Smart Control Strategies for Heat Pump Systems

A new perspective for improving the heat pump system performance can be given by the development of enhanced system control strategies able to achieve a considerable increase of the system Seasonal Performance Factor together with a reduction of operation and maintenance costs.

Project Background

Nowadays, with emergence of smart phones, credit card-sized computers, and advanced building management systems, it is feasible to improve the control of heat pump systems considerably. The new paradigm shift in control and electronics is converting the traditional control units to “smart control units” which can adapt its parameters to the boundary conditions and communicate with installer, user, or serviceman in smarter way. However, there has not been many research studies focused on making the heat pump controller smarter and capable of communicating with the other systems or actors. This proposal aims at filling this research gap by introducing an advanced control for the heat pump systems.

Project Goals

This project aims at investigating the great potential of improvement the annual efficiency of heat pump system and reduction of the annual operating cost of the system via exploiting predictive control strategies. Predictive controls can harvest and process the large amount of data available regarding the people behavior, weather forecast and electricity spot price in order to reduce the annual electricity consumption, minimize the use of electrical auxiliary heater and maximize thermal comfort in single family houses.

Implementation

To capture the dynamic and complex behavior of the heating system and the interactions among all the system components, it is essential to develop a system model. A conventional heat pump system will be selected and the system model will be developed including all the sub-models such as climate, building, building inhabitants behavior, heat pump unit, heat source (borehole ground heat exchanger or ambient air), liquid pumps, electricity spot price, central control unit. 

Heat Pump smart system conceptual model

Furthermore, a hardware-in-loop approach will be adopted to develop a standard platform to evaluate any new control strategy.

Two modeling approaches are carried out in parallel

The system model will be used to test several smart control strategies such as continuous adaptation of control parameters based on heat demand prediction and electricity spot price. Heat demand will be predicted based on numerous inputs such as weather forecast, occupancy level, domestic hot water profile, when operating under changing boundary conditions such as climate, domestic Hot Water demand and electricity prices, predictive and adaptive control methods provide high flexibility. The best control strategies will be tested in a heat pump installation.

Timeline

Summer 2016

Software modeling of single family house heating system with standard on-off control.

Beginning of hardware-in-loop system development.

Autumn 2016

State-of-art conference paper regarding advanced heat pump system controls.

Software model of representative swedish single family house heating system.

Winter 2016

Data monitoring and field measurements from at least two heat pump system currently in operation.

Spring 2017

Evaluation of different control strategies.

Development of hardware-in-loop system.

Autumn 2017

Method development and field measurement employing advanced system control.

Spring 2018

Publication of project results and conclusions.

Final Report

EffSys Expand P18: Smart Control Strategies for Heat Pump Systems (PDF)

Funding

This project is financed by The Swedish Energy Agency (Energimyndigheten) under the Effsys Expand program.

Project Partners

Project Partner Documents Folder

Contact

Davide Rolando

Researcher

davide.rolando@energy.kth.se

Brinellvägen 68, SE-100 44 Stockholm

Mobile: +46 76 416 51 81

Hatef Madani

Assistant Professor

hatef.madani@energy.kth.se

Brinellvägen 68, SE-100 44 Stockholm

Phone: +46 87 90 86 53

Page responsible:bpalm@energy.kth.se
Belongs to: Department of Energy Technology
Last changed: Nov 27, 2018