Meeting Inelastic Demand in Systems with Storage and Renewable Sources

Soongeol Kwon, Yunjian Xu, Natarajan Gautam

Research output: Contribution to journalArticlepeer-review

29 Scopus citations

Abstract

We consider a system where inelastic demand for electric power is met from three sources: 1) the grid; 2) in-house renewables such as solar panels; and 3) an in-house energy storage device. In our setting, energy demand, renewable power supply, and cost for grid power are all time-varying and stochastic. Furthermore, there are limits and inefficiency associated with charging and discharging the energy storage device. We formulate the storage operation problem as a dynamic program with parameters estimated from real-world demand, supply, and cost data. As the dynamic program is computationally intensive for large-scale problems, we explore algorithms based on approximate dynamic programming (ADP) and apply them to a test data set. Using the real-world test data, we numerically compare the performance of two ADP-based algorithms against Lyapunov optimization-based algorithms that require no statistical knowledge. Our results ascertain the value of storage and the value of installing a renewable source.

Original languageEnglish (US)
Pages (from-to)1619-1629
Number of pages11
JournalIEEE Transactions on Smart Grid
Volume8
Issue number4
DOIs
StatePublished - Jul 2017
Externally publishedYes

Keywords

  • Approximate dynamic programming
  • energy storage
  • look-Ahead policies
  • renewable generation
  • solar PV

ASJC Scopus subject areas

  • Computer Science(all)

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