

Title of Thesis
Economic dispatch Using Hybrid Approaches 
Author(s)
Tahir Nadeem
Malik 
Institute/University/Department
Details Department of Electrical Engineering /
University of Engineering and Technology, Taxila 
Session 2009 
Subject Electrical Engineering 
Number of Pages 196 
Keywords (Extracted from title, table of contents and
abstract of thesis) Economic, dispatch, Hybrid,
Approaches, nonconvex, constrained, Newton’s, Raphson, algorithm 
Abstract Power Economic
Dispatch (ED) is necessary and vital step in power system
operational planning. It is nonconvex constrained optimization
problem defined as the process of calculating the generation of the
generating units for the minimum total production cost in such a way
that both equality and inequality constraints are satisfied. In
system operation studies generators are represented by inputoutput
curves. These characteristics curves are inherently nonlinear and
nonsmooth due to valve point effect, multiple fuels and operational
constraints such as prohibited operating zones. The accurate
economic dispatch depends mainly upon the accurate representation of
these curves and their handling in the optimization process.
Generally, economic dispatch is formulated as convex problem and has
been solved using mathematical programming techniques by
approximating generator input/output characteristic curves of
monotonically increasing nature thus resulting in an inaccurate
dispatch. However, the nonconvex ED problem cannot be handled
effectively by such approaches. The Genetic algorithm is the
potential solution methodology due to its inherent ability to
address the convex and nonconvex problems equally. This dissertation
presents the application of genetic algorithm (GA) for the solution
of economic dispatch problem independently as well as in hybrid form
in conjunction with the other techniques.
The problem is addressed first by developing a extensible and
flexible computational framework called “PED_Frame” as common
environment which becomes a platform for the computer implementation
of different algorithms under consideration. This framework has been
used for implementation of economic dispatch algorithms for (i) GA
based models, (ii) Hybrid models.
Economic dispatch problem has been formulated in binary coded
genetic algorithm environment based on real power search and λ
search methodologies. Two biological mechanism “inversion” and
“deletionregeneration” has also been mapped as an operator with
crossover probability. Various GA based evolution models have been
constructed by adopting different initial population generation
schemes, selection methods, and crossover operators. Convex ED
studies have been conducted using standard test systems and results
have been compared with λ iteration approach. GA based hybrid
approach for convex ED dispatch is proposed. This approach.
initially run GA based ED with λsearch and passes the control to
conventional λ iteration technique. This approach gives another
systematic method for selection of initial value of λ. The results
of the proposed approach on standard test system show that costs of
generation by this approach is almost the same as the λ iteration
alone, however, it takes less number of iterations.
The performance of GA based economic dispatch problem has been
evaluated with reference to different evolution models on the basis
of empirical data available by actually running the program for the
nonconvex ED due to valve point effect.
National utility system has been reviewed with reference to its
operation problems. Four test systems close to original network have
been developed and tested by load flow analysis using Newton’s
Raphson algorithm. Finally 12Machine 32 bus test circuit, 15, 25
and 34 Machines systems for economic dispatch studies have been
developed. ED studies have been conducted using test circuit.
The Genetic algorithm has the inherent ability to bring the solution
to the global minimum region of search space in a short time and
then takes longer time to converge to the solution. This research
work proposed hybrid approaches to fine tune the near optimal
results produced by GA. In this context, three hybrid approaches
have been used for the solution of nonconvex economic dispatch
problem with valve point effect. These include (i) A Synergy of GA
and ED using Newton’s Second Order Approach, (ii) NeuroGenetic
Hybrid Approach, and (iii) Hybrid of GA and Sequential Quadratic
Programming. These models have been tested on standard test systems
and the results obtained from all the three hybrid approaches offer
significant improvement in the generation cost showing the promise
of the proposed approaches.

