Generic demand model considering the impact of prosumers for future grid scenario analysis

Shariq Riaz, Hesamoddin Marzooghi, Gregor Verbic, Archie C. Chapman, David J. Hill

Research output: Contribution to journalArticleResearchpeer-review

40 Citations (Scopus)

Abstract

The increasing uptake of residential PV-battery systems is bound to significantly change demand patterns of future power systems and, consequently, their dynamic performance. In this paper, we propose a generic demand model that captures the aggregated effect of a large population of price-responsive users equipped with small-scale PV-battery systems, called prosumers, for market simulation in future grid scenario analysis. The model is formulated as a bi-level program in which the upper-level unit commitment problem minimizes the total generation cost, and the lower-level problem maximizes prosumers' aggregate self-consumption. Unlike in the existing bi-level optimization frameworks that focus on the interaction between the wholesale market and an aggregator, the coupling is through the prosumers' demand, not through the electricity price. That renders the proposed model market structure agnostic, making it suitable for future grid studies where the market structure is potentially unknown. As a case study, we perform steady-state voltage stability analysis of a simplified model of the Australian National Electricity Market with a significant penetration of renewable generation. The simulation results show that a high prosumer penetration changes the demand profile in ways that significantly improve the system loadability, which confirms the suitability of the proposed model for future grid studies.

Original languageEnglish
Pages (from-to)819-829
Number of pages11
JournalIEEE Transactions on Smart Grid
Volume10
Issue number1
DOIs
Publication statusPublished - Jan 2019
Externally publishedYes

Keywords

  • aggregators
  • bi-level optimization
  • Demand response
  • future grids
  • generic demand model
  • prosumers
  • PV-battery systems
  • scenario analysis

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