Optimal Thermostat Programming for Time-of-Use and Demand Charges with Thermal Energy Storage and Optimal Pricing for Regulated Utilities

Reza Kamyar, Matthew Peet

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

In this paper, we solve the optimal thermostat programming problem for consumers with combined demand (/kW) and time-of-use (/kWh) pricing plans. We account for energy storage in interior floors and surfaces by using a partial-differential model of diffusion. We consider two types of thermostats: the first can be programmed to vary continuously in time and the second is limited to four constant set-points. Thermostat settings were constrained to lie within a desired interval. Numerical testing shows that the resulting algorithm can reduce monthly electricity bills by up to 25% in the summer with average savings of 9.2% over a variety of building models by using prices from Arizona utility Salt River Project. Furthermore, we examine how optimal thermostat programming affects optimal electricity pricing by using a simplified model of utility generation costs to determine the optimal ratio of demand to time-of-use prices. Our results show that pricing electricity at the marginal cost of generation in this scenario is suboptimal.

Original languageEnglish (US)
Article number7592920
Pages (from-to)2714-2723
Number of pages10
JournalIEEE Transactions on Power Systems
Volume32
Issue number4
DOIs
StatePublished - Jul 2017

Keywords

  • Demand charges
  • dynamic programming
  • thermal energy storage
  • thermostat programming

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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