Energy and Power En gi neering, 2011, 3, 641-649
doi:10.4236/epe.2011.35080 Published Online November 2011 (
Copyright © 2011 SciRes. EPE
Optimal Operation and Size for an Energy Hub
with CCHP
Aras Sheikhi, Ali Mohammad Ranjbar, Hashem Oraee, Amir Moshari
Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
Recieved September 29, 2011; revised October 24, 2011; accepted November 5, 2011
The interest in distributed generation has been increasing in recent years, especially due to technical devel-
opment on generation systems that meet environmental and energy policy concerns. One of the most impor-
tant distributed energy technologies is Combined Cooling, Heat and Power (CCHP) systems. CCHP is a
small and self-contained electric, heating and cooling generation plant that can provide power for households,
commercial or industrial facilities. It can reduce power loss and enhance service reliability in distribution
systems. The proposed method in this paper determines the optimal size and operation of CCHP, auxiliary
boiler and also heat storage unit as elements of an energy hub, for users by an integrated view of electricity
and natural gas network. Authors apply cost and benefit analysis in the optimization. To confirm the pro-
posed method, the optimum sizes of these elements are determined for a hotel in Tehran as a case study.
Keywords: Combined Cooling Heating and Power (CCHP), Cost and Benefit Analysis, Energy Hub,
Optimal Operation, Optimal Size
1. Introduction
The electric power industry is under deregulation in re-
sponse to changes in legislation, technology, market and
competition. One of the main adv antages of deregulation
is that it can increase the efficiency of industrial and
commercial sectors and reduce the cost of electrical en-
ergy for all customers [1].
Deregulation has evolved in all three sectors of the
power system (i.e. generation, transmission, and distribu-
tion) from centralized to a decentralized status. One of
the main concepts in deregulation is Microgrids which
are used at the distribution level [2]. Microgrid, with its
decentralized electricity generation, combined with on-
site production of heat and cooling, could provide reli-
able electric power as well as heat and cooling to its
consumers at an economic cost. This set is named com-
bined cooling, heat and power (CCHP) system.
Nowadays, following the expansion of natural gas
networks and also benefits of this energy carrier such as
lower emission level and prices, CCHP technologies
have attained unprecedented level of popularity as one of
the most important distributed energy resources [3].
One of the major factors for users on choosing a
CCHP system is the overall costs of CCHPs which is
largely dependent on its size [4]. Hence finding the op-
timized size of a CCHP is economically important.
Generally, an optimized CCHP can be evaluated by
analyzing two main factors: costs and benefits. Cost is
one of the main components in nearly all DG evaluations,
but is inadequate for complete evaluations. Furthermore,
reliability enhancements [5], power cost saving, power
loss and emission reduction [6] are also key elements in
deciding which CCHP should be installed.
The cost of generation of electricity and heat from a
CCHP can be classified into capital investment cost, op-
eration and maintenance (O&M) costs and fuel cost. On
the other hand, the benefits from the CCHP placement
can be classified into power cost and power loss reduce-
tion and significantly decreasing the expected energy not
supplied which is a favorable effect in a power system.
CCHP can inject its power directly into distribution
feeders and by alleviating transmission losses the bene-
fits of power loss reduction become quite clear [6].
Moreover reliability enhancement has received substan-
tial attentions as it reduces the co sts of losses incurred by
utility customers as a result of power failures [7].
All of these costs and benefits are calculated in terms
of present value factor (PVF), accumulated over the eco-
nomic life of the respective equipment. It is common
practice for a decision maker to translate future cash
flows into their present values.
From a number of recent publications [1-16], it can be
seen that in a deregulated power system, each individual
distribution company may wish to determine the costs
and benefits of DG planning under different circum-
stances. It is difficult to find a single planning method
that satisfies all the company objectives simultaneously.
In this paper a value-based planning method for CCHP
placement based on the energy hub concept is proposed.
The proposed method takes the benefits and costs of
CCHP placement into account and determines the opti-
mal sizing and operation for an energy hub’s elements.
Test results show that with proper size selection, CCHP
placement can reduce the running cost of a multicarrier
energy system.
The contents of this paper are organized into the fol-
lowing six sect i ons.
