Comparative study of economic viability of rural electrification using renewable energy resources versus diesel generator option in Saudi Arabia: Journal of Renewable and Sustainable Energy: Vol 5, No 4

Abstract

The objective of this paper is to assess the economic viability of Saudi Arabia's renewable energy resources in electricity production in the rural and remote areas as against the use of diesel generators (DG). The methodology employed is to pick an existing isolated DG electric station for a rural community and assess the levelized cost of energy (LCOE) generated for incremental generation by adding either DG, wind electric conversion system (WECS), or solar Photo Voltaic (PV) electric system. Cost figures are derived from current technology price indices and consultancies studies as contained in the National Renewable Energy Laboratory cost report of November 2012. The existing power station of Addfa in the Southern region is analyzed based on the requirement to increase its current capacity to cater for surrounding smaller communities. An annual extra energy requirement of 4 GWh is to be met by scenarios of using DG, WECS, PV or a hybrid system. Two ownership structures are considered namely a public utility that pays no tax and a private independent power producer (IPP) that pays tax. Both the constant and current LCOE generated are determined for each ownership structure. The results indicate that the WECS is the first investment choice with a constant LCOE of $0.0922/kWh and $0.1090/kWh for the public utility and the IPP, respectively. The DG is the second choice with LCOE of $0.1082/kWh and $0.1175/kWh, the third is a hybrid DG plus WECS with LCOE of $0.1102/kWh and $0.1234/kWh for each ownership structure, respectively. Finally, the PV electric system ranks fourth with LCOE of $0.2791/kWh and $0.3279/kWh, respectively. The results of sensitivity analysis show that these values of LCOE are more sensitive to the initial capital cost and less sensitive to the operation and management costs.

I. INTRODUCTION

The quest of every developing country is to provide electricity to all citizens whether in urban or rural areas. Rural areas are often characterized by far distances, less population, low income, and less economic activities making it extraordinarily expensive to extend the national electricity supply network (national grid) to those areas. Thus most rural communities are supplied with electric power by means of isolated power supply in smaller scales. In Saudi Arabia there are many such isolated power generation stations mostly using the diesel generator (DG) option to provide power. Though Saudi Arabia has abundant deposits of fossil fuel that is used as a power source for the diesel generators, the global concern of greenhouse gas (GHG) emission which is responsible for global warming cannot be overlooked. Fossil fuels emit carbon dioxide (CO₂) into the atmosphere which is one of the GHGs that contributes to global warming.¹1. IEA, World Energy Outlook - 2009. Retrieved January 2010 (International Energy Agency, 2009). The need to find alternative sources of generating electricity that will curtail the emission of CO₂ is an obligation of every responsible nation. Renewable energy resources such as wind, solar, hydro, geothermal, etc., are potential energy sources that could be tapped and used in generating electricity. In view of this, this paper has the overriding objective to economically assess the capabilities of the renewable energy resources of Saudi Arabia as alternative to conventional electric generation such as the diesel generator option in supplying rural communities with electricity. Hourly electricity consumption data is collected from one of the isolated power generation stations at Addfa, a rural community in the Southern province of Saudi Arabia and it is used as a representative load for a typical rural community in the country. There are many small rural communities near Addfa that are not yet supplied with electricity. In this study the economics of integrating all the surrounding communities with the Addfa electric station is evaluated in terms of adding next generation units. A comparative economic viability of the next generation units being DG, wind electric conversion system (WECS), PV electric system, or a hybrid system is studied. The wind and solar data of the area are used for the comparative economic analysis in different scenarios of supplying additional power either by conventional means or through the use of renewable energy technologies (RETs) or by hybrid system.

