Forecasting short-term electricity consumption using a semantics-based genetic programming framework: The South Italy case

2015 ◽  
Vol 47 ◽  
pp. 37-41 ◽  
Author(s):  
Mauro Castelli ◽  
Leonardo Vanneschi ◽  
Matteo De Felice
2020 ◽  
Vol 13 (1) ◽  
pp. 104
Author(s):  
Dana-Mihaela Petroșanu ◽  
Alexandru Pîrjan

The accurate forecasting of the hourly month-ahead electricity consumption represents a very important aspect for non-household electricity consumers and system operators, and at the same time represents a key factor in what regards energy efficiency and achieving sustainable economic, business, and management operations. In this context, we have devised, developed, and validated within the paper an hourly month ahead electricity consumption forecasting method. This method is based on a bidirectional long-short-term memory (BiLSTM) artificial neural network (ANN) enhanced with a multiple simultaneously decreasing delays approach coupled with function fitting neural networks (FITNETs). The developed method targets the hourly month-ahead total electricity consumption at the level of a commercial center-type consumer and for the hourly month ahead consumption of its refrigerator storage room. The developed approach offers excellent forecasting results, highlighted by the validation stage’s results along with the registered performance metrics, namely 0.0495 for the root mean square error (RMSE) performance metric for the total hourly month-ahead electricity consumption and 0.0284 for the refrigerator storage room. We aimed for and managed to attain an hourly month-ahead consumed electricity prediction without experiencing a significant drop in the forecasting accuracy that usually tends to occur after the first two weeks, therefore achieving a reliable method that satisfies the contractor’s needs, being able to enhance his/her activity from the economic, business, and management perspectives. Even if the devised, developed, and validated forecasting solution for the hourly consumption targets a commercial center-type consumer, based on its accuracy, this solution can also represent a useful tool for other non-household electricity consumers due to its generalization capability.


2021 ◽  
Author(s):  
Hagar ElDidi ◽  
Chloe van Biljon ◽  
Muzna Fatima Alvi ◽  
Claudia Ringler ◽  
Nazmun Ratna ◽  
...  

2018 ◽  
Vol 15 (29) ◽  
pp. 199
Author(s):  
Airton Pollini

L’Italie du Sud est probablement la région la mieux connue du monde grec antique. Quelques sources écrites mais surtout des études archéologiques menées depuis longtemps ont permis le développement des recherches sur plusieurs aspects au cœur de la thématique de la colonisation grecque. Ce travail se concentre sur trois aspects essentiels : l’appropriation de l’espace colonial, l’interaction avec les populations indigènes et l’urbanisation des nouvelles installations. The South Italy is probably the best known region of the ancient Greek world. Some written sources but especially archaeological work undertaken for a long time allowed the development of research on several aspects at the heart of the issues of Greek colonization. This paper concentrates on three essential aspects: the appropriation of colonial space, the interaction with the native populations, and the urbanization of new establishments.


2022 ◽  
pp. 124-144
Author(s):  
Nima Norouzi

This chapter investigates the effects of COVID-19 on electricity consumption in some countries, especially in Iran. The effect of COVID-19 in the electricity industry and the amount of electricity consumption in Iran and in the countries that have been most affected have been studied. A study of COVID-19's impact on the world shows a reduction of about 15% in electricity demand during the short term of the COVID-19 outbreak. This amount varies from country to country. Studies show that the countries under study have experienced a relative decline in electricity demand in the short term, but with the continued prevalence of COVID-19 and the removal of some restrictions, the state of electricity consumption has more or less returned to pre-COVID-19 levels. It is worth noting that at the time of writing this chapter, the COVID-19 pandemic continues.


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