1. Final report
Smart & Cool Project
WP1: Control Methods for Energy Balancing via
Consumption in Supermarket Refrigeration Systems
Seyed Ehsan Shafiei
November 15, 2014
1 Contribution to Society
The modern life, especially in developed countries, are more and more relying on availability of
electricity, almost everywhere. In US, the electricity use would increase by 0.9% per year, from
3,826 TWh in 2012 to 4,954 TWh in 2040 [1]. Similarly in Europe (Eu27+), it would increase
by 1.2% per year from 3,043 TWh in 2008 to 4,300 TWh in 2050 [2]. The huge energy use
all around the world has resulted in tremendous CO2 emissions and consequently the problem of
global warming that threats our planet. One solution to respond to the energy demand in a clean
way is to integrate the renewable energy resources such as wind and solar energy into the electricity
generation sector.
On the other hand, the volatility nature of the renewable recourses may affect the stability of the
electricity power grid in terms of the imbalance between the power generation and consumption.
The Smart & Cool project aims at addressing this problem by coordination of the power genera-
tion and consumption, such that the balance of energy in the grid is preserved. The focus of the
work package 1 is on the energy management at the consumer side, specifically for supermarket
refrigeration systems.
Another important factor in offering a clean and environmentally friendly solution is the energy
efficiency of the consumer units. For this purpose, at this work package, we try to improve the
energy efficiency of the refrigeration systems to the highest possible level as well as performing
the energy management.
From research point of view, the project is in line with the Danish strategic research towards green
and smart energy systems. It can help Denmark keep going as one of the leading countries using
renewable resources within a stable power grid providing high quality electricity to the energy
consumers. Collaborating with industrial partners who support the project, especially Danfoss
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2. for this work package, would keep the Danish industry on the track of innovation. The latter is
particularly important as can open up new opportunities for future investments that may lead to
new opportunities for researchers, job seekers and entrepreneurs.
This work package is seeking solutions for energy management of refrigeration systems in the
smart grid. In general, the research topic is within the field of control theory and applications,
but it is actually a multidisciplinary area requiring different knowledge such as thermodynamics,
mathematical modeling, system identification, control theory and optimization. The chief goal of
the project is not to extend and develop the theories, but instead the relevant theories and methods
already developed in those different fields are applied to find a state-of-the-art solutions for this
specific application problem.
A mathematical model of supermarket refrigeration systems is created using thermodynamic prin-
ciples and modeling and parameter estimation methods. Such a model can be utilized by companies
to explore different scenarios and new applications in a short period of time without using an ex-
pensive laboratory and spending too much manpower/hour. For example, by integration of several
supermarket models with different sizes into a simulation environment, it is possible to examine
the capacity provided by aggregation of those supermarkets in terms of the energy usage flexibility.
A similar investigation by doing a real life experiment, if not impossible, requires several (maybe
hundreds) supermarkets available for test and it may take up to couple of years.
It is also shown how advanced control strategies can be employed to manage the energy consump-
tion of the system while respecting the daily operation and practical limitations. Depending on the
availability of model or data, and also the type of the grid level service that needs to be provided
by the consumer, different control solutions are proposed. Finally, an advanced control strategy is
proposed that can avoid the complexity involved in the similar designs and at the same time can
keep up the performance at a very satisfactory level.
Although the main focus of this work package is to make refrigeration systems one of the smart
actors in the future smart grid, the methods explored here can be applied to other thermal systems
like heat pumps, HVAC, etc with some degree of modifications.
2 Key Performance Indicators
In order to evaluate the achievements of this PhD project, some measures are required. Some
of them can be quantized for which concrete measures can be defined. But there are also some
achievements that can only be assessed qualitatively.
• Publications
For a three-year PhD project, it seems reasonable to publish 4 conference papers and 2
journal articles
• Collaboration with industry
Industrial partner of the projects should benefit from the results
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3. • Collaboration with another academic groups
The knowledge exchange between the research group that performing the project and the
group that student visits during the study abroad
• Maturity in doing high quality research
After doing the PhD project, it is expected that the student be matured enough to do high
quality research (hard to measure quantitatively)
3 Collaboration with Industrial Partner
Amongst the industrial partners of the project, Danfoss Air-Conditioning & Refrigeration was
particularly interested in this work package. The collaboration with Donfoss was started after the
first project meeting held at the beginning of starting the current work package. Roozbeh Izadi-
Zamanabadi and Torben Green were the contact persons for Smart & Cool.
The first phase of this PhD project was planned to create a mathematical model of a supermarket
refrigeration system for model based control design and for simulation purposes. Danfoss provided
data from a supermarket refrigeration system in Denmark through another project called ESO2
[3]. Those data could help a lot understanding the system dynamics and validating the developed
model.
After around a year from starting the project, I visited the company for a period of three months.
