Abstract

One of the most important realities and uncertainties in the deregulated electricity market is electricity demand. Electricity demand scenario generation in day-ahead markets using newly proposed Enhanced path-based scenario generation method based on autoregressive moving average is developed in this paper. A new enhanced path-based scenario generation method to generate scenarios of the random variable and uncertainties modeling to achieve lower mean absolute percentage error for scenario generation compared to path-based autoregressive moving average method is proposed. Comparison of expected values obtained from the proposed method and path-based ARMA method, as well as real values, shows lower mean absolute percentage error for proposed method. It is observed that the mean absolute percentage error is decreased 5% for electricity demand using newly proposed scenario generation method. Lower mean absolute percentage error indicates higher accuracy of this method for generation of scenarios.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.