Publication Type
Journal Article
Version
submittedVersion
Publication Date
4-2019
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, energy storage, negative electricity prices, real options
Discipline
Environmental Sciences | Operations and Supply Chain Management
Research Areas
Operations Management
Publication
Production and Operations Management
Volume
28
Issue
4
First Page
970
Last Page
989
ISSN
1059-1478
Identifier
10.1111/poms.12946
Publisher
INFORMS
Embargo Period
9-21-2016
Citation
ZHOU, Yangfang (Helen); SCHELLER-WOLF, Alan; SECOMANDI, Nicola; and SMITH, Stephen.
Managing wind-based electricity generation in the presence of storage and transmission capacity. (2019). Production and Operations Management. 28, (4), 970-989.
Available at: https://ink.library.smu.edu.sg/lkcsb_research/4958
Copyright Owner and License
Authors
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
https://doi.org/10.1111/poms.12946