A Kullback-Leibler Divergence-based Distributionally Robust Optimization Model for Heat Pump Day-ahead Operational Schedule in Distribution Networks

TL;DR

This paper proposes a distributionally robust optimization model based on Kullback-Leibler divergence to improve the day-ahead operational scheduling of heat pumps in distribution networks, addressing peak load issues.

Contribution

It introduces a novel optimization framework that accounts for uncertainty in heat pump operation, enhancing grid stability and efficiency.

Findings

Improved peak load management in distribution networks.

Enhanced robustness of heat pump scheduling under uncertainty.

Potential reduction in operational costs and emissions.

Abstract

For its high coefficient of performance and zero local emissions, the heat pump (HP) has recently become popular in North Europe and China. However, the integration of HPs may aggravate the daily peak-valley gap in distribution networks significantly.