Essay: TECHNO – ECONOMICAL ANALYSIS FOR WIND POWER PROJECT

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  • TECHNO - ECONOMICAL ANALYSIS FOR WIND POWER PROJECT
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TECHNO – ECONOMICAL ANALYSIS FOR WIND POWER PROJECT
ABSTRACT
This paper presents a methodology for the selection of “Wind farm site and Wind Energy Generator WEG)” based on the Technical and Economical analysis. The prime objective of power generation is to satisfy the customer needs economically with emphasis on safety, reliability and quality.
Wind energy has become a prominent source in the present global energy picture. The average power output of a WEG is very important parameter for an economical viability of the project. Selection of Wind Energy Generator determines the total energy production & total income and also it demands good knowledge of wind related characteristics such as site selection and energy output.
The annual Energy generation using power curve of the WEG, annual capacity factor [ACF], annual capacity utilization factor [CUF] and power density has been calculated for technical analysis.
The cost analysis such as “ Cost of generation, Net Present Value (NPV), Internal Rate of Return (IRR), Benefit Cost Ratio (BCR), Levellised Cost of Generation and Life Cycle Cost i.e. Pay Back Period has been calculated for Economical viability assessment of the project.
In view of the technical considerations and economical analysis, the results are analyzed and recommended to implement the wind power project at a specific windy site with an optimum WEG.
CHAPTER ONE
1.0 INTRODUCTION
Renewable source of energy has least impact on environment, ecology and is ideally suited for decentralized variety of applications. Wind is free, clean, Eco-friendly form of energy and inexhaustible energy source. In our country various windy regions have been identified, having potential for generating electricity. One of the prime conditions for utilizing wind energy is knowledge of site/location and meteorological data.
In case of conventional source of energy, we have controllable input, so the amount of power developed can be easily estimated. But for wind power the position is different, neither the performance of the wind did indicate by its efficiency as a power unit, nor its annual output of energy can easily be measured or predicted in advance for two reasons, viz. (1) Wind speed and the power input to the machine and (2) The annual output of energy is influenced greatly by the precise location (micro siting) of the wind Electric generator installation in a given area, for which, the general value of the annual mean wind speed may be known. In addition to above, it demands good knowledge of wind related characteristics such as, a) Location /or selection of windy site, b) Air density and wind speed velocity, c) Influence of height of installation above ground, d) choice of wind Electric generator, e) Grid connected or stand alone for remote areas. i.e. Utilization of power and f) Wind power density and annual energy generation.
The prime objective of power generation is to satisfy the customer needs economically with emphasis on technically safety, reliability and quality. Recent events have posed a set back to the sector of Conventional power generation, the reasons for which include high fuel price, societal pressures to conserve resources, environmental awareness, increases in production cost and concern for safety related to certain technology (like the nuclear). Hence in present day energy scenario for meeting the ever-increasing energy demand, efforts have come into focus with a view to develop new generation technologies. The major goals of these approaches are to have reduced environmental damages, conversion of energy, inexhaustible sources and increased safety. In this context, during the past few years renewable energy sources have received greater attention and considerable inputs have been given to develop efficient energy conversion and utilization techniques.
The realization of enormous need to electrify and energies remote rural areas of developing countries where Renewable and Non-conventional energy sources are adequately available.
In view of the above facts, the Technical and Economical viability of the wind power project for power generation is considered and analyzed in this paper for implementation of the project.
2.0. MAJOR PROBLEMS OF WIND POWER:
Some of the problems raised by the gust for a more favorable economic environment are. (1). Adaptation of wind plant features to the wind conditions and types of utilization, ( 2) Selection of optimum unit size and power output, (3) Whether one unit or more than one should be used to generate the total energy required, (4) Design selection, possible series production, uses of new materials especially plastics and (5) Design details appropriate to climatic conditions incorporating case of maintenance and corrosion resistance.
