Energy Education Science and Technology Part A: Energy Science and Research 2012 Volume (issues) 28(2): 877-888

Feasibility study of off-shore wind farms in Malaysia

S. Mekhilef 1, A. Safari1,*, D. Chandrasegaran2

1University of Malaya, Department of Electrical Engineering, 50603 Kuala Lumpur, Malaysia

2University of Malaya, Department of Mechanical Engineering, 50603 Kuala Lumpur, Malaysia

Abstract

The paper describes the current situation of wind energy across the world and specifically discusses the offshore wind farm technology. Subsequently, wind energy potentiality and techno- economic feasibility of offshore wind farms is investigated in Malaysia. Analysis was conducted using HOMER software to assess the potential of wind energy along the South China Sea coastline. This study indicates the best sites to set up offshore wind farms in Malaysia while costs associated for wind energy generation are calculated. Also, case studies for two types of Vestas wind turbine models (V-47 and V-80) are conducted. The analysis shows the feed-in tariff policy reduces the energy price and increases wind farms profitability. Investment, operation and maintenance costs have been evaluated for offshore wind energy system. Keywords: Wind energy; offshore wind energy; Wind turbine; South China Sea; Malaysia © Sila Science. All rights reserved.

Nomenclature RE

Renewable energy

R&D Research and development UKM University Kebangsaan Malaysia TNB Tenaga Nasional Berhad WTG Wind turbine generator O&M Operation and maintenance NPC Net present cost CRF Capital recovery factor COE Cost of energy

1. Introduction

Currently, global energy demand is supplied by three main categories: fossil fuels, renewable energy (RE) sources and nuclear fusion, however, renewable energy sources poses significant _____________ Corresponding author: Tel.: +60-03-7967-6851; fax: +60-3-7967-5316. E-mail address: azadehsafari2008@gmail.com (A. Safari).

878 S. Mekhilef et al. / EEST Part A: Energy Science and Research 28 (2012) 877-888 advantages over other energy sources that make them as the best source of energy. One reason that makes RE so advantageous is that they are sustainable solution to the world energy crisis since early 1970’s. In addition, they can save great expenditures of traditional power production and compensate the harsh environmental impacts caused by fossil fuels [1-5]. Among RE sources, wind energy is dynamic energy source that fascinated more attentions since it is easily accessible in a wide range around the world. In spite of minor environmental impacts of wind energy, it is considered as green energy source with no green house gas (GHG) emissions. Intense research and development (R&D) should be allocated to find solutions and overcome fundamental problems as well as technology enhancement [6-9]. Pursuant to worldwide development for wind energy resources, offshore wind energy facilities have grown in recent years. Onshore wind stations are usually apart from coastal load centers and the public electricity grid is not capable for interstate electric transmission; hence, offshore wind stations are very practical when the offshore wind stations are adjacent to the load centers. There are other benefits of using offshore winds since they are more vigorous, steady and stable compare with onshore winds. Higher offshore wind energy resources are available for wind turbine installations because offshore wind speed is generally higher over the sea and oceans than over the land areas. The wind conditions generally determine the economic feasibility of offshore wind energy utilization. In addition, there is no area limitation for off shore power installation and devices [10]. In this paper, current situation of global wind energy utilization is reviewed. Potential of wind energy, techno-economic analysis, annual energy yield and energy price for offshore wind installations are presented. Assessments are applied to six selected sites with high potential of harnessing off shore winds in Malaysia. Results offer promising potentials of introducing this technology for harnessing wind in the selected sites. 2. Offshore wind power Wind analysis shows that offshore winds are notably stronger than onshore wind resources hence provide substantial amounts of energy. It is also proved that offshore wind turbines can be easily installed due to slow increase in water depth vs. distance from shoreline, hence the benefits of the harnessing sea wind are firmly accepted [11-13]. Offshore wind sources has higher potential of wind energy, less turbulence, steadier wind, higher mean speed wind, more aesthetics, more options for power transmission, access to low loaded lines, vicinity to heavy load centers, no constraints on turbine size, more economic features due to larger machines, no limits for shipping roadway and no restriction for crane erection. Offshore wind power R&D first began in 1970’s in Europe and United States. Fig. 1 shows the contribution of countries for offshore wind projects by 2010 which is totally around 11,455 MW. Offshore wind energy systems are different from onshore installation due to several reasons. Offshore wind turbines generate more power than onshore installations because the wind speeds are higher and steadier. In addition, offshore wind turbine generators (WTGs) usually have larger diameter blades and yields higher rated power. From the other point of view, offshore wind plants are inaccessible during high wind periods because of hazards of windy sea and high waves. Installation and maintenance costs of the

