Pricing Model For Hydroelectric Power Stations

PRICING MODEL FOR HYDROELECTRIC GENERATING STATIONS UNDER DEREGULATED POWER MARKET Reji, P.1 and Ashok, S.2 1

Department of Electrical Engineering, Govt. Engineering College, Trichur, 680009 Kerala, Ph: 0487 2338687, Mobile.9847548666, E-mail: [email protected] 2 Department of in Electrical Engineering, National Institute of Technology Calicut, Calicut, Kerala

Abstract This paper presents a model for determining the optimal electricity price in hydroelectric generating stations under deregulation. The deregulated market is characterized by a number of power producers trying to sell electric power though bilateral agreements or power exchanges. In the deregulated market, pricing based on marginal cost principle is commonly used. Each utility follows their own pricing strategy. Absence of a generalized model causes price volatility. The model presented in the paper is a general one, which can be used by different types of hydroelectric generating stations. The proposed model is formulated based on performance incentive and penalty considering peak/off peak loads, plant load factor and availability of the plant. The developed model is applied to a typical hydro electric utility in India to determine the electricity price. Results show that the percentage error in estimated value falls within the limits. Keywords: Deregulation, Optimal price, Pricing model.

1. Introduction Competitive energy markets are instituted around the world and electric supply industries are restructured to compete in the new emerging markets [8]. Monopolized structure prevailed in old power systems has been broken and fully competitive and open power markets are emerging. From the consumer point of view, it is the increasing freedom to choose their supplier, high quality of services and expectedly lowering of prices [4]. Under deregulated environment, private investors can take independent decisions according to their own assessments rather than those of the government regulated bodies [11].All firms compete to provide generation services at a price set by the market, as a result of the interaction of all of them and the demand [3]. Power generation in India has been a state owned monopoly and the deregulation era began after the introduction of the Electricity Act 2003 along with Availability Based Tariff. The act envisages transforming the power sector from a system of monopoly providers at regulated rates to a system in which different companies compete to provide electricity [2,7].Competition is expected to yield efficiency gains and in turn result in availability of quality supply of electricity to consumers at competitive rates. After the introduction of electricity market liberalization, the generators schedule their production at the terminal points and transactions are processed in terms of energy delivery [10]. The generation business has been given a greater degree of freedom in fixing price structure, respecting a set of regulatory rules and possible revenue caps. The price of electricity has the key role of all activities in the power market and hence it is important to fix the price of electricity in a generating station more accurately and efficiently [1]. In a deregulated market state regulations regarding prices and rates of return do not exist. The private producers generally follow a marginal cost based pricing. Each utility follows their own pricing strategy. In a deregulated system, electricity price varies with reliability of service, peak and off peak period demand. Hence a more standardized pricing model becomes essential for electricity under competitive markets. This paper proposes a model to determine the electricity price considering all operational constraints of the plant and economical variables, for hydroelectric generating companies. This model can be used for calculating electricity price of different types of generators such as new and existing investors in power generation, independent power producers, investors in power exchange and utilities coming under regulatory authorities. It can be also used for estimating electricity price of storage type, pondage type and run off river type hydroelectric

Pricing Model for Hydroelectric Generating Stations Under Deregulated Power Market

47

stations. Along with the rate of energy charge, another factor - operational cost of the generators, is also included. Each utility is trying to minimize the operational cost by using high efficiency motors and keeping tail raise head high. This model is applied to a typical hydroelectric utility in India for calculating electricity price.

2. Proposed Model for Fixing Electricity Price The proposed model is designed for calculation of the electricity price in hydroelectric generating stations under deregulated market. In this model, there is flexibility to charge operational cost and other service charges like reactive power control, voltage control or cess /surcharge etc in addition to the fixed charges and variable charges. The price structure is worked out based on peak load/off peak load, plant load factor and availability of the plant. The main components of price structure are capital cost, fixed charges and variable charges.

2.1 Capital Cost The capital cost includes the cost of land, the cost of building and equipment, cost of installation and the cost of designing and planning of the station. It varies with the site and location of the station and the type of the equipment used. The generating company obtains the capital for financing their investment in the form of equity or debt or both. Price variation includes the change in the cost due to foreign exchange rate, inflation or deflation. Equity E = CC * Y /100 Debt L = (CC * (100 − Y )) / 100

(1) (2)

where Y is percentage equity with utility company.

2.2. Fixed Charges Fixed charges are proportional to cost of installed capacity subject to in house consumption. A cost escalation component is included to accommodate any variation in the initial project cost due to unexpected events. The components of the demand charges are interest on loan capital (Y1), depreciation (Y2), return on investment (Y4), operation and maintenance expense(Y6), interest on working capital(Y7), taxes(Y8) and cost escalation component(Y9). Taxes and insurance is that on land, building and on income. A generating company can choose these components as per the company policy. 2.2.1 Interest on Loan Capital The interest on loan can be calculated either loan wise or considering previous years’ loans. In the new generating station, the loan opening is calculated during the year, but in the existing station, the gross loan is taken. Maximum loan opening is limited to quantity of debt in the capital cost.

