Review on probabilistic forecasting of photovoltaic power production and electricity consumption
Abstract tAccurate forecasting simultaneously becomes more important and more
challenging due to the increasing penetration of photovoltaic (PV) systems in the built …
challenging due to the increasing penetration of photovoltaic (PV) systems in the built …
[HTML][HTML] Forecasting solar photovoltaic power production: A comprehensive review and innovative data-driven modeling framework
The intermittent and stochastic nature of Renewable Energy Sources (RESs) necessitates
accurate power production prediction for effective scheduling and grid management. This …
accurate power production prediction for effective scheduling and grid management. This …
Short-term photovoltaic power forecasting using an LSTM neural network and synthetic weather forecast
In this paper, a forecasting algorithm is proposed to predict photovoltaic (PV) power
generation using a long short term memory (LSTM) neural network (NN). A synthetic …
generation using a long short term memory (LSTM) neural network (NN). A synthetic …
Credible capacity calculation method of distributed generation based on equal power supply reliability criterion
J Chen, B Sun, Y Li, R **g, Y Zeng, M Li - Renewable Energy, 2022 - Elsevier
Increasing distributed generation (DG) enables distribution network (DN) carry more load.
Therefore, DG includes both electricity and capacity values. The DG capacity value can be …
Therefore, DG includes both electricity and capacity values. The DG capacity value can be …
Short-term photovoltaic power point-interval forecasting based on double-layer decomposition and WOA-BiLSTM-Attention and considering weather classification
M Yu, D Niu, K Wang, R Du, X Yu, L Sun, F Wang - Energy, 2023 - Elsevier
A reliable short-term forecast of photovoltaic power (PVPF) is essential to maintaining stable
power systems and optimizing power grid dispatch. A hybrid prediction framework of PVPF …
power systems and optimizing power grid dispatch. A hybrid prediction framework of PVPF …
Capacity and output power estimation approach of individual behind-the-meter distributed photovoltaic system for demand response baseline estimation
Accurate customer baseline load (CBL) estimation is critical for implementing incentive-
based demand response (DR) programs. The increasing penetration of grid-tied distributed …
based demand response (DR) programs. The increasing penetration of grid-tied distributed …
[HTML][HTML] Probabilistic solar irradiance forecasting based on XGBoost
X Li, L Ma, P Chen, H Xu, Q **ng, J Yan, S Lu, H Fan… - Energy Reports, 2022 - Elsevier
Solar energy has received increasing attention as renewable clean energy in recent years.
Power grid operators and researchers widely value probabilistic solar irradiance forecasting …
Power grid operators and researchers widely value probabilistic solar irradiance forecasting …
Deep learning-based multivariate probabilistic forecasting for short-term scheduling in power markets
In the current competition framework governing the electricity sector, complex dependencies
exist between electrical and market data, which complicates the decision-making procedure …
exist between electrical and market data, which complicates the decision-making procedure …
Convolutional graph autoencoder: A generative deep neural network for probabilistic spatio-temporal solar irradiance forecasting
Machine learning on graphs is an important and omnipresent task for a vast variety of
applications including anomaly detection and dynamic network analysis. In this paper, a …
applications including anomaly detection and dynamic network analysis. In this paper, a …
A Practical Approach for Predicting Power in a Small‐Scale Off‐Grid Photovoltaic System using Machine Learning Algorithms
Climate change and the energy crisis substantially motivated the use and development of
renewable energy resources. Solar power generation is being identified as the most …
renewable energy resources. Solar power generation is being identified as the most …