Evaluation of Alternative Operating Strategies for Residential Micro Combined Heat and Power

Omar A. Shaneb and Phil C. Taylor School of Engineering

Durham University Durham, UK

Email: {o.a.shaneb, p.c.taylor }@durham.ac.uk

Abstract— Introducing micro combined heat and power (μCHP) technology into residential energy systems could offer several advantages over traditional systems. Introducing an appropriate operating strategy for such a technology could increase its benefits. A model of a μCHP system, from the authors’ previous work, has been improved and used to evaluate alternative operating strategies for μCHP units in residential buildings in terms of annual cumulative operation costs and CO2 emissions. Results have shown that operating strategies have a significant effect on operation costs and CO2 emissions.

I. INTRODUCTION In response to growing concerns regarding climate change,

reduction of CO2 emissions has become a priority for many countries, especially the developed ones such as the UK. Residential applications are considered among the most important areas for substantial reduction of CO2 emissions because they represent a major part of the total consumed energy in those countries. For instance, in the UK, the residential sector is currently accountable for approximately 150 Mt CO2 emissions, which represents approximately 25% of the total UK CO2 emissions [1]. In order to achieve a significant CO2 reduction, many strategies must be adopted in the policies of these countries. One of these strategies is to introduce micro combined heat and power (μCHP) technology into residential energy systems, since μCHP technology offers several advantages over traditional systems [2] such as reduction of CO2 emissions. There are three main technologies used in this field: internal combustion engine (ICE), Stirling engine (SE) and fuel cell (FC). These systems are complex because of their interdependency on many uncertain variables; energy demand of a house is a case in point.

Integrating a μCHP unit in a single dwelling, faces significant challenges since thermal demand does not coincide with electrical demand. For instance, the annual heat to power (H:P) ratio in a single house, which depends on the age of that house, its size, and occupancy, varies from 2:1 up to 8:1 approximately [3], and this ratio is not always constant along the operation time of the μCHP unit. As a result, it is beneficial to connect a μCHP unit to a low voltage distribution network (LVDN)/micro-grid (μG); alternatively electrical

storage device storage must be integrated into the system to compensate for any differences that might occur [2]. On the other hand, larger residential applications such as multifamily, commercial, or institutional applications can benefit from the demand diversity which occurs due to the multiple demands served; this reduces the need for storage devices.

The μCHP system for a single dwelling, which has been considered in this study, consists of: a proton exchange membrane fuel cell (PEMFC), a thermal storage device, a backup heater and the system is also connected to the LVDN/μG in order to export/import power, as illustrated in fig. 1. In this paper, a model of a μCHP system, from the authors’ previous work, has been improved. This model has been used to evaluate the impact of using alternative μCHP operating strategies in residential buildings.

Figure 1. A conceptual arrangement of residential μCHP system with thermal and electrical storage

Central heating

Natural gas

Imported power

Exported power

Electricity Interface(s)

Backup heater

Heat losses

FC power

μCHP unit

Electricity consumption

Backup heat

Natural gas

Controller

FC Heat

Parasitic load

Low voltage distribution network

Thermal Storage

Dumped heat

DHW

Heat losses

Natural gas flow

Electricity flow

Control signals

Heat flow

Heat losses

2010 IEEE International Energy Conference

978-1-4244-9380-7/10/$26.00 ©2010 IEEE 143

II. TECHNOLOGIES USED AS RESIDENATIAL μCHP

Many technologies are used for μCHP systems but only three types are suitable to be integrated in single dwellings’ energy systems: ICEs, SEs and FCs. A detailed review of these technologies can be found in [2].

ICE is a well-known technology and has been applied in many fields such as automobiles and medium power generation since it offers several advantages [2]. However, it has some disadvantages that can impede its application in a single dwelling, which are: its electrical efficiency drops noticeably at low load [3]; it has comparatively high amounts of pollutant gases such as NOx and CO [4]; it requires regular servicing because of the large number of moving parts; and it has a relatively high level of noise [5].

