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Applied Thermal Engineering 71 (2014) 729e735

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Applied Thermal Engineering

journal homepage: www.elsevier .com/locate/apthermeng

Biomass-fired CHP and heat storage system simulations in existingdistrict heating systems

Michel Noussan a,*, Giulio Cerino Abdin a, Alberto Poggio a, Roberta Roberto b

a Politecnico di Torino e DENERG, C.so Duca degli Abruzzi 24, 10129 Turin, ItalybC.R. ENEA di Saluggia e UTTS, Strada per Crescentino 41, 13040 Saluggia, VC, Italy

h i g h l i g h t s

� Analysis of a wood-biomass ORC unit in an existing DH system.� Parametric study with optimization on ORC size and heat storage system size.� Simulation of heat demand from a dataset of a similar DH system in operation.� Different optimal configurations when considering energetic or economic criteria.� The Italian incentive still not encourages system layouts with higher efficiency.

a r t i c l e i n f o

Article history:Received 7 July 2013Accepted 11 November 2013Available online 21 November 2013

Keywords:BiomassDistrict heatingCombined heat and powerHeat storageOrganic Rankine cycleEnergy

* Corresponding author. Tel.: þ39 011 090 4529; faE-mail addresses: michel.noussan@polito.it (M. No

(G. Cerino Abdin), alberto.poggio@polito.it (A. Pog(R. Roberto).

1359-4311/$ e see front matter � 2013 Elsevier Ltd.http://dx.doi.org/10.1016/j.applthermaleng.2013.11.021

a b s t r a c t

The installation of a biomass-fired Organic Rankine Cycle (ORC) unit coupled to a heat storage system(HSS) in an existing district heating (DH) system is proposed and analyzed from both energetic andeconomic point of view. A real DH system is considered as case study, and the optimal layout configu-ration is investigated varying the size of the components. The analysis is carried out tuning the heatdemand dataset obtained from real data of a different existing DH systemwith a 6-min time step and tenyears of operation. The heat demand is used to match the production from different generation units. Theoverall efficiency of the system, the primary energy savings related to CHP production, as well as the payback time of the investment are evaluated. Calculations show that for the considered case study themaximum size of the HSS that gives noticeable advantages is 150 m3/MWth. The optimal configuration isdifferent when considering energetic or economic criteria. Moreover, the current Italian incentive tariffon electricity production from renewable sources appears to promote the choice of low efficiency layoutsfor the case study under consideration.

� 2013 Elsevier Ltd. All rights reserved.

1. Introduction

Energy production from renewable sources, together with en-ergy efficiency and energy saving measures, is a key question in thelimitation of greenhouse gases emissions (GHG) and in the diver-sification of energy resources.

The European Union in its Climate Package has set a target of20% of energy production from renewable sources by 2020, withfurther objectives for 2050 [1,2].

Energy production from renewable sources has increased inrecent years up to 1660 Mtoe in 2010 [3]. Biomass is currently the

x: þ39 011 090 4499.ussan), giulio.cerino@polito.itgio), roberta.roberto@enea.it

All rights reserved.

most diffused and exploited renewable source all over the world. In2010 about 75% of primary energy production from renewablesources was produced from biomass and renewable wastes [3].

However, research and planning activities are still required inorder to improve overall sustainability and energy conversion ef-ficiency of biomass to energy pathways.

The use of wood-fired combined heat and power (CHP) anddistrict heating (DH) systems can play an important role inimproving a rational use of bioenergy [4e6], when an accurateanalysis of both availability of local biomass and thermal demand isperformed.

CHP plants can reach higher overall efficiencies due to the re-covery of the waste heat resulting from electricity generation, eventhough wood-fired plants often work at lower performances thanexpected due to not optimal design and operational strategies. Forthese reasons, a careful design and operation of the plant based on

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Fig. 1. Cumulative specific power profiles for different heating seasons.

M. Noussan et al. / Applied Thermal Engineering 71 (2014) 729e735730

integrated analysis of both thermal demand side evaluation andCHP unit, boilers and HSS performance can allow to enhance theoverall efficiency of the system. Furthermore, reduced emissions ofpollutants typical from a wood-fired combustion plant (above allparticulate matter and nitrogen dioxide) can be obtained limitingpart load operation of the plant and with proper operational andcontrol strategies that are beyond the scope of the study performedso far.

