Methodology to estimate the economic, emissions, and energy

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energy benefits from combined heat and power systems ... between power to heat ratio, base loading fraction, percentage of recovered heat used, and minimum ratios for cost, ... provide benefits comes from making the best possible use.
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Methodology to estimate the economic, emissions, and energy benefits from combined heat and power systems based on system component efficiencies Pedro J. Mago1,*,† and Amanda D. Smith2 1

Department of Mechanical Engineering, Mississippi State University, Mississippi State, MS, USA 2 Department of Mechanical Engineering, University of Utah, Salt Lake City, UT, USA

ABSTRACT This paper presents a methodology to estimate the economic, emissions, and energy benefits that could be obtained from a base loaded CHP system using screening parameters and system component efficiencies. On the basis of the location of the system and the facility power to heat ratio, the power that must be supplied by a base loaded CHP system in order to potentially achieve cost, emissions, or primary energy savings can be estimated. A base loaded CHP system is analyzed in nine US cities in different climate zones, which differ in both the local electricity generation fuel mix and local electricity prices. Its potential to produce economic, emissions, and energy savings is quantified on the basis of the minimum fraction of the useful heat to the heat recovered by the CHP system (ϕ min). The values for ϕ min are determined for each location in terms of cost, emissions, and energy. Results indicate that in terms of cost, four of the nine evaluated cities (Houston, San Francisco, Boulder, and Duluth) do not need to use any of the heat recovered by the CHP system to potentially generate cost savings. On the other hand, in cities such as Seattle, around 86% of the recovered heat needs to be used to potentially provide cost savings. In terms of emissions, only Chicago, Boulder, and Duluth are able to reduce emissions without using any of the recovered heat. In terms of primary energy consumption, only Chicago and Duluth do not require the use of any of the recovered heat to yield primary energy savings. For the rest of the evaluated cities, some of the recovered heat must be used in order to reduce the primary energy consumption with respect to the reference case. In addition, the effect of the efficiency of the power generation unit and the facility power to heat ratio on the potential of the CHP system to reduce cost, emissions, and primary energy is investigated, and a graphical method is presented for examining the trade-offs between power to heat ratio, base loading fraction, percentage of recovered heat used, and minimum ratios for cost, emissions, and primary energy. KEY WORDS combined heat and power systems; CHP; based loaded CHP; emissions reduction; primary energy Correspondence *Pedro J. Mago, Department of Mechanical Engineering, Mississippi State University, Mississippi State, MS, USA. † E-mail: [email protected]

1. INTRODUCTION CHP systems can provide economic, environmental, and energy savings benefits when compared with purchased electricity and thermal energy produced from an on-site boiler [1–6]. A CHP system produces electricity and useful thermal energy from one fuel source, and its potential to provide benefits comes from making the best possible use of the fuel energy. Previous work has demonstrated that the ability to obtain operational costs savings, reduced emissions, and primary energy savings is related to a number of factors, including the efficiencies of the system components [7–9], the operating strategy of the CHP system

[10,11], and the loads required by the facility to be served by the CHP system [12]. The location of the facility affects the potential for CHP systems to provide these benefits based on the local climate, which affects energy demands [13], local prices for electricity and fuel [14–16], the amount of emissions associated with electricity purchased from the grid in that region [17], and the amount of source energy used to produce delivered electricity in that region of the grid [18,19]. The concept of a minimum spark spread, which was previously introduced by Smith et al. [20], describes the minimum difference in electricity and fuel prices (per unit of energy) that would be necessary for a CHP system to show a cost benefit. Analogous spark