Determination the optimum operational point, the en-
ergy hub concept and a brief ov erview of the Energy hub
modeling is presented in Section II. Section III discusses
the potential benefits of deploying energy hubs. Section
IV provides detailed formulations of the problem and
case studies are debated in detail in section V. Finally,
conclusions are drawn in Section VI.
2. Energy Hub Concept and Modeling
Some conceptual approaches for an integrated view of
transmission and distribution systems with distributed
generation have been published. Besides “energy-ser-
vices supply systems” [17], “basic units” [18], and “mi-
cro grids” [19], so-called “hybrid energy hubs”, are sug-
gested, where the term “hybrid” represent the use of
multiple energy carriers [20,21]. An energy hub is con-
sidered a unit where different energy carriers can be
converted, conditioned, and maybe stored. It represents
an interface between different energy infrastructures
and/or loads. Energy hubs consume power at their input
ports which is connected to, e.g. electricity and natural
gas infrastructures, and perform certain required energy
services such as electricity, heating, cooling, and com-
pressed air at their output ports [4].
Energy hubs include two basic elements: direct con-
nections and converters. Direct connections are used to
deliver an input power to the output without converting.
Converter elements are used to change carriers into other
forms or qualities. Such as gas turbines, combustion en-
gines or fuel cells. Figure 1 demonstrates an example of
an energy hub.
The components within the hub may create extra con-
nections between inputs and outputs. For instance, the
electrical load connected to the hub in Figure 1 can be
met by consuming all power directly from the electricity
grid or generating part or all of the required electricity
Figure 1. An energy hub containing an electric transforme r,
a CHP, a boiler (B) an absorption chiller (C): and Heat
Exchanger (HEX).
from natural gas. This redundancy in supply results in a
significant benefit, which can be achieved using energy
hubs: Reliability of supply can be enhanced from the
load’s perspective because it is not completely dependent
on a single supply.
From a system point of view, co mbining and co upling
different energy carriers show a number of potential
benefits over conventional, decoupled energy supply.
The energy hub is an archetype with no limitations to
the size of the modeled system. Single power plants or
industrial buildings as well as bounded geographical ar-
eas such as entire towns can be modeled as energy hubs.
The model of the system is formulated below.
In the system under study, the ener gy hub represents a
general consumer as a household which uses both elec-
tricity and gas. The hub is connected to a large gas net-
work and the electricity network.
The hub consumes electric power Pe and gas Pg and
provides energy to its electric load Le, heating load Lh
and cooling load Lc. The hub contains conversion tech-
nologies in order to fulfill their energ y load requirements.
For energy conversion, the hub contains a CCHP and an
auxiliary boiler. The CCHP device couples the three en-
ergy systems at the same time that produces electricity,
cooling and heat from natural gas. Depending on the
prices of energy and load profiles, the CCHP device is
utilized differently. At high electricity prices, the electric
load is supplied by CCHP for longer times. The pro-
duced heat is then used to supply the thermal load. At
low electricity prices, the electric load is rather supplied
directly by the electricity network and the gas is used for
supplying the thermal load via the boiler house. Hence,
there are several ways in which electric and thermal load
demands can be met. This redundancy increases the reli-
ability of supply overtly and simultaneously provid es the
possibility for optimizing the input energies, e.g. using
Copyright © 2011 SciRes. EPE
criteria such as cost, availability, emissions, etc.
Consider a converter device as depicted in Figure 2
that converts an input energy carrier α into β. Input and
output power flows are not independent; they are con-
sidered to be coupled,
Lc P
 
 (1)
where Pα and Lβ are the steady state input and output
energy flows respectively, cαβ is the coupling factor
which defines the coupling between input and output
energy flow. For a simple converter device with one in-
put and one output, the coupling factor corresponds to
the converter’s steady state energy efficiency.
A general model covering all types of couplings can
be stated all power inputs ,,,PP P
and outputs
,,,LL L
in vector form and enables the formula-
tion of a multi-input, multi-output power conversion as
follow [7]:
 
 
 
3. Proposed Optimization Method
In this study, CCHP has a central role in the energy hub.
Hence investigating the best size of CCHP as the most
important elements of an energy hub system has a sub-
stantial effect on the users’ benefits.
