Design Optimization of a Heat Thermal Storage Coupled with a Micro-CHP for a Residential Case Study

Design Optimization of a Heat Thermal Storage Coupled with a Micro-CHP for a Residential Case Study

Available online at www.sciencedirect.com ScienceDirect Energy Procedia 101 (2016) 830 – 837 71st Conference of the Italian Thermal Machines Enginee...

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Available online at www.sciencedirect.com

ScienceDirect Energy Procedia 101 (2016) 830 – 837

71st Conference of the Italian Thermal Machines Engineering Association, ATI2016, 14-16 September 2016, Turin, Italy

Design optimization of a heat thermal storage coupled with a microCHP for a residential case study Sandro Magnania*, Lorenzo Pezzolaa, Piero Dantia a

Yanmar R&D Europe, Viale Galileo 3/A, Florence 50125, Italy

Abstract Energy efficiency is a key target of the European Union policy. The “Europe 2020 strategy” quantitative targets account an increase by 20% of the energy efficiency by the end of 2020. The attention to power sources optimization and energy waste reduction leads European Countries to develop subsidy strategies to drive the energy market towards efficiency enhancement. According to this trend, energy efficiency of residential buildings has significantly grown in Italy in the last years. Combined production of electric and thermal power is a notable example of efficiency enhancement awarded by the CAR (Cogenerazione ad Alto Rendimento) Italian subsidies system. In these circumstances, the optimization of the ensemble between power generators and thermal storages becomes crucial to satisfy in an efficient way thermal power requirement independently from electric power production. The purpose of this paper is to find the optimal power plant design of power generators and thermal storages in order to minimize daily management costs and environmental impact. The power plant layout in analysis consists in a micro-CHP (Combined Heat and Power) and an absorption chiller both coupled with respective thermal storages. Through this evaluation, it is possible to identify the optimal coupling of the devices as a function of the load requirements and understand the great influence of their sizing on the energy management benefits. The analysis is performed with reference to cold and warm thermal load required by a residential case study. The performance analysis takes place in representative days of different seasons and the results are extended on an annual base. The power request profiles are developed on the basis of literature data. The results are compared on an economic basis considering the NPV (Net Present Value) index, evaluated using as the benchmark a standard plant layout composed by a water boiler and an electric chiller. © Published by Elsevier Ltd. This © 2016 2016The TheAuthors. Authors. Published by Elsevier Ltd. is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the Scientific Committee of ATI 2016. Peer-review under responsibility of the Scientific Committee of ATI 2016. Keywords: CHP; cogeneration; thermal storage; design optimization; energy efficiency; CO2 reduction

* Corresponding author. Tel.: +39-055-5121694/5; fax: +39-055-5121693; .e-mail address: [email protected]

1876-6102 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the Scientific Committee of ATI 2016. doi:10.1016/j.egypro.2016.11.105

Sandro Magnani et al. / Energy Procedia 101 (2016) 830 – 837

1. Introduction In the last years Green House Gases (GHGs) emission reduction and efficiency increase are two of the main challenges that the energy industry has to face with, due to the climate change combined with the increase in the World energy requests (even if the economic crisis flattered this trend), especially in developing Countries, where the fast-grow energy request has led to the installation of several large power plant scarcely matching with the environmental needs. The European Union (EU) in particular is paying attention to these problems, resulting in the policies to mitigate or defeat the global warming (e.g. the 2020 Energy Strategy [1] and the 2030 Energy Strategy [2] in the Energy Roadmap to 2050 [3]). Among the initiatives for the reduction of the CO2 and the increase of the efficiency in the power industry, the Combined Heat and Power (CHP) systems represent one of the ready-to-use options for efficiently supplying energy, especially in buildings, also applying the now mature small- and microscale technologies, with rated power outputs lower than 50 kWe. With this focus in mind, the analysis of the application of the Combined Cooling, Heating and Power (CCHP) technology to a residential household, especially if combined with thermal storages, has a great relevance in the large view panorama of the climate change issue. In the following, the application of a cogeneration unit coupled with an absorption chiller and two thermal storage, one for each thermal loop (heating and cooling) applied to a residential case study will be analyzed, in particular focusing the attention on the effects of the reciprocal sizing between the CHP and the storages. In more detail, in paragraph 2 all the elements to define the problem will be provided, in terms of load profiles of the case study, of the installed pieces of equipment and of the reference energy scenario; in section 3 the analysis results will be shown and discussed, and a brief summary will be reported in paragraph 4. Nomenclature CAR CCHP CHP EER EU ICE GHG PES PM TEE

