Generation Capacity Expansion Planning in Deregulated Electricity ...

5i

∑

k=

5i−4

Ac

( k)

≤ Bd(

i)

∀ i = 1,

2 & 3

i Index for a plan sub-period

Bd(i) Total available budget over a plan sub-period

3.3 Case Study

3.3.1 System Data

The mathematical model discussed **in** Section-3.2 is a Mixed-Integer l**in**ear programm**in**g (MILP)

model which is programmed **in** the GAMS [19] environment. As discussed earlier, this model is

designed for f**in**ancial analysis for a firm will**in**g to **in**vest **in** discrete sized generation units with three

options of technologies. In the base case the optimal value of IRR is determ**in**ed while the objective

function is maximization of the present value of total profits. Data used **in** the base case scenario has

been given **in** Chapter-2, Table I. The discrete unit sizes considered **in** this chapter is chosen

arbitrarily, without any loss of generality, to demonstrate the function**in**g of the proposed model.

• Gas-based = 100 MW

• Coal-based = 300 MW

• Comb**in**e-cycle plants = 200 MW

The assumptions perta**in****in**g to electricity market prices rema**in** the same, as discussed **in** Chapter-2,

Section-2.3.1, Table II. The firm’s budget constra**in**t is applied every sub-period **in** order to arrive at a

risk averse plan. The budgetary allocations of the firm over different plan sub-periods are given **in**

Table VIII. The justifications with regard to the budgetary allocations were discussed **in** Chapter-2.

It should be noted that **in** this chapter, the firm’s budget available over a given sub-period has been

significantly **in**creased, as compared that used **in** Chapter-2. This **in**crease of budget was necessary

because of the discrete nature of unit sizes which are added, and the m**in**imum unit size considered

be**in**g 100 MW.

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