This paper proposes a distributed strategy to the chance-constrained energy management for smart grid with penetration of stochastic wind power. This energy management model is constructed including chance constraints of spinning reserves for the sake of guaranteeing the maximum utilization of wind power on the basis of reliability. With the available wind power characterized by Weibull distribution

the chance constraints can be converted into deterministic ones by the derived analytical form of inverse cumulative distribution function. Although the original problem is transformed into a typical convex optimization problem

the tight coupling of constraints presents challenges to the design of distributed strategy. Therefore

we formulate the problem into a compact form with each generator unit depending on individual decision variables

instead of the common form with a decision vector being the collection of all local decision variables. Then

by developing a new initialization method and an adaptive weight matrix selection method

a distributed strategy based on tracking Alternating Direction Method of Multipliers (ADMM) is proposed to solve the model. The simulation results indicate that the proposed distributed strategy achieves comparable performance to the corresponding centralized scenario

and better performance than distributed consensus-based ADMM in the related literature. Moreover

the validity of the proposed distributed strategy is confirmed in day-ahead chance-constrained energy management with stochastic wind power.