spread-type screening parameters were developed for CO2 emissions and primary energy consumption [21]. The minimum spark spread is computed from the minimum cost ratio or the ratio of electricity and fuel prices [22]. The minimum cost ratio is a simple way to express the necessary relationship between electricity and fuel prices in order for a CHP system to show cost savings potential. The cost ratio in a given location has been described as ‘the key parameter used for making optimal decisions’ when optimizing the operation of a CHP system [23]. Mago and Luck [24] presented a methodology to size base loaded CHP systems based on ratios of conversion factors applied to imported electricity to conversion factors applied to fuel consumed. They concluded that in order to achieve savings in operational cost, emissions, and primary energy reduction, the ratios must be larger than a unique constant that only depends on the CHP components efficiencies. Researchers have discussed many CHP operational strategies such as base loading, following the electric load, following the thermal load, and following an optimal operation strategy to maximize savings [11,25,26,6,27,19]. Some of these strategies apply linear programming techniques [28–30] or evolutionary algorithm [31] to determine the optimal PGU size and operational scheme. These strategies may use different approaches to determine the CHP system performance, but typically, these strategies require hourly load data in their calculations. Because hourly load data are not readily available in most facilities, the goal of this paper is to present a methodology to estimate the economic, emissions, and energy benefits that could be obtained from a base loaded CHP system from monthly or yearly data. Another important parameter to consider for CHP system operation is the overall efficiency [7,32]. The amount of the heat recovered from the CHP system that is actually used to satisfy part or all of the building thermal demand is a critical variable affecting the performance of the system. This paper presents a methodology to estimate the economic, emissions, and energy benefits that could be obtained from a base loaded CHP system using screening parameters and system component efficiencies. Its potential to produce economic, emissions, and energy savings is quantified on the basis of the minimum fraction of the useful heat to the heat recovered by the CHP system (ϕ min). In addition, the effect of the efficiency of the power generation unit (PGU) and the facility power to heat ratio on the potential of the CHP system to reduce cost, emissions, and primary energy is investigated, and a graphical method is presented for examining the trade-offs between power to heat ratio, base loading fraction, percentage of recovered heat used, and minimum ratios for cost, emissions, and primary energy.

2. ANALYSIS A CHP system energy flow is presented in Figure 1. The overall system efficiency for a CHP system, indicating

Figure 1. CHP system energy flow.

the amount of fuel energy used for providing electricity or heat to the facility, can be described as the addition of the electrical efficiency of the PGU, ηpgu, with the net thermal efficiency, ηthermal, as shown in Eq. (1): (1) ηCHP ¼ ηpgu þ ηthermal The electrical efficiency of the PGU and the CHP system thermal efficiency can be expressed as E CHP ηpgu ¼ (2) F pgu ηthermal ¼

Quseful ϕQCHP ¼ F pgu F pgu

(3)

where ECHP is the electrical energy provided by the PGU of the CHP system, Fpgu is the fuel energy consumed by the PGU of the CHP system, Quseful is the thermal energy delivered to the facility that is used for space heating or hot water, and ϕ is the fraction of the useful heat to the heat recovered by the CHP system, QCHP. The heat recovered is given by  QCHP ¼ Qpgu ηhrs ξ ¼ F pgu  ECHP ηhrs ξ

(4)

where Epgu is the electricity provided by the PGU, ξ is a factor that accounts for energy lost both before and after the hot stream reaches the heat recovery equipment, and ηhrs is the heat recovery system (HRS) efficiency. By using Eqs. (3) and (4), the thermal efficiency can be expressed as   ηthermal ¼ ϕ 1  ηpgu ηhrs ξ

(5)

The cost to operate the CHP system is given by Cost CHP ¼ Cost f F pgu

(6)

where Costf is the cost of the fuel. The cost to operate the separate heat and power (SHP) system can be expressed as Cost SHP

  ϕQCHP ¼ Cost e E CHP þ Cost f ηhs

where Coste is the cost of electricity.

(7)

The cost ratio, Rcost, represents the ratio of the cost of purchased electricity to the cost of purchased fuel, as in Eq. (3): Rcost ¼

Cost e Cost f

(8)

where Coste and Costf should be expressed in the same units, yielding a dimensionless parameter. By setting CostSHP = CostCHP, the minimum cost ratio, which represents equivalent operating costs for producing electricity and heat with a CHP system compared with the same amount of electricity and heat using SHP, can be expressed as Rmin ¼

ηhs  ξϕηhrs ξϕηhrs þ ηhs ηpgu ηhs

Rcost Rmin

Qb α=β ¼ QCHP Π

α¼

ηpgu E CHP  ¼ QCHP 1  ηpgu ηhrs ξ

(14)

Eb Qb

(15)

E CHP Eb

(16)

β¼

Π¼

(10)

where Eb and Qb represent the building electric and thermal load. Equations (12) and (13) can be compared to determine the potential cost savings from the CHP system θ ≥ ϕ min →Qb > Qpgu →Potential Savings θ ≤ ϕ min →Qpgu > Qb →No Savings

Then, if ε > 1→Cost CHP < Cost SHP if ε ¼ 1→Cost CHP ¼ Cost SHP

(11)

if ε < 1→Cost CHP > Cost SHP where CHPcost and SHPcost represent the operational cost of the CHP system and the operational cost of the SHP system. Equation (11) indicates that the higher the value of ε, the greater the potential for cost reduction by using a CHP system rather than a SHP system. On the other hand, if the system component efficiencies and Rcost are known, the minimum value of ϕ, fraction of the useful heat to the heat recovered by the CHP system, to guarantee savings from the CHP system can be determined by setting Rcost = Rmin using Eq. (9) as ϕ min ¼