SE is a reciprocating engine as ICE but the combustion process occurs outside the cylinder. SE based μCHP systems offer several advantages but they have two main disadvantages. Firstly, they have the highest H:P ratio among the alternatives, which is not preferred during mild and hot seasons. Secondly, they have a relatively high capital cost of approximately twice the cost of ICE [2].

FC is based, in its operation, on a chemical reaction, in the presence of an electrolyte, between oxygen and hydrogen to produce electricity, and as a result heat and water are by-products. FC based μCHP system for residential application consists of: fuel cell processor, fuel cell stack and auxiliary systems such as heat exchanger. The fuel cell processor reforms hydrogen from hydrocarbons while the fuel cell stack is the place of reaction [2]. There are many types of FCs but PEMFC is most promising [4 and 6]. FC based μCHP systems, in general, offer several advantages. They have a rapid adaptability to load variation and a high performance at partial load. In addition, they have the lowest level of noise. Moreover, they have high reliability and availability because it possesses few moving parts. Furthermore, they have low emissions. They also have a high overall efficiency ranges from 85-90% even for very small units. Besides, they have the highest electrical efficiency among the alternatives. On the other hand, they have three main disadvantages: a high capital cost; a relatively short life time [2]; and a relatively long start up time [6]. These disadvantages can be overcome once the technology is widely used.

III. ENERGY DEMAND FOR RESIDENTIAL APPLICATIONS

Energy demand in houses can be divided into two main categories: electricity demand and heat demand. Both electricity demand and heat demand vary significantly from one household to another [7]. For instance, the annual heat demand of a sample of nine dwellings, for a full calendar year, ranged from 9.3 to 27.2 MWh, the annual electricity demand varied from 3.5 to 7.5 MWh; and the annual H:P ratio was in the range 1.5 to 5.7 [8].

Residential heat demand is more flexible than electricity demand because it does not contain rapid fluctuations, especially when a thermal storage device is used [9]. This is because residential heat demand has only two common

significant periods of demand in cold seasons occurring in the morning and evening. Electricity demand in a house has transient behavior since it dramatically depends on daily and seasonal variations. For instance, when the house is empty, operating an individual appliance, such as a fridge, may consume only 1kW or even less, but the usage of different appliances at the same time, generally leads to peaks of several kilowatts at peak times [10].

Residential electricity demand may be divided into three categories: “predictable”, “moderately predictable” and “unpredictable” [11]. Predictable demand, which invokes small cyclic loads such as refrigeration appliances and steady loads from security lighting and standby items, occurs during un-occupancy and sleeping periods only. The rest of the demand is affected by both occupancy and external influences such as the seasonal/weather variations. Moderately predictable demand is subject to occupants’ habitual behavior patterns. For instance, many people operate television and switch lights on/off regularly. Finally, unpredictable demand, which represents the greatest part of the whole demand, has an irregular nature according the occupants’ wishes such as cooking and washing dishes/clothes.

IV. AUXILIARY COMPONENTS OF μCHP SYSTEM It is often beneficial to integrate a μCHP unit with other

components to improve its performance, and to connect it to the LVDN/μG enabling it to export/import electricity whenever it is required. The main components that might be integrated with a μCHP unit are: thermal storage device, back-up heater and electrical storage device. However, an electrical storage device has been excluded in this study because the system is connected to a LVD/μG.

Firstly, integrating the μCHP system with a thermal storage device allows the μCHP unit to operate more continuously since switching on/off and ramping up/down at partial load will no longer be required. Consequently, frequent starting-up and shutting down can be avoided. Furthermore, operational time of the μCHP unit will be extended resulting in more energy savings and larger CO2 reductions [12].

Secondly, adding a back-up heater is useful because it can fulfill peak demands as well as low level demand that cannot be met by the μCHP unit, since each μCHP unit has upper and lower operating limits which it cannot work efficiently beyond. As a result heat dump can be avoided because there is no need to design the system according to the peak heat demand. Moreover, many feasible operating strategies such as heat-led and electricity-led can be applied when the μCHP system is integrated with a backup heater, because such integrated systems allow electricity production to be partially de-coupled in time from the thermal demand profiles [9].

