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2.2.2.4 Economic Load Dispatch without Transmission Losses
Suppose there is a station with n generators committed and the active power load P_(D )is given, the real power generation P_(g_i ) for each generator has to be allocated so as to minimize the total cost. Min F=∑_(i=1)^(N_g)▒〖f_i (P_(g_i ) ) 〗 (2.3)
2.2.2.5 Economic Load Dispatch with Transmission Losses
The transmission losses cannot be neglected particularly when long distance transmission of power is involved. While developing the ELD policy, transmission losses P_L are considered. Mathematically, the ELD optimization problem is defined as Min F=∑_(i=1)^(N_g)▒〖f_i (P_(g_i ) ) 〗
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P_L is calculated using B-coefficient b) Inequality Constraint : Inequality constraints for the generating unit can be given as follows: 〖〖〖 P〗_(g_i)^min≤P〗_(g_(i ) )≤P〗_(g_i)^max (2.8) P_(g_i)^min & P_(g_i)^max are output of the minimum & maximum operation of the generating unit i^th (in MW) 2.3 PREVIOUS APPOACHES 2.3.1 GENETIC ALGORITHM (GA) The GA [43] is basically an evolutionary algorithm developed by D. E. Goldberg in 1989, some of the other of its kind being evolution strategies, genetic programming, and EP. An evolutionary algorithm sustains a population of candidate solutions to an optimization problem. The population changes through repeated application of stochastic operators. GA considers the ELD problem as the environment where the living individuals are the feasible solutions. Finding globally acceptable solutions to the problem is analogous to adjusting to the surrounding by a natural habitat. Just as a new generation of a population is promoted by elimination of useless traits and by developing useful features, a new and better solution is found by iterative fine-tuning of fitness function. Generally, GA enters a loop with an initial population created with a set of individuals generated randomly. In each iteration (called “generation”), a fresh population is created applying a number of stochastic operators to the earlier

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