Sell or Store? – An ADP Approach to Marketing Renewable Energy
34 Pages Posted: 16 Aug 2014 Last revised: 8 Feb 2017
Date Written: January 27, 2016
In deregulated markets, electricity is usually traded in advance and the advance commitments have a time lag of several periods. For example, in the German intraday market, the seller commits to providing electricity 45 minutes before the 15-minute interval in which delivery has to be made. We consider the problem of a producer that generates energy from stochastic, renewable sources, such as solar or wind, and uses a storage device with conversion losses.
We model the problem as a Markov Decision Process and consider lagged commitments for the first time in the literature. The problem is solved using an innovative approximate dynamic programming approach. Its key elements are the analytical derivation of the optimal action based on the value function approximation, and a new combination of approximate policy iteration with classical backward induction. The new approach is quite general with regard to the stochastic processes describing the energy production and price evolution. We demonstrate the application of our approach by considering a wind farm/storage combination.
A numerical study using real world data shows the applicability and performance of the new approach and investigates how the storage device’s parameters influence profit.
Keywords: electricity, renewable energy, storage, dynamic programming
JEL Classification: Q42, C44
Suggested Citation: Suggested Citation