Renewable energy: Present research and future scope of Artificial Intelligence

SK Jha, J Bilalovic, A Jha, N Patel, H Zhang - Renewable and Sustainable …, 2017 - Elsevier
The existence of sunlight, air and other resources on earth must be used in an appropriate
way for human welfare while still protecting the environment and its living creatures. The …

A review on operation and maintenance of hydropower plants

K Kumar, RP Saini - Sustainable Energy Technologies and Assessments, 2022 - Elsevier
Hydropower is one of the renewable energy sources having the highest conversion
efficiency than other renewable energy sources. The hydro turbine is considered as the …

Prediction of SOx–NOx emission from a coal-fired CFB power plant with machine learning: Plant data learned by deep neural network and least square support vector …

D Adams, DH Oh, DW Kim, CH Lee, M Oh - Journal of Cleaner Production, 2020 - Elsevier
The circulating fluidized bed boiler is an advanced clean energy technology that has
received much attention in the power industry due to its fuel flexibility. In this study, a deep …

Modeling and predicting the electricity production in hydropower using conjunction of wavelet transform, long short-term memory and random forest models

M Zolfaghari, MR Golabi - Renewable Energy, 2021 - Elsevier
Electricity is an important pillar for the economic growth and the development of societies.
Surveying and predicting the electricity production (EP) is a valuable factor in the hands of …

[PDF][PDF] Bibliography of self-organizing map (SOM) papers: 1998–2001 addendum

M Oja, S Kaski, T Kohonen - Neural computing surveys, 2003 - researchgate.net
Abstract The Self-Organizing Map (SOM) algorithm has attracted a great deal of interest
among researches and practitioners in a wide variety of fields. The SOM has been analyzed …

Hydropower operation optimization using machine learning: A systematic review

J Bernardes Jr, M Santos, T Abreu, L Prado Jr… - AI, 2022 - mdpi.com
The optimal dispatch of hydropower plants consists of the challenge of taking advantage of
both available head and river flows. Despite the objective of delivering the maximum power …

Condition monitoring and fault diagnostics for hydropower plants

L Selak, P Butala, A Sluga - Computers in Industry, 2014 - Elsevier
This paper presents a condition monitoring and fault diagnostics (CMFD) system for
hydropower plants (HPP). CMFD is based on the concept of industrial product-service …

Artificial intelligence for management and control of pollution minimization and mitigation processes

CW Chan, GH Huang - Engineering applications of artificial intelligence, 2003 - Elsevier
The reduction of environmental pollution and the conservation and recycling of natural
resources are significant social and environmental concerns. As valuable means for …

Using measured daily meteorological parameters to predict daily solar radiation

SM Mousavi, ES Mostafavi, A Jaafari, A Jaafari… - Measurement, 2015 - Elsevier
A major factor for an efficient design of solar energy systems is to provide accurate
estimations of the solar radiation. Many of the existing studies are focused on the analysis of …

[PDF][PDF] Predictive maintenance and life cycle estimation for hydro power plants with real-time analytics

A Åsnes, A Willersrud, F Kretz… - Predict. Maint. life cycle …, 2018 - researchgate.net
Optimal operation of hydro power plants could give substantial cost savings. Typically, daily
operation and maintenance of the plant is carried out based on pre-scheduled events and …