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Correction to: Structural measures of personal networks predict migrants’ cultural backgrounds: an explanation from Grid/Group theory | 10.1093/pnasnexus/pgad469 | https://doi.org/10.1093/pnasnexus/pgad469 | npj Clean Energy | 2,023 | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |||
New estimates of the storage permanence and ocean co-benefits of enhanced rock weathering | 10.1093/pnasnexus/pgad059 | https://doi.org/10.1093/pnasnexus/pgad059 | npj Clean Energy | 2,023 | Kanzaki, Y.; Planavsky, N.; Reinhard, C. | Abstract
Avoiding many of the most severe consequences of anthropogenic climate change in the coming century will very likely require the development of “negative emissions technologies”—practices that lead to net carbon dioxide removal (CDR) from Earth's atmosphere. However, feedbacks within the carbon ... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Forecasting & Prediction | |
Transformer fault diagnosis method based on TLR-ADASYN balanced dataset | 10.1038/s41598-023-49901-9 | https://doi.org/10.1038/s41598-023-49901-9 | Scientific Reports | 2,023 | Guan, S.; Yang, H.; Wu, T. | AbstractAs the cornerstone of transmission and distribution equipment, power transformer plays a very important role in ensuring the safe operation of power system. At present, the technology of dissolved gas analysis (DGA) has been widely used in fault diagnosis of oil-immersed transformer. However, in the actual scen... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | AI & Deep Learning | |
The role of double-skin facade configurations in optimizing building energy performance in Erbil city | 10.1038/s41598-023-35555-0 | https://doi.org/10.1038/s41598-023-35555-0 | Scientific Reports | 2,023 | Naddaf, M.; Baper, S. | AbstractCarefully designing a building facade is the most crucial way to save energy, and a double-skin facade is an effective strategy for achieving energy efficiency. The improvement that can be made depends on how the double-skin facade is set up and what the weather conditions are like. This study was designed to i... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
A big data association rule mining based approach for energy building behaviour analysis in an IoT environment | 10.1038/s41598-023-47056-1 | https://doi.org/10.1038/s41598-023-47056-1 | Scientific Reports | 2,023 | Dolores, M.; Fernandez-Basso, C.; Gómez-Romero, J.; Martin-Bautista, M. | AbstractThe enormous amount of data generated by sensors and other data sources in modern grid management systems requires new infrastructures, such as IoT (Internet of Things) and Big Data architectures. This, in combination with Data Mining techniques, allows the management and processing of all these heterogeneous m... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Analysis of renewable energy consumption and economy considering the joint optimal allocation of “renewable energy + energy storage + synchronous condenser” | 10.1038/s41598-023-47401-4 | https://doi.org/10.1038/s41598-023-47401-4 | Scientific Reports | 2,023 | Wang, Z.; Li, Q.; Kong, S.; Li, W.; Luo, J. | Abstract
As renewable energy becomes increasingly dominant in the energy mix, the power system is evolving towards high proportions of renewable energy installations and power electronics-based equipment. This transition introduces significant challenges to the grid’s safe and stable operation. On the... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Optimizing upside variability and antifragility in renewable energy system design | 10.1038/s41598-023-36379-8 | https://doi.org/10.1038/s41598-023-36379-8 | Scientific Reports | 2,023 | Coppitters, D.; Contino, F. | AbstractDespite the considerable uncertainty in predicting critical parameters of renewable energy systems, the uncertainty during system design is often marginally addressed and consistently underestimated. Therefore, the resulting designs are fragile, with suboptimal performances when reality deviates significantly f... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Interrelationships between urban travel demand and electricity consumption: a deep learning approach | 10.1038/s41598-023-33133-y | https://doi.org/10.1038/s41598-023-33133-y | Scientific Reports | 2,023 | Movahedi, A.; Parsa, A.; Rozhkov, A.; Lee, D.; Mohammadian, A. | AbstractThe analysis of infrastructure use data in relation to other components of the infrastructure can help better understand the interrelationships between infrastructures to eventually enhance their sustainability and resilience. In this study, we focus on electricity consumption and travel demand. In short, the p... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | AI & Deep Learning | |
Electricity consumption in Finland influenced by climate effects of energetic particle precipitation | 10.1038/s41598-023-47605-8 | https://doi.org/10.1038/s41598-023-47605-8 | Scientific Reports | 2,023 | Juntunen, V.; Asikainen, T. | AbstractIt is known that electricity consumption in many cold Northern countries depends greatly on prevailing outdoor temperatures especially during the winter season. On the other hand, recent research has demonstrated that solar wind driven energetic particle precipitation from space into the polar atmosphere can in... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Forecasting & Prediction | |
Author Correction: Enhancing the Australian Gridded Climate Dataset rainfall analysis using satellite data | 10.1038/s41598-023-28997-z | https://doi.org/10.1038/s41598-023-28997-z | Scientific Reports | 2,023 | Chua, Z.; Evans, A.; Kuleshov, Y.; Watkins, A.; Choy, S. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Optimized scheduling study of user side energy storage in cloud energy storage model | 10.1038/s41598-023-45673-4 | https://doi.org/10.1038/s41598-023-45673-4 | Scientific Reports | 2,023 | Wang, H.; Yao, H.; Zhou, J.; Guo, Q. | AbstractWith the new round of power system reform, energy storage, as a part of power system frequency regulation and peaking, is an indispensable part of the reform. Among them, user-side small energy storage devices have the advantages of small size, flexible use and convenient application, but present decentralized ... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Simulation of melting paraffin with graphene nanoparticles within a solar thermal energy storage system | 10.1038/s41598-023-35361-8 | https://doi.org/10.1038/s41598-023-35361-8 | Scientific Reports | 2,023 | Jafaryar, M.; Sheikholeslami, M. | AbstractIn this paper, applying new structure and loading Graphene nanoparticles have been considered as promising techniques for enhancing thermal storage systems. The layers within the paraffin zone were made from aluminum and the melting temperature of paraffin is 319.55 K. The paraffin zone located in the middle se... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Forecasting & Prediction | |
