Taylor, James (2006) Density Forecasting for the Efficient Balancing of the Generation and Consumption of Electricity. International Journal of Forecasting, 22 (4). pp. 707-724.
The transmitters of electricity in Great Britain are responsible for balancing generation and consumption. Although this can be done in the hour between closure of the market and real-time, off-loading or calling-up electricity at this late stage can be costly. Costs can be substantially reduced if the imbalance can be anticipated ahead of time and balanced by trading on the market. Efficient trading relies on accurate density forecasts for the Net Imbalance Volume, which is defined as the sum of all actions taken to balance the system. Forecasting this density is the focus of this paper. We break down the problem into point and volatility prediction. We evaluate density forecasts in terms of the economic benefit generated from trading advice resulting from the forecasts. Promising results were achieved using a seasonal ARMA model or a periodic AR model for point forecasting, with a simplistic approach to volatility forecasting.
|Keywords:||Electricity markets; Volatility forecasting; Density forecasting; Seasonality; Periodic models; Economic value|
|Centre:||Faculty of Management Science|
|Date Deposited:||05 Feb 2012 15:01|
|Last Modified:||23 Oct 2015 14:06|
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