Levellised electricity cost for wind and PV–diesel hybrid system in Oman at selected sites

Abstract

Solar and wind energy data available for Oman indicate that these two resources are likely to play an important role in the future energy generation in this country. In this paper, a model is designed to assess wind and solar power cost per kWh of energy produced using different sizes of wind machines and photovoltaic (PV) panels at two sites in Oman, which then can be generalised for other locations in Oman. Hourly values of wind speed and solar radiation recorded for several years are used for these locations. The wind profiles from Thumrait and Masirah island are modelled using the Weibull distribution. The cost of wind-based energy is calculated for both locations using different sizes of turbines. Furthermore, this paper presents a study carried out to investigate the economics of using PV only and PV with battery as an energy fuel saver in two villages. The results show that the PV energy utilisation is an attractive option with an energy cost of the selected PV ranges between 0.128 and 0.144 $/kWh at 7.55% discount rate compared to an operating cost of 0.128–0.558 $\kWh for diesel generation, considering the capital cost of diesel units as sunk.

Keywords::

• hybrid energy system
• wind energy
• PV
• battery

1. Introduction

The electricity in Oman is mainly produced by using natural gas. However, fossil fuel has limited reserve, and also it raises the pollution levels. Policy-makers in Oman realise that renewable resources should be used as an essential components of national energy supplies, as well as a global strategic option for both extending the life of oil and gas reserves and reducing carbon dioxide emissions and thus combating climate change. In 2010, the Authority for Electricity Regulation in Oman has confirmed a shortlist of six renewable energy pilot projects out of which four of them are solar projects (The Authority for Electricity Regulation Oman). Oman has a high level of solar energy in all its regions, but this level is varying according to the location. The desert and northern parts of Oman areas has the highest solar energy density whereas the coastal areas in the southern part have the lowest solar energy density and relatively high wind speed (Al-Badi 2011a, 2011b, 2012a, 2012b; Al-Badi and Al-Badi 2012; Al-Badi, Al-Badi, et al.2011, Al-Badi, Al-Toobi, et al.2011, Al-Badi et al.2012; Al-Badi, Malik, and Gastli 2009a, 2009b, 2011; Albadi et al.2011; Al-Yahyai et al.2012; Bourdosen and Al-Badi 2009; Malik and Al-Badi 2009).

This paper reports the assessment of wind energy cost per kilowatt hour using different sizes of wind turbines at two sites: Thumrait and Masirah island. In addition, photovoltaic (PV)–diesel hybrid system for two remote villages is proposed for small power applications on the basis of actual loads for Al Mazyounah and Al Mathafa villages in the southern part of Oman. Hourly values of wind speed and solar radiation recorded for several years are used to assess solar and wind energy potentials for these locations.

2. Development of cost model for wind energy

2.1 Wind energy resources

The measured hourly wind speed data for Thumrait and Masirah sites for 9 years from 2000 to 2008 are analysed (Ministry of Transport and Communications; Directorate General of Civil Aviation and Meteorology 2009). The monthly average wind speed for Thumrait and Masirah sites for the 9 years are shown in Figures 1 and 2. It is noticed that the wind speed for both places is high during the summer which also coincides with the demand of electrical power in the summer period.

Figure 1 Monthly averages of wind speed for Thumrait.

Figure 2 Monthly averages of wind speed for Masirah.

The wind speed data for Thumrait and Masirah sites are modelled using the Weibull distribution. Figures 3 and 4 show the probability density versus wind speed at 10 m above the ground level, where k is the shape parameter and c is the scale parameter. Wind profile model can be used for further studies such as turbine-site matching (Albadi and El-Saadany 2010).

Figure 3 Probability density versus wind speed at 10 m above the ground level in Thumrait.

Figure 4 Probability density versus wind speed at 10 m above the ground level in Masirah.

2.2 Calculation of energy cost

The measurements of the wind speed through those years illustrate that Thumrait and Masirah have relatively good wind energy potential. Different sizes of turbines are used to calculate the cost of energy. Table 1 shows the technical data of the chosen turbines (My Wind Power System Products 2011).

Table 1 Technical data for four different sizes of turbines.

Wind turbine	Rated power (kW)	Cut-in speed (m/s)	Cut-out speed (m/s)	Rated speed (m/s)	Hub height (m)	Rotor diameter (m)	Lifetime (year)
S48-750 kW	750	3.5	25	14–15	50	50	20+
BENZ-PMG/DD 900 KW	900	3	25	12–14	50	52	20+
WWD-1 1 MW	1000	3.6	20	12.5	70	60	20+
FDMG1.5 MW	1500	3.5	25	12	65.1	70.5	20+

Source: from Adapted My Wind Power System Products (2011).

