Work

Robust offering and bidding curves of compressed air energy storage plant via stochastic p-robust optimization technique

Year: 2025

Type: article

Abstract: This work presents a stochastic optimization technique (SOT) for CAESP to handle uncertain data and generate bidding-offering curves contributing to the electricity markets. Furthermore, the robust bidding-offering curves are obtained using the proposed stochastic p-robust optimization technique (SPROT), a novel robust-level measurement technique. The robust-oriented form of CAESP is modeled via SPROT, and robust scheduling is obtained by minimizing the maximum relative regret (MRR) in the worst scenario and maximizing the total performance profit. To mitigate the relative regret (RR) imposed by uncertain parameters, the SPROT is employed in conjunction with stochastic problems. Using the SPROT in stochastic issues enables the CAESP operator to derive a robust strategy that yields consistent profitability across all scenarios. The results indicate that the anticipated profit of the stochastic model is $9,584.65. When the SPROT is implemented, the proposed approach yields a profit of $9,188.36, suggesting a 4.13% decrease in the predicted profit and a 43.22% reduction in the MRR.

Source: Energy Conversion and Management X

DOI: 10.1016/j.ecmx.2025.101080

Author: Sayyad Nojavan

Institution: University of Bonab

Language: English

Topic: Electric Power System Optimization

Subfield: Electrical and Electronic Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Climate action

Open Access status: gold

Estimated APC paid: $3,170