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Abstract Electricity production in highly hydrological‐dependent systems is determined by different weather phenomena, which strongly impact spot prices. To account for such stylized facts, we propose a stochastic process with a mean reversion and switching regime component to represent the dynamics of the spot price. The short‐term movements are represented by semi‐nonparametric (SNP) distributions, in contrast to previous studies that traditionally assume Gaussian processes. We consider the Colombian electricity market as a study case, in which 68% of its electrical generation comes from water resources, and the El Niño phenomenon represents a critical source of risk for maintaining long‐term supply, sustainability of investments, and efficiency of prices. We show that under scarcity seasons, the spot price mean, variance, and some superior‐order moments of electricity price distribution increase, as does the risk level of the system. In particular, the switching regime model with SNP distributions for the random components outperforms traditional models, leading to accurate estimates and simulations, thus being a helpful tool for resource planning, risk management, and policy‐makers for electricity markets with high climatic dependency. |
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