A review and evaluation of the state-of-the-art in PV solar power forecasting: Techniques and optimization
Integration of photovoltaics into power grids is difficult as solar energy is highly dependent
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
on climate and geography; often fluctuating erratically. This causes penetrations and voltage …
[HTML][HTML] Forecasting: theory and practice
Forecasting has always been at the forefront of decision making and planning. The
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
uncertainty that surrounds the future is both exciting and challenging, with individuals and …
Artificial intelligence based MPPT techniques for solar power system: A review
In the last decade, artificial intelligence (AI) techniques have been extensively used for
maximum power point tracking (MPPT) in the solar power system. This is because …
maximum power point tracking (MPPT) in the solar power system. This is because …
Taxonomy research of artificial intelligence for deterministic solar power forecasting
With the world-wide deployment of solar energy for a sustainable and renewable future, the
stochastic and volatile nature of solar power pose significant challenges to the reliable …
stochastic and volatile nature of solar power pose significant challenges to the reliable …
Short-term photovoltaic power forecasting based on long short term memory neural network and attention mechanism
Photovoltaic power generation forecasting is an important topic in the field of sustainable
power system design, energy conversion management, and smart grid construction …
power system design, energy conversion management, and smart grid construction …
A survey of machine learning models in renewable energy predictions
The use of renewable energy to reduce the effects of climate change and global warming
has become an increasing trend. In order to improve the prediction ability of renewable …
has become an increasing trend. In order to improve the prediction ability of renewable …
Machine-learning methods for integrated renewable power generation: A comparative study of artificial neural networks, support vector regression, and Gaussian …
M Sharifzadeh, A Sikinioti-Lock, N Shah - Renewable and Sustainable …, 2019 - Elsevier
Renewable energy from wind and solar resources can contribute significantly to the
decarbonisation of the conventionally fossil-driven electricity grid. However, their seamless …
decarbonisation of the conventionally fossil-driven electricity grid. However, their seamless …
Advanced methods for photovoltaic output power forecasting: A review
Forecasting is a crucial task for successfully integrating photovoltaic (PV) output power into
the grid. The design of accurate photovoltaic output forecasters remains a challenging issue …
the grid. The design of accurate photovoltaic output forecasters remains a challenging issue …
Solar photovoltaic power prediction using artificial neural network and multiple regression considering ambient and operating conditions
This paper proposes artificial neural network (ANN) and regression models for photovoltaic
modules power output predictions and investigates the effects of climatic conditions and …
modules power output predictions and investigates the effects of climatic conditions and …
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 …