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Energy storage behind-the-meter with renewable generators: Techno-economic value of optimal imbalance management
V Trovato, B Kantharaj - International Journal of Electrical Power & Energy …, 2020 - Elsevier
There is a growing body of evidence that energy storage systems can provide significant
flexibility to the electricity grid. This study introduces a system comprising an energy storage …
flexibility to the electricity grid. This study introduces a system comprising an energy storage …
Wind power prediction based on deep learning models: The case of Adama wind farm
SM Ayene, AM Yibre - Heliyon, 2024 - cell.com
Wind is a renewable energy source that is used to generate electricity. Wind power is one of
the suitable solutions for global warming since it is free from pollution, doesn't cause …
the suitable solutions for global warming since it is free from pollution, doesn't cause …
Application of machine learning for optimal wind farm location
U Shahzad - Journal of Electrical Engineering, Electronics, Control …, 2021 - jeeeccs.net
Presence of renewable sources of energy in power systems is vital to cope the negative
impacts of environmental climate change. The drift in autonomous power network situations …
impacts of environmental climate change. The drift in autonomous power network situations …
Hybrid approach for short term wind power forecasting
Wind is one of the most important parts of renewable energy sources and optimal
scheduling of wind power in wind farms is essential. Therefore, accurate prediction is a …
scheduling of wind power in wind farms is essential. Therefore, accurate prediction is a …
Characterizing wind power forecast error using extreme value theory and copulas
Wind energy is one of the fastest-growing renewable energy sources in the world. However,
wind power is variable in all timescales. This variability is difficult to predict with perfect …
wind power is variable in all timescales. This variability is difficult to predict with perfect …
Integrated Machine Learning and Enhanced Statistical Approach‐Based Wind Power Forecasting in Australian Tasmania Wind Farm
F Yao, W Liu, X Zhao, L Song - Complexity, 2020 - Wiley Online Library
This paper develops an integrated machine learning and enhanced statistical approach for
wind power interval forecasting. A time‐series wind power forecasting model is formulated …
wind power interval forecasting. A time‐series wind power forecasting model is formulated …
Economic and financial benefits for wind turbines providing frequency response exploiting the kinetic energy or operating part‐loaded
This work assesses the financial viability of a wind farm where turbines are equipped to
provide frequency services. Two control strategies are compared: the former enables the …
provide frequency services. Two control strategies are compared: the former enables the …
[KSIĄŻKA][B] Contribution of Demand Side Management to Angular and Frequency Stability of Transmission Networks
M Wang - 2022 - search.proquest.com
Demand side management (DSM) has become one of the most popular solutions to
enhance and improve operational flexibility of future power systems, which are …
enhance and improve operational flexibility of future power systems, which are …
Analysis of Fuzzy Logic, ANN and ANFIS based Models for the Forecasting of Wind Power
Wind Energy Conversion System (WECS) is growing rapidly as one of the most beneficial
renewable energy sources available worldwide. The role of WECS is very essential in …
renewable energy sources available worldwide. The role of WECS is very essential in …
Short-term forecast analysis on wind power generation data
The forecasting of Wind power generation plays a critical role in the safe and stable
operation of a power grid. Grid operators rely on the short-term forecasts of load and …
operation of a power grid. Grid operators rely on the short-term forecasts of load and …