ηhs  Rcost ηhs ηpgu ξηhrs  ξηpgu ηhrs

(12)

where 0 ≤ ϕ min ≤ 1. Negative values of ϕ min mean that no heat needs to be recovered to potentially obtain savings from the CHP system. If the thermal and electric load for a facility, Qb and Eb, respectively, are known as well as the size and efficiency of the PGU, the potential for a CHP system to provide cost savings can be assessed by determining the ratio of the heat needed by the building to the heat recovered from the CHP system as follows:

(13)

where α represents the ratio of the power generated by the CHP system to the heat recovered, β is the ratio of the building electric to thermal load, and Π represents the fraction of the electric load provided by the CHP system (amount of base loading). These variables are defined as

(9)

If all the parameters in Eq. (9) are known, the value of Rmin can be determined and compared with the actual Rcost to determine a ‘break-even’ cost ratio, ε, as follows: ε¼

θ¼

(17)

If the thermal and electric load for a facility are known but the amount of base loading is unknown, by setting Eqs. (12) and (13) equal, the maximum fraction of base loading that can be used to achieve savings can be determined as Πmax ¼

ηpgu βηhs  Rcost βηhs ηpgu

(18)

The value obtained in Eq. (18) will provide the amount of base loading that yields the same savings as the SHP. Therefore, Π > Πmax →No Savings Π ¼ Πmax →Same as SHP

(19)

Π < Πmax →Potential Savings The same analysis can be performed to estimate the potential of emission and primary energy savings by changing Rcost to RCO2 and RPE, respectively. The CO2 emissions ratio represents the ratio of the CO2 emissions associated with a unit of purchased electricity to the CO2 emissions associated with on-site use of a unit of fuel as RCO2 ¼

EEF FEF

(20)

where EEF is the electricity emissions factor and FEF is the fuel emissions factor. EEF and FEF should be in the same units to obtain a dimensionless parameter. RCO2 is

similar to Rcost in that the EEF can be considered to be the environmental ‘cost’ of the purchased electricity rather than the monetary cost, and the FEF can be considered to be the environmental ‘cost’ of using fuel on-site rather than the monetary cost of purchasing that fuel. The primary energy consumption ratio represents the ratio of the amount of primary energy consumed to produce a unit of purchased electricity, as in Eq. (9): RPE ¼

ECF FCF

(21)

where ECF is the electricity emissions factor and FCF is the fuel emissions factor both on the same units. RPE is also similar to RCost and RCO2 in that the ECF can be considered to be the energetic ‘cost’ of the purchased electricity, and the FCF can be considered to be the energetic ‘cost’ of the fuel used on-site.

Table III. Emission factors for electricity and natural gas, RCO2, and ϕ min for the values presented in Table I. City

EEF (kg CO2/GJ) FEF (kg CO2/GJ) [34] [33] RCO2

Houston, TX Las Vegas, NV San Francisco, CA Baltimore, MD Seattle, WA Chicago, IL Boulder, CO Helena, MT Duluth, MN

City

Value

ηpgu ηhrs ηhs ς

654.12 654.12 654.12

2.95 2.974 1.644

0.183 0.171 0.804

1547.1 1337.7 2483 2979.3 1337.7 2659.4

654.12 654.12 654.12 654.12 654.12 654.12

2.365 2.045 3.796 4.555 2.045 4.065

0.461 0.613 0 0 0.613 0

Houston, TX Las Vegas, NV San Francisco, CA Baltimore, MD Seattle, WA Chicago, IL Boulder, CO Helena, MT Duluth, MN

ECF (GJ/GJ) [35]

FCF (GJ/GJ) [36]

RPE

ϕ min

3.16 2.92 2.45 3.25 1.81 3.5 3.32 2.91 3.53

1.047 1.047 1.047 1.047 1.047 1.047 1.047 1.047 1.047

3.018 2.789 2.34 3.104 1.729 3.343 3.171 2.779 3.372

0.15 0.259 0.473 0.109 0.764 0 0.077 0.264 0

with the associated RCost, RCO2, and RPE. Figure 2 illustrates ϕ min for each location for cost, emissions, and primary energy based on the values presented in Table I. Results indicate that in terms of cost, in four of the nine evaluated cities (Houston, San Francisco, Boulder, and Duluth), the CHP system does not need to used any of

Table I. Parameters used to determine the minimum heat ratio required. Variable

1929.7 1945.4 1075.6

Table IV. Site to source energy conversion factors for electricity and natural gas, RPE, and ϕ min for the values presented in Table I.

