A Hybrid Stochastic-Robust Planning Approach for the Flexible Devices in an Islanded Integrated Energy System Considering Multiple Uncertainties and Demand Response

As renewable energy integration continues to rise, addressing the challenges of uncertainty and operational flexibility in islanded integrated energy systems (IES) has become increasingly critical. This paper presents a hybrid stochastic-robust optimization method for islanded IES planning, aiming to achieve an optimal balance between economic efficiency and robustness while managing the inherent uncertainties of renewable generation and multi-energy loads. The proposed approach combines stochastic optimization (SO) and robust optimization (RO), leveraging SO to model renewable energy and load variations through representative daily scenarios and employing RO to define fluctuation intervals for ensuring system reliability. By incorporating the Copula function, this method accurately captures the joint probability distributions of wind and solar power, balancing computational efficiency with modeling accuracy. Additionally, a demand response (DR) model is integrated to dynamically adjust energy consumption in response to price signals, enhancing system flexibility and cost-effectiveness. The proposed methodology not only mitigates the computational limitations of conventional SO approaches but also avoids the excessive conservatism associated with pure RO methods, making it particularly well-suited for remote areas with energy supply constraints. The results highlight the method's effectiveness in achieving resilient and economically sustainable energy planning. This study provides valuable insights for designing robust, cost-efficient, and flexible energy systems, contributing to the advancement of low-carbon energy solutions in islanded regions.