Offset-Free Model Predictive Control of a Heat Pump

This article presents a 125-day experiment to investigate model predictive heat pump control. The experiment was performed in two parallel operated systems with identical components during the heating season. One of the systems was operated by a standard controller and thus represented a reference to evaluate the model predictive control. Both test rigs were heated by an air-source heat pump which is influenced by real weather conditions. A single-family house model depending on weather measurement data ensured a realistic heat consumption in the test rigs. The adapted model predictive control algorithm aimed to minimize the operational costs of the heat pump. The evaluation of the measurement results showed that the electrical energy demand of the heat pump can be reduced and the coefficient of performance can be increased by applying the model predictive controller. Furthermore, the self-consumption of photovoltaic electricity, which is calculated by means of a photovoltaic model and global radiation measurement data, was more than doubled. Consequently, the energy costs of heat pump operation were reduced by 9.0% in comparison to the reference and assuming German energy prices. The results were further compared to the scientific literature and short-term measurements were performed with the same experimental setup. The dependence of the measurement results on the weather conditions and the weather forecasting quality are shown. It was found that the duration of experiments should be as long as possible for a comprehensive evaluation of the model predictive control potential.

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Optimization-Based Control Concept with Feed-in and Demand Peak Shaving for a PV Battery Heat Pump Heat Storage System

Energies ◽

10.3390/en12112098 ◽

2019 ◽

Vol 12 (11) ◽

pp. 2098 ◽

Cited By ~ 5

Author(s):

Ronny Gelleschus ◽

Michael Böttiger ◽

Thilo Bocklisch

Keyword(s):

Model Predictive Control ◽

Heat Pump ◽

Predictive Control ◽

Degrees Of Freedom ◽

Heat Storage ◽

Storage System ◽

Energy Storage System ◽

Electricity Sector ◽

Storage Device ◽

Flexibility Options

The increasing share of renewable energies in the electricity sector promotes a more decentralized energy supply and the introduction of new flexibility options. These flexibility options provide degrees of freedom that should be used optimally. Therefore, in this paper, a model predictive control-based multi-objective optimizing energy management concept for a hybrid energy storage system, consisting of a photovoltaics (PV) plant, a battery, and a combined heat pump/heat storage device is presented. The concept’s objectives are minimal operation costs and reducing the power exchanged with the electrical grid while ensuring user comfort. In order to prove the concept to be viable and its objectives being fulfilled, investigations based on simulations of one year of operation have been carried out. Comparisons to a simple rule-based strategy and the same model predictive control scheme with ideal forecasts prove the concept’s viability while showing improvement potential in the treatment of nonlinear system behavior, caused by nonlinear battery losses, and of forecast uncertainties.

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