This section proposes an analytical method to deter-
mine the most advantageous selection.
To find the best elements of the energy hub between
existing choices the value based planning will be em-
ployed. The costs of CCHP placement include the in-
vestment, maintenance and operation cost (O&M) of
CCHP, auxiliary boiler and storage devices. To find the
benefit term for CCHP placement, it is assumed that the
outputs of CCHP are sold completely. Emission reduce-
tion is the other major term that would be added to form
the total benefit. This planning method attempts to real-
ize the minimum cost solution where the total benefits
can be maximized.
The total input flow Pg splits u p to differen t converters,
CCHP and auxiliary boiler in Figure 1. Dispatch factor,
, specifies how much of the total input power Pg flows
through the CCHP. At the same time, absorption chiller
uses heating power to generate cooling. α, β show the
Figure 2. Model of energy converter.
proportion of heating power that is produced by aux-
iliary boiler and CHP, consumed b y the chiller.
To investigate optimal value of this parameter, an ap-
propriate objective function which is considered the net
benefit for the energy hub system has to be formed.
The threat of global warming and climate change has
created worldwide concerns. As a result, many countries
have reached and signed agreements such as Kyoto in
order to reduce greenhouse gas emissions. Hence, CO2
emission consideration is highlighted as one of the ef-
fecttive factors on power generation. To model this fac-
tor e
are introduced. These parameters con-
vert CO2 emissions of electricity and natural gas, as the
energy hub input, into dollars.
Based on the social costs of carbon emissions, it is as-
sumed that the price of carbon is around $30 per ton
($0.03 per kg) which needs to increase with inflation
rates [22].
With these extensions, multi-period multi-carrier op-
timal power flow and limitations can be stated as nonlin-
ear programming (NLP) structure:
()()() ()()
ese eeegeg
LnP nPnnPn
  (3)
() ()
1()() ()()
() ()
inh outh
nnnn P
SnS n
 
 
CHP chiller
()()1() 1()
outc hc
LnC nnn
nn P
 
( )0.98(1)( )( )()
inh outh outc
SnSnS n Sn Sn
  (6)
()Maximum heatinputkWh
()Maximum heat outputkWh
() m
Sn S (9)
min max
PPP (10)
min max
PPP (11)
se se
Pn P (12)
()Hn H (13)
()Cn C
0,, 1
()() CHPCapacity
1( )( )AuxilaryBoilerCapacity
 (17)
Copyright © 2011 SciRes. EPE
CHP chiller
1( )( )ChillerCapacity
ghhc g
nn P
 (18)
()()()() ()()
eg eeg
ZPnenPngnPn Pn
The cost heat pumped in to the heating storage devices
is neglected.
Le is electrical load;
Lh is heating load;
is dispatch factor;
is the transformer efficiency;
is the boiler efficiency;
is the chiller efficiency;
is the electrical efficiency of CHP;
is the heating efficiency of CHP;
e(n) is the electricity price ($/kWh);
g(n) is the cost of natural gas ($/kWh);
Sm is the capacity of heat storage;
Sin is the input rate of heat storage;
Sout is the output rate of heat storage;
Pse is the electricity transferred from CHP to the elec-
tric grid;
C(n) is the sold cooling power;
H(n) is the sold heating power;
Z is the cost of consuming natural gas and electricity
of energy hub input;
b is the bonus for exporting electricity from CHP to
the electric grid.
Using CHP to produce electricity eliminates the cost
of transmission and this is one of the important factors
that make CHP as an economically attractive option for
governments to produce electricity. Decreasing the cost
of transmission dose not benefit the end users directly
and is a beneficial factor for governments. To make end
users share this benefit, governments provide some bo-
nus schemes for electricity producers by distributed gen-
eration, that this bonus has been added to the base price
of electricity exported to the grid.
Finding this added value need some calculations and
suppositions as follo w:
The effective efficiency considered as follows and it
must be more than the mean efficiency of conventional
power generation.
 (20)
: Effective efficiency;
: Electrical efficiency;
: Thermal efficiency;
: Percentage of the used heat of CHP.
