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, https://unidirectory.auckland.ac.nz/profile/g-zakeri
Geoff Pritchard: Electric Power Optimization Centre, University of Auckland, Postal: University of Auckland, Electric Power Optimization Centre, Private Bag 92019, Auckland 1142, New Zealand, https://www.stat.auckland.ac.nz/~geoff/
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, https://www.nhh.no/en/employees/faculty/mette-helene-bjorndal/
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
Authors registered in the RePEc Author Service: Endre Jostein Bjørndal

No 2016/15, Discussion Papers from Norwegian School of Economics, Department of Business and Management Science

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 (search for similar items in EconPapers)
JEL-codes: C60 L10 L94 (search for similar items in EconPapers)
Pages: 15 pages
Date: 2016-09-06
New Economics Papers: this item is included in nep-ene
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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