For the economic analysis, the following equation is used to find the present value of cost (PVC):

where IC is the initial cost of the wind turbine system, including civil works, transportation, supervision and the cables connection. The installation cost was assumed to be 10% of the initial cost that includes purchased price of the machine, civil works, transportation, supervision and the cables connection. A is the operation and maintenance cost which is assumed to be 1% of initial cost. PWF is the present worth factor, s is the scrap value (10% of the initial cost), n is the lifetime of the wind turbine and r is the discount rate (7.55%).

The PWF is found using the following formula:

The cost of energy is obtained using the following relationship:

where kWh represents the annual energy, which is found using the following equation:

where j is the wind speed at hub height in m/s, v₁ and v₂ are the cut-in and cut-out speeds, respectively, P_j is the output power of wind turbine in kW at speed j and h_j is the number of hours at that speed. Table 2 presents the initial cost, the operating and maintenance costs and PVC for different sizes of wind turbines (My Wind Power System Products 2011), and energy to rated power ratio for Thumrait site.

Table 2 Cost of wind turbines.

Wind turbine	IC ($)	A ($)	IC ($/kW)	PVC ($)	kWh/kW
S48-750 kW	541,200	4920	721.6	579,691	29,935
BENZ-PMG 900 kW	1,160,280	10,548	1289	1,242,812	30,448
WWD-1 1 MW	2,059,200	18,720	2059	2,205,656	40,047
FDMG 1.5 MW	2,244,000	20,400	1496	2,403,600	32,178

Data of wind speed for Thumrait and Masirah sites are used to calculate the total energy for each machine by means of Equation (4). The wind speed at hub height using the logarithmic law (Al-Yahyai et al.2010 is as follows):

where u₁ is the known velocity at height z₁, u₂ is the predicted wind speed at height z₂ and z₀ is the roughness length at that site. The roughness variable is related to anything that can interfere with the force of the wind for a wind turbine, which includes hills, trees and buildings. Roughness classes from 0 to 4 are usually used. A calm sea has a roughness length of 0, whereas a city with high buildings would have a roughness length of 4 (Al-Yahyai et al.2010). The measured wind shear values in Thumrait and Masirah sites are 0.05 and 0.08 m, respectively (Al-Yahyai et al.2010).

2.3 Discussion of results

Table 3 shows the energy cost summary of wind power generated at Thumrait and Masirah sites for different sizes of turbines. It is interesting to note that the calculated energy costs for the two sites are almost the same for the three different sizes of wind turbine. For FDMG 1.5 MW wind turbine, the cost of energy for Thumrait site is lower than that of Masirah, and this can be explained based on the fact that the amount of annual energy produced in Thumrait site is more compared to Masirah site.

Table 3 Cost summary of wind power generated at Thumrait and Masirah.

Turbine	S48-750 kW		BENZ-PMG/DD 900 kW		WWD-1 1 MW		FDMG 1.5 MW
location	Energy (kWh)	Cost ($/kWh)	Energy (kWh)	Cost ($/kWh)	Energy (kWh)	Cost ($/kWh)	Energy (kWh)	Cost ($/kWh)
Thumrait	22,451,510	0.026	27,403,170	0.045	40,047,500	0.055	48,267,270	0.05
Masirah	21,733,470	0.027	27,287,570	0.046	41,653,050	0.053	33,546,890	0.071

For Thumrait site results, the highest energy recorded with FDMG 1.5 MW is 48,267,270 kWh, while the lowest energy recorded with turbine S48-750 kW is 22,451,510 kWh. Moreover, the highest cost calculated with WWD-1 1 MW turbine is 0.055 $/kWh, whereas the lowest cost is 0.026 $/kWh. This low cost of energy can be attributed to the small initial cost of S48-750 kW [look at Table 2, IC = 721.6 ($/kWh)]. The WWD-1 1 MW turbine has the highest energy cost because its initial cost ($/kW) is very large compared with other turbines. Besides, it has a cut-out speed at 20 m/s, whereas other turbines have the cut-out speed at 25 m/s.

Masirah results show that FDMG 1.5 MW and WWD-1 1 MW turbines have the maximum kilowatt hour which are 33,546,890 and 41,653,050 kWh, respectively. S48-750 kW turbine has the lowest cost of 0.027 $/kWh and has the minimum kilowatt hour of 21,733,470 kWh. The second turbine that has low cost is BENZ-PMG/DD 900 kW turbine which has energy cost of 0.046 $/kWh. Generally speaking, it can be said that the turbine S48-750 kW and BENZ-PMG/DD 900 kW are appropriate for both regions since the energy cost ($/kWh) is low and their output annual energy is acceptable.

