A lightweight numerical model for predictive control of borehole thermal energy storages

TL;DR

This paper introduces a simplified yet accurate numerical model for borehole thermal energy storage that enables effective model predictive control, optimizing energy use while maintaining computational efficiency.

Contribution

It presents a novel linear-quadratic model for BTES that balances accuracy with ease of solving the optimal control problem.

Findings

The model accurately predicts BTES behavior.

The linear-quadratic formulation simplifies control optimization.

Potential for improved energy management in buildings.

Abstract

Borehole thermal energy storage (BTES) can reduce the operation of fossil fuel-based heating, ventilation, and air conditioning systems for buildings. With BTES, thermal energy is stored via a borehole heat exchanger in the ground. Model predictive control (MPC) may maximize the use of BTES by achieving a dynamic interaction between the building and BTES. However, modeling BTES for MPC is challenging, and a trade-off between model accuracy and an easy-to-solve optimal control problem (OCP) must be found. This manuscript presents an accurate numerical model yielding an easy-to-solve linear-quadratic OCP.