[PDF][PDF] Methods and models for electric load forecasting: a comprehensive review
Electric load forecasting (ELF) is a vital process in the planning of the electricity industry and
plays a crucial role in electric capacity scheduling and power systems management and …
plays a crucial role in electric capacity scheduling and power systems management and …
A state-of-the-art review of artificial intelligence techniques for short-term electric load forecasting
According to privatization and deregulation of power system, accurate electric load
forecasting has come into prominence recently. The new energy market and the smart grid …
forecasting has come into prominence recently. The new energy market and the smart grid …
Predicting electricity consumption for commercial and residential buildings using deep recurrent neural networks
This paper presents a recurrent neural network model to make medium-to-long term
predictions, ie time horizon of⩾ 1 week, of electricity consumption profiles in commercial and …
predictions, ie time horizon of⩾ 1 week, of electricity consumption profiles in commercial and …
Robust short-term electrical load forecasting framework for commercial buildings using deep recurrent neural networks
This paper presents a robust short-term electrical load forecasting framework that can
capture variations in building operation, regardless of building type and location. Nine …
capture variations in building operation, regardless of building type and location. Nine …
Deep belief network based electricity load forecasting: An analysis of Macedonian case
A number of recent studies use deep belief networks (DBN) with a great success in various
applications such as image classification and speech recognition. In this paper, a DBN …
applications such as image classification and speech recognition. In this paper, a DBN …
Empirical mode decomposition based deep learning for electricity demand forecasting
Electricity is of great significance for national economic, social, and technological activities,
such as material production, healthcare, and education. The nationwide electricity demand …
such as material production, healthcare, and education. The nationwide electricity demand …
Short-term energy forecasting using machine-learning-based ensemble voting regression
Meeting the required amount of energy between supply and demand is indispensable for
energy manufacturers. Accordingly, electric industries have paid attention to short-term …
energy manufacturers. Accordingly, electric industries have paid attention to short-term …
A comparative analysis of machine learning approaches for short-/long-term electricity load forecasting in Cyprus
D Solyali - Sustainability, 2020 - mdpi.com
Estimating the electricity load is a crucial task in the planning of power generation systems
and the efficient operation and sustainable growth of modern electricity supply networks …
and the efficient operation and sustainable growth of modern electricity supply networks …
A novel deep reinforcement learning based methodology for short-term HVAC system energy consumption prediction
Short-term energy consumption prediction has fundamental importance in many HVAC
system management tasks, such as demand-side management, short-term maintenance …
system management tasks, such as demand-side management, short-term maintenance …
Energy consumption control automation using Artificial Neural Networks and adaptive algorithms: Proposal of a new methodology and case study
M Benedetti, V Cesarotti, V Introna, J Serranti - Applied Energy, 2016 - Elsevier
Energy consumption control in energy intensive companies is always more considered as a
critical activity to continuously improve energy performance. It undoubtedly requires a huge …
critical activity to continuously improve energy performance. It undoubtedly requires a huge …