A two-stage risk mitigation-aware energy scheduling for integrated water-power system with hybrid energy convertors

The increasing complexity and interconnectedness of Integrated Water-Power Systems (IWPS) are increasingly becoming riskability against unauthorized intrusions. This complexity requires innovative solutions to ensure system resilience, operational efficiency, and risk mitigation. This paper introduces a novel two-stage approach to managing these intricate IWPSs by integrating sensitivity analysis, risk assessment, and optimization methodologies. In this regard, first the key decision variables are identified by sensitivity analyzing and their impact on the system state variables is evaluated. To evaluate risks, particularly in the context of cyber threats such as False Data Injection Attacks (FDIA), a Proposed Jacobian Matrix (PJM) analysis is then introduced. Additionally, this paper offers a hybrid two-stage structure aimed at enhancing risk management in IWPS drawing on insights from the Proposed Jacobian Matrix (PJM) analysis. To overcome the IWPS's vulnerabilities and enhance optimal performance across operating conditions, the framework employed a multi-layered approach utilizing three key energy converters: water-to-thermal conversion, electricity-to-thermal conversion, and photovoltaic system within IWPS. Meanwhile, the first stage begins to analyze the hybrid structure of energy converters with a focus on risk minimization, specifically aimed at reducing the IWPS's vulnerability to potential disruptions and cyber threats. The second stage is defined based on a cost-effective operational strategy aimed at optimizing the decision variables across the hybrid structure applied in the first stage. The proposed framework is carried out in a studied IWPS with 36 electrical buses, 5 thermal buses, and 5 water buses across an interconnected network. The maximum estimated economic impact is 1.6 × 1013, indicating that the threat from Foreign Data Injection Attacks (FDIA) to the electrical network is the highest, with a risk rating of 3.89. In comparison, the gas network has a risk rating of 3.58, and the water network has a rating of 3.64. Comparative studies show that the PJM technique provides more accurate and consistent risk assessments than Conditional Value-at-Risk (CVaR). Furthermore, the proposed architecture ensures a steady reduction in overall operating expenses while decreasing the Integrated Water and Power Supply (IWPS) risk coefficient from 5.45 to 3.17.