Together with Roozbeh, we could propose a practical and simple method for direct load control
of refrigeration systems at a supervisory level without needing to replace the local controllers.
Danfoss showed interest in the method and went ahead with filing a joined patent together with
Aalborg University [4]. This patent presents a control method including several proportional-
integral (PI) regulators equipped with anti-windup loops that is responsible to regulate the electrical
power consumption of the compressors to the assigned set-point. In order to respect the food
temperature limits, an adaptive saturation filter is proposed. This method does not need any model
of the system for practical implementations. Fig. 1 shows the test setup at Danfoss employed for
proof of concept for this patent application.
Another problem that we worked on it together with Roozbeh was to estimate the thermal capacity
of foodstuff in display cases. The energy management of refrigeration systems in the smart grid
relies on the thermal capacity of the foodstuffs inside the cooling units. The thermal capacity can
be estimated using a mathematical model and different measurements including the food tempera-
tures. But the problem is that the food temperature measurements are not available in commercial
applications. Fig. 2a shows the display cases filled with different containers. The blue containers
including the materials with freezing point around -30 ◦C to avoid the phase change process in
low temperature display cases that may be cooled down to -25 ◦C. The red liquid containers are
for medium temperature display cases. The temperature sensors placed on the surface and inside a
thermal mass is shown in Fig. 2b. The proposed method only uses available measurements such as
the air temperatures for commercial applications and does not need the expensive food temperature
measurements. The food temperature sensors in the setup are used for validation of the proposed
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4. Figure 1: The test setup of a refrigeration system at Danfoss. The setup includes 4 medium tem-
perature and 4 low temperature display cases. The system is operated by local controllers produced
by Danfoss. Supervisory controllers can be designed and implemented in the PCs placed in front
of the setup.
method. This new method was also found interesting by Danfoss and they filed another joined
patent together with Aalorg University afterwards [5].
(a) (b)
Figure 2: The test setup of a refrigeration system at Danfoss. (a) Display cases filled with contain-
ers. (b) Food temperature sensor.
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5. Apart from the patents and those specific works, whenever I had an idea that was discussed with the
supervisors, I also brought them up to Danfoss contacts and asked for their practical and industrial
opinions. I could usually receive very valuable feedbacks by doing so.
4 Dissemination and Public Presentations
The achievements and results at different phases of the project are published in nine proceedings
of reputable conferences in the relevant areas [6–14] as well as three journals [15–17]. However,
two of the journal articles are still under review process and not yet published [16,17].
Many control projects start with building a mathematical model of the system which would be
the subject of control. In this work package, a mathematical model of a supermarket refrigeration
system was developed [7,15] that can be used for example for
— Understanding the physical behavior of the system.
During the model development, the physical behavior of the system is investigated where
information about the systems operation in different conditions are obtained.
— Simulation purposes.
It is especially useful for supermarket systems that are usually not available for testing.
Moreover, if you want test an idea that may need a system to be run for couple of days
or even weeks, the simulation model can be used instead. In this case, several weeks of
operation can be simulated in a few minutes by a computer.
— Model-based design.
In model-based control design, the mathematical model gives a prediction of the system
response in case of applying a control command. It provides the possibility for control
system to send a command by which the system would react as it is expected.
If we can predict the price of electricity in a spot market, then it is possible to manage the electricity
consumption of the refrigeration system such that the total energy cost would be minimized during
a period of 24 hour [8,9]. In the smart grid literature it is known as indirect control scheme. It can
be done by further cooling down the foodstuff inside the display cases when the electricity price is
cheaper. It looks like — but not the same as — storing energy in a battery for a later use. Then the
stored energy is used during the hours when the electricity price is the most expensive. The model
can be used by the control system to ensure the temperature limits of foodstuffs not being violated
during the operation.
Another approach is to directly control the power consumption of refrigeration systems in accor-
dance with a reference signal received from a balance responsible party or an aggregator. It is
called direct load control approach. A simple method for direct load control which does not need
a model for implementation is proposed in [10].
In collaboration with other work packages in the Smart & Cool project, we showed how different
contributions in the three work packages can be consolidated in a complete design [11]. In that
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6. work, an algorithm developed in work package 3 by Morten Juelsgaard is responsible for sharing
load between two class of consumers, thermostatic loads and supermarket refrigeration systems;
a control method developed in work package 2 by Luminita Totu would take care of direct load
control of thermostatic loads; and a method developed by Ehsan Shafiei in work package 1 would
perform the direct load control for the supermarket refrigeration system.
An advanced control method is employed in [12] to perform direct load control in such a way that
an internal efficiency performance of the refrigeration system is improved as well as the demand
response implementation. By considering both the indirect and direct load control approaches
in one place, the problem of energy cost minimization as well as a realistic direct load control
scenario was addressed in [13].
