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Prediction markets to forecast electricity demand

Authors: Luciano I. de Castro; Peter Cramton;

Prediction markets to forecast electricity demand

Abstract

Forecasting electricity demand for future years is an essential step in resource planning. A common approach is for the system operator to predict future demand from the estimates of individual distribution companies. However, the predictions thus obtained may be of poor quality, since the reporting incentives are unclear. We propose a prediction market as a form of forecasting future demand for electricity. We describe how to implement a simple prediction market for continuous variables, using only contracts based on binary variables. We also discuss specific issues concerning the implementation of such a market.

Keywords

forecast of future demand, ddc:330, mechanism design of capacity markets, prediction market for continuous variables, winner-takes-all contract, D51, D6, D8 [Forecast of electricity demand, power generation planning, implementation of prediction markets, forecast of future demand, mechanism design of capacity markets, prediction market for continuous variables, winner-takes-all contract, index contract. JEL Classification Numbers], forecast of electricity demand, implementation of prediction markets, electricity market design, prediction markets, index contract, power generation planning, jel: jel:D44

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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