban Planning | Forecasting & Prediction | |
Switchable biomimetic nanochannels for on-demand SO2 detection by light-controlled photochromism | 10.1038/s41467-023-37654-y | https://doi.org/10.1038/s41467-023-37654-y | Nature Communications | 2,023 | Zhang, D.; Sun, Y.; Wang, Z.; Liu, F.; Zhang, X. | AbstractIn contrast to the conventional passive reaction to analytes, here, we create a proof-of-concept nanochannel system capable of on-demand recognition of the target to achieve an unbiased response. Inspired by light-activatable biological channelrhodopsin-2, photochromic spiropyran/anodic aluminium oxide nanochannel sensors are constructed to realize a light-controlled inert/active-switchable response to SO2 by ionic transport behaviour. We find that light can finely regulate the reactivit | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Membrane free-energy landscapes derived from atomistic dynamics explain nonuniversal cholesterol-induced stiffening | 10.1093/pnasnexus/pgad269 | https://doi.org/10.1093/pnasnexus/pgad269 | npj Clean Energy | 2,023 | Fiorin, G.; Forrest, L.; Faraldo-Gómez, J. | Abstract
All lipid membranes have inherent morphological preferences and resist deformation. Yet adaptations in membrane shape can and do occur at multiple length scales. While this plasticity is crucial for cellular physiology, the factors controlling the morphological energetics of lipid bilayers and the dominant mechanisms of membrane remodeling remain to be fully understood. An ongoing debate regarding the universality of the stiffening effect of cholesterol underscores the | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Bioinspired stability enhancement in deuterium-substituted organic–inorganic hybrid perovskite solar cells | 10.1093/pnasnexus/pgad160 | https://doi.org/10.1093/pnasnexus/pgad160 | npj Clean Energy | 2,023 | Tong, J.; Li, X.; Wang, J.; He, H.; Xu, T. | Abstract
In hybrid perovskite solar cells (PSCs), the reaction of hydrogens (H) located in the amino group of the organic A-site cations with their neighboring halides plays a central role in degradation. Inspired by the retarded biological activities of cells in heavy water, we replaced the light H atom with its abundant, twice-as-heavy, nonradioactive isotope, deuterium (D) to hamper the motion of H. This D substitution retarded the formation kinetics of the detrimental H halide | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Prebiotic synthesis of mineral-bearing microdroplet from inorganic carbon photoreduction at air–water interface | 10.1093/pnasnexus/pgad389 | https://doi.org/10.1093/pnasnexus/pgad389 | npj Clean Energy | 2,023 | Ge, Q.; Liu, Y.; You, W.; Wang, W.; Li, K. | Abstract
The origin of life on Earth is an enigmatic and intricate conundrum that has yet to be comprehensively resolved despite recent significant developments within the discipline of archaeology and geology. Chemically, metal-sulfide minerals are speculated to serve as an important medium for giving birth in early life, while yet so far direct evidence to support the hypothesis for the highly efficient conversion of inorganic carbon into praxiological biomolecules remains scarc | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Demand Response & IoT |
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