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Reconfiguration and reinforcement allocation as applied to hourly medium-term load forecasting of distribution feeders
(Institution of Engineering and Technology, 2020)
In this study, a methodology to develop hourly demand scenarios in a medium-term horizon for primary distribution substations is presented and applied to a case study. The main contribution of this study is that it addresses ...
Improvement on the sales forecast accuracy for a fast growing company by the best combination of historical data usage and clients segmentation
(2014-10-29)
Industrial companies in developing countries are facing rapid growths, and this requires having in place the best organizational processes to cope with the market demand. Sales forecasting, as a tool aligned with the general ...
Spatial load forecasting using a demand propagation approach
(2011-05-31)
A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses ...
Short-term multinodal load forecasting in distribution systems using general regression neural networks
(2011-10-05)
Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, ...
Short-term multinodal load forecasting in distribution systems using general regression neural networks
(2011-10-05)
Multinodal load forecasting deals with the loads of several interest nodes in an electrical network system, which is also known as bus load forecasting. To perform this demand, it is necessary a technique that is precise, ...
Forecasting Electric Load Demand through Advanced Statistical Techniques
(Institute of Physics Publishing, 2020-01-07)
Traditional forecasting models have been widely used for decision-making in production, finance and energy. Such is the case of the ARIMA models, developed in the 1970s by George Box and Gwilym Jenkins [1], which incorporate ...
Comparative study of continuous hourly energy consumption forecasting strategies with small data sets to support demand management decisions in buildings
(2022)
Buildings are one of the largest consumers of electrical energy, making it important to develop different strategies to help to reduce electricity consumption. Building energy consumption forecasting strategies are widely ...
An explainable machine learning model to optimize demand forecasting in Company DEOS
(Universidad de LimaPE, 2023)
Nowadays, having an accurate demand forecast is extremely important as it allows the company to manage resources in an optimal way and thus achieve greater productivity. There is a large demand for accurate forecasting, ...