Forecasting the carbon footprint of civil buildings under different floor area growth trends and varying energy supply methods | 10.1038/s41598-023-49270-3 | https://doi.org/10.1038/s41598-023-49270-3 | Scientific Reports | 2,023 | Teng, J.; Yin, H. | AbstractThe energy consumption and carbon footprint of buildings are significantly impacted by variations in building area and the number of households. Therefore, it is crucial to forecast the growth trend of building area and number of households. A validated time series model is used to predict the new building area... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | Forecasting & Prediction | |
Blending controlled-release urea and urea under ridge-furrow with plastic film mulching improves yield while mitigating carbon footprint in rainfed potato | 10.1038/s41598-022-25845-4 | https://doi.org/10.1038/s41598-022-25845-4 | Scientific Reports | 2,023 | Sun, M.; Ma, B.; Lu, P.; Bai, J.; Mi, J. | AbstractRidge-furrow with plastic film mulching and various urea types have been applied in rainfed agriculture, but their interactive effects on potato (Solanum tuberosum L.) yield and especially environments remain poorly understood. A three-year experiment was conducted to explore the responses of tuber yield, metha... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | Optimization & Control | |
Comprehensive energy efficiency optimization algorithm for steel load considering network reconstruction and demand response | 10.1038/s41598-023-46804-7 | https://doi.org/10.1038/s41598-023-46804-7 | Scientific Reports | 2,023 | Zang, Y.; Wang, S.; Ge, W.; Li, Y.; Cui, J. | AbstractIndustrial loads are usually energy intensive and inefficient. The optimization of energy efficiency management in steel plants is still in the early stage of development. Considering the topology of power grid, it is an urgent problem to improve the operation economy and load side energy efficiency of steel pl... | CrossRef | FLEXERGY | Demand Response | Demand Response & New Mobilities & Urban Planning | Forecasting & Prediction | |
Impact of implementing emergency demand response program and tie-line on cyber-physical distribution network resiliency | 10.1038/s41598-023-30746-1 | https://doi.org/10.1038/s41598-023-30746-1 | Scientific Reports | 2,023 | Osman, S.; Sedhom, B.; Kaddah, S. | AbstractRecently, due to the complex nature of cyber-physical distribution networks (DNs) and the severity of power outages caused by natural disasters, microgrid (MG) formation, distributed renewable energy resources (DRERs), and demand response programs (DRP) have been employed to enhance the resiliency of these netw... | CrossRef | FLEXERGY | Demand Response | Demand Response & New Mobilities & Urban Planning | Optimization & Control | |
The value of fusion energy to a decarbonized United States electric grid | 10.1016/j.joule.2023.02.006 | https://doi.org/10.1016/j.joule.2023.02.006 | Joule | 2,023 | Schwartz, J.; Ricks, W.; Kolemen, E.; Jenkins, J. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Coordinating distributed energy resources for reliability can significantly reduce future distribution grid upgrades and peak load | 10.1016/j.joule.2023.06.015 | https://doi.org/10.1016/j.joule.2023.06.015 | Joule | 2,023 | Navidi, T.; El Gamal, A.; Rajagopal, R. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Demand Response & New Mobilities & Urban Planning | Forecasting & Prediction | ||
Two million European single-family homes could abandon the grid by 2050 | 10.1016/j.joule.2023.09.012 | https://doi.org/10.1016/j.joule.2023.09.012 | Joule | 2,023 | Kleinebrahm, M.; Weinand, J.; Naber, E.; McKenna, R.; Ardone, A. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Thermally activated batteries and their prospects for grid-scale energy storage | 10.1016/j.joule.2023.02.009 | https://doi.org/10.1016/j.joule.2023.02.009 | Joule | 2,023 | Li, M.; Weller, J.; Reed, D.; Sprenkle, V.; Li, G. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Statistical and machine learning-based durability-testing strategies for energy storage | 10.1016/j.joule.2023.03.008 | https://doi.org/10.1016/j.joule.2023.03.008 | Joule | 2,023 | Harris, S.; Noack, M. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | AI & Deep Learning | ||
Reviewing the sociotechnical dynamics of carbon removal | 10.1016/j.joule.2022.11.008 | https://doi.org/10.1016/j.joule.2022.11.008 | Joule | 2,023 | Sovacool, B.; Baum, C.; Low, S. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Demand Response & IoT | ||
Getting methane under control: Paper policies, practical measurements, and the urgent need to verify emissions | 10.1016/j.oneear.2023.04.013 | https://doi.org/10.1016/j.oneear.2023.04.013 | One Earth | 2,023 | Nisbet, E. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Optimization of solar and battery-based hybrid renewable energy system augmented with bioenergy and hydro energy-based dispatchable source | 10.1016/j.isci.2022.105821 | https://doi.org/10.1016/j.isci.2022.105821 | iScience | 2,023 | Memon, S.; Upadhyay, D.; Patel, R. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Optimization & Control | ||
Hierarchical approach to evaluating storage requirements for renewable-energy-driven grids | 10.1016/j.isci.2022.105900 | https://doi.org/10.1016/j.isci.2022.105900 | iScience | 2,023 | Mahmud, Z.; Shiraishi, K.; Abido, M.; Sánchez-Pérez, P.; Kurtz, S. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Region-wise evaluation of price-based demand response programs in Japan’s wholesale electricity market considering microeconomic equilibrium | 10.1016/j.isci.2023.106978 | https://doi.org/10.1016/j.isci.2023.106978 | iScience | 2,023 | Malehmirchegini, L.; Suliman, M.; Farzaneh, H. | CrossRef | FLEXERGY | Demand Response | Demand Response & New Mobilities & Urban Planning | Demand Response & IoT | ||
