Abstract
This paper presents a novel approach for predicting electricity prices in fuzzy and stochastic environments. First, we analyze historical data on daily PJM Western Hub Real-Time Peak electricity prices and extract relevant features for modeling. Then, we introduce a comprehensive model for predicting the price of electricity within the PJM market. To adapt the model to the electricity price data, we implement algorithms based on the least squares algorithm to calibrate the model’s parameters. However, considering the model’s purpose in forecasting future electricity prices, we apply the parameters as fuzzy numbers. After that, acknowledging the significant losses that severe electricity fluctuations can incur for producers, consumers, and industrial owners, we develop a formula to assess the probability of such fluctuations occurring in both random and fuzzy spaces. Finally, because electricity transactions are conducted through contracts, we calculate the price of these contracts across various time frames and use the fuzzy numbers to obtain a margin for the price of the contracts.
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Alazemi, F., Alsenafi, A. & Najafi, A. Valuation of forward contract price in energy markets described by a fuzzy-stochastic model and mathematical algorithms: a case study of the PJM Western Hub Real-Time Peak market. Comp. Appl. Math. 43, 257 (2024). https://doi.org/10.1007/s40314-024-02780-w
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DOI: https://doi.org/10.1007/s40314-024-02780-w