A New Distributed Energy Management Strategy for Smart Grid With Stochastic Wind Power

In this article, a distributed energy management strategy is proposed for smart grid with stochastic wind power. The different Weibull probability distribution function (PDF) of wind power during different operation intervals, coupled with ramp rate limits of thermal generators across operation intervals, is considered in this operation cost optimization problem. Under multiagent system communication framework, we first decompose the problem into subproblems associated to operation interval. For each operation interval, parameters of Weibull PDF are estimated by maximum likelihood method according to wind speed obtained by wind speed forecast model of committed wind turbine. Then, a consensus-based alternating direction method of multipliers (ADMM) is proposed to get the optimal operation plan for all committed generators, where Armijo line search algorithm is employed to adaptively obtain the step size in the iterations. The simulation results show that the proposed consensus-based ADMM outperforms distributed projected gradient method in previous study on energy management with wind power; the proposed distributed strategy is valid for short-term energy management for smart grid with stochastic wind power.

Automated summary

A distributed energy management strategy is proposed for smart grid with stochastic wind power, taking into account the Weibull probability distribution of wind power and ramp rate limits of thermal generators to optimize operation cost. Through consensus algorithm and ADMM method, the proposed strategy outperforms previous distributed methods in short-term energy management for smart grid with stochastic wind power.