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Fig.1. Offshore wind projects prediction through 2010 [14].

facilities are expensive and submarine electrical transmission to the shore is a major difficulty for the plant’s installation. Moreover, offshore environmental issues are difficult to organize and more demanding than onshore plants. Hence, offshore wind installations require more capital investment and involve high risks. Recently, wind power research projects are focused on study about efficient methods of harvesting offshore wind energy and overcome the barriers to fully exploit wind energy. The emphasis is reducing the offshore wind farm setup costs and improves the wind turbine design. The aim is to design wind turbines specifically allocated for installation and operation with low maintenance in offshore wind farms and conquer costly and tough current maintenance requirements [15], [16].

3. Offshore wind energy in Malaysia

Malaysia is geographically located in 1°22'N latitude and 103°55'E longitude of Southeast Asia. Geographical location of Malaysia is shown in Fig. 2. Malaysia climate is governed by strong winds blowing Northeast and Southwest from the Indian Ocean. The Northeast monsoon blows between October and March while the Southwest monsoon blows during May and September [17]. Malaysia's location just amongst the South China Sea provides a marvelous potential for ocean based energy sources. The main ocean based energy sources are Thermal Energy Conversion (OTEC), ocean current, tidal, wave and offshore wind power [19]. As the first move toward the wind energy utilization, University Kebangsaan Malaysia (UKM) has conducted a wind data collection for ten stations in Malaysia (6 stations in Peninsular and the remained 4 stations in Sabah and Sarawak located in Malaysian Borneo) during 1982–1991. The research indicates, in Malaysia wind speed over the land area is generally low. Another research in 2003 revealed that annual offshore wind speed is about 1.2–4.1 m/s in Malaysia while the highest annual vector resultant wind speed of 4.1 m/s occurs during Northeast monsoon season between November and February in East peninsular Malaysia [10]. Locations facing the South China Sea are the most promising sites for wind power installations and in

880 S. Mekhilef et al. / EEST Part A: Energy Science and Research 28 (2012) 877-888

Fig. 2 Geograghical location of Malaysia [18]

particular Kuala Terengganu and Mersing have the maximum potential of wind power in the country [20-21]. Aware of the utilization benefits of wind energy, Malaysia government conducted a demonstration project of wind turbine installation in Terumbu Layang with energy capacity of 150 kW in 2005 [22]. Wind energy has a great prospect in tourist resort islands which are currently using their own diesel generators. In 2007, the state government of Terengganu joint with Tenaga Nasional Berhad (TNB) embarked on first solar-wind-diesel hybrid power plant project with combined capacity of 650 kW to supply Perhentian Island. The project is integrated of 2×100kW wind turbines, 100kW solar energy and 200kW and 150kW diesel generators. The system also comprises back up batteries with capacity of 480kWh to store up the power. The project is considered as the first of its kind in Asia. The hybrid system has reduced power generation costs on the island by almost 40% from the previous diesel generator system. The project is set up for domestic use only; however, it is technically possible for the resorts to switch to the renewable electricity from their diesel generators since there is now excess power. In addition, Ministry of rural and regional development have set up 8 wind turbines with capacity between 5-10kW in Sabah and Sarawak [23, 24].