3.0. PRINCIPAL PROBLEMS RELATED TO PLANT DESIGN:
The principal problems related to plant design are;
(1) Economy of design, imposed by the extreme dilation of wind power, (2) Relatively large rotor diameter, in consequence of that dilation, Rotor speed is therefore rather low, making a set up of good transmission necessary, (3) Especially strong design of the rotor blades, to withstand the stresses of turbulence acting in conjunction with the cyclical variation of stress, (4) System of blanking out the blades or the rotor imposed by the great gap between the rated wind speed and the maximum wind speed in a storm, (5) Speed control or adaptation of the characteristic of the wind power plant to the characteristics of the driven machine and (6) Other points, more specifically of economic nature is.
a. Determination of the tower height, b. Installed power, c. Point of maximum efficiency for varying
wind conditions and d. Normal operating motor speed
4.0. SYSTEM DESIGN AND OBJECTIVES:
The general objective in designing a WECS is to adequately match the WECS capabilities to the load requirements of the consumer, at a minimum cost of the system to the consumer. In order to accomplish this, the designer will need to know the following types of questions about the system.
(1) Power requirements, (2) Wind availability, (3) Type and size of WECS required, (4) Cost of energy produced, (5) WECS viability, (6) System characteristics, (7) System requirement, (8) Evaluation criteria, (9) Design optimization, (10) Economic viability and (11) Prospects of cost reduction:
4.1. Evaluation criteria
In most WECS applications, the objective will be to design the system to minimize the life-cycle cost of the system and the price of the energy produced by the system. Criteria that should be used in determining the viability of a WECS include.
(1) The energy pay back time, (i.e., the time required for the WECS to generate sufficient energy from the wind to equal the amount of energy expended in manufacturing the WECS as well as operating and maintaining it during this energy payback period.), (2) The energy gain of the system (i.e., the amount of energy generated by the WECS during its life time, divided by the amount of Energy required to manufacture, operate, and maintain it during its life time) and (3) Various possible environmental, aesthetic, legal, financial, institutional, or other types of constraints that might have an impact on the public acceptability of the WECS or its acceptability to public utilities, industries, farm owners, home owners or other possible users.
4.2. Design optimization
The principal factors that affect the economic viability of wind powered system are the (1) Availability of wind power at a given site, (2) The investment, (3) The operation and maintenance (O&M) costs of the wind power system, (4) The expected lifetimes of the systems, (5) The interest rate on investment capital and (6) The price of competing forms of energy.
4.3. Economic viability
For economic viability of the wind power project, the important deciding parameters are follows.
(1) Pay back period should be less than loan repayment period, (2) Net present value[ NPV ] > 1,
(3) Internal rate of return [ IRR ] > 1, (4) Benefit cost ratio [ BCR ]> 1., (5) Cost of generation for 1st year, (6) Cost of generation for 10 years average, (7) Cost of generation for 20 years average, (8) Levellised cost of generation and (9) Levellised cost of selling price.
4.4 Prospects of cost reduction:
It is possible to reduce the cost of the wind power project by considering the following aspects. (1) Reduce the capital cost of the system, (2) Locate the system in a good wind regime to maximize the plant factor, (3) Engineering the system to be simple and reliable, so that O & M cost can be reduced, (4) Design the system for long life, (5) Borrow money at the lowest possible interest rate and (6) Taking all advantages of the incentives, subsidy and tax credits made available by the various agencies of the Government.
5.0 TECHNICAL ANALYSIS:
5.1 Assessment of Energy Output:
The annual output of energy is influenced greatly by the precise location (micro siting) of the WEG’S installation in a given area, for which, the general value of the annual mean wind speed may be known. In addition to above, it demands good knowledge of wind related characteristics such as, Location /or selection of site, Air density and wind speed velocity, Influence of height of installation above ground, Choice of WEG’S, Grid connected or stand-alone for remote areas. i.e., Utilization of power , Wind power density and annual energy generation.
5.2 Site Selection:
Success or failure of a WEG’S to deliver the power depends critically on mean wind velocity available at the site / location depends on;
(1) Wind availability i.e., Wind velocity, (2) Influence of height of installation above ground, (3) Effect of wind gusting, (4) Sites with annual mean wind speed of 20 km/hour with a hub height of 30 m and power density of 150 watts /sq.m. is considered to be economically viable, (5) Two (2) years wind speed studies are required for assessment of wind power potential, (6) Siting in a flat and (7) Siting on non-flat terrain i.e., At ridge, its advantages are: a. The ridge acts as a huge tower, b. It increases the available power and c. Avoids undesirable effects of cooling near the ground.
