Wind Power Curtailment Optimization for Day-Ahead Operational Planning

被引：0

作者：

Alves, Rui ^{[1
]}

Reis, F. S. ^{[1
]}

Shen, Hong ^{[1
]}

机构：

[1] REN State Grid SA, Ctr Invest Energia, R&D Nester, Lisbon, Portugal

来源：

2016 IEEE PES INNOVATIVE SMART GRID TECHNOLOGIES CONFERENCE EUROPE (ISGT-EUROPE) | 2016年

关键词：

Wind Power Curtailment; Day-Ahead Operational Planning; Evolutionary Particle Swarm Optimization;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper a day-ahead operational planning methodology, for deciding how much wind power to curtail and where, is presented in order to support the wind power curtailment decision-making by system operators under scenarios of network bottlenecks. The Evolutionary Particle Swarm Optimization algorithm is used to provide robust wind power curtailment solutions at minimum cost. The methodology is validated on a case-study based on the Portuguese transmission system. Obtained results show the capability of the methodology to achieve near optimal curtailment solutions when applied to large-scale power systems.

引用

页数：6

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