Cogenerazione ad Alto Rendimento Combined Cooling, Heating and Power Combined Heat and Power Energy Efficiency Ratio European Union Internal Combustion Engine Green House Gas Primary Energy Saving Prime Mover Titoli di Efficienza Energetica

2. Problem definition 2.1. Case study definition The feasibility analysis of the local combined generation technology coupled with storages, in terms of both economic and environmental matters, is focused on a residential household. The loads requirement of the hypothesized case study is defined by the elaboration of the data reported in [4] by Macchi et al., which performed a long-term measurement campaign on the energy requests (electricity, heating, and cooling) of different contexts, spacing from residential, to industry, to tertiary sector. Starting from the daily power load profiles (hourly defined) for example winter and summer day for a single apartment in a block of flats and from its monthly average energy consumption in one year, the data in input to the analysis are summarized in Table 1 in terms of annual energy consumptions, power peak for electric, heating, and cooling loads. In Fig. 1 (a) and (b) are shown the daily power requests in winter and summer season, respectively, while in Table 2 the monthly correction factors are reported, determining the shifting of the example daily profiles to fit them with the different periods of the year. In Table 2, months going from May to September refer to the example summer day, and the remaining to the example winter

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day. The heating consumption referred to the summer days is attributable to the sanitary water requests, while for winter days this contribution is included in the overall profile. Table 1. Residential building main characteristics. Parameter

Value

Number of apartments [-]

35 3

Average volume of apartment [m ]

360

Loads contemporaneity factor [%]

40

Yearly electricity request [kWhe]

93,088

Yearly heating request [kWhth]

294,228

Yearly cooling request [kWhc]

52,886

Electric power peak [kWe]

24.9

Heating power peak [kWth]

146.2

Cooling power peak [kWc]

75.6

b

a

Fig. 1. (a) example winter day; (b) example summer day. Table 2. Monthly correction factors. Load

Jan

Feb

Mar

Apr

May

Jun

Jul

Aug

Sep

Oct

Nov

Dec

Electric

0.759

0.828

0.862

0.897

0.931

1

0.931

0.897

1

0.931

0.931

0.897

Heating

0.992

0.965

0.314

0.255

1

1

1

1

1

0.263

0.773

1

Cooling

0

0

0

0

0

0.730

0.968

1

0.508

0

0

0

Being the main focus the performance estimation of a micro-CCHP system coupled with thermal storages, as the base line for the analysis a “conventional” power supply is considered: in more detail, the heating request is fulfilled by a condensing natural gas boiler, representing the most common solution for new buildings construction or for the refurbishment of the thermal plant, while the cooling needs are considered supplied by an electric compression chiller; the power loads (proper + electric chiller consumption) are satisfied by the connection with the national power grid. In the “upgraded” local production plant the presence of a micro-cogeneration system is considered, based on an Internal Combustion Engine (ICE) as the Prime Mover (PM), fed by natural gas, being the most common technical solution for this kind of applications. The engine is coupled to an absorption chiller, with the purpose to increase the operation time of the CHP during the year and the energy production efficiency also during the cooling period. In order to partially decouple the use of the thermal output and of the electricity by the ICE, two storages (in the form of warm and chilled water tanks) are considered in the analysis, one demanded to operate as a buffer for the heat recovered by the CHP and the other for shifting the cooling demand by the production from the absorption chiller. The importance of their installation for the improvement of CHP performance is emphasized by several studies: Barbieri et al. in [5] analyze the economic profitability of the heat storage for a residential case study