The value of saving natural gas when CHP is used to
produce 1 kWh of electricity is calculated as follow:
860100 100
(1 )
gave E
 
SG: saving natural gas when 1 kWh of electricity gen-
erated by CHP instead of conventional power generation
system [m3]
HVg: Heating value of natural gas [kcal/m3]
: mean efficiency of conventional power genera-
L: percentage of transmission loss of electrical grid
Multiplying the natural gas price by the above value
results in the bonus that would be added to the base price
of electricity:
natural gas pricebSG
Note that the feasible region of the optimization prob-
lem is defined by different constraints. An equality con-
straint is given by the equation that describes the power
flow through the hub. Inequalities arise from limitations
of the hub’s input power vector and the power inputs to
the individual converters. The relation between the hub
input vector, the converter input vector and the amount
of heat in the heating storage devices are given by (3),
(4), (5) and (6). Maximum output and input heat transfer
rate, lower and upper limits of the main bran ch gas pipe-
line and transformer rates are defined in (7)-(11) respect-
tively. Maximum allowable values of heating, cooling
and electrical power for sale are given by (12)-(14).
Limitation of the dispatch factors in (15) has to be re-
garded as well. Inequ alities (16)-(18) sho w con strains for
maximum capacity of CCHP and aux iliary boiler.
Obviously, efficiency and size of energy hub elements
considerably affect the optimum value of parameters (Pe,
The main objective in this p aper is to calculate the op-
timum size of CCHP, auxiliary boiler and heat storage
device in an energy hub. The objective function of the
problem is:
max Benefit-Cost (23)
()()() ()
() ()()
() ()CPVF
esee eg
LnP nPnenb
LnCn CCn
Ln Hn
 
 
Copyright © 2011 SciRes. EPE
Copyright © 2011 SciRes. EPE
4. Case Study
CostCHP Cost+Boiler Cost
Heating Storage Cost+FixedCost
(25) The model presented in this paper has been applied to a
hotel building in Tehran as an energy hub.
where Hotels usually operate 7800 to 8760 hours yearly.
Most hotels, particularly larger ones, have large annual
electricity consumptions. They also have high thermal
needs [23,24]. This translates into a high thermal to elec-
trical ratio of about 1.2 for the average hotel [6,25], in-
dicating hotels can beneficially recapture waste heat
generated by a CHP system. The high number of operat-
ing hours and the rather constant electrical, heat and
cooling loads make hotels suitable candidates for a CCHP
Cm is the maintenance cost of CHP per year:
365maintenance cost per kWh()
 
CC(n) is the cost of sold cooling power per hour
CPVF is the cumulative present value:
(28) In this case study, operational costs of a 50,000 square-
feet hotel as an energy hub is calculated and used to se-
lect the best CCHP system.
where ir, if and EL are respectively the per unit (p.u)
interest rate, p.u inflation rate and economic life of the
equipment. Energy load profile and energy price [28-30] of this
hotel is depicted as follow (Figures 3-6):
Fixed cost term in (22) con sists of the cost of the cen-
tral controller, load controllers, interfacing equipment
and low voltage circuit breaker [26].
Note that in Figure 4 there are two load profiles. One
of them denotes winter and autumn day load sample and
the other indicates load profi le of summ e r and spring days.
Figure 3. Electricity consuption in a normal day [summer and winter].
Figure 4. Heating energy consuption in a normal day [summer and winter].
Figure 5. Cooling energy consuption in a normal day [summer and winter].
Figure 6. Energy price.
In this study, all efficiencies are independent of power
and have a constant value. The typical energy distribu-
tion for internal combustion engines is provided [31]. It
shows that 30% of the fuel energy is converted to heat
energy rejected through the coolant and another 30% of
the fuel energy is rejected as heat through the exhaust
gas. The total efficiency of heat exchangers for the cool-
ant and exhaust gas is estimated to be 0.85, and the total
fuel-to-thermal-energy conversion efficiency (i.e., total
heat recovered from the engine) is then calculated to be,
(30% + 30%) (0.85) = 51%.
The boiler thermal efficiency
is assumed to be
90%. The total efficiency of the cooling components
(chiller efficiency) was estimated by cons idering the Co-
efficient of Performance (CoP), amount of heat moved
per unit of input work required, of an absorption chiller
and the efficiency of an air handling unit.
