Aggregated Demand Response Modelling for Future Grid Scenarios

TL;DR

This paper introduces a demand response model incorporating aggregated user effects, enhancing future grid feasibility studies with higher renewable energy integration, demonstrated through a case study on the Australian market.

Contribution

It presents a simplified demand model that accounts for aggregated DR effects and user behavior as price anticipators, improving system study accuracy for future grids.

Findings

Demand model impacts load profile and loadability.

Model with price anticipators shows different demand patterns.

Results highlight importance of DR in high RES scenarios.

Abstract

With the increased penetration of intermittent renewable energy sources (RESs) in future grids (FGs), balancing between supply and demand will become more dependent on demand response (DR) and energy storage. Thus, FG feasibility studies will need to consider DR for modelling nett future demand. Against this backdrop, this paper proposes a demand model which integrates the aggregated effect of DR in a simplified representation of the effect of market/dispatch processes aiming at minimising the overall cost of supplying electrical energy. The conventional demand model in the optimisation formulation is augmented by including the aggregated effect of numerous users equipped with rooftop photovoltaic (PV)-storage systems. The proposed model is suited for system studies at higher voltage levels in which users are assumed to be price anticipators. As a case study, the effect of the demand model is studied on the load profile, balancing and loadability of the Australian National Electricity Market in 2020 with the increased penetration of RESs. The results are compared with the demand model in which users are assumed to be price takers.