Several simulation codes have been developed in recent years tosupport DH planning [7], both in the short-term [8] and the mid-term [9] perspective. Furthermore, some studies have investi-gated CHP systems coupled with DH [10] as well as CHP perfor-mances at partial load [11]. However, there is often a lack ofinformation about the data measured from DH systems duringoperation and consequently the real behavior can differ from thedesign hypothesis.

This work represents the first stage of a study aiming to simulatethe behavior of DH systems and to analyze energetic, economic andenvironmental aspects with a multi-criteria approach. The modelproposed is based on the integration of computed and measureddatasets.

2. Methodology

2.1. Methodology summary

This paper aims to describe the analysis of configuration andoperational criteria of a DH system through simulations withrespect to multiple parameters. The study is performed bymeans ofa simulation tool capable of analyzing the operation of multiplegeneration units in matching the heat demand load and of evalu-ating/assessing energetic, economic and environmental aspects.The model proposed is based on the integration of computed andmeasured datasets in order to analyze energetic, economic andenvironmental aspects with a multi-criteria approach.

In this paper the installation of a CHP unit coupled to a HSS in anexisting DH network is considered. The heat load profile has beensimulated bymeans of real data that has been recorded over severalyears of operation of an existing DH system with similarcharacteristics.

Different system configurations have been investigated byvarying the CHP nominal power, the HSS size and the operationmode of the system (e.g. full year or heating season only operation).In this case study the CHP unit is an organic Rankine cycle (ORC)system.

An economic analysis has been carried out, focusing on thecurrent Italian incentive tariff on electricity production fromrenewable sources and its effect on the pay back time, with the aimof evaluating the incentive attitude.

2.2. Description of the heat demand dataset

The heat demandmodel used for the simulations was developedby processing operational data collected over ten years of operationfrom the Turin DH system, which has similar characteristicsregarding users typology and climate conditions [12]. The heatsupplied to the thermal grid from each generation unit has beenrecorded every 6 min, as well as the water temperatures and flowrates, from 2002 to 2010. This large amount of data was processedtaking into account also the expansions of the network that haveoccurred over the years. Considering the specific thermal powerdemand a comparison between data of different years has beenperformed.

The Turin DH system currently supplies about 50 million cubicmeters of buildings, which represent more than 40% of the city.

The overall thermal peak power increased during last years toalmost 2 GW, with an annual heat requirement of 1800 GWh. Theheat is mainly provided by three gas turbine combined cycles,whereas backup boilers and heat storage systems provide theremaining part of the load. Over the next years several projectsaim to increase the generation capacity in order to connect newareas of the city to the grid and reach 73 million cubic meters ofconnected buildings.

Through the evaluation of cumulative specific power it has beenpossible to compare the network behavior for different years. Theresult is showed in Fig. 1, considering hourly heat demand. Theslight differences among the years are related to climate conditions,as well as some anomalies due to the connection of new generationunits or significant amount of buildings.

The calculation of specific heat power allows the analysis of thedata for different years and also the comparison with other DHsystems. The comparison with data of various systems is essentialin order to create a wider database, which can track the relationsbetween different parameters (e.g. volume of the buildings, degree-days, length of the grid, users typology, etc.).

Furthermore, the data related to heat production from eachgeneration unit have been analyzed to outline some considerationsabout unit operation behavior. The profiles of heat storage systemshave been analyzed in more detail, in order to assess the opera-tional criteria.

2.3. Description of the case study

This paper presents the results obtained from the application ofthe simulation model mentioned above to a small DH systemalready in operation, in order to analyze some possible improve-ments to the system concerning both design and operationalcriteria. Particular attention has been paid to the evaluation of thebest configurations and operational criteria of a biomass-fired CHPsystem coupled with a heat storage system.

