Model Predictive Control Design for Unlocking the Energy Flexibility of Heat Pump and Thermal Energy Storage Systems

TL;DR

The paper tackles enabling demand-side management for heat pump and thermal energy storage systems by exploiting thermal storage flexibility through a model predictive control framework. It introduces a two-step DSM approach: flexibility assessment, modeled as an MPC with auxiliary linear constraints to quantify feasible DR duration, and flexibility exploitation, where grid DR requests are satisfied via a standard mixed-integer MPC while ensuring feasibility. The authors develop a control-oriented HPTES model featuring a bilinear COP for the heat pump and a stratified multi-layer TES, along with constraints to limit HP switching, and validate the method with simulations on a real installation showing DR capability without compromising hot-water delivery or safety. The results indicate that energy flexibility can be systematically quantified and reliably exploited to reduce grid energy usage, offering a practical pathway for BMS integration and grid-supportive building operation.

Abstract

Heat pump and thermal energy storage (HPTES) systems, which are widely utilized in modern buildings for providing domestic hot water, contribute to a large share of household electricity consumption. With the increasing integration of renewable energy sources (RES) into modern power grids, demand-side management (DSM) becomes crucial for balancing power generation and consumption by adjusting end users' power consumption. This paper explores an energy flexible Model Predictive Control (MPC) design for a class of HPTES systems to facilitate demand-side management. The proposed DSM strategy comprises two key components: i) flexibility assessment, and ii) flexibility exploitation. Firstly, for flexibility assessment, a tailored MPC formulation, supplemented by a set of auxiliary linear constraints, is developed to quantitatively assess the flexibility potential inherent in HPTES systems. Subsequently, in flexibility exploitation, the energy flexibility is effectively harnessed in response to feasible demand response (DR) requests, which can be formulated as a standard mixed-integer MPC problem. Numerical experiments, based on a real-world HPTES installation, are conducted to demonstrate the efficacy of the proposed design.

Figures (9)

• Figure 1: Diagram of the considered general HPTES system.
• Figure 2: Heat flow diagram of a single layer of TES.
• Figure 3: Diagram of the two-step DSM scheme.
• Figure 4: Schematic of the logic in \ref{['eq:flexi_cons']} indicating flexibility periods.
• Figure 5: Motivating example of an HPTES system for our numerical case-study.