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Short-Range Fixed-Head Hydrothermal Generation Scheduling Using Various Optimization Algorithm

This document discusses short-range fixed-head hydrothermal generation scheduling using various optimization algorithms. Hydrothermal generation scheduling is an important optimization task in power system operation that involves nonlinear objective functions and constraints. Traditional optimization methods have limitations for solving these complex problems. Heuristic search methods like the novel Team Game Algorithm (TGA), which is based on team game strategies, are often used instead to overcome the shortcomings of traditional methods. The proposed algorithm would be applied to problems like generation scheduling, load flow studies, and load dispatch.

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kumar vicki
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56 views1 page

Short-Range Fixed-Head Hydrothermal Generation Scheduling Using Various Optimization Algorithm

This document discusses short-range fixed-head hydrothermal generation scheduling using various optimization algorithms. Hydrothermal generation scheduling is an important optimization task in power system operation that involves nonlinear objective functions and constraints. Traditional optimization methods have limitations for solving these complex problems. Heuristic search methods like the novel Team Game Algorithm (TGA), which is based on team game strategies, are often used instead to overcome the shortcomings of traditional methods. The proposed algorithm would be applied to problems like generation scheduling, load flow studies, and load dispatch.

Uploaded by

kumar vicki
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
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Short-range Fixed-head Hydrothermal Generation Scheduling using Various

Optimization Algorithm
Kumar Dayanidhi, kumardayanidhi39@gmail.com, 8608695780

In the electric power supply system, there exists a wide range of problems involving
optimization processes. Among them, hydrothermal generation scheduling is an important
optimization task in power system operation. Optimization methods are classified based on the
type of search space and the objective function along with equality and inequality constraints. In
general, the objective function or constraints or both contains nonlinearity giving rise to
nonlinear problem. The optimal scheduling of hydrothermal power system is basically a complex
programming problem involving nonlinear objective function and a mixture of linear and
nonlinear constraints. The objective of hydrothermal scheduling is to generate the power
economically by using water to its full extent, whereas satisfying various constraints. The
equality constraints include generation-demand balance and balance of available volume-water
discharge. The inequality constraints include generation limit on thermal and hydro power unit,
limit on water discharge rate and reservoir storage level limit. The hydrothermal scheduling
problem is broadly classified as convex and non-convex optimization problem. In convex
hydrothermal scheduling problem, the input–output characteristics are assumed piecewise linear
and monotonically increasing, optimization algorithms that are based on mathematical
programming can be applied. Several conventional methods have been used in hydrothermal
scheduling. But none can claim to be the best problem-solving tool because each technique has
its own limitations, advantages and disadvantages. For example: Traditional methods are only
applicable for the problems which have continuous differentiable objective function. The tuning
of genetic algorithm parameters in complex search spaces is difficult. Premature convergence of
genetic algorithm reduces its performance and search capability an evolutionary computation
technique, known as particle swarm optimization, has become a candidate for many optimization
applications due to its high performance and flexibility but is not self-adaptive.
Generally, heuristic search methods are used as tool for the solution of complex optimization
problems because of their strength to overcome the shortcomings of the traditional optimization
methods. Out of many heuristic search methods one of them is Team Game Algorithm (TGA). It
is a novel meta-heuristic optimization algorithm based on team game strategies involving
football, volleyball, basketball, water polo and so on. In this algorithm, agents are players and
their performance is measured by their stamina. The proposed algorithm would be applied on
generation scheduling problem, load flow study, load dispatch.

Software used - FORTRAN high level language

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