A Bilevel Optimization Model and a PSO-based Algorithm in Day-ahead Electricity Markets

被引：8

作者：

Zhang, Guoli ^{[1
]}

Zhang, Guangquan ^{[2
]}

Gao, Ya ^{[2
]}

Lu, Jie ^{[2
]}

机构：

[1] North China Elect Power Univ, Dept Math & Phys, Baoding 071003, Hebei, Peoples R China

[2] Univ Technol Sydney, Fac Engn & Informat Technol, Sydney, NSW 2007, Australia

来源：

2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9 | 2009年

基金：

澳大利亚研究理事会;

关键词：

bilevel programming; electricity market; optimization; particle swarm algorithm; strategic bidding; FOLLOWER;

D O I：

10.1109/ICSMC.2009.5346635

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Strategic bidding problems are becoming key issues in competitive electricity markets. This paper applies bilevel optimization theory to deal with this issue. We first analyze generating company strategic bidding behaviors and build a bilevel optimization model for a day-ahead electricity market. In this bilevel optimization model, each generating company will choose their bids in order to maximize their individual profits. A market operator will determine the output power for each unit and uniform marginal price based on the minimization purchase electricity fare. For solving this competitive strategic bidding problem described by the bilevel optimization model, a particle swarm optimization (PSO)-based algorithm is. Experiment results have demonstrated the validity of the PSO-based algorithm in solving the competitive strategic bidding problems for a day-ahead electricity market.

引用

页码：611 / +

页数：2

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