A CoP of 0.7 is used for the absorption chiller and an
efficiency of 0.85 is used for the air handling unit. The
total efficiency of cooling components is then calculated
to be (0.7) (0.85) 100 = 60%. The total efficiency of
the heating components is estimated 85% which is an
efficiency of the air handling unit.
The thermal energy losses due to energy transport/
transmission in the network are neglected in this simula-
tion because the pipes are well insulated in the facility.
CHP and boiler costs depend of the size. Figures 7
and 8 depict these relations.
Tables 1 and 2 show the cost and performance charac-
teristics of absorption ch iller and heating storage devices
[32]. Bonus for selling electricity to the grid is calculated
by (22). The price of sold cooling is considered to be 1.2
01000 20003000 4000
CHP cost ($/kW)
Si ze (kW )
Figure 7. CHP cost.
Copyright © 2011 SciRes. EPE
05001000150020002500 3000 3500
boi l er c ost ($/ k W )
Size (kW )
Figure 8. Boiler cost.
Table 1. Performance characteristics of CHP and auxiliary
Cost ($/kWh) CHP
$/kWh Fixed
Cost $
0.01 35% 40% 90% 98% 60% 0.0230,000
Table 2. Cost of heating storage devices and absorption
Thermal storage Absorption chiller
Fixed cost($) 10,000 20,000
Variables cost ($/kW) 100 115
times more than electricity price. A summary of energy
hub elements’ efficiency information for the algorithm
and the data needed for optimization problem is listed in
Table 1.
The boundary conditions are shows in Table 3.
The interest rate (ir) is 0.08 p.u., the inflation rate (if)
is 0.05 p.u., the economic life cycle (EL) of all equip-
ment is considered to be 15 years [26].
For Tehran Xe = 1.32 $/kWh and Xg = 0.6 $/kWh [27].
To solve the above problem, GAMS software is used
and the best size of energy hub’s elements is evaluated.
Table 4 demonstrates optimized values of energy hub
Pe equals zero at all times which indicates that the
electrical loads have been supplied by CHP completely
and Figure 9 shows the resulting Pg as an optimal hub
No heating is sold by installing the CHP. On the o ther
hand cooling is exported with the maximum power (160
kW/h) continuously. From Figure 10 it can be inferred
that exported electricity from energy hub has same shape
in winter and summer.
Figure 11 shows the stored heat for all 24 periods.
Each bar represents the energy stored at the end of the
period. The storage is assumed to be empty at the end of
the period.
5. Conclusions
Competition is a key wo rd in the deregulated market and
it is in close association with the econo my. The values of
BCR greater than one in all cases of CHP indicate the
economic viability of investment planning when CHPs
Table 3. Maximum value of parameters.
Pemax (kW)Pgmax (kW)Hmax (kW) Cmax (kW) Psemax (kW)
1000 2500 200 160 200
Note that the all parameters a re p osit ive.
Table 4. Optimized value of energy hub elements.
(Million $)
Capacity (kW)
Capacity (kW)
Capacity (kW)
2.48 948 296 366 30
Figure 9. Input natural gas (Pg).
Copyright © 2011 SciRes. EPE
Figure 10. Exported electricity to the grid.
Figure 11. Input, output and storage of heating energy in storage device.
are deployed optimally in the system and their use
reaches economies of scale. Still, there are a number of
factors, such as the size, electrical efficiency, heating ef-
ficiency, government policies about emission, EENS re-
duction, and the fuel price that influence the results.
In this paper, a value-based planning method for
CCHP placement has been proposed based on the energy
hub concepts.
The proposed method, determines the best operational
point of energy hub and the optimal size of CHP, absorp-
tion chiller, auxiliary boiler and heating storage devices
with the maximum net benefit. To solve the problem the
GAMS software is employed. Test results show that
CCHP installation with suitable size is one of the best
methods to improve service reliability and decrease the
power cost overtly.
Future work may be extended with benefits, such as
the type of manufacturer, type of technology, policies of
the local utility, and seasonal effect on demand and load
growth rate.
6. Acknowledgments
The authors would like to thank the Elite National
Foundation and FiFi for their useful advices and finan-
cial support during this research.
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