Death spiral of the legacy grid: A game-theoretic analysis of modern grid defection processes | 10.1016/j.isci.2023.106415 | https://doi.org/10.1016/j.isci.2023.106415 | iScience | 2,023 | Navon, A.; Belikov, J.; Ofir, R.; Parag, Y.; Orda, A. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Intrinsic theta oscillation in the attractor network of grid cells | 10.1016/j.isci.2023.106351 | https://doi.org/10.1016/j.isci.2023.106351 | iScience | 2,023 | Wang, Z.; Wang, T.; Yang, F.; Liu, F.; Wang, W. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Coherently remapping toroidal cells but not Grid cells are responsible for path integration in virtual agents | 10.1016/j.isci.2023.108102 | https://doi.org/10.1016/j.isci.2023.108102 | iScience | 2,023 | Schøyen, V.; Pettersen, M.; Holzhausen, K.; Fyhn, M.; Malthe-Sørenssen, A. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Data-driven multi-objective optimization for electric vehicle charging infrastructure | 10.1016/j.isci.2023.107737 | https://doi.org/10.1016/j.isci.2023.107737 | iScience | 2,023 | Farhadi, F.; Wang, S.; Palacin, R.; Blythe, P. | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Optimization & Control | ||
Mind the goal: Trade-offs between flexibility goals for controlled electric vehicle charging strategies | 10.1016/j.isci.2023.105937 | https://doi.org/10.1016/j.isci.2023.105937 | iScience | 2,023 | Gschwendtner, C.; Knoeri, C.; Stephan, A. | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Optimization & Control | ||
An overview of deterministic and probabilistic forecasting methods of wind energy | 10.1016/j.isci.2022.105804 | https://doi.org/10.1016/j.isci.2022.105804 | iScience | 2,023 | Xie, Y.; Li, C.; Li, M.; Liu, F.; Taukenova, M. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | ||
Spatiotemporal analysis of the future carbon footprint of solar electricity in the United States by a dynamic life cycle assessment | 10.1016/j.isci.2023.106188 | https://doi.org/10.1016/j.isci.2023.106188 | iScience | 2,023 | Lu, J.; Tang, J.; Shan, R.; Li, G.; Rao, P. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Demand Response & IoT | ||
Nonlinear terahertz control of the lead halide perovskite lattice | 10.1126/sciadv.adg3856 | https://doi.org/10.1126/sciadv.adg3856 | Science Advances | 2,023 | Frenzel, M.; Cherasse, M.; Urban, J.; Wang, F.; Xiang, B. |
Lead halide perovskites (LHPs) have emerged as an excellent class of semiconductors for next-generation solar cells and optoelectronic devices. Tailoring physical properties by fine-tuning the lattice structures has been explored in these materials by chemical composition or morphology. Nevertheless, its d... | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Manipulating nitration and stabilization to achieve high energy | 10.1126/sciadv.adk3754 | https://doi.org/10.1126/sciadv.adk3754 | Science Advances | 2,023 | Singh, J.; Staples, R.; Shreeve, J. |
Nitro groups have played a central and decisive role in the development of the most powerful known energetic materials. Highly nitrated compounds are potential oxidizing agents, which could replace the environmentally hazardous used materials such as ammonium perchlorate. The scarcity of azole compounds wi... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Machine learning for industrial processes: Forecasting amine emissions from a carbon capture plant | 10.1126/sciadv.adc9576 | https://doi.org/10.1126/sciadv.adc9576 | Science Advances | 2,023 | Jablonka, K.; Charalambous, C.; Sanchez Fernandez, E.; Wiechers, G.; Monteiro, J. | One of the main environmental impacts of amine-based carbon capture processes is the emission of the solvent into the atmosphere. To understand how these emissions are affected by the intermittent operation of a power plant, we performed stress tests on a plant operating with a mixture of two amines, 2-amino-2-methyl-1... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Forecasting & Prediction | |
Injectable, self-healing hydrogel adhesives with firm tissue adhesion and on-demand biodegradation for sutureless wound closure | 10.1126/sciadv.adh4327 | https://doi.org/10.1126/sciadv.adh4327 | Science Advances | 2,023 | Ren, H.; Zhang, Z.; Cheng, X.; Zou, Z.; Chen, X. |
Tissue adhesives have garnered extensive interest as alternatives and supplements to sutures, whereas major challenges still remain, including weak tissue adhesion, inadequate biocompatibility, and uncontrolled biodegradation. Here, injectable and biocompatible hydrogel adhesives are developed via catalyst... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Swarming self-adhesive microgels enabled aneurysm on-demand embolization in physiological blood flow | 10.1126/sciadv.adf9278 | https://doi.org/10.1126/sciadv.adf9278 | Science Advances | 2,023 | Jin, D.; Wang, Q.; Chan, K.; Xia, N.; Yang, H. | The recent rise of swarming microrobotics offers great promise in the revolution of minimally invasive embolization procedure for treating aneurysm. However, targeted embolization treatment of aneurysm using microrobots has significant challenges in the delivery capability and filling controllability. Here, we develop ... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Grid-based methods for chemistry simulations on a quantum computer | 10.1126/sciadv.abo7484 | https://doi.org/10.1126/sciadv.abo7484 | Science Advances | 2,023 | Chan, H.; Meister, R.; Jones, T.; Tew, D.; Benjamin, S. | First-quantized, grid-based methods for chemistry modeling are a natural and elegant fit for quantum computers. However, it is infeasible to use today’s quantum prototypes to explore the power of this approach because it requires a substantial number of near-perfect qubits. Here, we use exactly emulated quantum compute... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Light-stimulated micromotor swarms in an electric field with accurate spatial, temporal, and mode control | 10.1126/sciadv.adi9932 | https://doi.org/10.1126/sciadv.adi9932 | Science Advances | 2,023 | Liang, Z.; Joh, H.; Lian, B.; Fan, D. | Swarming, a phenomenon widely present in nature, is a hallmark of nonequilibrium living systems that harness external energy into collective locomotion. The creation and study of manmade swarms may provide insights into their biological counterparts and shed light to the rules of life. Here, we propose an innovative me... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Toward highly effective loading of DNA in hydrogels for high-density and long-term information storage | 10.1126/sciadv.adg9933 | https://doi.org/10.1126/sciadv.adg9933 | Science Advances | 2,023 | Fei, Z.; Gupta, N.; Li, M.; Xiao, P.; Hu, X. |
