Optimal operation of electric–heat–hydrogen integrated energy system considering conditional value-at-risk

The proliferation of load types and the widespread adoption of photovoltaic (PV) pose challenges for power prediction on both sides of the power grid. To address the problem of inaccurate PV and load forecasting, which can lead to fluctuating dispatch cost of the electric-heat-hydrogen integrated energy system (EIES), this work introduces the concept of risk management, and then formulates a model for the optimal operation of EIES considering conditional value-at-risk (CVaR). The objective function of the model includes day-ahead dispatch cost, expected real-time dispatch cost, and cost of risk. The day-ahead stage of operation seeks to determine the electricity purchased from the power grid and planned PV power output, whereas the real-time stage optimizes the operation of equipment under scenarios with different actual PV and load values. Furthermore, energy balance constraints, equipment operation constraints, and CVaR constraints are elaborated. The case study indicates that the weighted average dispatch cost for 135 actual PV and load scenarios is increased by 0.86% whereas the standard deviation of the 135-scenario dispatch cost is reduced by 8.47%, demonstrating that the fluctuation reduction for the dispatch cost comes at the expense of the increase of dispatch cost. This work investigates the relationship between the dispatch cost and risk level/cost fluctuation level, thus could offer valuable information to the operators of EIES.