Y1= ∑((loan opening during the year+ loan closing during the year)/2)* interest rate)

(3)

2.2.2 Depreciation and Advance Against Depreciation ( AAD ) Depreciation is the loss of value of an asset and is calculated asset-wise. It depends on the size, type of equipment and its estimated life. Advance against depreciation (Y3) is applicable only to generating stations, which comes under regulatory authority. In other cases, this is set to zero. Straight line method is used to calculate depreciation.

Depreciation =(initial value –salvage value)* rate of depreciation

(4)

2.2.3. Return on Investment /Return on Equity . Return on investment (Y5) is a measure of a company's ability to use its assets to generate additional value for shareholders. It is calculated as net profit after tax divided by net assets and expressed as a percentage [9]. A generating company can follow either return on investment or return on equity method according to the company’s rule

ROI = EBIT (1-T)/ Net Assets =EBIT (1-T)/NA

(5)

Return on equity (Y4) is applicable only to generating stations that come under regulatory authority. Any change in foreign exchange rate variation and additional capitalization affects equity. Equity is limited to specified percentage of capital cost [5, 6] .Return on equity is the rate of equity multiplied by the minimum of assessed equity of the company and equity from capital cost. If the assessed equity of the generating company is greater

48

Advances in Energy Research (AER – 2006)

than the specified percentage of the capital cost, assessed equity is made equal to the equity specified by authorities. 2.2.4 Operation and Maintenance Expense (O&M Expense) Operation and maintenance cost depends on the capacity of the plant as well as the operation and maintenance of the generating station, expenditure on spares and repairs, administration and general expenses and other miscellaneous expenses. Operation and maintenance expense can be calculated using average method, or comparison method. 2.2.5. Interest on Working Capital Working capital usually used for the purchase of raw materials, components and spares, payment of wages and salaries, the day-to-day expenses and overhead costs such as power and office expenses etc. The interest on working capital is determined on normative basis. 2.2.6 Taxes Each generating company can collect their taxes according to the prevailing policy. 2.2.7 Cost Escalation Factor The cost escalation component is to accommodate any variation in the initial project cost due to unexpected events. The fixed charges(FC) is mathematically expressed as L d FC = ∑ [ Y21 + Y22 / 2] * rli + ∑ (bvi − svi ) ∗ rDi + i =1 li =1

(

)

max((min(Y11 / k , Y13 ) − Y2 ), 0) + min(Y42 , Y43 ) * re + C * Y51 (1 − T ) / Y52 +

( 6)

yed ( n5−n 6) + ∑ [(OM yi − OMabn yi ) / y * (1 + esf ) yi = yst

(Y6*t1+(1+Y72 )( y3 −cod ) ∗ rw + Y8 + Y9 2. 3 Variable Charges

The variable charges are energy charges and based on ex-bus energy delivered. The ex-bus energy depends on availability of water, plant load factor, time of operation, auxiliary consumption, transformation losses and design energy of the station. In hydroelectric generating stations water is the source of energy. The rate of energy charge can be set between a minimum and maximum price. The rate of energy charge/KWH in the hydroelectric station offered in the competitive market should fall within this range. Rate of Energy Charges= (Fixed charges/month)/Energy for sale in one month.

(7)

2.4 Incentives The generating company can achieve incentives for maintaining reliable and quality power. Incentive is based on the declared capacity in MW corresponding to the generation and the incentive rate is in paise/kWh. Operational cost can also include with variable charges. A penalty clause also can be added for not maintaining quality and reliable power. Total electricity price/month = Demand charges/moth + Variable charge/month+ other service charges, like reactive power control, voltage and frequency control + cess/service tax implemented by the government. (8)

3. Case Study A case study for calculating the electricity price was done for a typical storage type hydroelectric utility. It has installed capacity of 1220MW. The generators can be taken for maintenance during the period of June to December on rotation. For rest of the year all generators are operated. The plant availability factor for this

Pricing Model for Hydroelectric Generating Stations Under Deregulated Power Market

49

particular year is 82.75%.The discharge of water from each machine is maintained as constant. The optimization of fixed charge is achieved by developing and applying a software programme. The selected variables are Y, rli, rDi, re,y,t1, rw, esf. Each variable has upper and lower boundaries. The results of the case study are shown in Table 1. Fig.1 shows availability of water per month. Fig.2 shows the rate of energy charges for the corresponding water availability. The results shows that, rate of energy charge is inversely proportional to water availability. In the absence of outages/ shut down, monthly demand charges remain constant throughout. The utility can reserve the available water in the monsoon season after meeting the demand in market, for the meeting the demand when availability of water is less. Thus, they can reduce the price of electricity when the water is less. There is flexibility to add operational cost and other service charges as a cost component. This enables a more rational work out of electricity price in a market driven system. The availability of plant depends on the time of operation. If the availability is high, the utility can achieve incentives. As availability of the plant is high, plant use factor is also high. The plant load factor depends upon time of operation. Hence, electricity price mainly depends on the plant load factor, plant capacity factor and plant use factor. The financial policy of the generating station mainly depends on these three factors. Table 1: Calculation of fixed charges and rate of energy charges Mont h

Installe d Capacit y

Fixed charges/year Rs.

