FORECASTING OF FUEL COST FOR ENVIRONMENT FRIENDLY POWER GENERATION IN THERMAL POWER STATION Samir Chandra Das 1*, Tamal Sarkar 2 and Tanay Chottopadhyay3 1,2 University Science Instrumentation Centre University of North Bengal, Siliguri, Darjeeling-734013, W.B., India 3 Kolaghat Thermal Power Station, WBPDCL, Mecheda- 721137, W.B., India

Introduction:

India being a large country having different geographical location and underground resources have Power Plants using different sources such as oil fired, coal fired, gas fired, Nuclear Reaction driven and hydro plant [5] with shares as mentioned in Table 1(a) and Table 1(b) (in Appendix-1) . Out of all type of power plant, coal driven i.e. thermal power plant has largest share. Since coal is available and its availability is more compare to oil and gas. Power plants in India uses coals from a variety of sources especially those located near sea shores even uses coal from different countries like Russia, China and Indonesia. As per standard Fuel analysis, the coal and oil that these power plants buys from different countries have different qualities. For example, some coals are environing coal whereas some coal needs blending. Though thermal power plant near sea shores has option to purchase coal and crude oil from different countries but faces the following problem as mentioned below. Most of the thermal power plants near sea shores are situated near a metropolitan city. They have to be very careful about pollution [1]. They got less area under their project and proper utilization of land is highly important for them. As they use different types of sources for producing power, each unit have got different efficiency. Further, the efficiency is coupled. If one unit runs for full capacity than other unit has to be run under low load. It has a losing point in terms of cost. If we run a 500 MW unit at low load for long time, then, we are going to face a huge loss in terms of efficiency. The task in our hand is to fix in which way one has to go so as to make optimum profit in long term. One solution to above problem in this regard is to switch from Coal to gas and hydro power plant but total depends on them is not possible due to non-availability of sources and high initial cost behind set up of such plant. Thermal Power Plant: Different Head Associated with Generation: The important head which are associated with Power Generation can be categories as given below:• • • • • •

Fuel Water and Chemical Treatment Auxiliary Energy Pollution Control Operation and Maintenance Insurance

* Further author information: (Corresponding author Samir Chandra Das, USIC, NBU) E-mail: [email protected], Fax: +91-353-2699283 E-mail: [email protected], Fax: +91-353-2699001

Fuel Cost

Water Cost

Insurance Cost

Net Cost of Generation

Environmental Cost

Auxiliary Energy Cost O & M Cost Fig. 1: Net Cost of generation

Out of them, the most important cost is fuel costs as other cost are very small in comparison to fuel cost. Important Constraints Associated with Fuel Cost: To understand the role of constraint, let us take a simple situation in which we have no constraint i.e. we can select by our own the Availability of fuel, load, demand etc. In that case, the most common way is to run the plant’s unit to its optimum value so that the efficiency is maximize. In rainy season, coal has maximum water content so during that season oil driven, hydro- electric driven and gas driven units will give better performance compare to coal driven units. In such a case, we would not need a method to optimize the cost of fuel. Only, the above mentioned technique would reduce the cost of fuel for generation of a unit of power. Now, we are considering the constraint that exist in a power plant that have to be considered for designing an objective function that gives the cost of fuel. The constraints are: 1. Availability of fuel 2. Generation Balance 3. Minimum Demand that is necessary to make a plant running 4. Maximum Demand that a plant has capability to supply 5. Capacity Balance 6. Auxiliary Electrical energy balance 7. Thermal balance 8. Boolean Constraints: ESP(Incase of Coal driven plant), FGD (Incase of Gas driven plant)

Important Physical Quantities Associated with Constraint: To begin with this topic, we have to understand the general structure or model of a thermal power plant. To a pure science student a power plant is a big experimental lab where a student will find most of the physical parameter that he has studied in book but never done experiment. It is a place where a physics student must work to see how their theoretical study of physical science is applied into reality. To name a few, here a learner will find real use of Modified Rankine Cycle, A.C. Motor, Generator, Turbine, AC Machine, DC Machine, Water Treatment Plant, Dam, Different Types of Pump, Furnace, Draft Fan, Electrostatic Precipitator, Coal Mill, different types of barometer, vacuum gauge, lubrication system, boiler, Sensor and

automated Control system, Process of cooling using hydrogen, condenser, de-aerator etc [2, 3]. There are many physical quantities which are associated with each of them but out of them we will considered only those quantities which significantly affect the cost of fuel for power generation. They are a given below. Physical Quantities and other factor associated with different constraint and objective function:• • •

• • • • • • • • •

Heat contribution of fuel-N, Calorific Value of fuel-Cv, Kcal/Kg Heat rate of plant-H Power generation of plant and a unit-G Cost of a fuel-C, INR/Metric Ton Cost of fuel for power generation-Z Weight of fuel available for power generation-W Operating hours per Kwh-Oh Total calendar hours of availability of a unit-Ch Planned shut down hours of a unit during planning horizon-Sd Auxiliary energy consumed –Ag Fractional availability of unit- Fa

