Smoothing Net Load Demand Variations Using Residential Demand Management

Fadi Elghitani, Ehab El-Saadany

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

Abstract

One of the major obstacles facing the large-scale integration of renewable energy sources to existing power networks is the large magnitude of fluctuations and uncertainties introduced to aggregated demand profiles. Such variations make the supply-demand matching a more challenging task, and increase the operational cost of the power system. In this paper, we provide an effective, yet simple, methodology for smoothing power variations using the demand response of a large number of residential appliances. We first present a demand aggregation model based on queueing theory that can accommodate both deferrable and thermostatically controlled loads. Second, controllable demands are scheduled using an online algorithm to smooth the net noncontrollable demand profile. The performance of our methodology is evaluated using realistic data.

Original languageBritish English
Article number8401890
Pages (from-to)390-398
Number of pages9
JournalIEEE Transactions on Industrial Informatics
Volume15
Issue number1
DOIs
StatePublished - Jan 2019

Keywords

  • Aggregation model
  • demand management
  • Lyapunov optimization
  • renewable energy sources (RES)
  • residential appliances

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