The literature of renewable energy electric systems (REES) is well developed, though there still remains a lot of unexplored area for research. Utilization of renewable energy sources (RES) for rural communities has been studied extensively with the conclusion that RES could be both economical and environmental friendly if employed for electricity generation in such rural areas.^2,32. A. K. Akella, M. Sharma, and R. Saini, “Otimum utilization of renewable energy sources in a remote area,” Renewable Sustainable Energy Rev. 11, 894–908 (2007). https://doi.org/10.1016/j.rser.2005.06.006 3. M. R. Nouni, S. Mullick, and T. Kandpal, “Techno-economics of small wind electric generator projects for decentralized power supply in India,” Energy Policy 35, 2491–2506 (2007). https://doi.org/10.1016/j.enpol.2006.08.011 Various studies have modeled the theoretical site-matching wind turbine for any area under study,^4–64. U. Bawah, K. E. Addoweesh, and A. M. Eltamaly, “Economic modeling of site-specific optimum wind turbine for electrification studies,” Adv. Mater. Res. 347–353, 1973–1986 (2012). https://doi.org/10.4028/www.scientific.net/AMR.347-353.1973 5. F. A. L. Jowder, “Wind power analysis and site matching of wind turbine generators in Kingdom of Bahrain,” Appl. Energy. 86, 538–545 (2009). https://doi.org/10.1016/j.apenergy.2008.08.006 6. M. H. Albadi and E. F. El-Saadany, “Optimum turbine-site matching,” Energy 35, 3593–3602 (2010). https://doi.org/10.1016/j.energy.2010.04.049 in addition to modeling site solar insolation on optimum tilt angles.⁷7. S. Rehman, “Solar radiation over Saudi Arabia and comparisons with empirical models,” Energy 23(12), 1077–1082 (1998). https://doi.org/10.1016/S0360-5442(98)00057-7 The economics of deploying such REES are mainly based on cost estimates and the use of levelized cost of electricity (LCOE) produced from these systems.^8,98. S. Diaf, M. Belhamel, M. Haddadi, and A. Louche, “Technical and economic assessment of hybrid photovoltaic/wind system with battery storage in Corsica island,” Energy Policy 36, 743–754 (2008). https://doi.org/10.1016/j.enpol.2007.10.028 9. A. Malik and A. H. Al-Badi, “Economics of wind turbine as an energy fuel saver - A case study for remote application in Oman,” Energy 34, 1573–1578 (2009). https://doi.org/10.1016/j.energy.2009.07.002 Based on the fact that a single renewable energy source is unreliable in providing continuous electricity, hybrid renewable energy systems composed of combinations of different renewable energy resources and/or conventional systems are currently being studied in detail.¹⁰10. S. Rehman, M. M. Alam, J. P. Meyer, and L. M. Al-Hadhrami, “Feasibility study of wind-pv-diesel hybrid power systems for a village,” Renewable Energy 38, 258–268 (2012). https://doi.org/10.1016/j.renene.2011.06.028 In this paper, various aspects of the literature are brought together in a comparative study of a remote area in Saudi Arabia in the Al-Jawf region using a typical rural load of Addfa in the region. The wind and solar resources of the region are used in modeling the renewable energy resources in providing electricity as compared to the currently standalone diesel generator (DG) system in the area. What makes this study different from those of previous studies is that while most of the previous studies assumed a public utility is the sole producer of electricity and hence will pay no tax; this study includes the independent power producer (IPP) which is a private profit oriented business and pays tax (this may also include investor owned utility (IOU)). The IPP/IOU became important since after 2008 economic crisis that calls for soliciting other financial means than depending on public sponsorship.¹¹11. I. Flavius and B. Viorel, “The potential of the local administration as driving force for the implementation of the national PV systems strategy in Romania,” Renewable Energy 38(1), 117–125 (2012). https://doi.org/10.1016/j.renene.2011.07.014 This addition requires more accounting and financial modeling than the no-tax public utility case. The issue of tax in Saudi Arabia is often considered zero but this is true for residence income tax. The Saudi corporate income tax rate for 2009 was quoted as 20% while that for natural gas companies is 30%.¹²12. PKF, Saudi Arabia Tax Guide 2009 (PKF, 2009). This calls for examining the case of a corporate power producer. Thus, the extension of the literature made here is by adding the economic analysis of a private profit utility company that pays tax in comparison with the generally assumed public utility company that pays no tax. The second addition to the literature is the consideration of the difference in the real and current discount rates in analyzing the economics of renewable energy systems. Most researchers have used only the real discount rate but this paper considers the two forms and how these discount rates are arrived at. The third difference is that cost estimates are taken from well known consultants studies and current price trends in renewable energy technology. The conventional system (DG) is also maintained as a competitive choice since private investment is more inclined to the most economical option.

II. SITE STUDY

The site chosen—Addfa; is a remote area in the Southern province of Saudi Arabia in the AlJawf region. The latitude and longitude for Addfa are, respectively, 29.42° and 41.25° with an estimated population of about 2300. The area is chosen as it represents a typical remote area and has isolated power generation from a private DG set. This area has several years of ground measured wind and solar energy data that facilitate its being considered for renewable energy electric projects. Addfa is surrounded by so many isolated rural communities and it is proposed to hook these communities to Addfa's electric station by expanding its installed capacity by nearly 100%. The concern here is to explore the economics of adding the next generation units as DG, WECS, PV electric system or hybrid system. The old DG station will continue to work and complement the electric energy production of the REES when the resources of the latter are absent.

III. METHODOLOGY

The methodology applied is to consider that Addfa needs an extra electric installed capacity of about 100% of the current value in order to be capable of hooking other communities nearby to it. The load requirement is thus modeled, followed by cost modeling of the extra supply scenarios such as by DG, WECS, or PV system. This paves the way for economic analysis of the total life cycle costing (TLCC) and levelized cost of energy generated (LCOE) by each scenario. The flow chart of Figure 1 summarizes the methodology and detail discussion of each aspect of the methodology is presented next.

FIG. 1. Flow chart of methodology.

High-resolution

A. Site load modeling

To build a renewable energy electric plant to cater for the type of load of Addfa, it is recommended to use the yearly peak load (P_L) to model the capacity to be installed. There are several load design approaches and this work uses the design standard for standalone power systems of the Australian/New Zealand Standard AS/NZS 4509.2:2010.¹³13. Joint Technical Committee EL-042 (2010). Australian/New Zealand Standard AS/NZS 4509.2:2010 (Standards Australia Limited/Standard New Zealand). The design load for rural community can be obtained as

P_{d} = P_{L} (1 + k_{g}) (1 + k_{c}),

(1)

where P_d is the design load power (kW), P_L is the peak load power, derived from the load profile (kW), K_g is a contingency for future load growth (%) typically between 5 and 20%, and K_c is a design margin (%) typically between 10 and 15%.

Modeling the annual design energy takes the same format,

E_{d} = E_{L} (1 + k_{g}) (1 + k_{c}),

(2)

where E_d is the design energy demand (kWh) and E_L is the total load energy, which is the area under the load profile (kWh)

B. Modeling the conventional DG plant

Based on the knowledge of the design load P_d and the design energy E_d for the load, the DG as well as other renewable energy power systems can be modeled to supply the load. The cost components of the DG are as follows:

-	Initial capital cost (ICC) which is made up of engineering, procurement, and construction costs (EPC), owner's cost and interest during construction. The owner's cost includes onsite works, office/administration buildings, fuel tanks, connection fees of pipelines, and de-rating costs using site conditions.
-	Fixed O&M costs (FOM) consist of operation personnel salaries, insurances, property taxes, etc.
-	Variable O&M costs (VOM) consist of star-up costs, scheduled maintenance, material such as lubricating oil and others.
-	Fuel cost (also variable) forms the major cost component in diesel plants and should be taken into consideration.
-	Transmission line (TL) and its accessory equipment.

The cost figures of the above cost components are obtained from the 2010 study of engine technology that was sponsored by KPMG; a UK based global professional auditing firm.¹⁴14. KPMG, “Image study diesel power plants: Study on image and actual potential of engine-based power plant.,” KPMG, 2010. Table I is extracted from the study and the original cost figures were in Euros (€) that are converted into U.S. dollars ($) using an exchange rate of €1 = $1.322.