Sandro Magnani et al. / Energy Procedia 101 (2016) 830 – 837

considering different PMs, while Haeseldonckx et al. in [6] are more focused on the effects of the buffer on CO 2 emissions; different technologies for the heat storage (sensible and latent heat) are shown by Mongibello et al. in [7], considering the technical and economic feasibility. With the purpose to always guarantee the satisfaction of the thermal loads, back-up systems are considered for both the heating and cooling loop: respectively, a condensing gas boiler and an electric compression chiller are hypothesized as generators able to always close the thermal balance. The power connection with the national grid is considered, as well, for supplying the electricity lack that can occasionally be experienced. 2.2. Energy market scenario definition The operating context of the analyzed case study is supposed to be the Italian energy market. In Italy, the reception of the guidelines from EU for the energy efficiency applied to the cogeneration sector led to the definition of subsidies for efficient micro-CHP systems, known as Cogenerazione ad Alto Rendimento (CAR, high efficiency cogeneration) mechanism, better explained in [8]. In brief, if in the operation of the CHP the parameters of total efficiency and Primary Energy Saving (PES) achieve some fixed threshold values (that for the particular case of a rated electric output lower than 50 kW e are fixed respectively in 75% and 0), the taxes on natural gas supply are remarkably reduced, determining a decrease in the gross price of about 33%. A supplementary incentive (called TEE, Titoli di Efficienza Energetica) is rewarded at the end of each year, for a maximum of a 10 years period, related to the measured saving in terms of primary energy compared to a conventional separated generation. Anyway, the future perspective of this incentive is not clear, and in the analysis will be neglected. Nevertheless, in recent times the sale to the power grid of the excess of electricity from the CHP is poorly rewarded, so that also subsidies are not enough to allow an electric overproduction of the cogeneration system compared to the power demand. For this reason, in the present analysis an “hybrid” operation strategy is considered for the ICE: the main driver is the thermal demand of the building (indifferently if heating of cooling), with a feedback control on the produced electricity and, of course, on the CHP technical limits. In more detail, if the request is under the minimum partial load operation of the engine, also considering the storage charging potential, its operation is inhibited, and the same happens if the thermal demand is high enough but the power request is under the technical minimum. Conversely, if both conditions are satisfied for the CHP operation, its power set-point is determined by the smallest load, electric or thermal: if the electric output corresponding to the thermal demand is larger than the loads request, the set-point is driven by electricity, vice versa in the opposite situation. A synthesis of the operational logic of the CHP is shown in Fig.2.

Fig. 2. Flow chart of the CCHP operation logic.

When considering the purchase of the energy vectors, i.e. electricity and natural gas, Italian scenario presents several different conditions. The electricity can be purchased by the free market or, as an alternative, by the market regulated by the energy authority AEEGSI (Autorità per l’Energia Elettrica, il Gas ed il Sistema Idrico, authority for the electric energy, the natural gas and the hydric system): in the former case a large selection of contracts is available, spacing from flat tariffs during all the hours of the day to purchase prices indexed with the electric stock exchange; in the latter one the tariff paradigm is on 3 different frames, the F1 involving the time period between 8 AM to 7 PM from Mondays to Fridays, the F2 that is comprehensive of the periods going from 8 AM to 9 AM and from 7 PM to 11 PM from Mondays to Fridays and from 7 AM to 11 PM on Saturdays, lasting with rate F3 in all the remaining periods of the week. In the analysis this last solution is considered, being mostly used in all the residential and tertiary sector contexts. Similarly, natural gas can be purchased indifferently by the free or regulated market, but

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in each case the tariff is flat. All the details on the price parameters and on the economic issues considered in the analysis are summarized in Table 3. Table 3. Economic reference conditions for Italian energy market scenario. Parameter

Value

Electricity price F1 [€/kWhe]

0.22

Electricity price F2 [€/kWhe]

0.215

Electricity price F3 [€/kWhe]