4. Energy analysis

To determine the annual energy (E) yield of an offshore wind farm, there are some technical aspects that should be appraised. a) Offshore wind flow prediction Predictions of wind flow for a particular site is a crucial factor to determine the feasibility of a project. Therefore, a detailed knowledge of wind characteristics and historical data is required for efficient planning and implementation of wind farms. These data can be sourced from meteorological department of the locality and marine surface observation reports. Fig.3 shows the coastline of Malaysia that faces that South China Sea. Numbers 1 to 16 were assigned to each location. Grids 1-7 represent area covering the east peninsular Malaysia coastline that faces east of South China Sea. Grids 8-16 represent area covering the north-west side of Borneo that forms pall of Sarawak and Sabah coast line [25]. Sites with numerical identification of 1, 2, 3, 4, 8 and 13 are selected. These sites face the South China Sea and present a potential offshore wind resource. The criterion for selecting these places is that during the Northeast monsoon season wind speeds at these sites reach more than 5 m/s; however, wind speed has been marked low for the rest of the year. The directions of the wind are from the northeast and east quadrant during the northeast monsoon season and south and southwest during the southwest monsoon season [26].

S. Mekhilef et al. / EEST Part A: Energy Science and Research 28 (2012) 877-888 881 Also, a general survey shown in Fig. 4 indicates the water depth for the sites are less than 50m; however, in this study, the wind farms are estimated to be 20m water depth, within a distance of 5km from the shore.

Fig.3 Selected offshore wind farm sites [2].

Fig.4 Bathymetry for South China Sea areas [2]. b) Gross energy assessment; EG (GWh/ year) Gross energy of the wind turbines can be calculated using wind flow information and the Wind Turbine Generators (WTGs) power curve. The HOMER software [26] has been used considering the WTGs power curves, prevailing wind directions and the Weibull distribution parameter of selected sites. The main parameters of selected sites are described in Table 1.

Table 1. Main parameters of selected sites Site Air Density Weibull

parameter Average Wind Speed

Available Area Mean Water Depth

Coast Distance

kg/ m3 m/ s km2 m km 1 1.08 2 3.5 2 20 2 2 1.08 2 4.1 2 20 2 3 1.08 2 3.8 2 20 2 4 1.08 2 3.3 2 20 2 8 1.08 2 3.1 2 20 2

13 1.08 2 3.8 2 20 2

882 S. Mekhilef et al. / EEST Part A: Energy Science and Research 28 (2012) 877-888 c) Wind farm design

Offshore wind farm layouts can be optimized to enhance the energy generation. Water depth and sea bed conditions also shall be considered to reduce the overall project costs. The available space is assumed to be 2km2. Layout is arranged by arrays distance (D) between rows (dr) and columns (dc) of 6D and 8D, respectively. The number of wind turbines (WTGs) in a wind farm (N) is calculated using: N = A/(48. D2) (1)

Also, the array efficiency (L) is often accessed via software programs considering the sheltering effects of the WTGs and wind flow characteristics, so the value is assumed to be 0.9. d) Wind farm Electrical transmission losses coefficient; E

A 20kV AC transmission line is the best solution for a wind farm size of 10-20 MW with estimated distance to coast of 0.5–2.0 km [27]. Hence, the electrical transmission losses coefficient (E) is expressed by (2) where (d) is distance to the shore (km).

E = 0.98 – (d/ 600) (2)

e) Wind farm availability; A Wind farm availability refers to the availability of plant to produce electricity in percentage. Wind farm availability considers both electrical system and WTGs availability. The availability is assumed to be 95% of the annual energy yield. Consequently, the annual gross energy yield, E (GWh/ year) can be concluded using previous assumptions in (3):

E = EG x N x L x E x A (3)

5. Economic analysis

HOMER software has been employed to calculate offshore wind energy costs. Total capital costs to establish offshore wind energy systems are comprised of the following items.

a) Wind turbine costs, CT

Wind turbine costs include the tower, shell and electrical devices of the WTGs which mainly depend on the size of the turbine. According to literature data CT is in the range of RM 3,750,000 to 4,500,000/MW.

b) Support and installation costs, CS

Support and installation costs comprise of material, construction and installation costs. Material cost is factored by hub height and site conditions such as water depth and climate, meanwhile, the installation cost is a function of number of WTGs erected:

CS = (H/0.5) 0.3 [(1700 W2 - 9455W+ 21836)/ 1000] (4)

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Where, (W) is the water depth and (H) stands for the wind turbine hub height.

c) Grid Connection Cost, CG

Grid connection costs are subject to the transmission system, distance from the shore-based station and also the distance from onshore point. A 20kV/ 150kV transformer costs around RM42,500/MW and the additional costs of other devices are of RM500,000/MW.