3. RESULTS In this section, the potential savings in terms of cost, emissions, and primary energy consumption in multiple locations is investigated. For the initial analysis, the values used for the PGU efficiency, heat recovery system efficiency, loss factor, and heating system efficiency to determine the minimum ratio of the heat (ϕ min, Eq. (9)) are presented in Table I. The cost [14,15], carbon dioxide emissions factors [33,34], and primary energy conversion factors [35,36] for electricity and natural gas for the selected locations are presented in Tables II, III, and IV

ϕ min

0.3 0.8 0.8 0.9

Table II. Cost of electricity and natural gas, Rcost, and ϕ min for the values presented in Table I.

City Houston, TX Las Vegas, NV San Francisco, CA Baltimore, MD Seattle, WA Chicago, IL Boulder, CO Helena, MT Duluth, MN

Coste ($/GJ) [14]

Costf ($/GJ) [15]

Rcost

ϕ min

15.53 14.33 26.92 22.72 11.14 15.19 18.89 13.86 18.64

3.33 5.59 6.16 7.72 7.27 5.27 4.68 7.26 4.13

4.668 2.566 4.369 2.944 1.532 2.882 4.037 1.908 4.511

0 0.365 0 0.185 0.858 0.215 0 0.679 0

Figure 2. Minimum heat ratio (ϕ min) for the different locations evaluated in this paper for the values presented in Table I.

the recovered heat to potentially generate cost savings. This can be explained because these locations have a high Rcost, and therefore, savings are possible by generating onsite electricity alone. On the other hand, CHP systems in cities such as Seattle need to use around 86% of the recovered heat to be able to provide cost savings. In terms of emissions, only Chicago, Boulder, and Duluth are able to reduce emissions without using any of the recovered heat. These three cities are the ones that present higher RCO2 values. For the rest of the evaluated cities, some of the recovered heat must be used in order to reduce the emissions with respect to the reference case. San Francisco, the city with the lowest RCO2, requires that around 81% of the recovered heat is used in order to provide emissions savings. In terms of primary energy consumption, only in Chicago and Duluth, the CHP system does not require the use of any of the recovered heat to yield primary energy savings. For the rest of the evaluated cities, some of the recovered heat must be used in order to reduce the primary energy consumption with respect to the reference case. Figure 3 illustrates the values of ϕ min versus R (RCost, RCO2, and RPE) for different PGU efficiencies. This figure was generated using the values presented in Table I while varying the efficiency of the PGU from 0.2 to 0.5. It can be observed that ϕ min decreases when the R value increases for the same ηpgu.On the other hand, for the same value of R, a more efficient PGU results in a lower ϕ min. It is important to highlight that for R values smaller than 1, ϕ min is greater than 1, which means that in order to achieve savings, the CHP system would have to use more than the heat recovered that is available, which is not possible. For example, for the city of Seattle, for Rcost = 1.532 and ηpgu = 0.3 (point A), ϕ min = 0.858. That means that 85.8% of the recovered heat has to be used to be able to achieve cost savings for this location. If ηpgu = 0.45, the new ϕ min = 0.627. Therefore, only 52% of the recovered heat has to be used to be able to achieve cost savings. In terms of emissions, for RCO2 = 2.045 and ηpgu = 0.3 (point B), for Seattle, ϕ min = 0.613. If ηpgu = 0.45, the new ϕ min = 0.161. Therefore, only 16.1% of the recovered heat has to be used

Figure 3. Minimum heat ratio need to obtain savings for different Rcost, RCO2, and RPE.

to be able to potentially reduce emissions. Similarly, for primary energy consumption (RPE = 1.729), for ηpgu = 0.3 (point C), ϕ min = 0.741. As with cost and emissions, increasing ηpgu to 0.45 would reduce ϕ min to 0.448. Figure 3 is useful for making quick analyses of savings potential for CHP systems, and it is easy to implement by determining values of ϕ min for each location based on the efficiency of the PGU. Figure 4 shows the variation of θ (ratio of the heat needed by the building to the heat recovered from the CHP system, defined in Eq. (13)) versus Π (fraction of the electric load provided by the CHP system, defined in Eq. (16)) for different β values (ratio of the building electric to thermal load, defined in Eq. (15)) for a PGU efficiency of 0.3. This figure clearly indicates that for the same value of Π, lower β values result in higher values of θ or the fraction of the facility thermal load that will be provided by the CHP system. In addition, for the same θ, lower β values result in higher values of Π or the percentage of power that needs to be supplied by the CHP system with respect to the facility electric load. Figures 3 and 4 can be used together to estimate the potential cost, emissions, and primary energy savings for a facility in any location as follows: a. From Figure 3, for a known value of R (RCost, RCO2, and RPE), ϕ min can be determined. b. For a known value of β, the maximum amount of power that can to be supplied by the PGU to guarantee savings can be determined using Figure 4 by setting θ = ϕ min. Figure 5 presents six different cases for the city of Seattle to implement the methodology described earlier. The cases are as follows: Case A: a. With Rcost = 1.532 and ηpgu = 0.3, the value of ϕ min can be determined as 0.858. b. Setting θcost = ϕ min = 0.858, for β = 5, the maximum Π can be estimated as 0.139, which means that

Figure 4. θ versus Π for different values of β.