V. OPERATING STRATEGIES Operating strategy can be basically defined as the strategy

for activating, deactivating, ramping up and ramping down the μCHP unit [3]. The purpose of operating the μCHP system is achieving specific beneficial targets of the householder, the supplier or the LVDN/μG [5]. The three main conventional

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operating strategies, which have been investigated in this study, are as follows:

A. Heat- led strategy This strategy is simply based on meeting thermal demand

by operating the μCHP prime mover firstly and then any deficiency can be met by a back-up heater [12 and 13]. Any excess electricity can be sold back to the LVDN/μG while any deficit can be imported from it. It is the common strategy for operating the μCHP units available in the market [5].

B. Electricity-led strategy It is based on operating the μCHP unit, within the

operating limits, to meet the maximum possible amount of the electrical demand while any deficiency can be imported from the LVDN/μG, [5 and 9]. The system in this strategy should be integrated with a thermal storage to store heat when there is no thermal demand or when thermal demand is less than the produced heat; and it should also be integrated with a back-up heater to compensate any deficiency that might occur [14].

C. Time- led strategy Time-led operation strategy is based on operating the

μCHP unit for one or more periods daily [3, 14 and 15] either at full load or at partial load to follow heat or electricity demand. Any excess power is exported to the LVDN/μG, while any deficiency can be imported from the LVDN/μG [15]. The system should be integrated with a back-up heater and a thermal storage to store any extra heat produced during the period of operation. In this study, the second choice has been investigated, where the μCHP unit is operated according to heat-led strategy during the main periods of high demand: the morning and the evening periods.

VI. MODELLING OF μCHP SYSTEM The proposed μCHP system, which has been previously

illustrated in fig 1, has been modeled in Matlab/Simulink as shown in fig. 2. The model is based on the authors’ previous model [16], where empirical mathematical expressions to approximate the efficiency and the thermal output of the PEMFC have been used as follows [4]:

For LFj < 0.05

ηe,j = 0.2716, H:Pj = 0.6801 (1)

For LFj ≥0.05

ηe,j=0.9033(LFj)5-2.9996(LFj)4-3.6503(LFj)3-

2.0704(LFj)2+ 0.4623(LFj)+0.3747 (2)

H:Pj=1.0785(LFj)4-1.9739(LFj)3+1.5005(LFj)2-

0.2817(LFj)+ 0.6838 (3)

Where:

LFj= load factor at time j, and it is defined as the ratio between the instantaneous DC output of the PEMFC and its maximum DC output.

ηe,j= electrical efficiency of PEMFC at time j

H:Pj= heat to power ratio at time j, and it is defined as the ratio between the thermal output of PEMF and its DC power output.

For further details regarding the model, the reader is referred to the author’s previous work [16].

All values of energy prices and CO2 emission factors in the previous work have been adopted. CO2 emission rate for LVDN/μG electricity is assumed 0.43 kg/kWh while CO2 emission rate for natural gas is assumed 0.189 kg/kWh based on LHV. Typically, gas-fired boilers emit around 0.25 kg of CO2 emission per kWh heat generation [16]. However, the model has been improved to include the ramping up and ramping down constraints of the μCHP unit and; losses from the thermal storage and a time-led operating strategy. Furthermore, three types of demand for a whole year have been used.

The model is based on operating the μCHP unit according to three different operating strategies: a heat-led, an electricity-led or a time-led strategy. Once the μCHP unit is being operated according to a particular strategy, the system will follow certain rules. First of all, the electricity demand of the house will be met by the μCHP unit but once the μCHP unit is unable to meet the demand, electricity can be imported from the LVDN/μG; and if the electrical power produced by the μCHP unit exceeds the demand, the excess power will be exported to the LVDN/μG. Secondly, the heat energy from the μCHP unit is used to meet the residential thermal demand and any excess heat energy will be stored in the thermal storage device. However, if the temperature of the water inside the thermal storage device is at its maximum value, the extra heat energy will be dumped through a sink. On the other hand, if the output from the μCHP unit cannot meet the residential thermal demand, then the stored heat is used to meet the rest of this demand. Meanwhile, a backup heater can be used to meet any deficit in heat that cannot be met by the thermal storage. In order to simplify modeling, the system has been divided into five models as it appears in fig. 2.

