A multi-objective evolutionary approach for generator scheduling

被引：8

作者：

Li, Dapeng ^{[1
]}

Das, Sanjoy ^{[2
]}

Pahwa, Anil ^{[2
]}

Deb, Kalyanmoy ^{[3
]}

机构：

[1] ERCOT, Austin, TX USA

[2] Kansas State Univ, ECE Dept, Manhattan, KS 66506 USA

[3] Michigan State Univ, ECE Dept, E Lansing, MI USA

来源：

EXPERT SYSTEMS WITH APPLICATIONS | 2013年 / 40卷 / 18期

关键词：

Optimal generation scheduling; Unit commitment; Emission allowance; Multi-objective optimization; Genetic algorithm; UNIT-COMMITMENT PROBLEM; GENETIC ALGORITHM; ENVIRONMENTAL/ECONOMIC DISPATCH; OPTIMIZATION ALGORITHM; ECONOMIC-DISPATCH; NSGA-II; DESIGN; SYSTEM;

D O I：

10.1016/j.eswa.2013.06.020

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a novel, two-phase approach for optimal generation scheduling, taking into account the environmental issue of emission allowance trading in addition to the economic issue of operation cost. In the first phase, hourly-optimal scheduling is done to simultaneously minimize operation cost, emission, and transmission loss, while satisfying constraints such as power balance, spinning reserve and power generation limits. In the second phase, the minimum up/down time and ramp up/down rate constraints are considered, and a set of 24-h optimal schedules is obtained using the outputs of the first phase. Simulation results indicate effectiveness of the proposed approach. (C) 2013 Elsevier Ltd. All rights reserved.

引用

页码：7647 / 7655

页数：9

共 47 条

[1] Environmental/economic power dispatch using multiobjective evolutionary algorithms [J].