0.20

Electricity selling price [€/kWhe]

0.03

Natural gas price [€/Sm3]

0.78

CHP reference cost [€/kWe]

1,500

Absorption chiller reference cost [€/kWc]

700

Gas boiler reference cost [€/kWth]

150

Electric chiller reference cost [€/kWc]

300

Water tank reference cost [€/m ]

1,000

CHP maintenance cost [€/h ON]

0.30 (CP10WE1)

(absorption chiller included)

0.40 (CP25WE)

3

Gas boiler maintenance cost [€/h]

0.07

Electric chiller maintenance cost [€/h]

0.07

Installation cost (fixed) [€]

7,000 3,000 (base scenario)

2.3. Equipment size and test definition Several studies were carried out for the selection of the most suitable size for CHP systems, also considering different application contexts: Ren et al. in [9] propose their Mixed-Integer Linear (MILP) approach to the problem, also considering the presence of a thermal storage, while Duki in [10] proposes a two-stage stochastic programming to optimally size the cogeneration system; Ghadimi et al. in [11] propose a method to optimally select the most suitable CHP output considering also the management strategy, which shall be integrated in the sizing method. In this analysis, an empirical approach is considered for deciding the optimal size of the combination between the CHP and the thermal storage: two sizes for the CHP and five volumes for the thermal storages are considered. For the selection of the cogeneration units, the criterion of the maximum area defined under the loads duration curve is considered, on both the electric and thermal loads. In deep detail, all the hourly loads for an entire year are listed from the larger to the smaller, and their duration is coupled: by plotting the curve representing the loads in the coordinate axis and their duration in the abscissa axis, the ideal size of the CHP is correspondent to y-axis value of the submitted rectangle whose vertex is lying on the curve and defining the maximum area, as shown in Fig. 3.

Fig. 3. Example of the loads duration curve sizing method.

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In the present case, considering the electric loads curve, the ideal size of the cogeneration unit is 11 kW e, so that the Yanmar CP10WE1 is selected as the reference micro-CHP, whose power output is 10 kWe and performance characteristics can be retrieved in [12]. When considering the heating loads (as proper or the equivalent in summer period by dividing the cooling request for a fixed conversion factor for the absorption chiller), the mentioned method lead to an optimal sizing of 50 kWe: with the hypothesized operation strategy of the CHP and the electric loads peak (see Table 1), the CHP so defined is electrically oversized, so the selection lies on a 25 kW e, being this value the maximum electric demand of the loads. As a consequence, the Yanmar CP25WE with a rated electric output of 25.1 kWe [12] is selected. The size of the absorption chiller coupled with the cogeneration units is defined so to allow the conversion into cooling power of all the heat recovered from the PM: by doing so, the rated outputs of the device are 12 kWc and 27 kWc for the CP10WE1 and the CP25WE, respectively. Its partial load performance is defined as described in [13], even if for sake of simplicity no influence of the ambient temperature is considered. For the thermal storage, the selected sizes are in the range between 1 m3 to 5 m3 with steps of 1 m3 for both the warm and chilled water tank, considering in each test the same size for both of them. Also the solution with no thermal storage is considered in the analysis. The size of the back-up pieces of equipment is defined on the basis of the thermal load peak demand: for the considered case study, a gas boiler of 150 kW th rated output and an electric compression chiller with 80 kW c rated are selected. The boiler performance in partial load conditions are considered as the same as for rated output, considering that the heat loss are negligible; the off-design characteristics of the electric chiller are hypothesized on the basis of the results obtained by In et al. in [14]. The main characteristics of all the selected pieces of equipment are summarized in Table 4. Table 4. Equipment main characteristics. Parameter

Value

Parameter

CP10WE1 min-max electric output [kWe]

1 - 10

Absorption chiller rated output (CP10) [kWc]

Value 12

CP10WE1 rated thermal output [kWth]

16.2

Absorption chiller rated output (CP25) [kWc]

27

CP10WE1 rated electric efficiency [%]

