Impact of Model Predictive Control-Enabled Home Energy Management on Large-Scale Distribution Systems with Photovoltaics

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15 Scopus Citations

Abstract

Residential customers use more than one-quarter of the electricity in the world. Optimally managing home energy consumption is an effective way of easing the operational challenges facing the electric grid with increasing solar photovoltaics (PV). This paper studies the impact of the future proliferation of home energy management systems (HEMS) in the presence of PV on large-scale distribution systems. First, we present a stochastic HEMS model that minimizes residential customers’ thermal discomfort and energy costs under uncertainty. The HEMS model schedules the optimal operations of residential appliances in the presence of PV within a mixed-integer linear programming-based model predictive control framework that links the proposed HEMS to a quasi-steady-state time-series simulation tool. Extensive simulations are conducted for a stand-alone residential home using two tariff structures and for 1977 homes on an 8,500-node distribution feeder. Simulation results quantify the impact of the future proliferation of HEMS on the large-scale distribution system with PV.

Original languageAmerican English
Article number100094
Number of pages11
JournalAdvances in Applied Energy
Volume6
DOIs
StatePublished - 2022

Bibliographical note

Publisher Copyright:
© 2022

NREL Publication Number

  • NREL/JA-5D00-81969

Keywords

  • Co-simulation
  • Electric vehicle
  • Home energy management system
  • Model predictive control
  • Photovoltaic
  • Stochastic optimization

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