Figure 5. θ versus Π for different values of power generation unit efficiencies.

any base loading up to approximately 14% of the electricity required by the facility can be supplied by the CHP system in order to achieve cost savings. Case B: a. With Rcost = 1.532 and ηpgu = 0.3, the value of ϕ min can be determined as 0.858. b. Setting θcost = ϕ min = 0.858, for β = 1.5, the maximum Π can be estimated as 0.347, which means that any base loading up to approximately 34.7% of the electricity required by the facility can be supplied by the CHP system in order to achieve cost savings. Comparing cases A and B, it can be seen that decreasing the value of β for the same conditions, the CHP system has the flexibility to provide more of the electricity needed by the facility (34.7% instead of 13.9%) and still obtains cost savings compared with the SHP system. Case C: a. With RCO2 = 2.045 and ηpgu = 0.3, the value of ϕ min can be determined as 0.613. b. Setting θCO2 = ϕ min = 0.613, for β = 5, the minimum Π can be estimated as 0.194, which means that a minimum of approximately 19.4% of the electricity required by the facility needs to be supplied by the CHP system in order to achieve emission savings. Case D: a. With RCO2 = 2.045 and ηpgu = 0.3, the value of ϕ min can be determined as 0.613. b. Setting θCO2 = ϕ min = 0.613, for β = 1.5, the maximum Π can be estimated as 0.647, which means that any base loading up to approximately 64.7% of the electricity required by the facility can be supplied by the CHP system in order to achieve emission savings. Comparing cases C and D, it can be seen that decreasing the value of β for the same conditions, the CHP system has the flexibility to provide more of the

electricity needed by the facility (64.7% instead of 19.4%) and still obtains carbon dioxide emission savings compared with the SHP system. Case E: a. With RPE = 1.729 and ηpgu = 0.3, the value of ϕ min can be determined as 0.741. b. Setting θPE = ϕ min = 0.741, for β = 5, the maximum Π can be estimated as 0.156, which means that any base loading up to approximately 15.6% of the electricity required by the facility can be supplied by the CHP system in order to achieve emission savings. Case F: a. With RPE = 1.729 and ηpgu = 0.3, the value of ϕ min can be determined as 0.741. b. Setting θPE = ϕ min = 0.741, for β = 1.5, the maximum Π can be estimated as 0.519, which means that any base loading up to approximately 51.9% of the electricity required by the facility can be supplied by the CHP system in order to achieve emission savings. Comparing cases E and F, it can be seen that decreasing the value of β for the same conditions, the CHP system has the flexibility to provide more of the electricity needed by the facility (51.9% instead of 15.6%) and still obtains primary energy consumption savings compared with the SHP system. In general, the results presented in this figure indicate that the cost, emissions, and primary energy are independent variables, and that optimizing one may result in an increase of the other two. Figure 6 shows the variation of θ versus Π for different ηpgu values for β = 5. Results indicate that for the same ηpgu, the value of θ decreases as Π increases. On the other hand, for the same value of Π, the value of θ increases as ηpgu increases. To illustrate the effect of the ηpgu on the fraction Π, three examples with different ηpgu are presented in Figure 7 for the city of Seattle. As before,

Figure 6. Example to illustrate the use of Figure 5.

Also, this clearly affects the amount of base loading that could be provided by the CHP system because higher efficiencies yield higher values of the maximum Π that could be used.

4. CONCLUSIONS

Figure 7. Example to illustrate the use of Figure 6.

