Long-term Value of Flexibility from Flexible Assets in Building Operation

TL;DR

This paper evaluates the long-term value of flexible assets in building operations using a mathematical model and case study, demonstrating how smart control can reduce peak demand and costs under different tariffs.

Contribution

It introduces a stochastic dynamic programming model for optimizing flexible building assets considering long-term costs and peak tariffs, with a case study on a Norwegian building.

Findings

EV charging reduces peak power and electricity costs by 14.6% under MPGT.

The EFCC model optimizes peak demand timing and level.

Smart control of flexible assets enhances cost savings.

Abstract

In this work, we investigate how flexible assets within a residential building influence the long-term impact of operation. We use a measured-peak grid tariff (MPGT) that puts a cost on the highest single-hour peak import over the month. We apply a mathematical model of a Home Energy Management System (HEMS) together with Stochastic Dynamic Programming (SDP), which calculates the long-term impact of operating as a non-linear expected future cost curve (EFCC) from the end of the scheduling period to the start. The proposed model is applied to a case study for a Norwegian building with smart control of a battery energy storage system (BESS), Electric vehicle (EV) charging and space heating (SH). Each of the flexible assets are investigated individually with MPGT and for an energy-based grid tariff. The results showed that EV charging has the highest peak-power impact in the system, decreasing the total electricity cost by 14.6% with MPGT when controllable compared to a reference case with passive charging. It is further shown how the EFCC helps achieve optimal timing and level of the peak demand, where it co-optimizes both real-time pricing and the MPGT.