The DH system under examination is located in Leini, a littletown of about 15,000 inhabitants in the outskirts of Turin. About500,000 cubic meters of buildings (mostly residential structures)are supplied by a 12-km DH system powered by two biomassboilers (5 MWeach) and a natural gas backup boiler (3.5 MW). Theannual thermal energy supplied by the system is about 17 GWh,with a consumption of more than 9500 tons of chipped wood. Inthe current configuration the system produces only heat (no CHP),without any HSS coupled to the boilers.

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Fig. 3. Daily energy supplied in the real case study compared to the simulatedbehavior (year 2010).

M. Noussan et al. / Applied Thermal Engineering 71 (2014) 729e735 731

This study considers the additional installation of a CHP system,simulating its behavior with respect to the current heat demand ofthe DH network. The proposed layout of the generation plant isreported in Fig. 2. An ORC turbine has been chosen as CHP unit,coupled to an HSS that allows to split the matching between heatproduction and demand. The existing biomass boilers are used asauxiliary heat generators, producing the excess heat requestedfrom the DH system. The simultaneous production of heat andpower can improve the overall efficiency of the system. Moreover,the installation of a HSS can lead to an efficiency increase thanks tothe recovery of a share of heat production that would be dissipatedto the environment.

The amount of daily energy produced from each boiler in thecurrent system configuration has been registered for five heatingseasons, from 2007/2008 to 2011/2012. The monitoring system canmeasure heat production with more precise time step, butcurrently these data are not stored in the database and thereforethey are not available.

Due to the lack of data regarding the case study operation, theTurin DH dataset has been used to estimate the heat load of theusers. This assumption is justified by the geographic proximity ofthe systems, resulting in similar climate conditions, and by thesimilar users typology. The heat demand has been scaled propor-tionally to the building volume supplied by the DH network and theresultingmodel has been applied to the case study for the year 2010for assessment. The resulting curves are presented in Fig. 3. Thechart shows an acceptable correspondence between the two casesboth during winter and middle-seasons, with some slight de-viations due to some anomalies or slight differences between thetwo DH systems.

2.4. Performance parameters assumed in the simulation

On the basis of the assumed demand input, the tool simulatesthe behavior of the whole DH system calculating the total annualenergy consumed and produced by each component, as well asother parameters. The total heat supplied to the DH network can beexpressed by Equation (1):

Qtot ¼ QCHP þ QHSS þ QBoiler (1)

where QCHP, QHSS and QBoiler represent the heat shares produced byeach component of the system. The amount of heat produced byeach component in matching the total demand is computed foreach time step of the simulation. Multiple factors need to beconsidered in the calculation, e.g. the total heat demand, theavailability of each component, the operation strategy, etc.Considering the efficiency of each component it is possible tocalculate the biomass consumption of the system.

DH network

Biomass fuel

Power grid

Combined heat and power generation plant

CHP Unit

(ORC turbine) Heat Storage

System

Biomass

boilersbiomasselectricity

heat

Fig. 2. Block diagram of the CHP system.

The time step of the simulation has been set to 6 min, accordingto the availability of demand data. The simulation with a detailedtime step can describe the energy system in an accurate way, and itis necessary in order to assess the real performance of the systemunder all the different operation conditions.

The main factor in the choice of a CHP unit is the nominalpower range, affecting both technological and economical con-straints. As a general rule, the CHP unit is usually designed inorder to cover less than half of the thermal peak load. In the LeiniDH the maximum power required by the grid reached 9.8 MWthin 2010, while the total nominal power of the wood-fired boilersis equal to 10 MWth. Considering the behavior of the thermalload, the CHP unit may have a useful thermal power lower than5 MWth.

Among the available wood-fired CHP technologies, the state ofthe art in this range of output power is the organic Rankine cycle(ORC). It is a consolidated and reliable technology with many unitsoperating all around theworld, powered by solid biomass and otherheat sources (heat recovered from industrial processes, geothermalsources, solar energy), and many studies have investigated ORCoperational parameters [13,14].