Mathematical Modeling for Forecasting of Fuel Cost: To design a mathematical model using the physical quantities described above, we are using the following indices •

• •

k to indicate a period of time i to indicate type of fuel used (Figure 2) j to indicate the Unit (Figure 3)

#1

#2

#3

#4

Coal Grad 1

Coal Grad2

Oil Grad 1

Oil Grad 2

Fig. 2: Power Plant

UNIT#1 (MW)

UNIT#2 (MW)

UNIT#3 (MW)

UNIT#4 (MW)

Fig. 3: Fuel

Month

Jan

Feb

Mar

April

May

June

July

Aug

Code for k

1

2

3

4

5

6

7

8

Sep 9

Oct 10

Nov

Dec

11

12

With above coal convention of indices and symbol for physical quantity, we can say

Cik = Cost of i th fuel in k th period of time, INR/MT N ik = Heat contribution of i th fuel in k th period of time, % Cvik = Calorific Value of i th in k th period of time, Kcal/Kg Gk = Generation of plant in k th period of time, MU H k = Heat Rate of Plant in k th period of time, Kcal/KW-Hr (targeted) Z k = Cost of fuel for power generation in k th period of time, INR G jk = Generation in k th period of time from j th unit, MU The required objective function which ought to be minimize is n

Z k = C * ￥(Cik * N ik / Cvik )* Gk * H k i =1

Subject to following constraints: Availability of fuel: C *( N ik * Gk * H k ) / Cvik ﾣW max ik , Where C=0.1 4

Generation balance: Gk = ￥G jk j =1

Minimum demand: Gk ﾣG min k Maximum demand: Gk ﾣG max k Capacity balance:

G jk * Oh jk ﾣ(Ch j − Sd j ) * Fa j

Auxiliary electrical energy balance: Ag k ﾣGk Derived Environmental constraints: ESP#j Not available: G jk ﾣGWesp max jk , Maximum generation allowed without ESP (This depends upon stack height and maximum limit of S.P.M & NOx allowed.) FGD#j Not available: G jk ﾣGWfgd max jk , Maximum generation allowed without FGD Conclusions: The forecasting technique describe above is highly depended on the data of operations of similar unit that is already exits in monitoring cell of a power plant. What one has to do is to feed the previous data and check whether the objective function is giving the expected result. Once, we get the expected result, we are in a position to determine the fuel cost per unit by dividing Z by G. At last, the paper describes a very simple method of finding the fuel amount as well as cost which could easily be understood by management executive who don’t have engineering background. We hope that using the optimization technique proposed by us it is possible to generate environment friendly power in thermal power plant. References:

[1]Wood Bill, Loyer Joseph, Miller Ross , Klein Joel , Power plant, fuel cost, air pollutant emission, and O& M cost characteristics, California Energy Commission, 1998. [2]Khurmi R.C, Gupta J.K, A TextBook of Thermal Engineering, S. Chand & Company Ltd., 2000 [3]NPTI, Thermal Power Plant Familiarization, Vol. IV Generator & Electrical Plants, 2001 [4]Wentzel E.S. (Translated from the Russian by Michael G. Edelev), Operations Research A Methodological Approach, MIR Publishers, 1988 [5]Ministry of Power, Annual Reports, Government of India

Appendix 1: Table 1(a): Power Sector Performance at a Glance Ownership and Mode-wise Pattern of Installed Capacity (MW) as on 31.03.2002 Ownership /Mode State Central Private Total % of Installed Capacity

Hydel

Steam

Gas

Diesel

Wind

Nuclear

22636.02 3049.00 576.20 26261.22 25.03

36302.00 21417.51 4411.38 62130.89 59.22

2661.70 4419.00 4082.40 11163.10 10.64

582.89 0.00 551.94 1134.83 1.08

62.86 0.00 1444.60 1507.46 1.44

0.00 2720.00 0.00 2720.00 2.59

Total 62245.47 31605.51 11066.52 104917.50 100.00

Table 1(b): Power Sector Performance at a Glance Ownership and Mode-wise Pattern of Installed Capacity (MW) as on 31.03.2001 Ownership /Mode State Central Private Total % of Installed Capacity

Hydel

Steam

Gas

22020.78 2644.00 477.00 25141.78 24.73

35817.00 20917.50 4291.38 61025.88 60.03

2428.00 4449.00 3614.90 10491.90 10.32

Diesel 539.69 0.00 331.20 870.89 0.86

Wind 57.46 0.00 1212.17 1269.63 1.25

Nuclear 0.00 2860.00 0.00 2860.00 2.81

Total 60862.93 30870.50 9926.65 101660.08 100.00