3. Levellised cost of PV–diesel hybrid system at selected sites

Oman's excellent location between latitudes 16° and 26°N, and longitudes 51° and 59°E makes it appropriate for utilising PV and wind technology as a source to produce electricity to meet the growing demand for electricity. Masirah and Thumrait sites have high amounts of global sunshine and solar radiation as shown in Figure 5 (Al-Badi, Al-Toobi, et al.2011). As a result, they are expected to be a good location for PV power stations.

Figure 5 Global sunshine duration and solar radiation values for 25 locations.

3.1 Al Mazyounah diesel power station

Al Mazyounah area is located in southern Oman in Dhofar Governorate. The size of Al Mazyounah power station is about 5.5 MW (Al-Yahyai et al.2010; Annual report from Rural Areas Electricity Company 2010). It is planned to install 292 kW PV panels in this station (5% of the system capacity) without batteries to reduce the dependence on fossil fuel (Al-Yahyai et al.2010; Annual report from Rural Areas Electricity Company 2010). The schematic diagram in HOMER model for the built PV–diesel hybrid system is presented in Figure 6. Actual load curve obtained from Rural Areas Electricity Company is used in the model. The economic assumptions of the system are given in Table 4.

Figure 6 HOMER schematic diagram for Al Mazyounah area with PV.

Table 4 Economic assumptions of Al Mazyounah system.

Component	Capital ($/kW)	Lifetime (years)	Replacement ($)	O&M ($)	Fuel ($)	Salvage value ($)
PV	308,219	25	0	34,357	0	0
Diesel generators	454,200	25	0	22,905	17,336,423	25,743
Converter	10,000	15	10,000	1115	0	0

After running the model, 192 feasible solutions are found, and out of these 16 best solutions ranked according to system's minimum net present cost (NPC) are shown in Table 5. In the optimal solution, generator 4 (2000 kW) is not chosen and the total NPC is $18,146,168 with operation cost of 1,558,611 $/year, and the cost of energy equals to 0.128 $/kWh. The current operating cost in this station is also 0.128 $/kWh (Annual report from Rural Areas Electricity Company 2010). Thus, the cost stays the same after adding PV system to the power station. However, since one of the existing diesel generators is not required for the proposed system, diesel consumption and greenhouse gas emissions will be lower.

Table 5 Optimal solution for Al Mazyounah area with PV.

3.2 Al Mathafa area diesel power station

Al Mathafa is a small region in Dhofar Governorate. The total size of Al Mathafa power station is about 360 kW (Annual report from Rural Areas Electricity Company 2010). It is planned to install 28 kW PV panels in Al Mathafa with batteries to reduce the dependence on fossil fuel (Annual report from Rural Areas Electricity Company 2010). HOMER schematic diagram for Al Mathafa region is presented in Figure 7. Actual load curve obtained from Rural Areas Electricity Company is used in the model. The energy from the battery is used to eliminate the need to bring another diesel generator online to meet only short-term increases in the load due to battery fast charging/discharging. The total size of the batteries is selected such that they provide the total energy required by the load for 30 min. Thus, nine battery units are chosen with size of 2.16 kWh each. Battery parameters are presented in Table 6.

Figure 7 HOMER schematic diagram for Al Mathafa area with PV and batteries.

Table 6 Battery parameters.

Capital cost ($)	Efficiency (%)	Lifetime (years)	Replacement cost ($)	O&M cost ($/year)	Salvage value ($)
3768 (9 units)	86	5	3768 (9 units)	10	0

After running the model, there are 768 possible solutions, and out of these 16 best solutions prioritised according to system's minimum NPC are shown in Table 7.

Table 7 Optimal solution for Al Mathafa area with PV and batteries.

In the optimal solution, generator 4 (160 kW) is not chosen and the total NPC is $540,222 with operation cost of 43,637 $/year, and the cost of energy equals to 0.144 $/kWh. The current operating cost of energy in this station is 0.5581 $/kWh (Annual report from Rural Areas Electricity Company 2010) which is far more expensive compared to the proposed hybrid system.

4. Conclusions

The paper has presented a model to assess wind power cost per kilowatt hour of energy produced using different sizes of wind machines at two sites in Oman. The energy costs of wind power generated at Thumrait and Masirah sites for four different sizes of turbines are estimated between 2.6 ¢/kWh and 7.5 ¢/kWh. The low cost of energy can be explained based on the fact that the initial cost of some turbines was small. Furthermore, this paper presented studies carried out to investigate the economics of using PV and PV with battery as an energy fuel saver in two villages. The results show that combining the PV with the existing system is an attractive option which can reduce the cost of energy in one village from 55.81 ¢/kWh to 14.4 ¢/kWh.

Acknowledgments

The authors would like to acknowledge the quality support of the Rural Areas Electricity Company Oman for providing the load data. The acknowledgement is also extended to the Directorate General of Civil Aviation and Meteorology, Department of Meteorology, for providing the wind and solar radiation data for the sites.