Table I. Commercial diesel generator plants.

Plant type	EPC cost ($/kW)	Investment cost ($/kW)	Fixed O&M ($/kW)	Variable O&M ($/MWh)	Fuel cost ($/MWh)
Diesel engine HFO 160 MW	1110.50	1310.10	24.33	34.77	38.33
Diesel engine LFO 160 MW	856.66	999.43	10.31	32	38.33

It is worth mentioning that to make this study comparable to other studies the local fuel cost in Saudi Arabia which is about $0.17/l is not used. Similarly there are no local cost figures for ICC and other cost components hence it will be uniform if cost figures are derived from studies that involved several power system analysis such as that of KPMG.

The cost of TL is assumed to be 20% of the ICC as inferred from the work of the Institute for Energy and Research.¹⁵15. Institute for Energy and Research, Levelized cost of generating technologies (Institute for Energy and Research, 2009). See also at http://www.instituteforenergyresearch.org/2009/05/12/levelized-cost-of-new-generating-technologies/.

The Light Fuel Oil (LFO) 160 MW diesel engine has been chosen for this study due to its cost effectiveness. Thus the ICC is $1000/kW installed (EPC plus investment cost). The efficiency of the chosen DG is 52% with CO₂ emission of 513 g/kWh.¹⁴14. KPMG, “Image study diesel power plants: Study on image and actual potential of engine-based power plant.,” KPMG, 2010.

C. WECS

The WECS is sized using the load information and the wind data of the site. Using the theoretical site-matching wind turbine (WT) technique,⁴4. U. Bawah, K. E. Addoweesh, and A. M. Eltamaly, “Economic modeling of site-specific optimum wind turbine for electrification studies,” Adv. Mater. Res. 347–353, 1973–1986 (2012). https://doi.org/10.4028/www.scientific.net/AMR.347-353.1973 it is possible to get a rough estimate of the following:

Economic WT ’ {s speed rating for the site V}_{rate} = 0.95 υ_{max},

(3)

where V_rate is the rated speed of the site matching WT and υ_max is the wind speed carrying the maximum power in the site given by¹⁶16. L. Lu, H. Yang, and J. Burnet, “Investigation on wind power potential on Hong Kong islands - an analysis of wind power and wind turbine characteristics,” Renewable Energy 27, 1–12 (2002). https://doi.org/10.1016/S0960-1481(01)00164-1

v_{\max} = c {[1 + \frac{2}{k}]}^{\frac{1}{k}} in m / s,

(4)

k is the Weibull dimensionless parameter known as the shape parameter. Approximate value of k can be determined from

k = {(\frac{σ}{v_{m}})}^{- 0.086},

(5)

σ is the standard deviation of the collected site wind speed data over many years and υ_m is the mean speed of the site. k can also be approximated in the absence of detail data from¹⁷17. G. L. Johnson, Wind Energy Systems (Prentice-Hall, 1985).

k = d_{1} \sqrt{v_{m}},

(6)

where 0.73 ≤ d₁ ≤ 1.05 with an average value of d₁ = 0.94.

Another Weibull site parameter required is the scale parameter c in m/s given as

c = \frac{v_{m}}{Γ (1 + \frac{1}{k})}

(7)

or approximated by

c = 1.12 v_{m} f o r 1.5 \leq k \leq 3.

(8)

The theoretical cut-in-wind speed υ_cin, the cut-out-wind speed υ_cou, and the most probable site wind speed υ_mp are also estimated by¹⁸18. M. El-Shimy, “Optimal site matching of wind turbine generator: Case study of the Gulf of Suez region, Egypt,” Renewable Energy 35, 1870–1878 (2010). https://doi.org/10.1016/j.renene.2009.12.013

υ_{cin} = 0. {25 V}_{rate} and υ_{cou} = 1 . {75 V}_{rate},

(9)

Or υ_{cin} = 0. {5 V}_{rate} and υ_{cou} = {2 V}_{rate},

(10)

and¹⁹19. A. Oguz, “Technoeconomic analysis of electricity generation from wind energy in Kutahya, Turkey,” Energy 35, 120–131 (2010). https://doi.org/10.1016/j.energy.2009.09.002

v_{m p} = c {[1 - \frac{1}{k}]}^{\frac{1}{k}} m / s .

(11)

From the above site values, the site capacity factor C_F can be estimated as follows:

C_{F} = {\frac{\exp [- {| \frac{v_{c i n}}{c} |}^{k}] - \exp [- {| \frac{v_{r a t e}}{c} |}^{k}]}{{[\frac{V_{r a t e}}{c}]}^{k} - {[\frac{v_{c i n}}{c}]}^{k}} - \exp [- {| \frac{v_{c o u}}{c} |}^{k}]} .

(12)

The average wind power (P_ave,WT) of the site is given by

P_{a v e, W T} = C_{F} \times P_{W T},

(13)

where P_WT is the total installed wind power capacity. Alternatively the annual energy load requirement (E_d) should be

E_{d} = C_{F} \times P_{W T} \times 8760,

(14)

knowing P_WT, the cost of the WECS can be determined from various studies. The Lawrence Barkeley National Laboratory surveyed WT prices in the U.S. from 1997 to early 2011 and arrived at a range of $900/kW–$1400/kW for 2010 to 2011.²⁰20. B. Mark and W. Ryan, “Understanding trends in wind turbine prices over the past decade,” Lawrence Barkeley National Laboratory, LBNL-5119E, 2011. See also at http://eetd.lbl.gov/emp. The other costs components that go along with the WT are priced according to the cost break-up of a typical onshore WECS as contained in the most recent cost report from the National Renewable Energy Laboratory (NREL) of 2012 and summarized in Table II below.²¹21. National Renewable Energy Laboratory, Cost and Performance Data for Power Generation Technologies (Black & Veatch, 2012).

Table II. Capital cost breakdown of an onshore WECS.