Electricity demand total cost

total CO2 emissions

internal energy ofthe thermal storage

dumped heat

backup heat

dumped heat

internal energy

Thermal storage and heat supply system

AC power

Operating strategy model

DC power

heat

NG flow rate

Micro CHP model

AC power

Invertor

MK0812H.mat

Heat demand

SDH.mat

total cost

total CO2

Emissions and costs model

imported power

exported power

Electricity supply system

Figure 2. Simulink model of the proposed residential μCHP system

The μCHP model simulates the behavior of the μCHP unit (PEMFC in this case). The model can estimate the amount of thermal power, electric power and natural gas flow rate of the PEMFC at any time according to the signal received from the control strategy model. This model is a parametric relationship

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between the efficiencies and the thermal and electrical output power, which is based on empirical data. The model μCHP has been improved by adding realistic constraints to the ability of the PEMFC to ramp up and ramp down. Experimental data has shown that a 1 kWe PEMFC cannot ramp up more than 41.67 Watts of electricity per minute and cannot ramp down more than 50 Watts per minute [17]. So, theses values have been included in the model to make it more realistic.

The operational strategy model controls the output of the μCHP unit (PEMFC) to the allowable levels according to the chosen control strategy: heat-led, electricity-led or time-led.

The electricity supply system model simulates the LVDN/μG and the electricity interface(s), where all the calculation of electricity flow, such as exporting and importing of electricity, are executed.

The thermal storage and heat supply system model simulates the thermal storage, the backup heater and the sink.

The operation costs and CO2 emissions model estimates the operation cost and CO2 emissions for the μCHP system.

Heat losses from the thermal storage Qloss can be estimated by equation 4:

Qloss(t)= KstAtt[Tst (t-�t)-Tamb] �t (4)

Where: Qloss(t)= heat losses from the thermal storage for a period of �t at the time t.

Kst= the specific loss coefficient that takes into account the heat transfer by convection, conduction and radiation from the water inside the thermal storage in W/m2.K.

Ast= Heat transfer area of the thermal storage in m2.

Tst (t-�t) = the temperature of the water in the storage in degrees at time (t-�t.

Tamb= the ambient temperature of the surrounding.

�t= the time step in seconds.

Internal energy of the water inside the thermal storage at any time can be estimated by equation 5:

)TT(CPV)t(U minststststst ���� (5)

Where: Ust is the internal energy of the water inside the storage at instantaneous temperature (Tst)

Tmin =the minimum allowable temperature of the water in degrees.

The change of the internal energy of the water inside the storage by the time can be calculated by equation 6:

)6(dt

dUdt

dTCPV ststststst ��

By integration equation 6 and substitute with Ust=0 when Tst=Tmin equation 7 is obtained as follows:

minststst

stst T

CPVU)t(T ��

� (7)

VII. DISCUSSION Three types of residential demand have been considered in

this study as summarised in tables 1 and 2 below. This demand data, which is hourly energy consumption for a whole year, was collected for dwellings in an area North West of London. It was accessed through the UK Energy Research Centre Energy Data Centre (UKERC-EDC) [18].

TABLE I. SPECIFICATION OF THE HOUSES AND OCCUPANCY

Demand type

Item SDH ETH DH

House type Semi-

detached house (SDH)

End-terrace house (ETH)

Detached house (DH)

U-value of floor 0.45 W/m2K not known 0.28 W/m2K

Construction Type timber frame (TF) not known timber frame

(TF) Floor area 64.8 m2 64.8 m2 139.1 m2

Depth of floor insulation 50 mm 50 mm 100 mm

U-value of roof 0.26 W/m2K not known 0.2 W/m2K U-value of the external walls 0.34 W/m2K 0.3 W/m2K 0.31 W/m2K