Digital information, when converted into a DNA sequence, provides dense, stable, energy-efficient, and sustainable data storage. The most stable method for encapsulating DNA has been in an inorganic matrix of silica, iron oxide, or both, but are limited by low DNA uptake and complex recovery techniques. Th... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
An all-Africa dataset of energy model “supply regions” for solar photovoltaic and wind power | 10.1038/s41597-022-01786-5 | https://doi.org/10.1038/s41597-022-01786-5 | Scientific Data | 2,022 | Sterl, S.; Hussain, B.; Miketa, A.; Li, Y.; Merven, B. | AbstractWith solar and wind power generation reaching unprecedented growth rates globally, much research effort has recently gone into a comprehensive mapping of the worldwide potential of these variable renewable electricity (VRE) sources. From a perspective of energy systems analysis, the locations with the strongest... | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | |
A long-term reconstructed TROPOMI solar-induced fluorescence dataset using machine learning algorithms | 10.1038/s41597-022-01520-1 | https://doi.org/10.1038/s41597-022-01520-1 | Scientific Data | 2,022 | Chen, X.; Huang, Y.; Nie, C.; Zhang, S.; Wang, G. | AbstractPhotosynthesis is a key process linking carbon and water cycles, and satellite-retrieved solar-induced chlorophyll fluorescence (SIF) can be a valuable proxy for photosynthesis. The TROPOspheric Monitoring Instrument (TROPOMI) on the Copernicus Sentinel-5P mission enables significant improvements in providing h... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | AI & Deep Learning | |
A high spatial resolution dataset for anthropogenic atmospheric mercury emissions in China during 1998–2014 | 10.1038/s41597-022-01725-4 | https://doi.org/10.1038/s41597-022-01725-4 | Scientific Data | 2,022 | Chang, W.; Zhong, Q.; Liang, S.; Qi, J.; Jetashree, . | AbstractChina is the largest atmospheric mercury (Hg) emitter globally, which has been substantially investigated. However, the estimation of national or regional Hg emissions in China is insufficient in supporting emission control, as the location of the sources may have significant impacts on the effects of Hg emissi... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | Optimization & Control | |
Solar and wind power data from the Chinese State Grid Renewable Energy Generation Forecasting Competition | 10.1038/s41597-022-01696-6 | https://doi.org/10.1038/s41597-022-01696-6 | Scientific Data | 2,022 | Chen, Y.; Xu, J. | AbstractAccurate solar and wind generation forecasting along with high renewable energy penetration in power grids throughout the world are crucial to the days-ahead power scheduling of energy systems. It is difficult to precisely forecast on-site power generation due to the intermittency and fluctuation characteristic... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Forecasting & Prediction | |
Datasets on South Korean manufacturing factories’ electricity consumption and demand response participation | 10.1038/s41597-022-01357-8 | https://doi.org/10.1038/s41597-022-01357-8 | Scientific Data | 2,022 | Lee, E.; Baek, K.; Kim, J. | AbstractThis study describes the release of electricity consumption data of some manufacturing factories located in South Korea that participate in the demand response (DR) market. The data (in kilowatt) comprise individual factories’ total power usage details that were acquired using advanced metering infrastructures.... | CrossRef | FLEXERGY | Demand Response | Demand Response & New Mobilities & Urban Planning | Demand Response & IoT | |
A residential labeled dataset for smart meter data analytics | 10.1038/s41597-022-01252-2 | https://doi.org/10.1038/s41597-022-01252-2 | Scientific Data | 2,022 | Pereira, L.; Costa, D.; Ribeiro, M. | AbstractSmart meter data is a cornerstone for the realization of next-generation electrical power grids by enabling the creation of novel energy data-based services like providing recommendations on how to save energy or predictive maintenance of electric appliances. Most of these services are developed on top of advan... | CrossRef | FLEXERGY | Smart Home & EMS | Demand Response & New Mobilities & Urban Planning | Optimization & Control | |
Planning sustainable electricity solutions for refugee settlements in sub-Saharan Africa | 10.1038/s41560-022-01006-9 | https://doi.org/10.1038/s41560-022-01006-9 | Nature Energy | 2,022 | Baldi, D.; Moner-Girona, M.; Fumagalli, E.; Fahl, F. | AbstractAn inadequate understanding of the energy needs of forcibly displaced populations is one of the main obstacles in providing sustainable and reliable energy to refugees and their host communities. Here, we provide a first-order assessment of the main factors determining the decision to deploy fully renewable min... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Charging infrastructure access and operation to reduce the grid impacts of deep electric vehicle adoption | 10.1038/s41560-022-01105-7 | https://doi.org/10.1038/s41560-022-01105-7 | Nature Energy | 2,022 | Powell, S.; Cezar, G.; Min, L.; Azevedo, I.; Rajagopal, R. | AbstractElectric vehicles will contribute to emissions reductions in the United States, but their charging may challenge electricity grid operations. We present a data-driven, realistic model of charging demand that captures the diverse charging behaviours of future adopters in the US Western Interconnection. We study ... | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Forecasting & Prediction | |
Towards a repair research agenda for off-grid solar e-waste in the Global South | 10.1038/s41560-022-01103-9 | https://doi.org/10.1038/s41560-022-01103-9 | Nature Energy | 2,022 | Munro, P.; Samarakoon, S.; Hansen, U.; Kearnes, M.; Bruce, A. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Optimization & Control | ||