Cost component	Proportion	Cost $/kW
Wind turbine	68%	1346
Distribution	10%	198
Balance of plant/erection	13%	257
Engineering, procurement, construction management services	4%	79
Owner's cost	5%	100
Total	100%	1980 ± 25%

The operation and management costs (O&M) is taken from a study made on cost distribution of O&M in Germany, UK, and the US²²22. M. David, “Breaking down the cost of wind turbine maintenance,” Wind Power Monthly (15 June 2010); available online at http://www.windpowermonthly.com/article/1010136/breaking-down-cost-wind-turbine-maintenance. that of the US €15/MWh ($20/MWh) is used in this study.

D. Modeling the solar PV electric system

The knowledge of the design load P_d and energy E_d is also used in sizing the solar PV electric system (PV for short). The solar insolation or irradiation in kWh/m²/d (where d is day) of the site collected on horizontal plane ((G(o)) is converted to the corresponding value at optimal tilt angle (β_opt) as approximated in the Handbook of PV Science and Engineering,²³23. A. Luque and S. Hegedus, Handbook of Photovoltaic Science and Engineering (Wiley, 2011).

β_{o p t} = 3.7 + 0.69 | φ |,

(15)

where φ is the latitude of the site in degree hence the unit of β_opt is degree.

From β_opt the irradiation of horizontal plane, (G(o)) can be converted to irradiation for optimal tilt angle (G(β_opt)) in kWh/m²/d as

G (β_{o p t}) = \frac{G (o)}{1 - 4.46 \times 10^{- 4} \times β_{o p t} - 1.19 \times 10^{- 4} \times β_{o p t}^{2}} .

(16)

To size the system, a solar model should be picked and used in the following procedure as contained in the Australian/New Zealand Standard AS/NZS 4509.2:2010.¹³13. Joint Technical Committee EL-042 (2010). Australian/New Zealand Standard AS/NZS 4509.2:2010 (Standards Australia Limited/Standard New Zealand). For Maximum Power Point Tracker (MPPT) regulator,

P_{\mod} = P_{s t c} \times f_{t e m p} \times f_{m a n} \times f_{d i r t},

(17)

P_stc is the nominal module power under standard test conditions (STC) in watts and f_temp is the temperature derating factor defined as

f_{t e m p} = 1 - γ (T_{c e l l, e f f} - T_{s t c}),

(18)

where γ is the power temperature coefficient (% per degree C) and T_stc is the temperature under STC (25 °C). f_man is manufacturer's power output tolerance (pu) taken as 0.95, f_dirt is the derating factor for dirt; for clean soil the factor is 1, for low it is 0.98, medium is 0.97 and high is 0.92.

For the MPPT controller the number of PV array (N_pv) is obtained as

N_{p v} = \frac{E_{d d} \times f_{o}}{P_{\mod} \times G \times η_{p v s s}},

(19)

where E_d_d is total design average daily energy (E_d/365), f_o is the oversupply co-efficient (usually between 1.3 and 2). This study assumes 1.5 value η_pvss is system efficiency considered as 85%. G is the solar irradiation (kWh/m²/d) of the site on optimal tilt angle. The rated PV power (PV_rate) to handle the load is thus

{PV}_{rate} = Chosen PV module peak watt \times Npv .

(20)

The Suntech 70 W 12 V mono crystalline solar module STP070S-12Bb is selected for this study and used in sizing the PV module. The components that go with the PV system are taken from the NREL report and are summarized in Table III.

Table III. Capital cost components of a PV Electric System.²¹21. National Renewable Energy Laboratory, Cost and Performance Data for Power Generation Technologies (Black & Veatch, 2012).

Cost component	Proportion	Cost $/kW
PV modules	49%	1400
Structures	29%	810
Inverters	8%	240
Balance of station	7%	185
Engineering, procurement, construction management services	2%	55
Owner's cost	5%	140
Total	100%	2830 ± 25%

The ICC for the solar PV system is thus considered to be $2830/kW of installed capacity and the O&M cost is taken as $12.1/MWh or $0.0121/kWh in line with other studies.¹⁵15. Institute for Energy and Research, Levelized cost of generating technologies (Institute for Energy and Research, 2009). See also at http://www.instituteforenergyresearch.org/2009/05/12/levelized-cost-of-new-generating-technologies/.

E. Economic modeling

The economic model used is based on determining the TLCC and the levelized cost of energy (LCOE) generated first for a public utility referred to as the no-tax case and secondly for a profit oriented investor (IPP). The latter ownership case pays tax and, therefore, is concerned with before-tax revenue requirement to make it profitable thus; it is referred to as the before-tax case.

1. TLCC

TLCC is the present value of all costs involved in acquisition, installation, upgrades, repair, running of the system, and decommissioning.²⁴24. S. Walter, J. P. Daniel, and H. Thomas, A Manual for the Economic Evaluation of Energy Efficiency and Renewable Energy Technologies (National Renewable Energy Laboratory, 1995).

The no-tax ownership TLCC is given as

T L C C = I C C \times \sum_{t = 1}^{n 1} \frac{Δ I}{{(1 + r)}^{t}} + \sum_{t = 1}^{n} \frac{O & M}{{(1 + r)}^{t}},

(21)

where ΔI is any incremental investment/cost such as replacement, upgrading, and decommissioning cost (if there is a salvage value it will be considered as negative cost); t is the time when investment or cost occurs, n₁ is the analysis period in years for the incremental investment/cost, n is the total number of useful life years (analysis period for the entire project), and r is the discount rate or cost of capital. DEP is the depreciation of the fixed assets. The three major components are the present value of investment (PVI), the present value of O&M (PVOM), and the present value of depreciation (PVDEP). Where

P V I = I C C + \sum_{t = 1}^{n 1} \frac{Δ I}{{(1 + r)}^{t}},

(22)

P V O M = \sum_{t = 1}^{n} \frac{O & M}{{(1 + r)}^{t}},

(23)

P V D E P = \sum_{t = 1}^{n} \frac{D E P}{{(1 + r)}^{t}} .

