Risk adjustable optimal operation for electricity-hydrogen integrated energy system based on chance constrained goal programming

Abstract

The electricity-hydrogen integrated energy system (EH-IES) enables synergistic operation of electricity, heat, and hydrogen subsystems, supporting renewable energy integration and efficient multi-energy utilization in future low-carbon societies. However, uncertainties from renewable energy and load variability threaten system safety and economy. Conventional chance-constrained programming (CCP) ensures reliable operation by limiting risk. However, increasing source-load uncertainties that can render CCP models infeasible and exacerbate operational risks. To address this, this paper proposes a risk-adjustable chance-constrained goal programming (RACCGP) model, integrating CCP and goal programming to balance risk and cost based on system risk assessment. An intelligent nonlinear goal programming method based on the state transition algorithm (STA) is developed, along with an improved discretized step transformation, to handle model nonlinearity and enhance computational efficiency. Experimental results show that the proposed model reduces costs while controlling risk compared to traditional CCP, and the solution method outperforms average sample sampling in efficiency and solution quality.

Keywords

electricity-hydrogen integrated energy system / chance constrained goal programming / risk adjustment / state transition algorithm

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Central South University