Results 31 to 40 of about 7,175,735 (307)
Household-Level Energy Forecasting in Smart Buildings Using a Novel Hybrid Deep Learning Model
IEEE Access, 2021 Forecasting of energy consumption in Smart Buildings (SB) and using the extracted information to plan and operate power generation are crucial elements of the Smart Grid (SG) energy management. Prediction of electrical loads and scheduling the generation
Dabeeruddin Syed +3 more
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IEEE Access, 2021 This work deals with the design of a Fuzzy Logic Control (FLC) based Energy Management System (EMS) for smoothing the grid power profile of a grid-connected electro-thermal microgrid.
Diego Arcos-Aviles +8 more
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A Review of Machine Learning-based Photovoltaic Output Power Forecasting: Nordic Context
IEEE Access, 2022 Motivated by factors such as the reduction in cost and the need for a shift towards achieving UN’s Sustainable Development Goals, PV (Photovoltaic) power generation is getting more attention in the cold regions of the Nordic countries and Canada.
B. Dimd +3 more
semanticscholar +1 more source
Research on Marine Photovoltaic Power Forecasting Based on Wavelet Transform and Echo State Network
Polish Maritime Research, 2017 With the rapid development of photovoltaic power generation technology, photovoltaic power generation system has gradually become an important component of the integrated energy system of marine.
Xinhui Du, Shuai Wang, Juan Zhang
doaj +1 more source
Day-ahead power market behavior for a small supplier: case of Turkish market [PDF]
Environmental Economics, 2018 The day-ahead power market has become more complex with the allowance of block purchases from private sales companies. Resource handling has become the prominent problem for both energy suppliers and energy distributers.
Avni Özözen +2 more
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Recent developments in multivariate wind and solar power forecasting
WIREs Energy and Environment, 2022 The intermittency of renewable energy sources, such as wind and solar, means that they require reliable and accurate forecasts to integrate properly into energy systems. This review introduces and examines a selection of state‐of‐the‐art methods that are
M. L. Sørensen +5 more
semanticscholar +1 more source
ElectricityThis study presents a novel methodology for determining zonal electricity generation and capacity requirements corresponding to forecasted annual production in an integrated power system (IPS).
Artur Zaporozhets +3 more
doaj +1 more source
Deep Learning Models for PV Power Forecasting: Review
EnergiesAccurate forecasting of photovoltaic (PV) power is essential for grid scheduling and energy management. In recent years, deep learning technology has made significant progress in time-series forecasting, offering new solutions for PV power forecasting ...
Jun Yu +10 more
semanticscholar +1 more source
Artificial Neural Networks for Photovoltaic Power Forecasting: A Review of Five Promising Models
IEEE AccessSolar energy is largely dependent on weather conditions, resulting in unpredictable, fluctuating, and unstable photovoltaic (PV) power outputs. Thus, accurate PV power forecasts are increasingly crucial for managing and controlling integrated energy ...
Rafiq Asghar +3 more
semanticscholar +1 more source
An Effective and Efficient Renewable Energy Generation Forecasting via Meteorological Assistance
Journal of Applied Science and EngineeringAccurate signal pattern mining of renewable energy generation forecasting (REGF) is important to the daysahead power scheduling of renewable energy power systems. Despite achieving excellent performance with current methods, two issues still persist. (1)
Zengyao Tian +3 more
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