Simulated co-optimization of renewable energy and desalination systems in Neom, Saudi Arabia | 10.1038/s41467-022-31233-3 | https://doi.org/10.1038/s41467-022-31233-3 | Nature Communications | 2,022 | Riera, J.; Lima, R.; Hoteit, I.; Knio, O. | AbstractThe interdependence between the water and power sectors is a growing concern as the need for desalination increases globally. Therefore, co-optimizing interdependent systems is necessary to understand the impact of one sector on another. We propose a framework to identify the optimal investment mix for a co-opt... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Synchronization in electric power networks with inherent heterogeneity up to 100% inverter-based renewable generation | 10.1038/s41467-022-30164-3 | https://doi.org/10.1038/s41467-022-30164-3 | Nature Communications | 2,022 | Sajadi, A.; Kenyon, R.; Hodge, B. | AbstractThe synchronized operation of power generators is the foundation of electric power network stability and a key to the prevention of undesired power outages and blackouts. Here, we derive the conditions that guarantee synchronization in power networks with inherent generator heterogeneity when subjected to small... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Data-driven load profiles and the dynamics of residential electricity consumption | 10.1038/s41467-022-31942-9 | https://doi.org/10.1038/s41467-022-31942-9 | Nature Communications | 2,022 | Anvari, M.; Proedrou, E.; Schäfer, B.; Beck, C.; Kantz, H. | AbstractThe dynamics of power consumption constitutes an essential building block for planning and operating sustainable energy systems. Whereas variations in the dynamics of renewable energy generation are reasonably well studied, a deeper understanding of the variations in consumption dynamics is still missing. Here,... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
Electrifying passenger road transport in India requires near-term electricity grid decarbonisation | 10.1038/s41467-022-29620-x | https://doi.org/10.1038/s41467-022-29620-x | Nature Communications | 2,022 | Abdul-Manan, A.; Gordillo Zavaleta, V.; Agarwal, A.; Kalghatgi, G.; Amer, A. | AbstractBattery-electric vehicles (BEV) have emerged as a favoured technology solution to mitigate transport greenhouse gas (GHG) emissions in many non-Annex 1 countries, including India. GHG mitigation potentials of electric 4-wheelers in India depend critically on when and where they are charged: 40% reduction in the... | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Optimization & Control | |
Disruption of the grid cell network in a mouse model of early Alzheimer’s disease | 10.1038/s41467-022-28551-x | https://doi.org/10.1038/s41467-022-28551-x | Nature Communications | 2,022 | Ying, J.; Keinath, A.; Lavoie, R.; Vigneault, E.; El Mestikawy, S. | Abstract
Early-onset familial Alzheimer’s disease (AD) is marked by an aggressive buildup of amyloid beta (Aβ) proteins, yet the neural circuit operations impacted during the initial stages of Aβ pathogenesis remain elusive. Here, we report a coding impairment of the medial entorhinal cortex (MEC) gri... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Electro-active metaobjective from metalenses-on-demand | 10.1038/s41467-022-34494-0 | https://doi.org/10.1038/s41467-022-34494-0 | Nature Communications | 2,022 | Karst, J.; Lee, Y.; Floess, M.; Ubl, M.; Ludwigs, S. | AbstractSwitchable metasurfaces can actively control the functionality of integrated metadevices with high efficiency and on ultra-small length scales. Such metadevices include active lenses, dynamic diffractive optical elements, or switchable holograms. Especially, for applications in emerging technologies such as AR ... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Magnetically assisted drop-on-demand 3D printing of microstructured multimaterial composites | 10.1038/s41467-022-32792-1 | https://doi.org/10.1038/s41467-022-32792-1 | Nature Communications | 2,022 | Liu, W.; Chou, V.; Behera, R.; Le Ferrand, H. | AbstractMicrostructured composites with hierarchically arranged fillers fabricated by three-dimensional (3D) printing show enhanced properties along the fillers’ alignment direction. However, it is still challenging to achieve good control of the filler arrangement and high filler concentration simultaneously, which li... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Feasibility of hybrid in-stream generator–photovoltaic systems for Amazonian off-grid communities | 10.1093/pnasnexus/pgac077 | https://doi.org/10.1093/pnasnexus/pgac077 | npj Clean Energy | 2,022 | Brown, E.; Johansen, I.; Bortoleto, A.; Pokhrel, Y.; Chaudhari, S. | Abstract
While there have been efforts to supply off-grid energy in the Amazon, these attempts have focused on low upfront costs and deployment rates. These “get-energy-quick” methods have almost solely adopted diesel generators, ignoring the environmental and social risks associated with the known noise... | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Unexpected no significant soil carbon losses in the Tibetan grasslands due to rodent bioturbation | 10.1093/pnasnexus/pgac314 | https://doi.org/10.1093/pnasnexus/pgac314 | npj Clean Energy | 2,022 | Huang, M.; Gan, D.; Li, Z.; Wang, J.; Niu, S. | AbstractThe Tibetan grasslands store 2.5% of the Earth’s soil organic carbon. Unsound management practices and climate change have resulted in widespread grassland degradation, providing open habitats for rodent activities. Rodent bioturbation loosens topsoil, reduces productivity, changes soil nutrient conditions, and... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Demand Response & IoT | |
Structural measures of personal networks predict migrants’ cultural backgrounds: an explanation from Grid/Group theory | 10.1093/pnasnexus/pgac195 | https://doi.org/10.1093/pnasnexus/pgac195 | npj Clean Energy | 2,022 | Molina, J.; Ozaita, J.; Tamarit, I.; Sánchez, A.; McCarty, C. | Abstract
Culture and social structure are not separated analytical domains but intertwined phenomena observable in personal networks. Drawing on a personal networks dataset of migrants in the United States and Spain, we show that the country of origin, a proxy for diverse languages and cultural instituti... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Cryocampsis: a biophysical freeze-bending response of shrubs and trees under snow loads | 10.1093/pnasnexus/pgac131 | https://doi.org/10.1093/pnasnexus/pgac131 | npj Clean Energy | 2,022 | Ray, P.; Bret-Harte, M. | Abstract