32

Absorption chiller rated EER [-]

0.7

CP10WE1 rated thermal efficiency [%]

52

Gas boiler rated thermal output [kWth]

150

CP25WE min-max electric output [kWe]

2.5 - 25.1

Gas boiler rated thermal efficiency [%]

100

CP25WE rated thermal output [kWth]

38.4

Electric chiller rated thermal output [kWc]

80

CP25WE rated electric efficiency [%]

33.5

Electric chiller rated EER [-]

3

CP25WE rated thermal efficiency [%]

51.5

3

Thermal storages size [m ]

1 - 2 - 3 - 4 -5

3. Results and discussion The yearly economic results of the feasibility analysis are shown in Table 5. In Fig. 4 the NPV results are reported for CP10WE1 in (a) and for CP25WE in (b), considering a time horizon of 15 years estimated as the life of the CHPs; as the reference conditions for the yearly money loss of value, 3% is considered, while the inflation trend is estimated in 1%. The trends are shown for volumes of the storage up to 3 m3 only, because the larger sizes of the thank give values overlapping the mentioned one. As expected, in all cases the installation of the thermal storages (of the same size on the heating and cooling loop) with the CHP gives some economic advantage both in the short and long time, also considering that their cost and the investment difference among the different volumes is almost negligible. Nevertheless the advantage is small, with a maximum difference in the yearly plant operations of about 1,500 € for the CP10WE1 and 1,700 € for the CP25WE, representing a small percentage of the total cost saving variable from 2.5% to 9.3% for the 10 kWe-rated CHP and from 2.1% to 8.2% for the cogeneration unit with the larger size. If needed, the evidence of this aspect is also carried out by considering that no variation in the Pay-Back Time (PBT) is experienced when the volume of the storage is modified, being approximately 5 years for all the considered configurations. On the contrary, the largest difference is when considering the bigger size of the CHP, with an average of about 8% compared to the base line. On the authors opinion, this is mainly attributable to two different aspects: at first, the residential context presents a remarkable unbalance of the loads towards the thermal demand, with an average yearly ratio larger than 3.7.

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Sandro Magnani et al. / Energy Procedia 101 (2016) 830 – 837 Table 5. Yearly plant operation advantage compared with conventional solution. Yearly advantage [€]

Configuration

a

Yearly advantage [€]

Configuration

CP10WE1 - no storage

16,219

CP25WE - no storage

20,179

CP10WE1 - 1 m3

16,630

CP25WE - 1 m3

20,597

CP10WE1 - 2 m3

17,086

CP25WE - 2 m3

21,129

3

CP10WE1 - 3 m

17,488

3

CP25WE - 3 m

21,509

CP10WE1 - 4 m3

17,616

CP25WE - 4 m3

21,762

CP10WE1 - 5 m3

17,732

CP25WE - 5 m3

21,826

b

Fig. 4. (a) NPV results for CP10WE1; (b) NPV results for CP25WE.

a

c

b

d

Fig. 5. (a) Yearly primary energy savings for CP10WE1; (b) Yearly CO2 emission savings for CP10WE1; (c) Yearly primary energy savings for CP25WE; (d) Yearly CO2 emission savings for CP25WE.

As a consequence, an optimal size of the CHP based on the thermal request would determine an oversize on the electric size and with the hypothesized operation logic of the PM, a frequent partial load running and a low

