Integrated Smart Risk Management for Siwa Solar Energy Systems: A Case Study and Strategies

Abstract

This study introduces a novel risk measurement and control framework tailored to optimize the stochastic energy trading strategy of a solar storage system at Egypt's Siwa solar station. By integrating key risk measurements Shortfall Probability (SP), Value at Risk (VaR), and Conditional Value at Risk (CVaR)-into a stochastic optimization model, this framework caters to diverse risk preferences and effectively addresses uncertainties associated with electricity prices and solar power production. Using realistic data, simulation analysis reveals a significant finding: increasing the energy capacity of battery storage significantly enhances the system's arbitrage capability, leading to a notable profit increase of approximately 20%. Furthermore, the integration of the risk framework demonstrates its effectiveness by revealing significant improvements in key areas, including risk mitigation, system stability, financial performance, decision-making insights, and adherence to international standards. These findings equip decision-makers in the Egyptian energy sector with actionable strategies to optimize their energy trading practices, thereby enhancing profitability and risk management in this dynamic industry.