A Stochastic Optimal Control Approach for Exploring Tradeoffs between Cost Savings and Battery Aging in Datacenter Demand Response

Abdullah Al Mamun, Iyswarya Narayanan, Di Wang, Anand Sivasubramaniam, Hosam K. Fathy

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

This brief paper optimizes power management for datacenters employing lithium-ion battery storage, with the specific goal of addressing the tradeoff between: 1) the cost saving achievable through the peak demand shaving and 2) the corresponding battery aging. To the best of the authors' knowledge, this tradeoff has never been addressed using physics-based models of battery performance and degradation combined with stochastic models of datacenter demand. We build: 1) a Markov chain model of datacenter power demand; 2) a second-order model of battery diffusion/reaction dynamics; and 3) a physics-based model of battery aging via solid electrolyte interphase growth. Together, these models enable the solution of the battery health-conscious demand response problem via stochastic dynamic programming (SDP). A penalty function is used for enforcing a datacenter "power cap" within this SDP problem. By varying this power cap, we traverse the Pareto tradeoff between the cost savings due to demand response and battery health degradation.

Original languageEnglish (US)
Article number7812654
Pages (from-to)360-367
Number of pages8
JournalIEEE Transactions on Control Systems Technology
Volume26
Issue number1
DOIs
StatePublished - Jan 2018

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering

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