Progress on the demand side management in smart grid and optimization approaches
The integration of demand side management (DSM) with smart grid (SG) can facilitate
residents' transfer into smart homes and sustainable cities by reducing the carbon emission …
residents' transfer into smart homes and sustainable cities by reducing the carbon emission …
Photovoltaic power forecasting: A hybrid deep learning model incorporating transfer learning strategy
Y Tang, K Yang, S Zhang, Z Zhang - Renewable and Sustainable Energy …, 2022 - Elsevier
Accurate forecasting of photovoltaic power is essential in the integration, operation, and
scheduling of hybrid grid systems. In particular, modeling for newly built photovoltaic sites is …
scheduling of hybrid grid systems. In particular, modeling for newly built photovoltaic sites is …
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 …
[HTML][HTML] Application of improved version of multi verse optimizer algorithm for modeling solar radiation
For better estimation of renewable environmental friendly and carbon-free energy resources,
precise prediction of solar energy is very essential. However, accurate prediction of solar …
precise prediction of solar energy is very essential. However, accurate prediction of solar …
A novel structure adaptive new information priority discrete grey prediction model and its application in renewable energy generation forecasting
Renewable energy has made a significant contribution to global power generation.
Therefore, accurate mid-to-long term renewable energy generation forecasting is becoming …
Therefore, accurate mid-to-long term renewable energy generation forecasting is becoming …
PV power forecasting based on data-driven models: a review
Accurate PV power forecasting techniques are a prerequisite for the optimal management of
the grid and its stability. This paper presents a review of the recent developments in the field …
the grid and its stability. This paper presents a review of the recent developments in the field …
A novel long term solar photovoltaic power forecasting approach using LSTM with Nadam optimizer: A case study of India
Solar photovoltaic (PV) power is emerging as one of the most viable renewable energy
sources. The recent enhancements in the integration of renewable energy sources into the …
sources. The recent enhancements in the integration of renewable energy sources into the …
An improved moth-flame optimization algorithm for support vector machine prediction of photovoltaic power generation
GQ Lin, LL Li, ML Tseng, HM Liu, DD Yuan… - Journal of Cleaner …, 2020 - Elsevier
With the expansion of grid-connected solar power generation, the variability of photovoltaic
power generation has become increasingly pronounced. Accurate photovoltaic output …
power generation has become increasingly pronounced. Accurate photovoltaic output …
Investigating photovoltaic solar power output forecasting using machine learning algorithms
Solar power integration in electrical grids is complicated due to dependence on volatile
weather conditions. To address this issue, continuous research and development is required …
weather conditions. To address this issue, continuous research and development is required …
A systematic review of metaheuristic algorithms in electric power systems optimization
GH Valencia-Rivera, MT Benavides-Robles… - Applied Soft …, 2024 - Elsevier
Electric power system applications are intricate optimization problems. Most literature
reviews focus on studying an electrical paradigm through different optimization techniques …
reviews focus on studying an electrical paradigm through different optimization techniques …