We report a biophysical mechanism, termed cryocampsis (Greek cryo-, cold, + campsis, bending), that helps northern shrubs bend downward under a snow load. Subfreezing temperatures substantially increase the downward bending of cantilever-loaded branches of these shrubs, while allowing them to re... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
Energy and thermal modelling of an office building to develop an artificial neural networks model | 10.1038/s41598-022-12924-9 | https://doi.org/10.1038/s41598-022-12924-9 | Scientific Reports | 2,022 | Santos-Herrero, J.; Lopez-Guede, J.; Flores Abascal, I.; Zulueta, E. | AbstractNowadays everyone should be aware of the importance of reducing CO2 emissions which produce the greenhouse effect. In the field of construction, several options are proposed to reach nearly-Zero Energy Building (nZEB) standards. Obviously, before undertaking a modification in any part of a building focused on i... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | AI & Deep Learning | |
Enhancing the Australian Gridded Climate Dataset rainfall analysis using satellite data | 10.1038/s41598-022-25255-6 | https://doi.org/10.1038/s41598-022-25255-6 | Scientific Reports | 2,022 | Chua, Z.; Evans, A.; Kuleshov, Y.; Watkins, A.; Choy, S. | AbstractRainfall estimation over large areas is important for a thorough understanding of water availability, influencing societal decision-making, as well as being an input for scientific models. Traditionally, Australia utilizes a gauge-based analysis for rainfall estimation, but its performance can be severely limit... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Linking the long-term variability in global wave energy to swell climate and redefining suitable coasts for energy exploitation | 10.1038/s41598-022-18935-w | https://doi.org/10.1038/s41598-022-18935-w | Scientific Reports | 2,022 | Kamranzad, B.; Amarouche, K.; Akpinar, A. | AbstractThe sustainability of wave energy linked to the intra- and inter-annual variability in wave climate is crucial in wave resource assessment. In this study, we quantify the dependency of stability of wave energy flux (power) on long-term variability of wind and wave climate to detect a relationship between them. ... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Authentication of smart grid communications using quantum key distribution | 10.1038/s41598-022-16090-w | https://doi.org/10.1038/s41598-022-16090-w | Scientific Reports | 2,022 | Alshowkan, M.; Evans, P.; Starke, M.; Earl, D.; Peters, N. | AbstractSmart grid solutions enable utilities and customers to better monitor and control energy use via information and communications technology. Information technology is intended to improve the future electric grid’s reliability, efficiency, and sustainability by implementing advanced monitoring and control systems... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Ecological driving on multiphase trajectories and multiobjective optimization for autonomous electric vehicle platoon | 10.1038/s41598-022-09156-2 | https://doi.org/10.1038/s41598-022-09156-2 | Scientific Reports | 2,022 | Xiaofeng, T. | AbstractAutonomous electric vehicles promise to improve traffic safety, increase fuel efficiency and reduce congestion in future intelligent transportation systems. Ecological driving characteristics are first studied to concentrate on energy consumption, the ability to quickly pass its destination, etc. of autonomous ... | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Optimization & Control | |
Collection mode choice of spent electric vehicle batteries: considering collection competition and third-party economies of scale | 10.1038/s41598-022-10433-3 | https://doi.org/10.1038/s41598-022-10433-3 | Scientific Reports | 2,022 | Li, X. | AbstractWith the rapid development of the electric vehicle (EV) industry, the recycling of spent EV batteries has attracted considerable attention. The establishment and optimization of the collection mode is a key link in regulating the recycling of spent EV batteries. This paper investigates an EV battery supply chai... | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Optimization & Control | |
Enhancing wind direction prediction of South Africa wind energy hotspots with Bayesian mixture modeling | 10.1038/s41598-022-14383-8 | https://doi.org/10.1038/s41598-022-14383-8 | Scientific Reports | 2,022 | Rad, N.; Bekker, A.; Arashi, M. | AbstractWind energy production depends not only on wind speed but also on wind direction. Thus, predicting and estimating the wind direction for sites accurately will enhance measuring the wind energy potential. The uncertain nature of wind direction can be presented through probability distributions and Bayesian analy... | CrossRef | DigiEnergy | Renewable Energy Resource Mapping | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
A weighted energy consumption minimization-based multi-hop uneven clustering routing protocol for cognitive radio sensor networks | 10.1038/s41598-022-18310-9 | https://doi.org/10.1038/s41598-022-18310-9 | Scientific Reports | 2,022 | Wang, J.; Li, C. | AbstractAiming at solving the effective data delivery and energy hole problem in multi-hop cognitive radio sensor networks (CRSNs), a weighted energy consumption minimization-based uneven clustering (ECMUC) routing protocol is proposed in this paper. For the first time, the impact of control overhead on the network per... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Low-carbon economic dispatch considering integrated demand response and multistep carbon trading for multi-energy microgrid | 10.1038/s41598-022-10123-0 | https://doi.org/10.1038/s41598-022-10123-0 | Scientific Reports | 2,022 | Long, Y.; Li, Y.; Wang, Y.; Cao, Y.; Jiang, L. | AbstractWith the rapid development of distributed energy resources and natural gas power generation, multi-energy microgrid (MEMG) is considered as a critical technology to increase the penetration of renewable energy and achieve the target of carbon emission reduction. Therefore, this paper proposes a low-carbon econo... | CrossRef | EnergiTrade | Energy & Carbon Trading | Carbon Trading & New Business Models | Optimization & Control | |
