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Transmission Expansion Planning in Deregulated Power ... - tuprints

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2 <strong>Transmission</strong> <strong>Expansion</strong> <strong>Plann<strong>in</strong>g</strong> Approaches 7<br />

M<strong>in</strong> E<br />

k<br />

with:<br />

k<br />

∑<br />

= l<br />

l k , l<br />

υ f<br />

(2.1)<br />

k<br />

E expected cost of plan k<br />

l<br />

υ occurrence degree of scenario l<br />

f<br />

k l<br />

, cost of plan k <strong>in</strong> scenario l<br />

2. M<strong>in</strong>imax regret criterion (risk analysis): <strong>in</strong> risk analysis the best solution is<br />

determ<strong>in</strong>ed by m<strong>in</strong>imiz<strong>in</strong>g the regret [14]-[22]. Regret is a measure of risk.<br />

Regret of plan k <strong>in</strong> scenario l is def<strong>in</strong>ed as difference between the cost of plan k <strong>in</strong><br />

scenario l and cost of the optimal plan of scenario l, i.e.:<br />

r<br />

k,<br />

l k , l op,<br />

l<br />

= f − f<br />

(2.2)<br />

with:<br />

k l<br />

r , regret of plan k <strong>in</strong> scenario l<br />

f<br />

op l<br />

, cost of the optimal plan of scenario l<br />

In risk analysis the plan that m<strong>in</strong>imizes the maximum weighted regret over all<br />

future scenarios is selected as the f<strong>in</strong>al plan, i.e.:<br />

M<strong>in</strong><br />

k<br />

l k , l { Max(<br />

r ) }<br />

l<br />

υ (2.3)<br />

3. Laplace criterion: accord<strong>in</strong>g to this criterion the plan that m<strong>in</strong>imizes the sum of<br />

costs over all scenarios is selected as the f<strong>in</strong>al plan [14].<br />

4. Von Neumann-Morgenstern criterion: this criterion is extremely pessimist and<br />

believes that the most unfavorable scenario is bound to occur [14]. Accord<strong>in</strong>g to<br />

this criterion the plan that m<strong>in</strong>imizes the maximum cost over all scenarios is<br />

selected as the f<strong>in</strong>al plan, i.e.:<br />

M<strong>in</strong><br />

k<br />

k , l { Max(<br />

f ) }<br />

l<br />

(2.4)<br />

Alternatively, an extremely optimist criterion can be also used for select<strong>in</strong>g the<br />

f<strong>in</strong>al plan, i.e.:<br />

M<strong>in</strong><br />

k<br />

k , l { M<strong>in</strong>(<br />

f ) }<br />

l<br />

(2.5)

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