Prediction of photovoltaic power output based on similar day analysis, genetic algorithm and extreme learning machine
Recently, many machine learning techniques have been successfully employed in
photovoltaic (PV) power output prediction because of their strong non-linear regression …
photovoltaic (PV) power output prediction because of their strong non-linear regression …
Photovoltaic power forecasting based on GA improved Bi-LSTM in microgrid without meteorological information
Due to flexible and clean nature, distributed photovoltaic (PV) power plants in micro-grid are
essential for solving energy and environmental problems. However, because of the high …
essential for solving energy and environmental problems. However, because of the high …
Delay optimization and energy balancing algorithm for improving network lifetime in fixed wireless sensor networks
Since wireless in terms of energy-restricted processes, dispersion radii, processing power
limitations, buffers, bandwidth-limited connections, active network topologies, and network …
limitations, buffers, bandwidth-limited connections, active network topologies, and network …
PV power forecasting using an integrated GA-PSO-ANFIS approach and Gaussian process regression based feature selection strategy
This paper presents a hybrid approach for the forecasting of electricity production in
microgrids with solar photovoltaic (PV) installations. An accurate PV power generation …
microgrids with solar photovoltaic (PV) installations. An accurate PV power generation …
Estimation of wind turbine output power using soft computing models
Among renewable energy generation technologies, wind energy has become one of the
most outstanding issues, especially in the last decade. Wind speed is the most critical …
most outstanding issues, especially in the last decade. Wind speed is the most critical …
Short term wind power prediction using ANFIS
Y Kassa, JH Zhang, DH Zheng… - 2016 IEEE international …, 2016 - ieeexplore.ieee.org
This paper proposes an ANFIS based approach for one-day-ahead hourly wind power
generation prediction. The increasing penetration of wind energy to electric power …
generation prediction. The increasing penetration of wind energy to electric power …
An overview on wind power forecasting methods
With the continually increasing growth in wind generation being integrated into the electric
networks, it brings about significant challenges for decision-makers of power system …
networks, it brings about significant challenges for decision-makers of power system …
Short‐term wind power prediction in microgrids using a hybrid approach integrating genetic algorithm, particle swarm optimization, and adaptive neuro‐fuzzy …
This paper proposes an integrated hybrid approach combining genetic algorithm (GA),
particle swarm optimization (PSO), and adaptive neuro‐fuzzy inference systems (ANFIS) for …
particle swarm optimization (PSO), and adaptive neuro‐fuzzy inference systems (ANFIS) for …
A GA-BP hybrid algorithm based ANN model for wind power prediction
Y Kassa, JH Zhang, DH Zheng… - 2016 IEEE Smart Energy …, 2016 - ieeexplore.ieee.org
This paper deals with a hybrid GA-BP ANN approach for wind power prediction. Wind
energy is one of the renewable energy options recently being developed significantly …
energy is one of the renewable energy options recently being developed significantly …
Comparison of three methods for short-term wind power forecasting
Wind power forecasting is critical for effective grid operation and management. An accurate
short-term wind forecasting model is an important tool for grid reliability and market-based …
short-term wind forecasting model is an important tool for grid reliability and market-based …