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This thesis presents a new fuzzy linear programming (FLP)
approach to determine the multiobjective power dispatch problem
where the objectives of minimum fuel cost and minimum environ-
mental impact of nitrogen oxides (NOx) emission are considered.
The FLP technique first optimizes each objective separately to
obtain respective minimum attainable cost and emission and the
corresponding maximum values of the other objective. Through
these minimum and maximum objective values, the utility member-
ship function of desired fuel cost and emission are defined.
Based on the Max-Min operator and the utility functions
defined, the set of non-inferior solutions are extracted. A
preference index of distance (PID) is then used to find the
tentative best compromise solution. To further offer the best
compromise solutions out of the tentative ones, the calcu-
lated marginal rate of substitution (MRS) values are employed
to aid the power system operator to adjust the generation
levels in a most economic manner but also with minimal impact
on the environments. If the final solutions are not
satisfactory to the operators, the operator can adjust the
distance parameter in the PID to the problem again until the
results are satisfactory. So, the proposed method is the one of
interactive satisfying method for solving the multiobjective
power dispatch problem. The effectiveness of the proposed
approach has been demons- trated on a 10-bus, 5-generator
system and the IEEE 30-bus, 6- generator system. Numerical
results reveal that the FLP is a promising and efficient
approach for dealing with the multi- objective nature of power
dispatch problem.
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