(24)

Thus,

T L C C = P V I + P V O M .

(25)

The Before-tax ownership TLCC is given as

T L C C = \frac{P V I - (T x \times P V D E P) + P O V M (1 - T x)}{(1 - T x)},

(26)

where Tx is the tax rate paid by the IPP. Equation (26) is also the present value of the total revenue required to make the business earn its cost of capital (r) plus retrieval of its investments.²⁴24. S. Walter, J. P. Daniel, and H. Thomas, A Manual for the Economic Evaluation of Energy Efficiency and Renewable Energy Technologies (National Renewable Energy Laboratory, 1995).

2. LCOE generated

The LCOE is the present value of the cost of producing one unit of energy. This figure when multiplied by the total energy produced by the system throughout its useful life should give the TLCC. Thus,

\sum_{t = 1}^{n} \frac{E_{t} \times L C O E}{{(1 + r)}^{t}} = T L C C .

(27)

Therefore,

L C O E = \frac{T L C C}{\sum_{t = 1}^{n} \frac{E_{t}}{{(1 + r)}^{t}}},

(28)

where E_t is the energy produced in year t. The denominator of Eq. (28) is the present value of energy produced (PVE) throughout the useful life of the project. Thus,

L C O E = \frac{T L C C}{P V E} .

(29)

On the other hand, if the annual output (E_a) of the power systems is constant then

L C O E = (\frac{T L C C}{E_{a}}) \times U C R F,

(30)

where UCRF is the uniform capital recovery factor defined as

U C R F = \frac{r {(1 + r)}^{n}}{{(1 + r)}^{n} - 1} .

(31)

3. Discount rate r

The discount rate or cost of capital (r) is the desired minimum return of the project that would make it worthy of being an investment choice. There are many ways to determine r and it is considered here to be composed of only two parts: equity and debt. This leads to the concept of weighted cost of capital (WACC) which is used as the cost of capital in the equations above.²⁵25. A. R. Stephen, W. W. Randolph and D. J. Bradford, Fundamentals of Corporate Finance, 5th ed. (Irwin MCGraw-Hill, 2000).

WACC for no-tax case

W A C C_{T x = 0} = W_{E} \times R_{E} + W_{D} \times R_{D},

(32)

where WACC_Tx ₌ ₀ is the WACC (discount rate r) for a public utility that pays no tax, W_E is the weight or proportion of equity used in financing the project, R_E is the cost of equity which is the minimum return required by those who invest in the project as owners. W_D is the weight of debt employed in financing the project and R_D is the cost of debt or simply the interest rate of borrowed capital.

WACC for before-tax case

W A C C_{T x = 0} = W_{E} \times R_{E} + W_{D} \times R_{D} \times (1 - T x) .

(33)

4. The two forms of r

The discount rate (r or WACC) can be either real discount rate (r_r or WACC_a) that excludes the effect of inflation (e) or nominal discount rate (r_n or WACC_n) that includes the effect of inflation.²⁴24. S. Walter, J. P. Daniel, and H. Thomas, A Manual for the Economic Evaluation of Energy Efficiency and Renewable Energy Technologies (National Renewable Energy Laboratory, 1995). These terms are defined as

r_{n} = [(1 + r_{r}) (1 + e)] - 1,

(34)

r_{r} = \frac{(1 + r_{n})}{(1 + e)} - 1.

(35)

From these equations, it is seen that there is big difference in the forms of the discount rate that comes from the forms of cost of equity (R_E) or the cost of debt (R_D). For example, the form of debt which is the interest rate (R_D) can either be quoted as real interest rate (R_D_r) or nominal interest rate (R_D_n). The nominal interest rate that includes the effects of inflation (e) appears very high so financial institutions sometimes quote the interest rate in real terms (R_D_r) that excludes inflation. This issue is not made clear in most renewable energy research publications. The inflation rate (e) in Saudi Arabia was quoted as 5.3% in April 2012 but it has averaged 3.79% from 2003 to 2012.²⁶26. See http://www.tradingeconomics.com/saudi-arabia/inflation-cpi for Saudi Arabia Inflation rate, Trading Economics, 2012. On the other hand, the benchmark interest rate in Saudi Arabia is 2%.²⁶26. See http://www.tradingeconomics.com/saudi-arabia/inflation-cpi for Saudi Arabia Inflation rate, Trading Economics, 2012. It should be noted that the 2% interest rate is a real rate and not a nominal rate because rationally no institution will learn money with a return lower than inflation. The nominal interest rate (R_D_n) which lenders actually pay can be obtain from Eq. (34) if the latest inflation figure (5.3%) assumed is

R_{D n} = (1 + 0.02) \times (1 + 0.053) - 1 = 0.074.

(36)

Thus, the interest rate to be used in the project evaluation is 7.4% as it is the actual interest rate to be paid by borrowers.

5. Forms of cash flows (CF)

The cash flows from the project: negative (cost/investment) or positive (revenue/salvage) also have two forms—current cash flow (CF_t) to reflect market values at the time this CF occurs or constant cash flow(CF_n) using base year (year zero of the starting) cash. If the first year O&M cost is say $15 000; subsequent years could also remain constant at $15 000 in this case the CFs are in constant dollars and the discount rate to be used to find the present value should be real discount rate. On the other hand, if the O&M cost increase yearly by an inflationary factor (e), then the nominal discount rate should be used in the evaluation. That is to say that the correct form of discount rate must be used to match the form of CFs otherwise the assessment will be faulted,²⁴24. S. Walter, J. P. Daniel, and H. Thomas, A Manual for the Economic Evaluation of Energy Efficiency and Renewable Energy Technologies (National Renewable Energy Laboratory, 1995).

C F_{n} = \frac{C F_{t}}{{(1 + e)}^{t - n}},

(37)

C F_{t} = C F_{n} \times {(1 + e)}^{t - n} .

