A New Particle Swarm Optimization Based Strategy for the Economic Emission Dispatch Problem Including Wind Energy Sources

被引：0

作者：

Alshammari, Gharbi A. ^{[1
]}

Alshammari, Fand A. ^{[1
]}

Guesmi, Tawfik ^{[1
]}

Alshammari, Bath M. ^{[1
]}

Alshammari, Ahmed S. ^{[1
]}

Alshammari, Naif A. ^{[1
]}

机构：

[1] Univ Hail, Dept Elect Engn, Hail, Saudi Arabia

来源：

ENGINEERING TECHNOLOGY & APPLIED SCIENCE RESEARCH | 2021年 / 11卷 / 05期

关键词：

economic emission dispatch; wind energy; stochastic optimization; particle swarm optimization; POWER UNCERTAINTY; ALGORITHM; SYSTEM; COST;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Power dispatch has become an important issue due to the high integration of Wind Power (WP) in power grids. Within this context, this paper presents a new Particle Swarm Optimization (PSO) based strategy for solving the stochastic Economic Emission Dispatch Problem (EEDP). This problem was solved considering several constraints such as power balance, generation limits, and Valve Point Loading Effects (VPLEs). The power balance constraint is described by a chance constraint to consider the impact of WP intermittency on the EEDP solution. In this study, the chance constraint represents the tolerance that the power balance constraint cannot meet. The suggested framework was successfully evaluated on a ten-unit system. The problem was solved for various threshold tolerances to study further the impact of WP penetration.

引用

页码：7585 / 7590

页数：6

共 26 条

[1] A dynamic economic emission dispatch considering wind power uncertainty incorporating energy storage system and demand side management [J].