Daily peak-based short-term demand prediction using backpropagation combined to chi-squared distribution
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Nisrine Kebir
,
Abdessamad Lamallam
Abstract
An efficient and economic scheduling of power plants relies on an accurate demand forecast especially for the short-term due to its tight relation to power markets and trading operations in interconnected power systems. A slight deviation of load prediction from real demand could engender the start-up of a conventional power station which could be either time-consuming or requiring expensive combustible, a deviation that could interfere as well with renewables intermittency and demand response strategies. Hence, load forecasting still a challenging subject because of the various transformations that the energy sector undergoes and that directly impact the demand profile shape. Therefore, conceiving dynamic load demand forecast approaches will permit utilities save money in different vertical structures and regulation schemes. In this paper, we propose a novel approach for short-term demand prediction valid for normal and special days to address the impact of climate changes along with events occurrence on forecast accuracy. This approach is based on the prediction of hourly loads, established on the daily peak load prediction using backpropagation combined to chi-squared method for weighting historical data to enhance the training process. Obtained results from extensive testing on the Moroccan’s power system confirm the strength of the developed approach, that improved the forecast accuracy by a range of 1.1–4% compared to the existing methods.
Author contribution: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.
Research funding: None declared.
Competing interest: The authors declare no conflicts of interest regarding this article.
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© 2020 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Research Articles
- Smart branch and droop controller based power quality improvement in microgrids
- Daily peak-based short-term demand prediction using backpropagation combined to chi-squared distribution
- Frequency regulation of a weakly connected microgrid using the fuzzy-PID controller
- Assessment method of comprehensive energy saving potential of distribution network considering source-load power uncertainty
- Application of partial eigenvalue assignment techniques to dampen electromechanical oscillations in multi-machine power systems
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- Development and scaled-up simulation of an automated electrical energy management system for passageway illumination
Artikel in diesem Heft
- Research Articles
- Smart branch and droop controller based power quality improvement in microgrids
- Daily peak-based short-term demand prediction using backpropagation combined to chi-squared distribution
- Frequency regulation of a weakly connected microgrid using the fuzzy-PID controller
- Assessment method of comprehensive energy saving potential of distribution network considering source-load power uncertainty
- Application of partial eigenvalue assignment techniques to dampen electromechanical oscillations in multi-machine power systems
- Influence of magnets magnetization direction on the performance of high-speed permanent magnet synchronous starter-generator for micro-gas turbine
- Development and scaled-up simulation of an automated electrical energy management system for passageway illumination