In the present study (power range from 400 kWe to 1200 kWe)the gross electrical efficiency of the ORC has been set to 19.0% andthe heat efficiency to 77.9%. The heat to power ratio, which remainsconstant in all the different operation conditions, is equal to 4.1. Thenominal efficiency of the thermal oil boiler coupled with the ORCunit has been set to 85% (considering the LHV of the fuel). The CHPunit is assumed to work continuously at nominal power conditions,coupled with a HSS in order to recover part of the surplus heatproduced during off-peak hours.

The HSS performance has been considered on the basis of theDH operation temperature of 90 �C and the return temperature of60 �C. The HSS simulation has been performed considering dailyload/unload cycles, without accounting for eventual infra-dailycycles.

The two biomass-fired boilers currently in operation areassumed to operate as auxiliary boiler, in order to supply the excessheat demand. The actual efficiency of the boilers at partial load iscurrently under investigation, and therefore an estimated value of80% has been assumed as an average annual efficiency. This value islower than the nominal efficiency of the thermal oil boiler in orderto take into account partial load operation and age of the boilers.The DH grid losses have been calculated for the year 2010, and theyare equal to 15.4%.

Table 1Investment and O&M costs for ORC units.

ORC unit Investment cost O&M cost

Total [V] Specific [V/kWe] Total [V/y]

400 kWe V3,794,000 V9,485 V68,840600 kWe V4,251,000 V7,085 V73,260800 kWe V4,708,000 V5,885 V77,6801000 kWe V5,165,000 V5,165 V82,1001200 kWe V5,622,000 V4,685 V86,520

M. Noussan et al. / Applied Thermal Engineering 71 (2014) 729e735732

Multiple output factors have been computed in order to assessthe performance of the system, e.g. overall efficiency, total biomassconsumption, energy produced from each generation unit andsimple pay-back time. The overall efficiency and the primary en-ergy saving index (PES) have been selected as indicators for ener-getic and environmental performance of the system. All the factorshave been calculated with respect to the annual energy, thereforeall the operation conditions are included in the analysis.

2.5. Definition of performance indicators

Overall CHP system efficiency and primary energy savings havebeen selected as main indicators for system performances. Theindicators are calculated considering all the different conditionsanalyzed by the simulation tool.

The overall CHP system efficiency is the ratio between the sumof electricity and useful heat (supplied directly or through HSS tothe network) produced by the CHP unit and the total biomassconsumption of the unit. The efficiency has been calculated for thewhole period of operation, considering all the different conditionswhich occurred during the year.

Primary energy savings have been evaluated calculating the PESindex, as defined in the Directive 2004/8/EC [15] (and transposed inItaly with the DM 4 agosto 2011).

The PES index is defined as follows:

PES ¼0@1� 1

CHP HhRef Hh þ CHP Eh

Ref Hh

1A� 100% (2)

where:

PES is the primary energy saving index;CHP Hh is the heat efficiency of the cogeneration productiondefined as annual useful heat output (Qu) divided by the fuelinput used to produce the sum of useful heat output and elec-tricity from cogeneration (Fin);Ref Hh is the efficiency reference value for separate heatproduction;CHP Eh is the electrical efficiency of the cogeneration produc-tion defined as annual electricity from cogeneration (E) dividedby the fuel input used to produce the sum of useful heat outputand electricity from cogeneration (Fin);Ref Eh is the efficiency reference value for separate electricityproduction.

The annual useful heat output (Qu), the annual electricity pro-duced (E) and the fuel consumptions (Fin) are calculated by thesimulation tool.

The efficiency reference values listed above are defined in theannexes of the DM 4 agosto 2011; for wood-fired systems Ref Eh is0.33 and Ref Hh is 0.86. Some corrections are applied to Ref Eh as afunction of geographical position (and consequent average ambienttemperature). The resulting value for Ref Eh in this case study isequal to 0.33369.

In Italy a CHP system smaller than 1 MWe needs to reach a pos-itive PES to be considered as CAR (High Efficiency Cogeneration),whereas larger systems need to reach at least a PES of 0.1. Thesethresholds are assumed to set the eligibility of a system to receiveincentives related to cogeneration (defined as “CHP bonus”).