Performance optimization of monolithic all-perovskite tandem solar cells under standard and real-world solar spectra | 10.1016/j.joule.2022.06.027 | https://doi.org/10.1016/j.joule.2022.06.027 | Joule | 2,022 | Gao, Y.; Lin, R.; Xiao, K.; Luo, X.; Wen, J. | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | ||
The demand-side resource opportunity for deep grid decarbonization | 10.1016/j.joule.2022.04.010 | https://doi.org/10.1016/j.joule.2022.04.010 | Joule | 2,022 | O'Shaughnessy, E.; Shah, M.; Parra, D.; Ardani, K. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Extreme weather and electricity markets: Key lessons from the February 2021 Texas crisis | 10.1016/j.joule.2021.12.015 | https://doi.org/10.1016/j.joule.2021.12.015 | Joule | 2,022 | Levin, T.; Botterud, A.; Mann, W.; Kwon, J.; Zhou, Z. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | Forecasting & Prediction | ||
Understanding battery aging in grid energy storage systems | 10.1016/j.joule.2022.09.014 | https://doi.org/10.1016/j.joule.2022.09.014 | Joule | 2,022 | Kumtepeli, V.; Howey, D. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Policy-driven solar innovation and deployment remains critical for US grid decarbonization | 10.1016/j.joule.2022.07.012 | https://doi.org/10.1016/j.joule.2022.07.012 | Joule | 2,022 | O’Shaughnessy, E.; Ardani, K.; Denholm, P.; Mai, T.; Silverman, T. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Optimization & Control | ||
Global land-use intensity and anthropogenic emissions exhibit symbiotic and explosive behavior | 10.1016/j.isci.2022.104741 | https://doi.org/10.1016/j.isci.2022.104741 | iScience | 2,022 | Sarkodie, S.; Owusu, P. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Demand Response & IoT | ||
Seasonal challenges for a California renewable- energy-driven grid | 10.1016/j.isci.2021.103577 | https://doi.org/10.1016/j.isci.2021.103577 | iScience | 2,022 | Abido, M.; Mahmud, Z.; Sánchez-Pérez, P.; Kurtz, S. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Targeted demand response for mitigating price volatility and enhancing grid reliability in synthetic Texas electricity markets | 10.1016/j.isci.2021.103723 | https://doi.org/10.1016/j.isci.2021.103723 | iScience | 2,022 | Lee, K.; Geng, X.; Sivaranjani, S.; Xia, B.; Ming, H. | CrossRef | FLEXERGY | Demand Response | Carbon Trading & New Business Models | Optimization & Control | ||
Changing sensitivity to cold weather in Texas power demand | 10.1016/j.isci.2022.104173 | https://doi.org/10.1016/j.isci.2022.104173 | iScience | 2,022 | Shaffer, B.; Quintero, D.; Rhodes, J. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | ||
Distribution grid impacts of electric vehicles: A California case study | 10.1016/j.isci.2021.103686 | https://doi.org/10.1016/j.isci.2021.103686 | iScience | 2,022 | Jenn, A.; Highleyman, J. | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Optimization & Control | ||
Planning for the evolution of the electric grid with a long-run marginal emission rate | 10.1016/j.isci.2022.103915 | https://doi.org/10.1016/j.isci.2022.103915 | iScience | 2,022 | Gagnon, P.; Cole, W. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Aqueous zinc batteries: Design principles toward organic cathodes for grid applications | 10.1016/j.isci.2022.104204 | https://doi.org/10.1016/j.isci.2022.104204 | iScience | 2,022 | Grignon, E.; Battaglia, A.; Schon, T.; Seferos, D. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Large balancing areas and dispersed renewable investment enhance grid flexibility in a renewable-dominant power system in China | 10.1016/j.isci.2022.103749 | https://doi.org/10.1016/j.isci.2022.103749 | iScience | 2,022 | Lin, J.; Abhyankar, N.; He, G.; Liu, X.; Yin, S. | CrossRef | FLEXERGY | Demand Response | Demand Response & New Mobilities & Urban Planning | Optimization & Control | ||
Heterogeneous changes in electricity consumption patterns of residential distributed solar consumers due to battery storage adoption | 10.1016/j.isci.2022.104352 | https://doi.org/10.1016/j.isci.2022.104352 | iScience | 2,022 | Qiu, Y.; Xing, B.; Patwardhan, A.; Hultman, N.; Zhang, H. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Novel Low/Zero Carbon Technologies | Demand Response & IoT | ||
Uncovering the biological basis of control energy: Structural and metabolic correlates of energy inefficiency in temporal lobe epilepsy | 10.1126/sciadv.abn2293 | https://doi.org/10.1126/sciadv.abn2293 | Science Advances | 2,022 | He, X.; Caciagli, L.; Parkes, L.; Stiso, J.; Karrer, T. | Network control theory is increasingly used to profile the brain’s energy landscape via simulations of neural dynamics. This approach estimates the control energy required to simulate the activation of brain circuits based on structural connectome measured using diffusion magnetic resonance imaging, thereby quantifying... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Addressing gain-bandwidth trade-off by a monolithically integrated photovoltaic transistor | 10.1126/sciadv.abq0187 | https://doi.org/10.1126/sciadv.abq0187 | Science Advances | 2,022 | Li, Y.; Chen, G.; Zhao, S.; Liu, C.; Zhao, N. |
The gain-bandwidth trade-off limits the development of high-performance photodetectors; i.e., the mutual restraint between the response speed and gain has intrinsically limited performance optimization of photomultiplication phototransistors and photodiodes. Here, we show that a monolithically integrated p... | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | |
Influence of voids on the thermal and light stability of perovskite solar cells | 10.1126/sciadv.abo5977 | https://doi.org/10.1126/sciadv.abo5977 | Science Advances | 2,022 | Wang, M.; Fei, C.; Uddin, M.; Huang, J. | The formation of voids in perovskite films close to the buried interface has been reported during film deposition. These voids are thought to limits the efficiency and stability of perovskite solar cells (PSCs). Here, we studied the voids formed during operation in perovskite films that were optimized during the soluti... | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Optimization & Control | |