5.3 Assessment of Wind Availability – Wind Data:
Selection of a windy site for wind power generation requires meteorological data as a base for installation of WEG’s for power generation.
The uses of meteorological data are:
(1) As a basis for which surveys indicating the areas where the highest wind speeds are to be found.
(2) As an indication of the direction of prevailing wind knowledge. This is important in selecting wind power sites.
(3) As a measure of the constancy or variability of the annual mean wind speeds from year to year.
(4) As an indication of the annual wind regime for an area from values by monthly mean wind speeds.
(5) As a measure of derived variations in wind speeds to be expected at different seasons of the year.
(6) PRE-REQUISITE – DETAILED WIND DATA CONSISTING OF:
a. Month wise frequency distribution for power estimation.
b. Wind rose data for the micro siting of WEG’S.
c. Time series data for the analysis of peak-time contribution of energy to the grid.
In this paper, 2 years and 4 years wind speed data of 2 sites have been used. Wind speed measurements constitute the fundamental information for assessment of wind energy availability. Wind speed is summarized using statistical methods as shown in table [1] and table [2] for a site A and site B respectively.
5.4. Micro Sitting of Wind Electric Generators [ WEG’s]:
In addition to the above the micro siting of land also influences the above-mentioned factors. These factors are:
(1) A visual inspection of the land gives an idea of the topography of the terrain. Locate the WEG’S at the
highest level of the land [i.e., Utilizing natural hub height] in the region of least turbulence.
(2) Main direction of the wind flow at the proposed location is determined by magnetic compass and wind
vane. Map of wind roses gives the frequency distribution of main wind flow.
(3) Minimum distance criteria of 2D and 5D distance between two turbines in adjacent rows and along the same row respectively.
5.5 ESTIMATION OF WIND ENERGY POTENTIAL:
1. WIND SPEED EXTRAPOLATION:
Wind speed data are usually recorded in the data loggers at a height of 10 m and 20 m, wind speed increases with height as per power law equation. Since the WEG’s is several meters height, the mean wind speed at a particular height will be greater than mean wind speed at 10 or 20 m height. Therefore, to obtain mean wind speed at a WEG’s hub height, the mean wind speed has to be projected / upgraded to the hub height.
2. METHODS OF CALCULATION:
Estimation of wind energy potential based on the following methods:
(1) Based on wind data of a specific site using frequency distribution.
(2) Based on type of Wind energy generator [WEG ].
(3) Based on Weibull factors of the wind data and WEG’s characteristics.
3. EQUATIONS USED FOR CALCULATIONS:
A) BASED ON WIND DATA:
Annual energy generation and other factors are calculated at a specific site based on the following Equations and characteristics of WEG’s.
1. POWER LAW INDEX [ ￿], (U2/U1) = (H2/H1)￿
Where U2= WIND SPEED AT HEIGHT H2 and U1= WIND SPEED AT HEIGHT H1
2. WIND POWER [Pw], Pw=0.5* ￿* A*U3 Watts
3. POWER DENSITY [Pd], Pd=0.5* ￿* U3 Watts/sq.m
4. MONTHLY ENERGY [Em], Em = Power density * Monthly hours kWh
B) BASED ON WIND ELECTRIC GENERATOR [ WEG ]:
1. Machine capacity factor [CF] = Average output (Pa) /Rated power (Pr)
2. Plant load factor [ PLF ] = Annual energy generated / (8760 * rated capacity of WEG )
3. Capacity utilization factor [ CUF ] = Actual energy generated / Theoretical energy generated
4. Annual capacity factor [ACF ] = Estimated annual energy output per MW / 8760
5. Capacity factor on the basis of WEG characteristics and using Weibull factors of scale factor [C] & shape factor [K].
6. Average power [ Pave] = CF * Rated power of WEG
The annual energy, ACF, CF, Average power [Pave], PLF, Power density and power generation kWh / kW installed capacity of WEG are calculated using above equations based on frequency distribution, Weibull factors and using power curve of the given WEG’s, the results are tabulated in tables – 3[A] and 3[B] for site – A and site-B respectively.