2.6. Economic analysis

Performing an in-depth economic analysis is beyond the scopeof this study. However, since in evaluating the design of a CHP

system economic aspects cannot be neglected, a simplified analysishas been performed. Only simple PBT (Pay Back Time) is consid-ered, without taking into account interest rates.

The value of investment cost for the ORC units is reported inTable 1 [16]. This value includes the ORC unit, the wood-firedthermal oil boiler, the pipe connections, the building and thedesign and installation costs. The cost of the HSS has been esti-mated equal to 2400 V/m3 [17]. No other investment costs havebeen taken into account since the DH system is already inoperation.

The operational costs are mainly related to biomass consump-tion and in a minor part to maintenance costs. The lower calorificvalue for chipped wood has been assumed to 3 kWh/kg (consid-ering chipped wood with a moisture content of 35%), according tothe current biomass supply conditions in Leini, and the base pricefor biomass equal to 75 V/t (corresponding to 25 V/MWh). Themaintenance costs for the ORC unit have been expressed withrespect to the size of the system [16], and they are showed inTable 1.

The profits of the system are related to the incomes from theheat supplied to the users, the electricity produced and the avail-able incentives. The current price of the heat sold to final usersdepends on many parameters, and is often defined by differenttariff formulations. A base price of 90 V/MWh has been considered,according to the current conditions of the case study.

From January 2013 the electricity produced from renewablesources in Italy is incentivated with a feed-in tariff described in DM6 luglio 2012. The base price offered for biomass-fired systems(considering chipped wood) is equal to 180 V/MWhel for nominalelectric power between 300 kWe and 1 MWe, and 133V/MWhel forpower larger than 1 MWe. Some bonus can be added to this baseprice, as defined in the same Decree:

� “CHP bonus” of 40 V/MWhel for units operating in high effi-ciency CHP (i.e. PES > 0 for Pe < 1 MWe and PES > 0.1 forPe > 1 MWe);

� “emission bonus” of 30 V/MWhel for systems respectings pre-scribed pollutant emission limits for NOx, CO, SO2, TOC and dust.

A sensitivity analysis has been performed on the heat price andelectricity price, comparing the results with the current incentiveframework. The aim of this analysis is to provide a methodology toassess the effect of the incentive tariff, and discuss somealternatives.

3. Results and discussion

3.1. Performance analysis

The CHP nominal power and the HSS size have been consideredas the leading parameters for the analysis. The ORC power has beenvaried from a minimum of 400 kWe to a maximum of 1.2 MWe,whereas the HSS size is defined with respect to the ORC nominalheat output (m3/MWth), varying the capacity up to 250 m3 per each

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Fig. 5. Overall CHP system efficiency over CHP size and HSS size.

0.25

M. Noussan et al. / Applied Thermal Engineering 71 (2014) 729e735 733

MW of nominal heat power. This upper value of the range is thevolume of storage needed to store all the energy produced duringone night with no heat demand.

The typical behavior of the system during three winter days isshowed in Fig. 4, considering a unit of 800 kWe coupled to a HSS of325 m3, corresponding to 150 m3/MWth. The CHP unit provides thebase load, while the HSS is charged at night in order to supply themorning peak load and allow a gradual operation of the biomassauxiliary boilers. Other operational logics of the HSS can be definedinto the model in order to assess other possible advantages (e.g. aconstant discharge during the day, the total matching of themorning peak load, etc.).

Fig. 5 shows the variation of the overall CHP system efficiency(considering both heat and power) over the two parameters.Without the installation of a HSS the efficiency behavior is linear,while the use of a HSSmodifies the pattern thanks to the increase ofthe useful heat that can be obtained from the CHP unit.

The PES index has a similar behavior (see Fig. 6), as the energysavings are related to the system efficiency. The two dashed linesrepresent the limit set by the regulations to the PES index in orderto reach the high efficiency CHP operation, and obtain the resultingincentive bonus. The CHP system is always operating over thisthreshold for systems smaller than 1 MWe, whereas larger systemsnever reach the target, which is set to PES � 0.1.

The optimum system configuration for this case study, bothfrom efficiency and energy savings point of view, requires a smallCHP system (under 600 kWe) and a HSS larger than 100 m3/MWth.However, the installation of a HSS larger than 150 m3/MWth ap-pears to have negligible effect on the efficiency, especially forsmaller CHP systems.

