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Fatma Yaprakdal and Merve Varol Arisoy
In the smart grid paradigm, precise electrical load forecasting (ELF) offers significant advantages for enhancing grid reliability and informing energy planning decisions. Specifically, mid-term ELF is a key priority for power system planning and operati...
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Cristiana Tudor and Robert Sova
The European Union (EU) has positioned itself as a frontrunner in the worldwide battle against climate change and has set increasingly ambitious pollution mitigation targets for its members. The burden is heavier for the more vulnerable economies in Cent...
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Jorge Amantegui, Hugo Morais and Lucas Pereira
Even though Industrial Kitchens (IKs) are among the highest energy intensity spaces, very little work has been done to forecast their consumption. This work explores the possibility of increasing the accuracy of the consumption forecast in an IK by forec...
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Mohammad (Behdad) Jamshidi, Sobhan Roshani, Fatemeh Daneshfar, Ali Lalbakhsh, Saeed Roshani, Fariborz Parandin, Zahra Malek, Jakub Talla, Zdenek Peroutka, Alireza Jamshidi, Farimah Hadjilooei and Pedram Lalbakhsh
Complex phenomena have some common characteristics, such as nonlinearity, complexity, and uncertainty. In these phenomena, components typically interact with each other and a part of the system may affect other parts or vice versa. Accordingly, the human...
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Thabang Mathonsi and Terence L. van Zyl
Hybrid methods have been shown to outperform pure statistical and pure deep learning methods at forecasting tasks and quantifying the associated uncertainty with those forecasts (prediction intervals). One example is Exponential Smoothing Recurrent Neura...
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Kejin Wu and Sayar Karmakar
Forecasting volatility from econometric datasets is a crucial task in finance. To acquire meaningful volatility predictions, various methods were built upon GARCH-type models, but these classical techniques suffer from instability of short and volatile d...
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Alket Cecaj, Marco Lippi, Marco Mamei and Franco Zambonelli
Accurately forecasting how crowds of people are distributed in urban areas during daily activities is of key importance for the smart city vision and related applications. In this work we forecast the crowd density and distribution in an urban area by an...
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Giuseppe La Tona, Massimiliano Luna, Annalisa Di Piazza and Maria Carmela Di Piazza
As the adoption of distributed generation and energy storage grows and the attention to energy efficiency rises, Energy Management is assuming a growing importance in smart homes. Energy Management Systems (EMSs) should be easily deployable on smart home...
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Taiyong Li, Zhenda Hu, Yanchi Jia, Jiang Wu and Yingrui Zhou
Crude oil is one of the most important types of energy and its prices have a great impact on the global economy. Therefore, forecasting crude oil prices accurately is an essential task for investors, governments, enterprises and even researchers. However...
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Pamela MacDougall, Bob Ran, George B. Huitema and Geert Deconinck
With the growth of renewable generated electricity in the energy mix, large energy storage and flexible demand, particularly aggregated demand response is becoming a front runner as a new participant in the wholesale energy markets. One of the biggest ba...
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