arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 1504.03274math.OCcs.DC
收藏

高穿透风电分布式随机市场出清

Distributed Stochastic Market Clearing with High-Penetration Wind Power

Yu Zhang, Georgios B. Giannakis

摘要:

将可再生能源整合到现代电网中需要对资源进行风险认知调度,以考虑可再生能源的随机可用性。针对这一目标,本文基于直流最优潮流(OPF),研究了高渗透率风电的日前随机市场出清问题。其目标是最大限度地减少社会成本,其中包括传统的发电成本,最终用户负效用,以及系统重新调度成本的风险措施。利用条件风险价值(CVaR),新模型能够减轻潜在的高风险的追索行动,以补偿风预测误差。由此产生的凸优化任务是通过一个基于分布的样本平均值的近似来解决的,以绕过过于复杂的高维积分。此外,为了应付可能的大规模可调度负荷,一个快速分布式求解器的开发与保证收敛使用的交替方向法的乘法器(ADMM)。在一个改进的基准系统上测试的数值结果证实了新框架和所提出的方法的优点。

英文摘要:

Integrating renewable energy into the modern power grid requires risk-cognizant dispatch of resources to account for the stochastic availability of renewables. Toward this goal, day-ahead stochastic market clearing with high-penetration wind energy is pursued in this paper based on the DC optimal power flow (OPF). The objective is to minimize the social cost which consists of conventional generation costs, end-user disutility, as well as a risk measure of the system re-dispatching cost. Capitalizing on the conditional value-at-risk (CVaR), the novel model is able to mitigate the potentially high risk of the recourse actions to compensate wind forecast errors. The resulting convex optimization task is tackled via a distribution-free sample average based approximation to bypass the prohibitively complex high-dimensional integration. Furthermore, to cope with possibly large-scale dispatchable loads, a fast distributed solver is developed with guaranteed convergence using the alternating direction method of multipliers (ADMM). Numerical results tested on a modified benchmark system are reported to corroborate the merits of the novel framework and proposed approaches.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