d) Operation and Maintenance Cost, CM

CM is ties up with the overall operational and maintenance strategy employed by the plant operator. In addition, distance from shore points and plant reliability affect the cost. It is estimated to be RM250, 000/ MW.

e) Project and Development Cost, CP

The project and development cost constitute about 4% of the total investment cost. The total investment cost (I) is: I = N [PR (CT + CG + CM +CP) + CS] (5) where PR is the WTG rated power.

f) Operation and Maintenance Annual Cost (O&M)

The O & M cost is about 2% of total investment costs. However, total operating cost is the sum of the annual O & M costs, total fuel cost, and annualized replacement cost minus the annualized salvage value. For grid-connected systems, the operating cost includes the annualized cost of grid purchases minus grid sales. The total Net Present Cost (NPC) is the current value of the total costs minus current value of total revenues that has earned during the system lifetime. Costs are consisting of investment, operation and maintenance, replacement and fuel costs. In addition, emission penalties and the prices of the power bought from the grid should be considered. Revenues include salvage value and grid sales revenue: NPC = Total annualized cost of the system/ CRF (6) CRF = i(1+i)n/[(1+i)n – 1] (7)

where CRF is the Capital Recovery Factor, (i) is discount rate and (n) is the number of years. Cost of Energy (COE) is average cost of the efficient generated electricity per kWh and can be calculated as the result of the annualized cost of producing electricity divided by total efficient electric energy production. COE = Total annualized cost of the system/ Total electricity produced (8)

884 S. Mekhilef et al. / EEST Part A: Energy Science and Research 28 (2012) 877-888 The economic parameters are defined in Table 2. Table 2 Economic parameters Parameter Value (unit)Economic lifetime 20 yearsDiscount rate 4%Electricity Price RM 0.29Feed-in- Tariff RM 0.29 6. Case study of selected sites

The economic feasibility analyses are considered for two model of the wind turbines. Table3 is the technical data for Vestas V-47 and V-80 wind turbines. Investment and also O&M costs for each wind turbine are presented in Table 4. Table 3. Wind turbine parameters [28]

Parameters Vestas V-47

Vestas V-80

Rated power (kW) 660 2000 Rotor diameter (m) 47 80 Hub height (m) 50 78 Number of WTGs 19 7 Availability 0.95 0.95 Array efficiency 0.93 0.95 Transmission efficiency 0.978 0.978 Plant size (MW) 12.54 14 Table 4. Investment and O & M Costs (1RM=0.16€) Description Vestas

V-47 Vestas V-80

Investment cost (kRM) 162,828 132,750 CT (%) 36 56 CS (%) 50 26 CG (%) 9 10 CM (%) 2 3 CP (%) 3 5 O&M cost (kRM/yr) 3,258 2,658

To assess the monthly average electric production by each wind turbine, site 2 is adopted. Fig. 5 shows the results that confirm electricity production during the Northeast monsoon season is the highest and decreases for the rest of the year. Wind farm capacity, costs of energy and energy generation for all the selected sites are tabulated in Table 5. Each site is considered for using both models of wind turbines. Results indicates that larger sized WTG produces higher energy output compared to the smaller sized WTG, corresponding to Site 1, 4, 8 and 13. However, the variances are between the two models

S. Mekhilef et al. / EEST Part A: Energy Science and Research 28 (2012) 877-888 885

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0

2,000

4,000

6,000

8,000

Po

we

r (k

W)

Monthly Average Electric ProductionWindGrid

(a)V-47

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec0

2,000

4,000

6,000

8,000

Po

we

r (k

W)

Monthly Average Electric ProductionWindGrid

(b)V-80

Fig. 5. Monthly average electric production for site 2: (a) V-47 (b) V-80

is less than 5%. The COE for both models of WTG in all the investigated sites is presented as well. The results confirm that the higher rated WTGs are more competitive at approximately 33% lower against the lower rated WTGs, due to their lower energy system cost. As it shows, the lowest cost of energy system is achieved at Site 2. Meanwhile, highest cost of energy system is found on Site 8. The reason is differences available in wind resources for a particular site. Net specific production results in having smaller rated WTG with higher value for all sites as shown in Fig. 6. Influence of the feed-in tariffs in the energy price for Site 2 using the V-80 wind turbine is explored for the sensitivity analysis. Table 6 shows the variation in the cost of energy vs. feed-in tariff ratio. The analysis shows that feed-in tariff ratio of 2.38 would represent the breakeven point for the energy system cost. Any subsequent increase in feed-in tariff ratio would be present an attractive climate for private sectors to invest [30-32].