a. From Figure 3, for a known value of R (RCost, RCO2, and RPE), ϕ min can be determined for an specific ηpgu. b. For a known value of β (5 in this figure) and ηpgu the amount of power that needs to be supplied by the PGU can be determined using Figure 6 by setting θ = ϕ min. Figure 7 presents three different cases for the city of Seattle to implement the methodology described earlier. The cases are as follows: Case A: a. With Rcost = 1.532 and ηpgu = 0.2, the value of ϕ min can be determined as 0.963. b. Setting θcost = ϕ min = 0.963, for ηpgu = 0.2, the maximum Π can be estimated as 0.072, which means that a maximum of approximately 7.2% of the electricity required by the facility can be supplied by the CHP system in order to achieve cost savings. Case B: a. With Rcost = 1.532 and ηpgu = 0.3, the value of ϕ min can be determined as 0.858. b. Setting θcost = ϕ min = 0.858, for ηpgu = 0.3, the maximum Π can be estimated as 0.139, which means that a maximum of approximately 13.9% of the electricity required by the facility can be supplied by the CHP system in order to achieve cost savings. Case C: a. With Rcost = 1.532 and ηpgu = 0.4, the value of ϕ min can be determined as 0.717. b. Setting θcost = ϕ min = 0.717, for ηpgu = 0.4, the maximum Π can be estimated as 0.258, which means that a minimum of approximately 25.8% of the electricity required by the facility can be supplied by the CHP system in order to achieve cost savings. From the cases presented earlier, it can be observed that increasing the efficiency of the PGU decreases the value of ϕ min while keeping the other conditions the same.

This paper presented a methodology to estimate the economic, emissions, and energy benefits that could be obtained from a base loaded CHP system using screening parameters and system component efficiencies. On the basis of the location of the system and the facility power to heat ratio, the maximum power that could be supplied by a base loaded CHP system in order to potentially achieve cost, emissions, or primary energy savings can be estimated using the proposed methodology. A base loaded CHP system was analyzed in nine US cities in different climate zones, which differ in both the local electricity generation fuel mix and local electricity prices. The potential of a CHP system to generate economic, emissions, and energy savings was quantified on the basis of the minimum fraction of the useful heat to the heat recovered by the CHP system (ϕ min). The values for ϕ min were determined for each location in terms of cost, emissions, and energy. In terms of cost, four of the nine evaluated cities (Houston, San Francisco, Boulder, and Duluth) do not need any of the recovered heat to potentially generate cost savings, indicating that on-site power generation alone may reduce electrical costs. On the other hand, the use of CHP systems in cities such as Seattle needs to use around 86% of the recovered heat to be able to provide cost savings. In terms of emissions, only Chicago, Boulder, and Duluth are able to reduce emissions without using any of the recovered heat. In relation to primary energy consumption, only Chicago and Duluth do not require the use of any of the recovered heat to yield primary energy savings. In addition, the efficiency of the PGU and the facility’s power to heat ratio affects the potential of the CHP system to reduce operating costs, emissions, and primary energy consumption. The proposed methodology can be a valuable tool during the initial analysis and design of a CHP system in a given location.

NOMENCLATURE CHP Costfuel Coste Epgu Fpgu PGU Qpgu QCHP Quseful

= combined heat and power = cost of the fuel = cost of the electricity = electricity generated by the PGU = fuel consumed by the PGU = power generation unit = heat available from the PGU = heat recovered from the CHP system = thermal energy delivered to the facility that is used for space heating or hot water

Qb ηCHP ηhs ηhrs ηpgu ηthermal ξ

Rcost RCHP RSHP Rmin RCO2

RPE ϕ ϕ min Πmax Π β θ

= thermal load of the facility = CHP total system efficiency = efficiency of the heating system of the building = CHP heat recovery system efficiency = electrical efficiency of the PGU = net thermal efficiency = factor that accounts for losses before thermal energy reaches the heat recovery system = ratio of the cost of purchased electricity to the cost of purchase fuel = cost to operate the CHP system = cost to operate the separate heat and power system = minimum cost ratio = ratio of the CO2 emissions associated with a unit of purchased electricity to the CO2 emissions associated with on-site use of a unit of fuel = ratio of the amount of primary energy consumed to produce a unit of purchased electricity = fraction of the useful heat to the heat recovered by the CHP system = minimum fraction of the useful heat to the heat recovered by the CHP system = maximum fraction of base loading that can be used to achieve savings = fraction of the electric load provided by the CHP system (amount of base loading = ratio of the building electric to thermal load = parameter defined in Eq. (13)

4.

5.

6.

7.

8.

9.

REFERENCES 1. Mago PJ, Chamra LM, Hueffed A. A review on energy, economical, and environmental benefits of the use of CHP systems for small commercial buildings for the North American climate. International Journal of Energy Research 2009a; 33(14): 1252–1265 doi:10.1002/er.1630, ISSN: 1099-114X, URL http://dx.doi.org/10.1002/er.1630 2. Cho H, Mago PJ, Luck R, Chamra LM. Evaluation of CCHP systems performance based on operational cost, primary energy consumption, and carbon dioxide emission by utilizing an optimal operation scheme. Applied Energy 2009a; 86(12):2540–2549. ISSN: 0306–2619, doi:10.1016/j.apenergy.2009.04.012, URL http://www.sciencedirect.com/science/article/pii/ S0306261909001421 3. Wang J, Zhai ZJ, Zhang C, Jing Y. Environmental impact analysis of {BCHP} system in different climate

10.

