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 …
A review on renewable energy and electricity requirement forecasting models for smart grid and buildings
The benefits of renewable energy are that it is sustainable and is low in environmental
pollution. Growing load requirement, global warming, and energy crisis need energy …
pollution. Growing load requirement, global warming, and energy crisis need energy …
Forecasting renewable energy generation with machine learning and deep learning: Current advances and future prospects
This article presents a review of current advances and prospects in the field of forecasting
renewable energy generation using machine learning (ML) and deep learning (DL) …
renewable energy generation using machine learning (ML) and deep learning (DL) …
Solar photovoltaic generation forecasting methods: A review
S Sobri, S Koohi-Kamali, NA Rahim - Energy conversion and management, 2018 - Elsevier
Solar photovoltaic plants are widely integrated into most countries worldwide. Due to the
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …
ever-growing utilization of solar photovoltaic plants, either via grid-connection or stand …
Accurate photovoltaic power forecasting models using deep LSTM-RNN
M Abdel-Nasser, K Mahmoud - Neural computing and applications, 2019 - Springer
Photovoltaic (PV) is one of the most promising renewable energy sources. To ensure secure
operation and economic integration of PV in smart grids, accurate forecasting of PV power is …
operation and economic integration of PV in smart grids, accurate forecasting of PV power is …
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 …
Forecasting methods in energy planning models
KB Debnath, M Mourshed - Renewable and Sustainable Energy Reviews, 2018 - Elsevier
Energy planning models (EPMs) play an indispensable role in policy formulation and energy
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
sector development. The forecasting of energy demand and supply is at the heart of an EPM …
Photovoltaic and solar power forecasting for smart grid energy management
Due to the challenge of climate and energy crisis, renewable energy generation including
solar generation has experienced significant growth. Increasingly high penetration level of …
solar generation has experienced significant growth. Increasingly high penetration level of …
Comparison of different physical models for PV power output prediction
The electricity produced from renewable energy, in particular from wind and photovoltaic
plants, has seen exponential rise in the last decade. Consequently, the prediction of power …
plants, has seen exponential rise in the last decade. Consequently, the prediction of power …