(38)

In the base year CF_n = CF_t. Any of the cash flow types could be used in the analysis but consistency should prevail.

The present value of say O&M costs (PVOM) when the cost is increasing yearly by an inflationary rate (e) is

P V O M = \sum_{t = 1}^{N} \frac{O M {(1 + e)}^{t}}{{(1 + r)}^{t}} .

(39)

The r in the denominator of Eq. (39) is nominal: r_n.

6. Forms of LCOE

From the foregoing, it can be inferred that the LCOE would either be in constant dollars (excluding inflation) or current dollars (including inflation). The TLCC using real or nominal discount rate will end up being the same so the form of the LCOE is distinguished only by the type of discount rate used in the denominator of Eq. (28) or the type of discount rate used in Eq. (31) then applied in Eq. (29) or (30).

7. DEP

Depreciation is an accounting allowance that systematically reduces the fixed assets year by year to zero. It is a cost of operation that accounts for the cost of the fixed assets in a particular year in producing the output. There are several methods of depreciation and here the straight line (SL) depreciation is used in depreciating all auxiliary fix assets such as batteries, inverters, TL, etc. The double declining balance (DDB) method that ensures that technology assets are depreciated faster is used here for the main generating equipment such as the DG, WT, and solar PV modules.

The annual depreciation (D_t) for the SL depreciation is the total cost of the asset (C_o) less any expected salvage value (S) divided by useful service life of the asset in question (n_i).

D_{t} = \frac{(c_{o} - s)}{n_{i}} .

(40)

The annual depreciation (D_t) of the DDB depreciation is obtained by using double of the SL for the first year and its ratio as a percentage (r_d or 200%) of the total investment multiplied by the remaining book value (B_n₋₁) for subsequent years until the asset's value is reduced to zero.²⁷27. E. K. Donald and J. W. Jerry, Intermediate Accounting, 9th ed. (John Wiley & Sons, Inc., New York, 1998). Salvage values are not considered in the DDB,

D_{t} = r_{d} \times B_{n - 1} .

(41)

Depreciation charge is always in current dollars (CF_t) so nominal discount rate should be used to find the present value. If it is desired to use the real discount rate then the depreciation charge (D_t) should first be converted into constant dollars using Eq. (37).

IV. RESULTS AND DISCUSSIONS

A. Data of the study area—Addfa in AlJawf region

The following tables summarize the essential components of the study. Table IV specifies the mean wind speed (ʋ_m) in m/s of Addfa and determines the minimum, maximum and average values of k using Eq. (6) and the range of d₁ (K_min, K_max, and K_ave). These values are used in determining the low, high and average values of V_max applying Eq. (4) (V_max low, V_max high, and V_max Ave). The suitable rated WT speed of the site (V_rate) in m/s is determined from Eq. (3).

Table IV. AL-Jawf wind data at 50 m.

V_m m/s	K_min	K_max	K_ave	C m/s Eq. (8)	ʋ_mp m/s Eq. (11)	V_max low	V_max high	V_max Ave	V_rate m/s Eq. (3)	V_cin m/s Eq. (9)	V_cou m/s Eq. (9)	C_F Eq. (12)
5.21	1.67	2.40	2.14	5.83	4.35	7.51	9.36	7.93	8.89	2.22	15.56	0.32

Equations (15) and (16) were used to determine the values of Table V, where P_Min, P_Max, and P_Ave are the minimum, maximum, and average monthly power in kW, respectively, as were obtained on a visit to the site. E_Min, E_Max, and E_Ave are the minimum, maximum, and average monthly energy in GWh, respectively, as were obtained on a visit to the site. Annual peak load P_L = 940 kW annual average load P_ave = 360 kW and design load. P_d = 1.2 MW assuming k_g = 13% and K_c = 13% (Ref. 1313. Joint Technical Committee EL-042 (2010). Australian/New Zealand Standard AS/NZS 4509.2:2010 (Standards Australia Limited/Standard New Zealand). ) to take losses into consideration. Annual load energy E_L = 3 145 498 kWh and design energy E_d = 4 GWh.

Table V. Al-Jawf solar insolation in kWh/m²/d at 2 4.25° inclined plane.

Jan	Feb	Mar	Apr	May	June	July	Aug	Sept	Oct	Nov	Dec	Mean	C_F
3.39	4.44	5.56	6.78	7.39	8.36	8.15	7.57	6.46	4.76	3.55	3.03	5.79	0.25

B. Sizing and costing the different power systems

Each of the power supply systems: DG, WECS, and Solar PV are sized to produce 4 GWh of energy per year.

1. Conventional DG

P_d = 1.2 MW. All cost figures are in millions of U.S. dollars. From Table VI, the number of DG units and ratings to match the load profile can be determined and the combined total capacity will be 1200 kW, annual energy E_d = 4000 MWh, and capacity factor (C_F) = 0.381 (Table VII is the monthly energy description).

Table VI. Monthly load description of Addfa (kW).

	Jan	Feb	Mar	Apr	May	June	July	Aug	Sept	Oct	Nov	Dec
P_Min	44	150	105	108	129	165	207	264	247	178	199	162
P_Max	576	500	478	319	616	702	800	940	795	450	690	521
P_Ave	382	314	274	213	294	393	434	579	437	290	375	326

Table VII. Monthly energy description GWh.

	Jan	Feb	Mar	Apr	May	June	July	Aug	Sept	Oct	Nov	Dec
E_Min	0.327	0.104	0.078	0.078	0.096	0.119	0.154	0.196	0.178	0.132	0.143	0.121
E_Max	0.429	0.348	0.356	0.230	0.458	0.505	0.595	0.699	0.572	0.335	0.497	0.388
E_Ave	0.284	0.219	0.204	0.1534	0.219	0.283	0.323	0.431	0.315	0.216	0.270	0.243

The total investment cost going by Table I is $1000/kW hence the DG cost of installation is $1.2 m and a transmission line cost of 20% is assumed making the total ICC = $1.44 m. Annual energy is 3146 kWh and increasing by 0.7% annually over the 20 years useful life. The running costs are as shown in Table I.