Sandro Magnani et al. / Energy Procedia 101 (2016) 830 – 837

efficiency of the system; reversely, by considering a smaller size of the engine the ICE would run at full load each time, but the increase of the ratio of the installation costs on the total capital investment would determine longer PBT values. The second aspect is attributable to the operation logic of the cogeneration system itself, mainly determined by the energy market scenario: if the remuneration for the sale of the exceeding electricity from the ICE to the grid would be larger, then the production and the storage of the energy. On the basis of the previous analysis, the opportunity to consider water storage tanks in such a kind of application is not determined by economic evaluations, rather than technical evaluation like the availability of space in the installation context. The yearly environmental results, in terms of both primary energy consumptions and equivalent CO2 emissions is shown in Fig. 5 (a) and (b) respectively for the CP10WE1, and in (c) and (d) for the CP25WE. The estimation is made by considering a conversion efficiency for the electricity purchased from the grid of 46% (Italian reference value as in [15]), and supposing that the ratio for passing from the electricity from the grid and from the natural gas to the equivalent carbon dioxide emissions are respectively defined in 0.448 kg/kWhe and 1.957 kg/Sm3. As expected, environmental performance is similar to the economic one. The difference attributable to the different size of the CHP can be considered as negligible, with an average decrease of about 7.2% in primary energy savings and about 3% in CO2 emissions in favor of the largest rated output. Similar percentages can be calculated when modifying the storage volume, with a decrease of 7.6% and 9.1% in primary energy consumptions and carbon emissions for the smallest CHP installing the largest water tank in comparison with no storage, and a decrease of 9% and 10.1% in the same situation with the CP25WE. 4. Conclusions The need for larger efficiency and lower carbon emissions in energy-related activities is continuously increasing. In the residential sector, one of the most interesting and remunerative options is the application of CCHP systems, even coupled with thermal storage. A feasibility analysis for this technology is carried out considering a block of flats case study in the Italian energy market scenario. The installation of a tri-generation unit shows encouraging results both in economic and environmental terms, with the larger CHP, sized on the electric peak load, experiencing the better performance, mainly due to the high ratio between thermal and electric loads (about 3.7) and to the poor remuneration for the sale of the exceeding electricity to the power grid. On the contrary, the presence of the water tank storages (on the hot and cold loop) gives small advantages, also increasing their volume: in a different energy context their use could be remarkably more useful than this. References [1] https://ec.europa.eu/energy/en/topics/energy-strategy/2020-energy-strategy. [2] http://ec.europa.eu/energy/en/topics/energy-strategy/2030-energy-strategy. [3] https://ec.europa.eu/energy/sites/ener/files/documents/2012_energy_roadmap_2050_en_0.pdf. [4] Macchi E, Campanari S, Silva P. La climatizzazione a gas e ad azionamento termico. Polipress; 2012. In Italian. [5] Barbieri ES, Melino F, Morini M. Influence of the thermal energy storage on the profitability of micro-CHP systems for residential building applications. Applied Energy 2012; pp.714-722, vol.97. [6] Haeseldonckx D, Peters L, Helsen L, D’haeseleer W. The impact of thermal storage on the operational behaviour of residential CHP facilities and the overall CO2 emissions. Renewable and Sustainable Energy Reviews 2007; pp.1227-1243, vol.11. [7] Mongibello L, Capezzuto M, Graditi G. technical and cost analyses of two different heat storage systems for residential micro-CHP plant. Applied Thermal Engineering 2014; pp.636-642, vol.71. [8] http://www.gse.it/it/Qualifiche%20e%20certificati/Certificati%20Bianchi%20e%20CAR/Pages/default.aspx. In Italian. [9] Ren H, Gao W, Ruan Y. Optimal sizing for residential CHP system. Applied Thermal Engineering 2008; pp.514-523, vol.28. [10] Duki EA. Optimal sizing of CHP for residential complexes by two-stage stochastic programming. Proceedings of the 17th Conference on Electrical Power Distribution Network (EPDC) 2012. [11] Ghadimi P, Kara S, Kornfeld B. The optimal selection of on-site CHP systems through integrated sizing and operational strategy. Applied Energy 2014; pp.38-46, vol.126. [12] http://www.yanmarenergysystems.eu/Product-Micro-Cogeneration/. [13] http://www.maya-airconditioning.com/base_menu_it.html. [14] In S, Cho K, Lim B, Lee C. Partial load performance test of residential heat pump system with low-GWP refrigerants. Applied Thermal Engineering 2015; pp.179-187, vol.85. [15] http://www.autorita.energia.it/allegati/docs/15/174-15.pdf.

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