Research

Genetic algorithm based optimal contracting strategy in a typical standing reserve market


Reference:

Li, F. and Lindquist, T. M., 2003. Genetic algorithm based optimal contracting strategy in a typical standing reserve market. In: Power Tech Conference Proceedings, 2003 IEEE Bologna, 2003-01-01.

Related documents:

This repository does not currently have the full-text of this item.
You may be able to access a copy if URLs are provided below.

Abstract

This paper proposes a coding scheme enhanced by problem specific knowledge for a genetic algorithm (GA) based contracting strategy used for optimal selection of standing reserve tenders, the aim of which is to provide the required operating reserve most economically. The proposed coding scheme enables the GA to handle tenders with flexible commitments, hence, to have greater potential to find lower cost solutions. The problem specific knowledge aims to significantly reduce the search space in the aid of reducing solution variance when comes to deal with large systems, such as the practical England & Wales power network. The effectiveness of the proposed technique is demonstrated on a small test system and the England and Wales power network with 83 tenders. The test results suggest that the cost of providing operating reserve has been significantly reduced when the GA is able to deal with tenders with flexible commitments, and further cost reduction and solution variance improvement can be achieved when incorporating the problem specific knowledge into the GA search.

Details

Item Type Conference or Workshop Items (Paper)
CreatorsLi, F.and Lindquist, T. M.
Uncontrolled Keywordscoding scheme, cost reduction, genetic algorithms, genetic algorithm, search space, optimal selection, power markets, standing reserve market, optimal contracting strategy
DepartmentsFaculty of Engineering & Design > Electronic & Electrical Engineering
RefereedNo
StatusPublished
ID Code6032

Export

Actions (login required)

View Item