Probabilistic optimization techniques in smart power system
Uncertainties are the most significant challenges in the smart power system, necessitating
the use of precise techniques to deal with them properly. Such problems could be effectively …
the use of precise techniques to deal with them properly. Such problems could be effectively …
Predicting household electric power consumption using multi-step time series with convolutional LSTM
Energy consumption prediction has become an integral part of a smart and sustainable
environment. With future demand forecasts, energy production and distribution can be …
environment. With future demand forecasts, energy production and distribution can be …
Smart distribution mechanisms—Part I: from the perspectives of planning
To enhance the reliability and resilience of power systems and achieve reliable delivery of
power to end users, smart distribution networks (SDNs) play a vital role. The conventional …
power to end users, smart distribution networks (SDNs) play a vital role. The conventional …
Electricity price forecasting in the Danish day-ahead market using the TBATS, ANN and ARIMA methods
OA Karabiber, G Xydis - Energies, 2019 - mdpi.com
In this paper day-ahead electricity price forecasting for the Denmark-West region is realized
with a 24 h forecasting range. The forecasting is done for 212 days from the beginning of …
with a 24 h forecasting range. The forecasting is done for 212 days from the beginning of …
Houseec: Day-ahead household electrical energy consumption forecasting using deep learning
I Kiprijanovska, S Stankoski, I Ilievski, S Jovanovski… - Energies, 2020 - mdpi.com
Short-term load forecasting is integral to the energy planning sector. Various techniques
have been employed to achieve effective operation of power systems and efficient market …
have been employed to achieve effective operation of power systems and efficient market …
Smart sensors for smart grid reliability
Sensors for monitoring electrical parameters over an entire electricity network infrastructure
play a fundamental role in protecting smart grids and improving the network's energy …
play a fundamental role in protecting smart grids and improving the network's energy …
Smart Metering Applications
In this chapter, the smart metering applications are classified with respect to the
stakeholders that are mainly interested in their deployment and can have the highest profit …
stakeholders that are mainly interested in their deployment and can have the highest profit …
[HTML][HTML] Innovative Load Forecasting Models and Intelligent Control Strategy for Enhancing Distributed Load Levelling Techniques in Resilient Smart Grids
W Fangzong, Z Nishtar - Electronics, 2024 - mdpi.com
Dynamic load forecasting is essential for effective energy management and grid operation.
The use of GRU (Gated Recurrent Unit) and Long Short-Term Memory (LSTM) networks for …
The use of GRU (Gated Recurrent Unit) and Long Short-Term Memory (LSTM) networks for …
Research on the evaluation model of a smart grid development level based on differentiation of development demand
J Li, T Li, L Han - Sustainability, 2018 - mdpi.com
In order to eliminate the impact of inter-regional differentiation of development demand on
the objective evaluation of the development level of smart grid, this paper establishes the …
the objective evaluation of the development level of smart grid, this paper establishes the …
[HTML][HTML] Enhancing the missing data imputation of primary substation load demand records
CE Borges, O Kamara-Esteban… - … Energy, Grids and …, 2020 - Elsevier
The daily analysis of loads is one of the most important activities for power utilities in order to
be able to meet the energy demand. This analysis not only includes short-term forecasting …
be able to meet the energy demand. This analysis not only includes short-term forecasting …