7. Conclusion

Malaysia which is surrounded by South China Sea has a great potential to utilize the offshore installation of wind energy. Although there are several strategies to encourage communities utilizing wind energy, there is no energy policy specifically approved for wind energy in

886 S. Mekhilef et al. / EEST Part A: Energy Science and Research 28 (2012) 877-888 Table 5. Techno-economic analysis for selected sites Site Model Wind

Farm Capacity

Initial capital

Operating cost

Total NPC COE E Net Specific Production

MW RM RM/ year RM RM/kWh kWh/ yr MWh/ MW

1 V-47 12.54 162,828 614,232 154,480,404 0.85 13,445,249 1,0721 V-80 14 132,750 871,438 83,294,371 0.64 13,451,246 9612 V-47 12.54 162,828 1,439,335 97,132,399 0.55 18,286,012 1,4582 V-80 14 132,750 1,856,770 69,903,402 0.40 18,225,138 1,3023 V-47 12.54 162,828 628,527 108,151,545 0.77 14,357,679 1,1453 V-80 14 132,750 1,043,950 80,949,874 0.58 14,287,065 1,0214 V-47 12.54 162,828 472,174 123,110,393 1.40 9,024,842 7204 V-80 14 132,750 20,300 94,861,629 1.04 9,327,512 6668 V-47 12.54 162,828 806,762 127,657,583 1.77 7,403,764 5908 V-80 14 132,750 309,527 99,344,070 1.32 7,729,525 552

13 V-47 12.54 162,828 599,816 108,541,727 0.79 14,218,581 1,13413 V-80 14 132,750 1,030,091 81,137,637 0.59 14,220,128 1,016

Net Spec Production for Different Site

0200

400600

8001000

12001400

1600

1 2 3 4 8 13

Site

MW

h/

MW

V-47 V-80

Fig. 6. Net specific production for different sites. Malaysia due to the new-fangled characteristics of the wind energy technology in the country. In addition, wind energy potential is not fully realized by related industries. Thus, to commercialize wind energy utilization a comprehensive wind energy policy can boost the country among the leaders in this field. In the presented paper, preliminary feasibility of offshore wind energy for 6 selected sites in Malaysia was conducted. Locations facing South China Sea are the best choices for offshore wind farm implementations with the maximum potential during Northeast monsoon season in November to February. The highest annual vector resultant wind speed of 4.1 mls is

S. Mekhilef et al. / EEST Part A: Energy Science and Research 28 (2012) 877-888 887

Table 6. Sensitivity analysis for V-80 model, Site 2 TNB - Commercial Sellback (RM/kWh)

COE (RM/kWh)

Feed-In Tariff Ratio

0.29 0.40 1.00 0.43 0.25 1.50 0.58 0.11 2.00 0.65 0.01 2.35 0.68 0.00 2.38 0.69 -0.01 2.40 0.71 -0.02 2.46 0.72 -0.04 2.50 0.73 -0.05 2.54 0.77 -0.08 2.67 0.78 -0.10 2.71 0.86 -0.18 3.00

recorded in the East peninsular Malaysia. Results indicate that Site 2 is the best location due to high wind resources availability. The 2 MW rated wind turbines, provides the lowest energy cost at RM0.40. However, higher net specific production is provided by the 0.66 MW rated wind turbine. The sensitivity analysis confirms that the feed-in tariff is a significant criterion to determine the feasibility of offshore wind farm in Malaysia. Feed-in tariff higher than the breakeven point, would attract private sectors to invest on this type of energy system. An attractive policy would determine the profitability of an investment in the offshore wind farms and encourage private sectors to invest here.

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