Number of bedrooms 2 2 4 Maximum occupancy 4 4 6

TABLE II. SUMMARY OF ELECTRICITY AND HEAT DEMANDS

Demand type Consumption SDH ETH DH

Min. electricity demand (kW) zero 0.029 0.176 Max. electricity demand (kW) 2.96 3.069 2.818 Average electricity demand (kW) 0.2126 0.229 0.495 Annual electricity demand (kWh) 1862.4 2010.3 4335.2 Min. heat demand (kW) zero zero zero Max. heat demand (kW) 9.156 10.682 15.566 Average heat demand (kW) 1.1241 1.560 1.931 Annual heat demand (kWh) 9848.5 13660.1 16919.9 Average H:P ratio 5.3 6.8 3.9

Results have shown that operating strategies have a significant effect on operation costs and CO2 emissions. None of the operating strategies can be considered the optimal since each one offers either savings in operation costs or reduction of CO2 emissions. For instance, operating a 4kWe PEMFC according to a heat-led instead of electricity-led strategy reduces the CO2 emissions of an end terraced house (ETH) by approximately 390 kg per year. However, operating it according to an electricity-led strategy can save over 150 € in operation cost per year. Fig. 3 shows emissions and operation costs of an ETH for different operating strategies and different sizes of PEMFC. Similar differences have been noticed for the demands of a semi-detached house (SDH) and a detached house (DH). For example, operating a 4kWe PEMFC according to a heat-led instead of electricity-led strategy reduces the CO2 emissions of a SDH and a DH by approximately 390 kg and 237 kg per year, respectively. On the other hand, operating a 4kWe PEMFC according to an electricity-led strategy can save over 100€ in operation cost per year for both demands, SDH and DH. Five different sizes

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of μCHP unit, ranging from 0.5 kWe to 4kWe, have been simulated for one year according to different operating strategies: heat-led, time-led and electricity-led, in order to estimate annual cumulative operational costs and annual cumulative CO2 emissions.

It should be noticed that the evaluation has been carried out by using fixed energy prices. It is likely that using diurnally varying prices of energy would lead to greater difference between the operating strategies in terms of operation costs. Another example would be an increase in the feed-in tariff, which could reduce the operation costs of heat-led strategy because the sold electricity would reduce the operation cost. Therefore, developing a sophisticated operating strategy for residential μCHP systems, which can combine different operating strategies and make optimized tradeoff between operation costs and CO2 emissions, could be of significant value to residential energy systems. Furthermore, all the simulations have been conducted for a μCHP system that contains a 200 liters thermal storage device. So, no heat dump has occurred and the internal energy of the thermal storage was within the allowed limit all the time. However, if a smaller thermal storage device is used this will result in wasted heat, especially when a 4kWe PEMFC is used.

Figure 3. Emissions and operat

Figure 4. ion costs of an ETH for different operating strategies

VIII. CONCLUSION Introducing micro combined heat and power (μCHP)

technology into residential energy systems, especially fuel cell technology, can be considered as one of the strategies that can contribute to the reduction of CO2 emissions since it offers several advantages over traditional systems.

A model of a μCHP system, from the authors’ previous work, has been improved. This model is a total energy system model, which simulates the performance of a PEMFC based μCHP system. The model simulates the flow of both thermal and electrical energy to/from the system and inside the system itself. In addition, the model allows to FC to be operated according to either a heat-led, time-led or electricity-led strategy.

Five different sizes of μCHP unit, ranging from 0.5 kWe to 4kWe, have been simulated for one year according to different operating strategies: heat-led, time-led and electricity-led, in order to estimate annual cumulative operational costs and annual cumulative CO2 emissions. Results have shown that using different operating strategies could lead to different savings in operation costs and CO2 emissions. For instance, operating a 4kWe PEMFC according to a heat-led instead of electricity-led strategy can reduce the CO2 emissions of a single dwelling by approximately 390 kg per year. However, operating it according to an electricity-led strategy can save over 150€ in operation cost per year. Therefore, developing a sophisticated operating strategy for residential μCHP systems, which can combine different control strategies, could have a significant economical and environmental impact on residential energy systems.

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