LAUSR

Abstract Integrated Multiple-Energy Carrier (MEC) systems with electricity and natural gas infrastructure systems offer distinctive opportunities to enhance the efficiency and the flexibility of energy supply. Efficient operation of these interdependent infrastructure systems faces several challenges corresponding to the risk associated with the uncertainty in the environmental parameters. In this paper, a risk-based framework for energy management of interconnected energy hubs in MEC systems is proposed to minimize the expected system operation cost. The conditional value at risk (CVaR) method is used to quantify the risk associated with uncertainties in the electrical and thermal loads, and the real-time price of electricity. The probability distribution function of the uncertain parameters and auto regressive integrated moving average (ARIMA) models are used to generate scenarios to represent the uncertainty in the system parameters. The proposed model is formulated as a mixed integer linear programming (MILP) problem and solved using CPLEX solver. The developed case studies show the risk-averse and risk-taker operator strategies to demonstrate the merits of the proposed risk-based scheduling over the risk-neutral operation scheme. It is further investigated that how the expected operation cost depends on the risk measures in the risk-averse operation. Also, sensitivity analyses are conducted to assess the energy procurement scheduling based on the proposed approach. Furthermore, the effect of risk parameter on managing the congestion in electricity and natural gas networks is examined.