Merchant Energy Trading in a Network

作     者：Nadarajah, Selvaprabu Secomandi, Nicola 

作者机构：Univ Illinois Coll Business Adm Chicago IL 60607 USA Carnegie Mellon Univ Tepper Sch Business Pittsburgh PA 15213 USA 

出 版 物：《OPERATIONS RESEARCH》 (运筹学)

年 卷 期：2018年第66卷第5期

页      面：1304-1320页

核心收录：

学科分类：1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：National Science Foundation [CMMI 1129163] 

主　　题：merchant commodity and energy operations Markov decision processes approximate dynamic programming dual bounds energy storage real options least squares Monte Cario linear optimization 

摘      要：We formulate the merchant trading of energy in a network of storage and transport assets as a Markov decision process with uncertain energy prices, generalizing known models. Because of the intractability of our model, we develop heuristics and both lower and dual (upper) bounds on the optimal policy value estimated within Monte Carlo simulation. We achieve tractability using linear optimization, extending near optimal approximate dynamic programming techniques for the case of a single storage asset, versions of two of which are commercially available. We propose (i) a generalization of a deterministic reoptimization heuristic, (ii) an iterative version of the least squares Monte Carlo approach, and (iii) a perfect information dual bound. We apply our methods to a set of realistic natural gas instances. The combination of our reoptimization heuristic and dual bound emerges as a practical approach to nearly optimally solve our model. Our iterative least squares Monte Carlo heuristic is also close to optimal. Compared to our other heuristic, it exhibits slightly larger optimality gaps and requires some tuning, but is faster to execute in some cases. Our methods could enhance single energy storage asset software and have potential relevance beyond our specific application.