Fixed charges/month Rs.

Available Water in MCM

Energy generated million KWH

Auxiliary consumpti on

Transf ormati on and Trans missio n losses

Energy for sale in million KWH

Rate of energy charges in Rs/KWH

Apr

1220

3393516326

282793027. 2

82.7

107.06

1%

2.5%

103.3129

2.74

May

1220

3393516326

282793027. 2

78.854

105.39

1%

2.5%

101.7014

2.78

June

1220

3393516326

282793027. 2

671.41

785. 69

1%

2.5%

758.1909

0.373

July

1220

3393516326

282793027. 2

1147.5

1367.55

1%

2.5%

1319.686

0. 214

Aug

1220

3393516326

282793027. 2

685.38

776.31

1%

2.5%

749.1392

0.3775

Sep

1220

3393516326

282793027. 2

296.89

360.77

1%

2.5%

348.1431

0. 81229

Oct

1220

3393516326

282793027. 2

523.98

652.43

1%

2.5%

629.595

0.45

Nov

1220

3393516326

282793027. 2

396.93

526.13

1%

2.5%

507.7155

0.56

Dec

1220

3393516326

282793027. 2

120.23

159.74

1%

2.5%

154.1491

1. 83

Jan

1220

3393516326

282793027. 2

64.384

83.88

1%

2.5%

80.9442

3.49

Feb

1220

3393516326

282793027. 2

48.919

68.11

1%

2.5%

65.72615

4. 3026

Mar

1220

3393516326

282793027. 2

42.685

56.62

1%

2.5%

54.6383

5.176

Figure 1: Variation of water availability per month

50

Advances in Energy Research (AER – 2006)

Figure 2: Variation of rate energy charges with available water.

4. Conclusion This paper presents a model for fixing electricity price in hydroelectric generating stations. This model can be used for calculating electricity price of different types of generators such as new and existing investors in power generation, independent power producers, investors in power exchange and utilities coming under regulatory authorities. It can be also used for estimating electricity price of storage type, pondage type and run-off- river type hydro electric stations. Incase of outages in one or more generators in a station, this model enables better calculation of demand charge and rate of energy charge by taking out the capacity of the outage machines. Along with the rate of energy charge, another factor - operational cost of the generators is also included. Each utility is trying to minimize the operational cost by using high efficiency motors and keeping tail raise head high. The parameters for calculating fixed charges and energy charges are suitably selected. In this model, more parameters are chosen as variables and solved by numerical methods. Optimisation of the model will yield an optimum price for electricity.

References 1. 2. 3. 4.

5. 6. 7. 8. 9.

H.Y.Yamin, S.M. Shahidehpour and Z.Li.’Adaptive, 2004., Short-term electricity price forecasting using artificial neural networks in the restructured power markets, International Journal of Electrical Power & Energy Systems, 26, 3, 571-581. I.M. Pandey, 1999, Financial Management, Vikas Publishing House Pvt Ltd, 8th edition, New Delhi. Luonan Chen, Hideki Suzuki, Tsunehisa Wachi and Yukihiro Shimura, 2002,Components of Nodal Prices for Electric Power Systems, IEEE Transactions on Power systems, 17, 1, 41 – 49. Nopporn Leeprechanon, A. Kumar David, Selva S. Moorthy, and Fubin Liu, 2002 Transition to an Electricity Market: A Model for Developing countries, IEEE Transactions on Power systems, 17, 3, 885 – 894, August . On line at -www.cercind.org. 2004, Notification on Final Regulation for Terms and Conditions for Electricity Tariff for the five year period beginning April 2004. L-25(5)/2003, Central Electricity Regulatory Commission, New Delhi. On line at – www.cercind.org, 2001, Notification on ‘Terms and conditions of Tariff. L-25(1)/2001CERC, Central Electricity Regulatory Commission, New Delhi. Part II & Part III of Electricity Act 2003. Government of India. Tong Wu, Member, IEEE, Mark Rothleder, Member, IEEE, Ziad Alaywan, Member, IEEE, and Alex D. Papalexopoulos, Fellow, 2004. Pricing Energy and Ancillary Services in Integrated Market Systems by an Optimal Power Flow. IEEE Transactions on Power Systems, 19, 1. Web: http://www.kalkitech.com. ‘Introduction to Availability Based Tariff.’ A White Paper, Revision 1.0, Version 1.0.Kalki Communication Technologies Private Limited #147,2nd Floor,5th Main Road, Sector 7,HSR Layout Bangalore, Karnataka, India.

Pricing Model for Hydroelectric Generating Stations Under Deregulated Power Market

51

10. Xiaohong Guan,Senior, Feng Gao, and Alva J.Savobada, 2000, Energy Delivery Capacity and Generation scheduling in the Deregulated Electric Power Market, IEEE Transactions on Power Systems,15, 4, 1275–1280. 11. Yog Rj Sood, Narayana Prasad Padhy and Hari Om Gupta, 2004, Assessment for feasibility and pricing of wheeling transactions under deregulated environment of power industry, International Journal of Electrical Power &Energy Systems, 26,3 ,163-171.