The effect of renewable energy incorporation on power grid stability and resilience | 10.1126/sciadv.abj6734 | https://doi.org/10.1126/sciadv.abj6734 | Science Advances | 2,022 | Smith, O.; Cattell, O.; Farcot, E.; O’Dea, R.; Hopcraft, K. | Contemporary proliferation of renewable power generation is causing an overhaul in the topology, composition, and dynamics of electrical grids. These low-output, intermittent generators are widely distributed throughout the grid, including at the household level. It is critical for the function of modern power infrastr... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
Safer carbon nanotube processing expands industrial and consumer applications | 10.1126/sciadv.abq4853 | https://doi.org/10.1126/sciadv.abq4853 | Science Advances | 2,022 | Lowery, J.; Green, M. | Safer, less-reactive superacid processing enables printing and coating of carbon nanotubes into films, fibers, and fabrics. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Demand Response & IoT | |
A synthetic building operation dataset | 10.1038/s41597-021-00989-6 | https://doi.org/10.1038/s41597-021-00989-6 | Scientific Data | 2,021 | Li, H.; Wang, Z.; Hong, T. | AbstractThis paper presents a synthetic building operation dataset which includes HVAC, lighting, miscellaneous electric loads (MELs) system operating conditions, occupant counts, environmental parameters, end-use and whole-building energy consumptions at 10-minute intervals. The data is created with 1395 annual simula... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
DEDDIAG, a domestic electricity demand dataset of individual appliances in Germany | 10.1038/s41597-021-00963-2 | https://doi.org/10.1038/s41597-021-00963-2 | Scientific Data | 2,021 | Wenninger, M.; Maier, A.; Schmidt, J. | AbstractReal-world domestic electricity demand datasets are the key enabler for developing and evaluating machine learning algorithms that facilitate the analysis of demand attribution and usage behavior. Breaking down the electricity demand of domestic households is seen as the key technology for intelligent smart-gri... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
An open tool for creating battery-electric vehicle time series from empirical data, emobpy | 10.1038/s41597-021-00932-9 | https://doi.org/10.1038/s41597-021-00932-9 | Scientific Data | 2,021 | Gaete-Morales, C.; Kramer, H.; Schill, W.; Zerrahn, A. | AbstractThere is substantial research interest in how future fleets of battery-electric vehicles will interact with the power sector. Various types of energy models are used for respective analyses. They depend on meaningful input parameters, in particular time series of vehicle mobility, driving electricity consumptio... | CrossRef | FLEXERGY | Electric Vehicles & Mobility | Demand Response & New Mobilities & Urban Planning | Forecasting & Prediction | |
Time series of useful energy consumption patterns for energy system modeling | 10.1038/s41597-021-00907-w | https://doi.org/10.1038/s41597-021-00907-w | Scientific Data | 2,021 | Priesmann, J.; Nolting, L.; Kockel, C.; Praktiknjo, A. | AbstractThe analysis of energy scenarios for future energy systems requires appropriate data. However, while more or less detailed data on energy production is often available, appropriate data on energy consumption is often scarce. In our JERICHO-E-usage dataset, we provide comprehensive data on useful energy consumpt... | CrossRef | DigiEnergy | Renewable Energy Simulation Tools | AI & Data Science for Urban Energy Systems | Forecasting & Prediction | |
Truck electrification has minor grid impacts | 10.1038/s41560-021-00857-y | https://doi.org/10.1038/s41560-021-00857-y | Nature Energy | 2,021 | Liimatainen, H. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Cleaning cars, grid and air | 10.1038/s41560-020-00769-3 | https://doi.org/10.1038/s41560-020-00769-3 | Nature Energy | 2,021 | Smith, S. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Inequality built into the grid | 10.1038/s41560-021-00873-y | https://doi.org/10.1038/s41560-021-00873-y | Nature Energy | 2,021 | Moreno-Munoz, A. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | ||
Inequitable access to distributed energy resources due to grid infrastructure limits in California | 10.1038/s41560-021-00887-6 | https://doi.org/10.1038/s41560-021-00887-6 | Nature Energy | 2,021 | Brockway, A.; Conde, J.; Callaway, D. | CrossRef | DigiEnergy | Load Forecasting & Demand Management | Carbon Trading & New Business Models | Optimization & Control | ||
Economic, environmental and grid-resilience benefits of converting diesel trains to battery-electric | 10.1038/s41560-021-00915-5 | https://doi.org/10.1038/s41560-021-00915-5 | Nature Energy | 2,021 | Popovich, N.; Rajagopal, D.; Tasar, E.; Phadke, A. | Abstract
Nearly all US locomotives are propelled by diesel-electric drives, which emit 35 million tonnes of CO
2
and produce air pollution causing about 1,000 premature deaths annually, accounting for approximately US$6.5 billion in annual h... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control | |
High resolution global spatiotemporal assessment of rooftop solar photovoltaics potential for renewable electricity generation | 10.1038/s41467-021-25720-2 | https://doi.org/10.1038/s41467-021-25720-2 | Nature Communications | 2,021 | Joshi, S.; Mittal, S.; Holloway, P.; Shukla, P.; Ó Gallachóir, B. | AbstractRooftop solar photovoltaics currently account for 40% of the global solar photovoltaics installed capacity and one-fourth of the total renewable capacity additions in 2018. Yet, only limited information is available on its global potential and associated costs at a high spatiotemporal resolution. Here, we prese... | CrossRef | CleanTech | Solar PV & Storage | Novel Low/Zero Carbon Technologies | Demand Response & IoT | |
Linear reinforcement learning in planning, grid fields, and cognitive control | 10.1038/s41467-021-25123-3 | https://doi.org/10.1038/s41467-021-25123-3 | Nature Communications | 2,021 | Piray, P.; Daw, N. | Abstract
It is thought that the brain’s judicious reuse of previous computation underlies our ability to plan flexibly, but also that inappropriate reuse gives rise to inflexibilities like habits and compulsion. Yet we lack a complete, realistic account of either. Building on control engineering, here... | CrossRef | DigiEnergy | Load Forecasting & Demand Management | AI & Data Science for Urban Energy Systems | Optimization & Control |
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