The larger systems have generally a lower efficiency comparedto the smaller ones because of the share of heat that needs to bedissipated during the middle seasons, when the heat required bythe users is lower. Moreover, it has to be noted that heat dissipationrequires additional energy consumptions related to the operationof the cooling towers, which have not be considered in this study.

3.2. Economic analysis

The case study under investigation has been analyzed also fromthe economic point of view, considering the simple pay back timeas the main output parameter for some comparisons andconsiderations.

The first case examined refers to the current Italian market,without considering the incentive tariff for electricity productionfrom renewable sources. The average national price for electricityhas been considered equal to 75V/MWhe (price for year 2012 [18]).The results of the calculation are showed in Fig. 7 (upper curves).The minimum PBT value (8.7 years) occurs for a 820 kWe ORC unitand a HSS of 100 m3/MWth, corresponding to about 335 m3.

0

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Heat lo

ad

[M

W]

Time [hours]

CHP direct aux boilers CHP through HSS HSS loading

Fig. 4. Example of simulated load (11th Jan e 13th Jan) for a CHP unit of 800 kWe

coupled to a HSS of 325 m3.

However, the PBT has slight variations in a wide range of parame-ters, resulting in significant higher values only for small ORC unitscoupled to large HSS. The economical optimum in this case differsfrom the energetic optimum, but in both cases the variations arelow and therefore an acceptable solution can be found.

The same analysis has been carried out for the current Italianincentive framework, as described previously. The lower curvesreported in Fig. 7 show some significant difference with respect tothe upper ones. The presence on the incentive on electricity pro-duction lowers the PBT range, which is lower than 7.5 years for allthe cases under examination. The minimumvalue of the PBToccursat 1 MWe, in correspondence of the discontinuity of the incentive.A secondary effect of the incentive tariff is evident from themodification of the differences between the curves: as the elec-tricity becomes muchmore profitable than heat, the investment fora HSS is nomore economically justifiable. Thus, the optimumvaluesof PBT are associatedwith systemswithout HSS or with a very smallone, in contrast with the performance analysis showed in Figs. 4and 5. In this case it is not possible to find an optimal solutionboth from energetic and economic point of view.

Some sensitivity analysis have been performed with respect toelectricity price, heat price and biomass price. The base prices are75 V/MWh for electricity, 90 V/MWh for heat and 25 V/MWh forwood biomass. In all the cases a HSS of 100 m3/MWth has beenconsidered.

Fig. 8 shows the variation of PBT over the electricity price. Theaverage price for the years 2008, 2010 and 2012 are marked on the

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PES limit

Fig. 6. PES index over CHP size and HSS size.

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T [years]

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no incentives

incentives (including CHP bonus)

Fig. 7. Pay back time over ORC and HSS size under different incentive conditions.

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PB

T [years]

Heat price [€/MWh]

400 kWe 800 kWe 1200 kWe

Fig. 9. Pay back time over heat price variation (electricity price: 75 V/MWh, biomassprice: 25 V/MWh, HSS size 100 m3/MWth).

M. Noussan et al. / Applied Thermal Engineering 71 (2014) 729e735734

plot, as well as the values of the base incentive. The smallest ORCsystem is significantly different from the average, while the othersystems provide comparable pay back times.

The variation of the heat price (Fig. 9) has a greater effect on thePBT, as the quantity of heat supplied to the user is greater than theelectricity produced. However, there are currently no incentives onheat production for the power range under examination, thereforethe range of variation of heat price remains lower. It has to beobserved that the same reduction in PBTcan be achieved by a lowerincrease of heat price with respect to the current incentive onelectricity price.

The third sensitivity analysis refers to the biomass price (Fig. 10),which can vary depending on the material, the origin, the transportcosts, etc. If the biomass is the waste from some process (e.g.pruning residues) its valuemay be equal to zero, but the fuel qualityin these cases is often very poor.