5.6 Selection of Optimum Wind Energy Generator [WEG] :
There are many different types of WEG commercially available in the market for power generation. The size of the WEG range from 1 kW to as large as 3 MW or more. Therefore, it is necessary to select a best- suited WEG for a particular site, regardless of turbine size. To choose the optimum WEG size for the site, 10 different rating / capacity of commercially available WEG were used in this study.
The production of electricity by a WEG at a specific site depends on many factors. These factors include the mean wind speed of the site and more importantly, the characteristics of the WEG itself, especially the hub height, cut in (UC), rated (UR) and furling (UF) wind speed of the machine.
In this section a methodology for the selection of the optimum WEG for a specific site is developed. The selection criteria is based on the comparative statement of annual energy made by the calculated values of the annual Energy generation using power curve of the WEG, annual capacity factor [ACF], annual capacity utilization factor [CUF]. The power density is calculated from the wind data obtained over a period of few years to select an optimum WEG using weibull parameters. These are the factor considered for utilization of a wind energy at a given time and site.
5.7 Technical Evaluation:
Based on the comparative statement from table- 1,2, 3[A] and 3[B] for annual energy output using power curve of the WEG’s and frequency distribution & Weibull parameters of a particular site wind data, it is concluded that
1. The annual mean wind speed and power density are higher side for site B. Hence the site B is windy site and suitable for development of wind farm compared with site A.
2. The WEG 10 is optimum one and suitable for installation at site A and also WEG 9 is optimum
one and suitable for installation at site B.
3. The ENERGY GENERATION, ACF, PLF AND UCF from the high capacity/rating of WEG’s is on lower side compared to low capacity/ rating WEG’s. Hence the high capacity/ rating WEG’s are not viable at these sites.
6.0 ECONOMICAL ANALYSIS:
This section provides the total cost of installation as also the cost per unit of energy delivered to grid. The methodology to calculate cost of energy is similar to the one adopted by Central Electricity Authority (CEA) and includes cost of all capital equipment’s, electrical and civil works. For Economic viability of the project, the following factors are considered while locating the Wind Energy Generators (WEG’s).
1.
2.
3.
Sites with annual mean wind speed of 20 km/hour with a hub height of 30 m and power density of 150 watts/sq.m. is considered to be economically viable.
Nearest load center and nearest distance from grid.
Availability of basic infrastructure such as Roads and institutional aspects they are
a). Cost of the land.
b). Safety considerations.
c) Meteorological hazards.
6.1 Project Details:
1. INSTALLED CAPACITY = 5 MW
2. PROJECT COST Rs. = 2000 LAKHS
3. INTEREST RATE = 14 %
4 CONSTRUCTION PERIOD = 6 Months
5. DEPRECIATION AMOUNT = 0.9 * PROJECT COST X DEPRECIATION [email protected] 4.5%
6. RETURN AND PROVISION = 3.5 %
7. LOAN REPAYMENT = 10 YEARS
8. MORATORIAM PERIOD = 1 YEAR
9. OPERATION AND MAINTAINANCE = 1% OF THE PROJECT COST
6.2 Calculations and Statements:
1. LOAN REPAYMENT SCHEDULE AND PHASING EXPENDITURE STATEMENT:
a. Loan repayment for 10 years at the rate of 14% interest
b. Interest during construction [IDC] calculated as per amount spent during construction.
c. C1 =amount spent during 1st, 3 rd and 6th month IDC and project cost.
2. COST OF GENERATION PER kWh:
a. Total fixed cost = Interest on loan + O and M charge +Depreciation +Return and provision.
b. Cost of generation per kWh =Total fixed cost / Net generation.
c. Present value for cost of generation and selling price calculated using discount factor (DCF) at 12. % and initial assuming-1.