2. WECS

E_d = 4000 MWh = C_F × 8760 × P_WT = 0.32 × 8760 × P_WT.

P_WT = 1.423 MW which is the capacity to installed.

Capital cost for this capacity is $2.82 m as shown in Table II. There is only fixed O&M cost which is $20/MWh for the WECS. This comes up to $0.08 m per year.

3. Solar PV system

The required installed energy capability is E_d = 4 GWh.

With the chosen Suntec the parameters are:

P_stc = 70Wp, Nominal voltage V_n = 17 V, γ = 0.38% per degree C, f_man = 5%.

P_mod = 70 × 0.848 × 0.95 × 0.97 = 54.7 W or 78.14% of rated PV is available at site.

From Eq. (19),

Npv = 52 921 solar modules are required. This translates into

_rate = 70Wp × 52 921 = 3.7 MW.

Using Table III, the initial capital cost (ICC) is $10.47 m. O&M cost is $12.1/MWh.

Other inputs of the analyses

-	Each of the supply scenarios will supply 3146 MWh for the first year of operation and thereafter increase by 0.7% yearly.
-	The solar PV has a useful life of 30 years, 20 years for the WECS, and 20 years for the DG.
-	To make effective comparison, the systems should have the same useful life. The solar PV life of 30 years is considered as the analysis period for each. Thus the WECS and DG will need reinvestment in the 20th year to extend their life to 30years. This is another issue that has been neglected in most economic analysis of RET.
-	Reinvestment in equipment will be affected by a 4% inflation and 6% de-escalation rate.
-	At the end of 30 years every asset can be sold for its book value.
-	According to the financial report of the Saudi Electric Company (SEC) the capital structure is expected to be 50% equity and 50% debt in 2011. The cost of equity is given as 9.8% and that of debt net Zakat (an Islamic charity) is 4.6% giving a WACC of 7.2% in real terms.²⁸28. See www.ncbc.com/uploads/library/20091027160630aSaudiElectric_In for Saudi Electricity Co: A monopoly undermined by margin pressure, NCB Capital, 2009. The 7.2% is taken as the real cost of capital for each of the ownership scenarios. The nominal cost of capital will thus be 11.488%
-	All assets are depreciated using DDB.

V. RESULTS OF THE ANALYSES

Based on making a TLCC schedule and depreciation schedule for the PV electric system the following results are obtained.

The PV* stands for the present value. It is worth mentioning that most of the publications use only the constant LCOE approach thus Ref. 1515. Institute for Energy and Research, Levelized cost of generating technologies (Institute for Energy and Research, 2009). See also at http://www.instituteforenergyresearch.org/2009/05/12/levelized-cost-of-new-generating-technologies/. got the average LCOE for PV as $0.210 (Table XIII) whereas Ref. 3232. See http://www.solarbuzz.com/moduleprices.htm for Solar Buzz, PV module price trend, 2012. gave a range of $0.24631 to $0.46176 (Table XII) for the no-tax case.

Using the same approach the results for the WECS and the DG standalone are as follows:

From the table of results, the investment ranking according to the system with the least LCOE is shown in Table VIII.

Table VIII. Investment ranking using the least constant LCOE.

Investment ranking	System	Public utility	IPP
First choice	WECS	$0.0922/kWh	$0.1090/kWh
Second choice	DG	$0.1082/kWh	$0.1175/kWh
Third choice	Hybrid WECS + DG	$0.1102/kWh	$0.1234/kWh
Fourth	Solar	$0.2791/kWh	$0.3279/kWh

Table VIII is arrived at by a comparison of Tables IX, X, XI, XII. The least LCOE is the most preferable since sales are made in terms of energy produced and this will provide a bigger profit margin to make the investment attractive.

Table IX. Results of analysis for the solar PV system.

	No-tax	Before-tax
TLCC	$11.4393 m	$13.439663 m
Current: PV* energy	27785.27 MWh	27785.27 MWh
Current: LCOE	$0.4117/kWh	$0.4837/kWh
Constant: PV energy	40988.84 MWh	40988.84 MWh
Constant: LCOE	$0.2791/kWh	$0.3279/kWh

Table X. Results of analysis for the WECS.

	NO-tax	Before-tax
TLCC	$3.7808 m	$4.4664 m
Current: PV* energy	27785.27 MWh	27785.27 MWh
Current: LCOE	$0.1361/kWh	$0.1607/kWh
Constant: PV* energy	40988.84 MWh	40988.84 MWh
Constant: LCOE	$0.0922/kWh	$0.1090/kWh

Table XI. Results of analysis for the DG.

	No-tax	Before-tax
TLCC	$4.4350 m	$4.8170 m
Current: PV* energy	27785.27 MWh	27785.27 MWh
Current: LCOE	$0.1596/kWh	$0.1734/kWh
Constant: PV* energy	40988.84 MWh	40988.84 MWh
Constant: LCOE	$0.1082/kWh	$0.1175/kWh

Table XII. Results of analysis for a hybrid WECS + DG system. The DG is rated 1000 kW to be able to handle the peak load of 940 kW and the WECS is rated at 600 kW.

	No-tax	Before-tax
TLCC	$4.5167 m	$5.0561 m
Current: PV* energy	27785.27 MWh	27785.27 MWh
Current: LCOE	$0.1626/kWh	$0.1820/kWh
Constant: PV* energy	40988.84 MWh	40988.84 MWh
Constant: LCOE	$0.1102/kWh	$0.1234/kWh

VI. SENSITIVITY ANALYSIS OF THE WECS

Since the WECS is ranked first in the investment choice further analysis in the form of sensitivity analysis is made to determine the variation of the assumptions that went into the analyses. The figures below summarize the analyses. The ICC of $1980/kW that is used in this study is considered the base value (1.0) and it is being varied from 0.5 to 1.5 times the base value. Similarly the $20/MWh used as the O&M is also considered the base value and varied from 0.5 to 1.5 times the base value.

