A Novel Methodology for Modeling Multimodal Electricity Market Prices with Truncated Gaussian Distribution and K-means Clustering

Electricity market prices modeling plays a pivotal role in trading and operational decisions. Modeling electricity market prices considering multimodality feature is the main contribution of this work. This paper introduces a novel methodology for multimodal electricity prices modeling using truncated Gaussian distribution combined with a K-means clustering algorithm. The proposed model is compared with high parametric distribution based on Mont Carlo simulation combined with Epanechnikov kernel smoother. The proposed methodology is applied to hourly electricity prices data. The results proved that scenarios generated by the proposed model precisely duplicate the provided prices.