11.

zones in China. Energy 2010; 35(10):4208–4216, ISSN: 0360–5442, doi:10.1016/j.energy.2010.07.007. Ren H, Gao W. Economic and environmental evaluation of micro {CHP} systems with different operating modes for residential buildings in Japan. Energy and Buildings 2010; 42(6):853 – 861. ISSN: 0378–7788, doi:10.1016/ j.enbuild.2009.12.007, URL http://www.sciencedirect. com/science/article/pii/S0378778809003302 Mago PJ, Smith AD. Evaluation of the potential emissions reductions from the use of {CHP} systems in different commercial buildings. Building and Environment 2012; 53(0):74–82. ISSN: 0360–1323, doi:10.1016/j. buildenv.2012.01.006, URL http://www.sciencedirect. com/science/article/pii/S0360132312000157 Mago P, Chamra L. Analysis and optimization of CCHP systems based on energy, economical, and environmental considerations. Energy and Buildings 2009; 41(10):1099 – 1106. ISSN: 0378–7788, doi:10.1016/j. enbuild.2009.05.014, URL http://www.sciencedirect. com/science/article/pii/S0378778809001157 Chen M, Lund H, Rosendahl LA, Condra TJ. Energy efficiency analysis and impact evaluation of the application of thermoelectric power cycle to today CHP systems. Applied Energy 2010; 87(4):1231–1238. ISSN: 0306–2619, doi:10.1016/j.apenergy.2009.06.009, URL http://www.sciencedirect.com/science/article/pii/S0306261909002475 Moran A, Mago PJ, Chamra LM. Thermoeconomic modeling of micro-CHP (micro-cooling, heating, and power) for small commercial applications. International Journal of Energy Research 2008; 32(9): 808–823. ISSN: 1099-114X, doi:10.1002/er.1395, URL http://dx.doi.org/10.1002/er.1395 Hueffed AK, Mago PJ. Influence of prime mover size and operational strategy on the performance of combined cooling, heating, and power systems under different cost structures, Proceedings of the Institution of Mechanical Engineers. Part A: Journal of Power and Energy 2010; 224(5):591–605. doi:10.1243/ 09576509JPE922, URL http://pia.sagepub.com/content/224/5/591.abstract Piacentino A, Cardona F. On thermoeconomics of energy systems at variable load conditions: Integrated optimization of plant design and operation. Energy Conversion and Management 2007; 48(8):2341 – 2355. ISSN: 0196–8904, doi:10.1016/j.enconman.2007.03.002, URL http://www.sciencedirect.com/science/article/ pii/S0196890407000696 Mago PJ, Fumo N, Chamra LM. Performance analysis of CCHP and CHP systems operating following the thermal and electric load. International Journal of Energy Research 2009b; 33(9):852–864. ISSN: 1099-114X, doi:10.1002/ er.1526, URL http://dx.doi.org/10.1002/er.1526

12. Kowalski GJ, Zenouzi M. Selection of Distributed Power-Generating Systems Based on Electric. Heating, and Cooling Loads, Journal of Energy Resources Technology 2006; 128(3):168–178. 13. Wang J, Zhai Z, Jing Y, Zhang C. Influence analysis of building types and climate zones on energetic, economic and environmental performances of BCHP systems. Applied Energy 2011; 88(9): 3097 – 3112. ISSN: 0306–2619, doi:10.1016/j.apenergy.2011.03.016, URL http://www.sciencedirect.com/science/article/pii/S0306261911001735 14. U.S. Energy Information Administration. Electricity: Sales. 2013a. Retrieved from http://www.eia.gov/electricity/data.cfm 15. U.S. Energy Information Administration. Natural Gas Prices. 2013b. Retrieved from http://www.eia.gov/ 16. Ahmadi P, Dincer I. Exergoenvironmental analysis and optimization of a cogeneration plant system using Multimodal Genetic Algorithm (MGA). Energy 2010; 35(12):5161–5172. 17. US Environmental Protection Agency. Emissions and Generation Resource Integrated Database (eGRID). 2010. Available at http://www.epa.gov/ 18. Fumo N, Chamra L. M.. Analysis of combined cooling, heating, and power systems based on source primary energy consumption. Applied Energy 2010; 87(6): 2023 – 2030. ISSN: 0306–2619, doi:10.1016/j. apenergy.2009.11.014, URL http://www.sciencedirect. com/science/article/pii/S0306261909005017 19. Fumo N, Mago PJ, Chamra LM. Energy and economic evaluation of cooling, heating, and power systems based on primary energy. Applied Thermal Engineering 2009; 29(13):2665–2671. 20. Smith AD, Fumo N, Mago PJ. Spark spread - A screening parameter for combined heating and power systems. Applied Energy 2011a; 88(5):1494 – 1499. ISSN: 0306–2619, doi:10.1016/j.apenergy.2010.11.004, URL http://www.sciencedirect.com/science/article/pii/ S0306261910004678 21. Smith AD, Mago PJ, Fumo N. Emissions spark spread and primary energy spark spread - Environmental and energy screening parameters for combined heating and power systems. Applied Energy 2011b; 88(11): 3891 – 3897. ISSN: 0306–2619, doi:10.1016/j. apenergy.2011.03.042, URL http://www.sciencedirect. com/science/article/pii/S0306261911002121 22. Smith AD, Mago PJ, Fumo N. Impact of CHP System Component Efficiencies on the Economic Benefit of CHP Systems Using Spark Spread Analysis, ASME 2011 International Mechanical Engineering Congress and Exposition. 2011c. 23. Yun K, Luck R, Mago PJ, Smith A. Analytic Solutions for Optimal Power Generation Unit

