An Agent-based computational economics model of the National Electricity Market of Singapore.

Abstract

Electricity markets in countries around the world are being restructured in pursuit of economic efficiency through competition. However, volatility in electricity prices and previous occurrences of market failure have indicated a need to better understand the complex interactions between the various market participants as well as to design market rules that maximizes efficiency and security. In this project, the techniques of Agent-based Computational Economics are employed to simulate the behavior of the participants in the National Electricity Market of Singapore (NEMS) in order to understand the ways in which they may react to changes in the underlying economic, financial, and regulatory environment. The main contributions of this thesis are (a) the development and test of a novel learning algorithm that more realistically models Generator Company's behavior and (b) a simulation platform designed for the NEMS.