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Real time photovoltaic power forecasting and modelling using machine learning techniques [PDF]
E3S Web of Conferences, 2022 Photovoltaic (PV) system installations have increased in recent years partly due to growing energy needs from a rising population. Such PV systems producing electricity contribute in promoting green energy.
Mwende Rita +2 more
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DeepVELOX: INVELOX Wind Turbine Intelligent Power Forecasting Using Hybrid GWO–GBR Algorithm
Energies, 2023 The transition to sustainable electricity generation depends heavily on renewable energy sources, particularly wind power. Making precise forecasts, which calls for clever predictive controllers, is a crucial aspect of maximizing the efficiency of wind ...
Ashkan Safari +2 more
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Collaborative Wind Power Forecast
, 2014 There are several new emerging environments, generating data spatially spread and interrelated. These applications reinforce the importance of the development of analytical systems capable to sense the environment and receive data from different locations.
Vânia Almeida, João Gama 0001
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, 2021 The wind power generation depends on wind speed and its derivatives like: wind speed and direction. With consideration of stochastic nature of wind power, this work addresses three main issues: first, it discusses the state of art of energy forecasting with emphasis on wind power forecasting. It provides an overview of different variables on which wind
Sumit Saroha +2 more
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IFAC-PapersOnLine, 2018 Abstract Accurate short-term wind power forecast is very important for reliable and efficient operation of power systems with high wind power penetration. There are many conventional and artificial intelligence methods that have been developed to achieve accurate wind power forecasting. Time-series based algorithms are known to be simple, robust, and
Q. Chen, K.A. Folly
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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
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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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Forecasting of Photovoltaic Solar Power Production Using LSTM Approach
, 2020 Solar-based energy is becoming one of the most promising sources for producing power for residential, commercial, and industrial applications. Energy production based on solar photovoltaic (PV) systems has gained much attention from researchers and ...
Sun, Ying +5 more
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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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