24.

25.

26.

27.

28.

29.

30.

31.

32.

33.

Operation in Combined Heating and Power Systems. Journal of Energy Resources Technology 2012; 134(1):011301–1. Mago PJ, Luck R. Prime mover sizing for base-loaded combined heating and power systems, Proceedings of the Institution of Mechanical Engineers. Part A: Journal of Power and Energy 2012; 226(1):17–27. doi:10.1177/0957650911406055, URL http://pia. sagepub.com/content/226/1/17.abstract Mago PJ, Luck R. Evaluation of a base-loaded combined heating and power system with thermal storage for different small building applications. International Journal of Energy Research 2013; 37(2):179–188. ISSN: 1099-114X, doi:10.1002/ er.1892, URL http://dx.doi.org/10.1002/er.1892 Jalalzadeh-Azar A. A comparison of electrical- and thermal-load following CHP systems. ASHRAE Transactions 2004; 110:85–94. Cardona E, Piacentino A, Cardona F. Matching economical, energetic and environmental benefits: An analysis for hybrid CHCP-heat pump systems. Energy Conversion and Management 2006; 47(20):3530–3542. ISSN: 0196–8904, doi:10.1016/ j.enconman.2006.02.027. Cho H, Luck R, Eksioglu SD, Chamra LM. Costoptimized real-time operation of {CHP} systems. Energy and Buildings 2009b; 41(4):445–451. ISSN: 0378–7788, doi:10.1016/j.enbuild.2008.11.011, URL http://www.sciencedirect.com/science/article/ pii/S0378778808002454 Ren H, Gao W, Ruan Y. Optimal sizing for residential CHP system. Applied Thermal Engineering 2008; 28(5):514 – 523. ISSN: 1359–4311, doi:10.1016/j. applthermaleng.2007.05.001, URL http://www. sciencedirect.com/science/article/pii/S1359431107001810 Beihong Z, Weiding L. An optimal sizing method for cogeneration plants. Energy and Buildings 2006; 38(3):189–195. ISSN: 0378–7788, doi:10.1016/j. enbuild.2005.05.009, URL http://www.sciencedirect. com/science/article/pii/S0378778805000897 Ahmadi P, Almasi A, Shahriyari M, Dincer I. Multiobjective optimization of a combined heat and power (CHP) system for heating purpose in a paper mill using evolutionary algorithm. International Journal of Energy Research 2012; 36(1):46–63. ISSN: 1099114X, doi:10.1002/er.1781, URL http://dx.doi.org/ 10.1002/er.1781 Martens A. The energetic feasibility of CHP compared to the separate production of heat and power. Applied Thermal Engineering 1998; 18(11):935–946. U.S. Environmental Protection Agency. Direct Emissions from Stationary Combustion Sources.

(EPA430-K-08-003). 2008. Retrieved from http:// www.epa.gov/climateleadership/documents/resources/ stationarycombustionguidance.pdf 34. U.S. Environmental Protection Agency. How clean is the electricity I use? - Power Profiler. 2012. Retrieved from http://www.epa.gov/

35. Czachorski M, Leslie N. Source energy and emission factors for building energy consumption. 2009. Retrieved from American Gas Association website: http://www.aga.org/ 36. U.S. Department of Energy. ENERGY STAR Performance Ratings: Methodology for Incorporating Source Energy Use. 2011. Retrieved from http://www.energystar.gov

1466

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