Title :
Modeling of electricity prices
Author :
Yunhe Hou ; He, Yang
Author_Institution :
Dept. of Electr. & Electron. Eng., Univ. of Hong Kong, Hong Kong, China
Abstract :
This is a summary of the presentation in the special session: “Digital Signal Processing for Green Power Systems and Delivery”. The power sectors in various countries have established competitive markets for an industry that, for decades, consists of utility companies that own and operate generation, transmission and distribution systems. The objective of deregulation in power industry is to enhance the efficiency of power energy. With the liberalization of electric power industry, electricity price is widely recognized as a signal of electricity supply, consumption, and investment. Although the mechanisms that determine electricity prices are known, random events such as contingencies and congestive conditions of transmission lines can cause uncertainties. Therefore, it is difficult to develop analytical models for electricity prices that can be used by market or system planners and investors in their decision making process. The purpose of this paper is to introduce models of electricity prices that can be used by different market participants.
Keywords :
digital signal processing chips; power markets; power transmission lines; Green power systems; competitive electricity market; decision making process; digital signal processing; electric power industry liberalization; electricity price; electricity supply; power energy; power industry deregulation; transmission lines; Electricity supply industry; Electricity supply industry deregulation; Energy consumption; Investments; Power generation; Power industry; Power system modeling; Power transmission lines; Signal processing; Uncertainty; Electricity Prices; Stochastic Process; Time series;
Conference_Titel :
Green Circuits and Systems (ICGCS), 2010 International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4244-6876-8
Electronic_ISBN :
978-1-4244-6877-5
DOI :
10.1109/ICGCS.2010.5543002