The annual balance composition has been investigated, and themain revenue is always related to the heat sales (Fig. 11), rangingfrom 53% to 58%, while on the electricity side the incentive value isalmost twice the electricity price for units smaller than 1 MWe, andslightly higher for larger plants. Looking at the operation costs,80%e90% of the cost is due to the biomass, while O&M costs ac-count for the remaining part.

The share of HSS in the total investment cost varies from 0% to34%, and in the optimum configuration without incentives it isequal to 14%.

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PB

T [y

ea

rs

]

Electricity price [€/MWh]

400 kWe800 kWe1200 kWe

IPEX price range Incentive tariff

> 1 MWe <1 MWe

Fig. 8. Pay back time over electricity price variation (heat price: 90 V/MWh, biomassprice: 25 V/MWh, HSS size 100 m3/MWth).

The system configuration corresponding the optimum withoutincentives (ORC unit of 820 kWe and HSS size of 335 m3) is used asreference also for an operational strategy analysis of the system.

In all the cases under consideration the system is operated onlyduring the heating season, but due to the incentive feed-in tariff onelectricity production is not infrequent that some systems areoperated throughout the year. The comparison of these twodifferent operational strategies of the system (Fig. 12) underlinesthe fact that only the presence of incentives for electricity pro-duction from renewable sources makes full-year operation profit-able. Moreover, the greater the incentive, the greater is theadvantage of this operation mode. To be noticed that for this spe-cific case study the CHP bonus, granted only to the share of theelectricity produced in high efficiency CHP, does not affect thistrend in a significant way.

These results are valid in the frame of the current Italian feed-intariff. Nevertheless, the methodology presented in this paper canbe extended to any incentive framework. Other kind of incentives(e.g. quota-based incentives) could lead to different results,reaching an economic optimumwith a higher energy performance.However, these alternatives are depending on many different pa-rameters, and could be the object of further analyses.

4. Conclusions

The simulations performed show some key features of theoperation of a wood biomass ORC unit coupled with a HSS in anexisting district heating network.

0

5

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0 5 10 15 20 25 30 35 40

PB

T [y

ea

rs

]

Biomass price [€/MWh]

400 kWe 800 kWe 1200 kWe

Fig. 10. Pay back time over biomass price variation (electricity price: 75 V/MWh, heatprice: 90 V/MWh, HSS size 100 m3/MWth).

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400 600 800 1000 1200

Re

ve

nu

es

a

nd

C

os

ts

[M

€]

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heat electricity incentive biomass O&M

Fig. 11. Composition of the annual balance over the ORC size (electricity incentives,HSS size 100 m3/MWth).

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No incentive Base incentive Base + CHP Base + CHP + emissions

Pa

y B

ac

k tim

e [y

ea

rs

]

heating season operation

full year operation

Fig. 12. Comparison of the pay back time over electricity tariff in winter and full yearoperation (CHP unit of 800 kWe, HSS size 325 m3).

M. Noussan et al. / Applied Thermal Engineering 71 (2014) 729e735 735

The installation of a HSS can lead to a significant increase of theoverall efficiency of the system (up to 8.6%). In the present casestudy the highest efficiencies are reached for a HSS size of 150 m3/MWth, whereas for higher sizes the HSS provides no additionaladvantages.

The current formulation of the national incentive on electricityproduction has a strong effect on the system layout and operation,and appears to discourage the more efficient solutions. The highvalue of electricity leads to a shift of the optimal configuration to asolution with no HSS and a corresponding lower overall efficiency.Moreover, the incentive has an influence also on the operationalstrategy, making in some cases the full year operation of the system(with heat dissipation during the summer season) more conve-nient. Finally, the discontinuity of the incentive at 1 MW of electricpower induces a significant distortion in the trends.

Considering the design of biomass-fired CHP units, energy effi-ciency and economic profit are still conflicting. Therefore a carefulanalysis of these two aspects, together with considerations about

environmental and social aspects, is crucial in order to reach aglobal sustainability of the system and of the wood-to-energypathway.

NomenclatureCHP combined heat and powerDH district heatingHSS heat storage systemORC organic Rankine cycleP nominal powerPBT Pay back time

Subscriptse electricth thermal

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