3. INCOME AND EXPENDITURE STATEMENT:
a. Revenue = Selling rate of energy per unit X Net generation
b. Operating surplus EBDIT =Revenue from sale of energy – O and M charges
c. Net surplus deficit = Operating surplus EBDIT – Interest on loan
4. CASH FLOW STATEMENT:
a. Cash inflow =C1
b. Cash outflow = Operating surplus EBDIT for 19 years+Cash out flow at 20th Year
c. Cash outflow at 20th Year = 20th year operating surplus EBDIT+ Book value
d. Book value Total project cost – Total depreciation for 20 years.
5. NET PRESENT VALUE [ NPV ]:
Net present value of the project is calculated using equation at the rate of 14 % interest for 20years i.e. life of the WEG.
N VALUES j
NPV=￿ VALUES =Cash inflow and outflow
j=1 ( 1+INTEREST RATE )^j N= No. Of years[ 20 years life of WEG],IF NPV >1 Project is viable and IF NPV <1 Project is not viable
6. INTERNAL RATE OF RETURN [IRR ]:
a. IRR is calculated similarly of NPV assuming interest rate of 10%IF IRR >1 Project is viable and
b. IRR <1 Project is not viable i.e. IRR should be greater than borrowed interest.
7. BENEFIT COST RATIO[BCR ]
Benefit cost ratio[ BCR ] = Net cash flow / investment
8. LEVELLISED TARIFF FOR COST OF GENERATION [ LTCG ]
Levellised tariff for cost of generation [ LTCG ] =Total PV cost of Generation / Total DCF
9. LEVELLISED TARIFF FOR COST OF SELLING PRICE [ LTCS ]
Levellised tariff for cost of selling price [ LTCS ] =Total PV cost of selling price / Total DCF
10. PAY BACK PERIOD:
FOR 20 years life of WEG, the pay back has been calculated.
a. Total loan amount = loan amount + Interest
b. Revenue = Sale of energy X Net generation
c. Available payment = Revenue– O&M charges
d. Balance payment = Available payment -Total loan amount
The pay back period will be decided when available payment will be more than the balance payment.
6.3 Cost Evaluation:
In addition to the above technical aspects, the cost analysis such as “ Cost of generation, Net Present Value (NPV), Internal Rate of Return (IRR), Benefit Cost Ratio (BCR), Levellised Cost of Generation and Life Cycle Cost i.e. Pay Back Period has been calculated using above equations for Economical viability assessment of the project. The results are tabulated for cost of generation in table – 4 [A] for site – A and table – 4[B] for site – B.
As per analysis and cost summary in table – 4 [A], for site – A and WEG – 10, it is concluded that cost of generation and pay back period is lower and NPV, IRR and BCR are also on positive side as per condition mentioned above. Therefore from cost analysis for the site – A and WEG 10 is optimum one and recommended to install at site A. Similarly, WEG 9 is optimum one and recommended to install at site B as per table 4[B].
7.0 TECHNO- ECONOMICAL ANALYSIS CONCLUSION / RESULTS:
Based on techno – economical analysis methodology for assessment of windy site, evaluation of wind energy potential and selection of optimum WEG for a particular site may be decided in general on the following.
1. Optimum windmill can be easily be determined by calculating capacity factor.
2. For an increase in Turbine rated wind speed, the capacity factor decreases.
3. Higher the capacity factor the over all rated wind speed of WEG should be nearer to the mean wind
speed, At this condition the size of the wind mill will be optimum.
4. Based on MWH / MW.
5. Based on the energy density watts/sq.m.
6. Cost of generation per kWh.
7. NPV should be more than one/positive and nearer to project cost is more viable.
8. IRR should be more than one/positive i.e. internal rate of return should be more than borrowed interest.
9. Benefit cost ratio [BCR] should be more than one/overall benefit should be more than investment cost.
10. Pay back period should be nearer / less than loan repayment period for more economical viability of the
wind power project.
11. Investment cost per kwh generation.
12. Rated power of the WEG [Per] increases for a given turbine, the cost of the necessary generator transformer, switches, circuit breakers and distribution lines all increases.
13. However, if the CF–capacity factor decreases it means that these items are being used proportionately less of the time.
14. Higher the rating of WEG, Equipment cost will increase more, rapidly than energy output.

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