Titlebook: Energy Informatics; Third Energy Informa Bo N?rregaard J?rgensen,Luiz Carlos Pereira da Sil Conference proceedings 2024 The Editor(s) (if a

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書(shū)目名稱Energy Informatics影響因子(影響力)




書(shū)目名稱Energy Informatics影響因子(影響力)學(xué)科排名




書(shū)目名稱Energy Informatics網(wǎng)絡(luò)公開(kāi)度




書(shū)目名稱Energy Informatics網(wǎng)絡(luò)公開(kāi)度學(xué)科排名




書(shū)目名稱Energy Informatics被引頻次




書(shū)目名稱Energy Informatics被引頻次學(xué)科排名




書(shū)目名稱Energy Informatics年度引用




書(shū)目名稱Energy Informatics年度引用學(xué)科排名




書(shū)目名稱Energy Informatics讀者反饋




書(shū)目名稱Energy Informatics讀者反饋學(xué)科排名

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Market Abstraction of?Energy Markets and?Policies - Application in?an?Agent-Based Modeling Toolbox

長(zhǎng)矛

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Multi-agent Based Simulation for Investigating Electric Vehicle Adoption and Its Impacts on Electricconsumers are chosen as the case study. The results show that both EV adoption curves of 1 million and 775k EVs by 2030 will not satisfy the Danish climate goal of reducing transport sector emissions by 30% by 2030. The results also show that the current residential electricity distribution grids ca

錯(cuò)

PALL

Distributed Energy Resources and EV Charging Stations Expansion Planning for Grid-Connected Microgrir linear programming model is used to formulate the problem, ensuring the solution’s optimality. The applicability of the proposed model is evaluated in the 69-bus distribution grid. Promising results concerning grid-connected MGs were obtained, including the enhancement of energy exchange with the

PALL

Comparison of Inputs Correlation and Explainable Artificial Intelligence Recommendations for Neural fluence on the prediction accuracy. The training and forecasting tasks are supported in this paper by the forecasting algorithm Artificial Neural Networks. In the case study, a historic of two years and six months is used to estimate the consumption values of a targeted week considering periods of f

跳動(dòng)

Deep Learning Models to?Estimate and?Predict the?Solar Irradiation in?Brazilferent time granularities: 5?min, 30?min, 6?h, and 1?day. The results show a small error between the measured irradiation data and the calculated results with regard to the following six meteorological variables: time, temperature, relative humidity, wind speed, precipitation, and atmospheric pressu

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Computational Approaches for Green Computing of Energy Consumption Forecasting on Non-working Periodhe CPU processing unit on forecasting activities may have in the forecasting accuracy. Such decisions include changing the training and forecasting schedule of five minutes to hour periods and excluding the retraining using updated data from the test set. The conclusions of this paper clarify that s

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