Scandinavian Working Papers in Economics

Discussion Papers,
Norwegian School of Economics, Department of Business and Management Science

No 2016/15: Pricing wind: A revenue adequate, cost recovering uniform price for electricity markets with intermittent generation

Golbon Zakeri (), Geoff Pritchard (), Mette Bjørndal () and Endre Bjørndal ()
Additional contact information
Golbon Zakeri: Electric Power Optimization Centre, University of Auckland, Postal: University of Auckland, Electric Power Optimization Centre, Private Bag 92019, Auckland 1142, New Zealand
Geoff Pritchard: Electric Power Optimization Centre, University of Auckland, Postal: University of Auckland, Electric Power Optimization Centre, Private Bag 92019, Auckland 1142, New Zealand
Mette Bjørndal: Dept. of Business and Management Science, Norwegian School of Economics, Postal: NHH , Department of Business and Management Science, Helleveien 30, N-5045 Bergen, Norway
Endre Bjørndal: Dept. of Business and Management Science, Norwegian School of Economics, Postal: NHH , Department of Business and Management Science, Helleveien 30, N-5045 Bergen, Norway

Abstract: With greater penetration of renewable generation, the uncertainty faced in electricity markets has increased substantially. Conventionally, generators are assigned a pre-dispatch quantity in advance of real time, based on estimates of uncertain quantities. Expensive real time adjustments then need to be made to ensure demand is met, as uncertainty takes on a realization. We propose a new stochastic-programming market clearing mechanism to optimize pre-dispatch quantities, given the uncertainties’ probability distribution and the costs of real-time deviation. This model differs from similar mechanisms previously proposed in that pre-dispatch quantities are not subject to any network or other physical constraints; nor do they play a role in financial settlement. We establish revenue adequacy in each scenario (as opposed to “in expectation”), welfare enhancement and expected cost recovery (including deviation costs), for this market clearing mechanism. We also establish that this market clearing mechanism is social welfare optimizing.

Keywords: Stochastic programming; locational pricing; wind power; regulation

JEL-codes: C60; L10; L94

15 pages, September 6, 2016

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