Quantification of Residential Flexibility Potential using Global Forecasting Models

TL;DR

This paper introduces a global forecasting approach to quantify residential flexibility potential and economic benefits of load control without historical data, using non-parametric models for electric water heaters and heat pumps.

Contribution

It presents a novel method combining forecasting and optimization to estimate flexibility and economic gains without relying on past observations.

Findings

Forecasting accuracy enables direct economic benefit estimation.

Flexibility including rebound effects can be effectively characterized.

Method applied successfully to electric water heaters and heat pumps.

Abstract

This paper proposes a general and practical approach to estimate the economic benefits of optimally controlling deferrable loads in a Distribution System Operator's (DSO) grid, without relying on historical observations. We achieve this by learning the simulated response of flexible loads to random control signals, using a non-parametric global forecasting model. An optimal control policy is found by including the latter in an optimization problem. We apply this method to electric water heaters and heat pumps operated through ripple control and show how flexibility, including rebound effects, can be characterized and controlled. Finally, we show that the forecaster's accuracy is sufficient to completely bypass the simulations and directly use the forecaster to estimate the economic benefit of flexibility control.