Managing Wind-Based Electricity Generation in the Presence of Storage and Transmission Capacity

43 Pages Posted: 25 Nov 2011 Last revised: 7 Aug 2018

See all articles by Yangfang Zhou

Yangfang Zhou

Singapore Management University - Lee Kong Chian School of Business

Alan Andrew Scheller-Wolf

Carnegie Mellon University

Nicola Secomandi

Carnegie Mellon University - David A. Tepper School of Business

Stephen Smith

Carnegie Mellon University - School of Computer Science

Date Written: August 4, 2018

Abstract

We investigate the management of a merchant wind energy farm co-located with a grid-level storage facility and connected to a market through a transmission line. We formulate this problem as a Markov decision process (MDP) with stochastic wind speed and electricity prices. Consistent with most deregulated electricity markets, our model allows these prices to be negative. As this feature makes it difficult to characterize any optimal policy of our MDP, we show the optimality of a stage- and partial-state-dependent-threshold policy when prices can only be positive. We extend this structure when prices can also be negative to develop heuristic one (H1) that approximately solves a stochastic dynamic program. We then simplify H1 to obtain heuristic two (H2) that relies on a price-dependent-threshold policy and derivative-free deterministic optimization embedded within a Monte Carlo simulation of the random processes of our MDP. We conduct an extensive and data-calibrated numerical study to assess the performance of these heuristics and variants of known ones against the optimal policy, as well as to quantify the effect of negative prices on the value added by and environmental benefit of storage. We find that (i) H1 computes an optimal policy and on average is about 17 times faster to execute than directly obtaining an optimal policy; (ii) H2 has a near optimal policy (with a 2.86% average optimality gap), exhibits a two orders of magnitude average speed advantage over H1, and outperforms the remaining considered heuristics; (iii) storage brings in more value but its environmental benefit falls as negative electricity prices occur more frequently in our model.

Keywords: Markov decision process, wind-based electricity generation, electricity storage, negative prices

Suggested Citation

Zhou, Yangfang and Scheller-Wolf, Alan Andrew and Secomandi, Nicola and Smith, Stephen, Managing Wind-Based Electricity Generation in the Presence of Storage and Transmission Capacity (August 4, 2018). Available at SSRN: https://ssrn.com/abstract=1962414 or http://dx.doi.org/10.2139/ssrn.1962414

Yangfang Zhou (Contact Author)

Singapore Management University - Lee Kong Chian School of Business ( email )

50 Stamford Road
Singapore 178899
Singapore

Alan Andrew Scheller-Wolf

Carnegie Mellon University ( email )

Pittsburgh, PA 15213-3890
United States

Nicola Secomandi

Carnegie Mellon University - David A. Tepper School of Business ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213-3890
United States

Stephen Smith

Carnegie Mellon University - School of Computer Science ( email )

5000 Forbes Avenue
Pittsburgh, PA 15213
United States

Register to save articles to
your library

Register

Paper statistics

Downloads
330
Abstract Views
1,444
rank
92,961
PlumX Metrics