Generation Capacity Expansion Planning in Deregulated Electricity ...

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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 linear programming (MILP)

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

designed for financial analysis for a firm willing to invest in discrete sized generation units with three

options of technologies. In the base case the optimal value of IRR is determined 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 functioning of the proposed model.

• Gas-based = 100 MW

• Coal-based = 300 MW

• Combine-cycle plants = 200 MW

The assumptions pertaining to electricity market prices remain the same, as discussed in Chapter-2,

Section-2.3.1, Table II. The firm’s budget constraint 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 increased, as compared that used in Chapter-2. This increase of budget was necessary

because of the discrete nature of unit sizes which are added, and the minimum unit size considered

being 100 MW.

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