In a collaboration with a work package of a different project titled “iPower”, a problem of aggre-
gation of different consumers in smart grid was addressed [14]. The idea is that a single consumer
like a supermarket does not have considerable capacity to help grid stay balanced. On the other
hand, if hundreds or thousands of such consumers are aggregated by an aggregator, then it can
provide a significant capacity for balancing services. The purpose of doing that work was to inves-
tigate that to which extent the assumption made for aggregator design might be valid and how the
designed direct load control scheme can be included in a loop closed by an aggregator.
The simple method presented in [10] does not show a high performance in carrying out some bal-
ancing services. On the other hand, the method proposed in [12] shows a very good performance,
but it relies on the model which makes the whole control system design quite complex. It mo-
tivates us to propose a solution that have the advantage of the latter design in terms of the high
performance, but at the same time be less complex for implementation and not rely on the model.
This solution will be presented in [16].
Another important aspect of the research accomplished in this work package was to open new
possibilities by exploring novel applications in refrigeration industry driven by advanced control
technology. For this purpose, in [17] it is shown how system efficiency and performance can be
improved by smart utilization of a thermal energy storage unit if advanced control technology is
used.
5 Fulfillment of the Project
In order to evaluate that to what extent the project has been fulfilled, the key indicators in Section 2
can be considered.
Publications — Doing academic research, it is important for us to publish the research results and
contributions in order to share the obtained knowledge with the society, to receive feedbacks on
the work (mostly by reviewers) and get academic credits for those who are doing it as well as the
research institute.
In this work package, I published nine conference papers that I was either the main author or
coauthor, as well as three journal articles which two of them are still under review. For a three-year
PhD, it shows a high degree of productivity.
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7. Industrial Collaboration — As already explained in Section 3, a close collaboration with Danfoss
as the main industrial partner for this work package was accomplished which resulted in two patent
applications. Moreover, different application ideas such as combination of direct and indirect load
control, and active utilization of thermal energy storages that the company was also interested
to check upon, were investigated. Investigation of the former idea was defined as a project for
a visiting student, Harm Weerts, from Eindhoven University of Technology. The results were
presented in the 19th IFAC World Congress [13]. Active utilization of thermal energy storages was
investigated during my stay at the University of Illinois at Urbana-Champaign and the results were
submitted for journal publication [17]. That is to say that the industrial collaboration has been
performed very successfully.
Academic Collaboration — In the half way of my PhD, I had a chance to visit a research group
at the University of Illinois at Urbana-Champaign (UIUC). The visit was supported by Aalborg
University. That was a very fruitful cooperation considering the fact that the competency of the
two research groups completed each other regarding the control of thermal systems. The group
in Illinois is quite competent in doing research in the area of thermal systems, and our group at
Aalborg has a strong background in doing control. The cooperation ended up a control design
for hybrid thermal energy systems in transport refrigeration that the results were submitted for
journal publication [17]. The group is placed in the mechanical laboratory leaded by professor
Andrew Alleyne [18]. They are utilizing different control techniques such as Iterative Learning
Control (ILC), Gain Scheduling, Model Predictive Control (MPC), and advanced PID for a range of
applications, including precision motion control from the macro to the nanoscale, hybrid-hydraulic
vehicles, and HVAC systems. Fig. 3 shows me together with the rest of the ARG at UIUC in
September 2013.
Maturity and Research Quality — It is hard to measure qualitative parameters like maturity and
research quality. Nonetheless, it can be evaluated to some extent if they are seen as a process.
As I was progressing in my PhD, the quality of the work in terms of how defining a problem,
proceeding with the contributions, presenting the idea and results, etc. was also improving. It can
be seen from the publications that at the end of the project, high profile journals were considered
for presenting the results. Regarding the maturity, at the last project meeting, it turned out based
on a feedback from the project leader Professor Rafael Wisniewski that the PhD students became
matured enough to present the research projects with a high level of understanding.
6 Reaching the Goals of the Project
A) Develop A Mathematical Model
Different articles and thesis addressing the thermodynamic modeling and vapor compression cycle
systems were studied. The data of a real supermarket refrigeration system provided by Danfoss
through ESO2 project [3] were analyzed. The model was developed and validated against data.
The results were presented in the 2013 American Control Conference [7] and the extended paper
was also published in the journal of Energies [15].
B) Develop A Simulation Tool for Energy Management of Refrigeration Systems
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8. Figure 3: Alleyne Research Group (ARG), University of Illinois at Urbana-Champaign, IL, USA,
September 2013.
Using the developed mathematical model, a simulation tool was created in Matlab environment.
It is modular, flexible and captures the nonlinear dynamics required for prediction of the power
consumption and thermodynamical states of the system. It is available at the refrigeration lab
homepage [19].
