Point estimate-based stochastic robust dispatch for electricity-gas combined system under wind uncertainty using iterative convex optimization

—In view of the growing deployment of wind power, reliable dispatches for wind uncertainty are becoming increasingly important, especially for the emerging electricity-gas combined system (EGCS). In this paper, a novel dispatch incorporating stochastic optimization and robust optimization is proposed for EGCS under wind uncertainty. Specifically, the objective is formulated with stochastic sampling to reduce the cost in actual operation, while security constraints are established based on affinely adjustable robust dispatch (AARD) to ensure the system reliability. Different from the traditional AARD which minimizes the base operation cost, the proposed stochastic robust dispatch optimizes the expected value of operation cost. The strategy essentially pre-optimizes the real-time adjustment in the look-ahead dispatch, such that the wind power fluctuation is balanced in a cost-effective way. Besides, A Nataf transformation-based three-point estimate is adopted, which accurately formulates the expected value of operation cost with a very small wind-sampling size. To solve the complex problem involving wind uncertainty, robust security constraints are converted into equivalent deterministic forms first, then a penalty convex–concave procedure-based optimization is developed to reformulate the nonconvex problem into an iterative convex programming. Simulation performed in two test systems validates the stochastic robust dispatch and the convex solution.