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

机译:具有随机风力的智能电网的新分布式能源管理策略

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摘要

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.
机译:在本文中,提出了一种具有随机风电网的智能电网的分布式能源管理策略。在该操作成本优化问题中考虑,在不同操作间隔期间的不同操作间隔的风电的不同Weibull概率分布函数(PDF)与热发生器的热发电机的斜坡率限制相结合,在该操作成本优化问题中被考虑。在多读系统通信框架下,我们首先将问题分解为与操作间隔相关联的子问题。对于每个操作间隔,通过封闭式风力涡轮机的风速预测模型获得的风速,通过最大似然方法来估计WIBULL PDF的参数。然后,提出了一种基于乘法器(ADMM)的交替方向方法,以获得所有承诺发生器的最佳操作计划,其中采用ARMIJO线搜索算法以自适应地获得迭代中的步长。仿真结果表明,拟议的基于共识的ADMM优于先前有关风电能源管理研究的分布式预计梯度法;拟议的分布式策略对于具有随机风力的智能电网的短期能源管理是有效的。

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