A review and analysis of regression and machine learning models on commercial building electricity load forecasting
Electricity load forecasting is an important tool which can be utilized to enable effective
control of commercial building electricity loads. Accurate forecasts of commercial building …
control of commercial building electricity loads. Accurate forecasts of commercial building …
Load forecasting techniques for power system: Research challenges and survey
The main and pivot part of electric companies is the load forecasting. Decision-makers and
think tank of power sectors should forecast the future need of electricity with large accuracy …
think tank of power sectors should forecast the future need of electricity with large accuracy …
A survey on electric power demand forecasting: future trends in smart grids, microgrids and smart buildings
Recently there has been a significant proliferation in the use of forecasting techniques,
mainly due to the increased availability and power of computation systems and, in particular …
mainly due to the increased availability and power of computation systems and, in particular …
[HTML][HTML] A comprehensive survey on load forecasting hybrid models: Navigating the Futuristic demand response patterns through experts and intelligent systems
Load forecasting is a crucial task, which is carried out by utility companies for sake of power
grids' successful planning, optimized operation and control, enhanced performance, and …
grids' successful planning, optimized operation and control, enhanced performance, and …
Short-term load forecasting in a non-residential building contrasting models and attributes
The electric grid is evolving. Smart grids and demand response systems will increase the
performance of the grid in terms of cost efficiency, resilience and safety. Accurate load …
performance of the grid in terms of cost efficiency, resilience and safety. Accurate load …
Optimisation of energy management in commercial buildings with weather forecasting inputs: A review
Abstract Information about the patterns that govern the energy demand and onsite
generation can generate significant savings in the range of 15–30% in most cases and thus …
generation can generate significant savings in the range of 15–30% in most cases and thus …
Modeling wind power investments, policies and social benefits for deregulated electricity market–A review
This paper reviews the different aspects of modeling wind energy systems namely
investment, policies, performance, and social benefits for integration in deregulated power …
investment, policies, performance, and social benefits for integration in deregulated power …
Energy management system, generation and demand predictors: a review
SF Rafique, Z Jianhua - IET Generation, Transmission & …, 2018 - Wiley Online Library
A microgrid can integrate distributed energy resources for satisfying load demand,
moreover, solve reliability, safety and environment issues. Spinning reserves in microgrid …
moreover, solve reliability, safety and environment issues. Spinning reserves in microgrid …
Demand forecasting in smart grids
Data analytics in smart grids can be leveraged to channel the data downpour from individual
meters into knowledge valuable to electric power utilities and end-consumers. Short-term …
meters into knowledge valuable to electric power utilities and end-consumers. Short-term …
Prediction-based multi-agent reinforcement learning in inherently non-stationary environments
Multi-agent reinforcement learning (MARL) is a widely researched technique for
decentralised control in complex large-scale autonomous systems. Such systems often …
decentralised control in complex large-scale autonomous systems. Such systems often …