Enhanced short-term load forecasting using artificial neural networks
Ημερομηνία
2021Γλώσσα
en
Λέξη-κλειδί
Επιτομή
The modernization and optimization of current power systems are the objectives of research and development in the energy sector, which is motivated by the ever-increasing electricity demands. The goal of such research and development is to render power electronic equipment more controllable, to ensure maximal use of current circuits, system flexibility and efficiency, as well as the relatively easy integration of renewable energy resources at all voltage levels. The current revolution in communication technologies and the Internet of Things (IoT) offers us an opportunity to supervise and regulate the power grid, in order to achieve more reliable, efficient, and cost-effective services. One of the most critical aspects of efficient power system operation is the ability to predict energy load requirements, i.e., load forecasting. Load forecasting is essential for balancing demand and supply and for determining electricity prices. Typically, load forecasting has been supported through the use of Artificial Neural Networks (ANNs), which, once trained on a set of data, can predict future loads. The accuracy of the ANNs’ prediction depends on the quality and availability of the training data. In this paper, we propose novel data pre-processing strategies, which we apply to the data used to train an ANN, and subsequently evaluate the quality of the predictions it produces, to demonstrate the benefits gained. The proposed strategies and the obtained results are illustrated using consumption data from the Greek interconnected power system. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.
Collections
Related items
Showing items related by title, author, creator and subject.
-
Fast power-up active link protection in autonomous distributed transmitter power control
Gitzenis, S.; Bambos, N. (2008)In this work, we propose an enhancement to the DPC/ALP (Distributed Power Control with Active Link Protection) algorithm that allows fast power ramp-up without compromising the ALP guarantee. The original DPC algorithm was ... -
An internet of things architecture for preserving privacy of energy consumption
Beligianni F., Alamaniotis M., Fevgas A., Tsompanopoulou P., Bozanis P., Tsoukalas L.H. (2016)Energy consumption by residential customers represents today around 30 to 40% of the total consumed energy, with the residential loads often to be charged for significant contribution to the peak demands both seasonal and ... -
The impact of wind generation on isolated power systems: The case of Cyprus
Andrianesis, P.; Liberopoulos, G.; Varnavas, C. (2013)In this paper, we explore the impact of wind generation on isolated power systems, using the system of Cyprus (an island) as a case study. Since 2010, Cyprus has been facing the challenge of integrating intermittent wind ...