From Figure 2, a 10% decrease in ICC leads to a decrease of about 8% in the LCOE. This means that ICC plays a major role in the economic analysis made here.

FIG. 2. Variation of the LCOE with changes in ICC in constant dollars.

High-resolution

A change of 10% in O&M leads to a change of 2.17% in the LCOE. Thus, the analysis is less sensitive to the O&M costs.

VII. COMPARISON WITH OTHER STUDIES

Two studies are used to verify the results obtained in this study. The first is that of the Institute of energy and Research (IER) in the U.S. that made a detail study of the LCOE for different technologies entering 2016.¹⁵15. Institute for Energy and Research, Levelized cost of generating technologies (Institute for Energy and Research, 2009). See also at http://www.instituteforenergyresearch.org/2009/05/12/levelized-cost-of-new-generating-technologies/. The second is a study made by the California Energy Commission (CEC) in a comparative study of the LCOE for different technologies.^29–3129. See http://energyalmanac.ca.gov/e;ectricity/levelized_cost.html for California Energy Commission, Energy ALMANAC, 2010. 30. I. B. Maria, “The economics of wind energy,” Renewable Sustainable Energy Rev. 13, 1372–1382 (2009). https://doi.org/10.1016/j.rser.2008.09.004 31. G. Murat and S. G. Mustafa, “Evaluation of electricity generation and energy cost of wind energy conversion systems (WECSs) in Central Turkey,” Appl. Energy 86, 2747391–2747392 (2009). The IER results obtained for only the case of a public utility as related to this work can be summarized as follows:

The CEC studies included both public and investor owned utilities and also includes high to low range and average values of the LCOE as shown in Table XIV.

Comparing the results of this study with those of Tables XIII and XIV, it is found that the results of this study fall within the average values of the two tables thus verifying the results obtained. From the sensitivity analyses, when the ICC is varied from 0.5 to 1.5 of base value the LCOE varies from $0.0556/kWh to $0.1284/kWh for the no-tax case and from $0.0646 to $$0.1553 for the before-tax case for the WECS.^33,3433. See www.photon.de/newsletter/document/68832.pdf for PHOTON module price index, 2012. 34. Exxon Mobil, The Outlook for Energy: A View to 2030 (Exxon Mobil, 2010). These variations fit into the range of minimum to maximum values for the LCOE as shown in the CEC studies in Table XIV.

Table XIII. Extracts from IER studies¹⁵15. Institute for Energy and Research, Levelized cost of generating technologies (Institute for Energy and Research, 2009). See also at http://www.instituteforenergyresearch.org/2009/05/12/levelized-cost-of-new-generating-technologies/. in constant dollars.

Technology	ICC	Average LCOE/kWh
Wind onshore	$2000/kW	$0.097/kWh
Solar PV	$4755/kW	$0.210/kWh
Conventional	$665–2060/kW	$0.0662/kWh

Table XIV. Constant dollar LCOE extracted from the CEC studies.³²32. See http://www.solarbuzz.com/moduleprices.htm for Solar Buzz, PV module price trend, 2012.

	Public utility (no-tax)			Investor owned utility (before-tax)
Technology	Low	Average	High	Low	Average	High
Onshore Wind class ¾	$0.06083/kWh	$0.08052/kWh	$0.13295/kWh	$0.05676/kWh	$0.0775/kWh	$0.18925/kWh
Onshore Wind class 5	$0.04965/kWh	$0.07244/kWh	$0.13585/kWh	$0.04684/kWh	$0.07019/kWh	$0.19357/kWh
Solar PV	$0.24631/kWh	$0.320/kWh	$0.46176/kWh	$20915/kWh	$0.27871/kWh	$0.60930/kWh
Conventional	$0.0622/kWh	$0.10791/kWh	$0.1717/kWh	$0.06643/kWh	$0.11476/kWh	$0.19344/kWh

VIII. CONCLUSIONS

The results obtained in this study demonstrate the fact that the WECS can be an alternative source of electric generation in remote areas of Saudi Arabia. The main findings from the study are as follows:

(a)	The electric utility ownership structure that pays tax (IPP) always have higher LCOE and TLCC than the public utility structure that pays no tax. Thus the differences in ownership structure cannot be ignored in making economic assessment of renewable energy projects.
(b)	In Saudi Arabia, the WECS is an economically viable alternative to conventional electric generation. However, the local subsidized fuel prices ($0.17/l) will always make investors to prefer the conventional means to the renewable means. To promote RET, policies to grant renewable credits and tax exemptions should be enacted.
(c)	The LCOE for solar PV electric system is still higher than the others and will need more government support as the solar resources are the most abundant renewable resources in the country. However, the LCOE for the solar has reduced by half since 2010 as a result of improvement that led to the decrease in capital cost. Future cost reductions as suggested by recent publications will make the PV system the first choice in Saudi Arabia by 2020.
(d)	In terms of system reliability, the hybrid system should be ranked first as its LCOE is very competitive with the DG option (Table VIII). The hybrid system is more reliable as it guarantees supply availability in the absence of wind speed and it is also capable of handling the peak load when the wind is calm.
(e)	The results also point to the role of ICC and O&M in the economics of the WECS (Figures 2 and 3, respectively). A 10% change in the ICC will lead to about 8% change in LCOE thus pointing to the fact that as the cost of technology improves, renewable energy would be viable options to reduce the emission of CO₂.
(f)	A suggestion for future study will be to include the cost of CO₂ as a penalty for conventional generation or give carbon credit to renewable energy projects to compare the economics of each system.

FIG. 3. Variation of the LCOE with changes in O&M costs in constant dollars.

High-resolution

ACKNOWLEDGMENTS

This work was financially supported by the National Plan for Science and Technology (NPST) program of the King Saud University, Project Number: 09 ENE 741-02

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Comparative study of economic viability of rural electrification using renewable energy resources versus diesel generator option in Saudi Arabia