Title :
Intelligent systems for dynamic price forecasting in a competitive electricity market
Author :
Pany, Prasanta Kumar ; Ghosa, S.P.
Author_Institution :
DRIEMS, Cuttack, India
Abstract :
The electric power industry in many countries all around the world is evolving into an era of market economy with deregulation and free competition. The understanding of electric power supply as a public service is being replaced by the notion that a competitive market is a more appropriate mechanism to supply energy to consumers with high reliability and low cost. A key element of the electricity sector restructuring is the establishment of a market-driven price for electricity. The pricing system of electricity plays an important role in a competitive market. In the power market, the electricity price depends on the evolution of balance between the demand for electricity and the available supply. At the same time, many other market factors also influence the electricity price, such as economic growth, weather, the power-plant mix, the prices of fuels and the strategic behavior of large players (usually on the generation side). An active, fully competitive and liquid spot market for wholesale electricity will translate the physical risk of inadequate capacity into a financial risk of high prices and place higher requirements on price forecasting. Producers and consumers rely on price-forecasting information to propose their corresponding bidding strategies. If a producer has an accurate forecast of the prices, it can develop a bidding strategy to maximize its profit. On the other hand, a consumer can make a plan to minimize his own electricity cost if an accurate price forecast is available.
Keywords :
financial management; load forecasting; power generation economics; power markets; pricing; profitability; risk management; bidding strategy; dynamic price forecasting; electric power industry; electric power supply; financial risk; intelligent system; market driven electricity price; profit maximization; public service; Conferences; Electricity supply industry; Forecasting; Industrial electronics; Intelligent systems; Service robots; autoregressive moving average; conventional wavelet neural network; dilation and translation; lolac linear wavelet neural network;
Conference_Titel :
Industrial Electronics, Control & Robotics (IECR), 2010 International Conference on
Conference_Location :
Orissa
Print_ISBN :
978-1-4244-8544-4
DOI :
10.1109/IECR.2010.5720172