Energy Not-Served-Based Method for Assessing Smart Grid Functions in Residential Loads

S. A. Saleh*, R. Ahshan, M. Haj-Ahmed, Julian L. Cardenas-Barrera, J. Meng, E. Castillo-Guerra

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


This article presents a method for evaluating smart grid functions that are implemented to operate residential loads. The proposed assessment method is developed based on the energy not-served (ENS) determined at a point-of-supply feeding residential loads. Smart grid functions can operate energy storage appliances (household water heaters, air conditioners, and heating units) to store thermal energy during the daily off-peak-demand hours. The stored thermal energy is discharged during the daily peak-demand hours, thus reducing the power demands of residential loads. The differences in daily energy demands created by smart grid functions can provide an accurate assessment of the effectiveness of smart grid functions. The ENS-based method is tested for 200 residential households fed from four distribution transformers, and are operated by smart grid functions. In these tests, smart grid functions are implemented by the peak-demand management, direct load control, and demand response. Test results demonstrate the accuracy and simplicity of the ENS-based method to assess smart grid functions in terms of the ability to reduce the power demands of residential loads during peak-demand hours.

Original languageEnglish
Pages (from-to)1720-1729
Number of pages10
JournalIEEE Transactions on Industry Applications
Issue number2
Publication statusPublished - 2022


  • Distribution power transformers
  • energy not-served (ENS)
  • load-side control actions
  • residential loads
  • smart grid functions

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


Dive into the research topics of 'Energy Not-Served-Based Method for Assessing Smart Grid Functions in Residential Loads'. Together they form a unique fingerprint.

Cite this