C) Investigation of the Economical Saving Potential
The model predictive control technique using the mathematical model was employed to investigate
that how much saving in the electricity cost might be possible in a real time pricing market. The
results were presented in the 2013 European Control Conference were two different approaches
are demonstrated [8,9].
D) Design a Model-Based Direct Load Control
A model-based predictive control was designed to regulated the power consumption of the com-
pressor racks to the assigned set-points. The simulation results were presented in 2014 American
Control Conference [12]. The method of this stage was combined to the method for economical
saving where the results were presented in the 19th IFAC World Congress [13].
E) Industrially Sound Designs
I stayed three months at Danfoss working on two different problems that already explained in more
details in Section 3. Two patent applications were filed [4, 5]. The results of the control design
were also presented in the 52nd IEEE Conference in Decision and Control [10].
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9. F) Investigation of the Data-Driven Methods
Considering the fact that data of the refrigeration system operation are usually logged with Danfoss
products and available for analysis and design purposes, it was important to see how those data can
be utilized for the direct load control design. For this purpose, a data-driven predictive control was
designed where the results have been submitted for journal publication [16].
G) Integration of the Refrigeration Control System into a Smart Grid Structure
Collaborating with Luminita and Morten from other Smart & Cool work packages, a control struc-
ture including the refrigeration direct load control for smart grid balancing purposes was proposed
and the results were presented in the 4th IEEE PES Innovation Smart Grid Technology Europe [11].
As another collaboration with Samira Rahnama from an iPower project work package, the inclu-
sion of the model-based direct load refrigeration control into the aggregator design was investigated
and the results were presented in the 19th IFAC World Congress [14].
H) Investigation of the New Technology and Applications
Utilization of thermal energy storages which can be designed in small sizes suitable for transport
refrigerations or single display cases were investigated. As a new application, the hybridization
of refrigeration systems using thermal energy storages was considered where the model predictive
control technique was employed for the control system design. This work was performed under
supervision of professor Andrew Alleyne from University of Illinois at Urbana-Champaign, IL,
USA. The results have been submitted for journal publication [17].
References
[1] EIA, “Annual energy outlook 2014, with projections to 2040,” U.S. Energy Information Ad-
ministration, Tech. Rep., Apr. 2014, http://www.eia.gov/forecasts/aeo/pdf/0383(2014).pdf.
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systems,” Technical University of Denmark, Department of Informatics and Mathematical
Modeling, Tech. Rep., 2012.
[4] S. E. Shafiei, R. Izadi-Zamanabadi, H. Rasmussen, and J. Stoustrup, “A method for control-
ling a vapor compression cycle system connected to a smart grid,” Submitted patent applica-
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[5] S. E. Shafiei and R. Izadi-Zamanabadi, “A method for estimating of thermal capacity of food
in display case/freezers,” Submitted patent application.
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10. [7] S. E. Shafiei, H. Rasmussen, and J. Stoustrup, “Modeling supermarket refrigeration systems
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[8] ——, “Model predictive control for a thermostatic controlled system,” in Proceedings of the
European Control Conference, Z¨urich, Switzerland, Jul. 2013.
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method for direct smart grid control of refrigeration systems,” in Proceedings of the 52nd
IEEE Conference on Decision and Control, Firenze, Italy, Dec. 2013.
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Conference, Portland, OR, USA, Jun. 2014.
[13] H. M. H. Weerts, S. E. Shafiei, J. Stoustrup, and R. Izadi-Zamanabadi, “Model-based predic-
tive control scheme for cost optimization and balancing services for supermarket refrigeration
systems,” in Proceedings of the 19th IFAC World Congress, Cape Town, South Africa, Aug.
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[14] S. Rahnama, S. E. Shafiei, J. Stoustrup, H. Rasmussen, and J. D. Bendsten, “Evaluation of
aggregators for integration of large-scale consumers in smart grid,” in Proceedings of the 19th
IFAC Word Congress, Cape Town, South Africa, Aug. 2014.
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for demand-side management,” Energies. Special issue: Smart Grid and the Future Electrical
Network., vol. 6, no. 2, pp. 900–920, 2013.
[16] S. E. Shafiei, T. Knudsen, R. Wisniewski, and P. Andersen, “Data-driven predictive direct load
control of refrigeration systems,” To be appeared in IET Control Theory and Applications,
2015.
[17] S. E. Shafiei and A. Alleyne, “Model predictive control of hybrid thermal energy systems in
transport refrigeration,” Second Revision Submitted to Applied Thermal Engineering, 2015.
[18] “Alleyne Research Group (ARG),” http://arg.mechse.illinois.edu/, accessed: 12-11-2014.
[19] SRSim, “A simulation benchmark for supermarket refrigeration systems using matlab,” http:
//www.es.aau.dk/projects/refrigeration/simulation-tools/, Feb. 2013, accessed: March 2014.
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