OPTIMAL VOLTAGE REGULATOR PLACEMENT IN A RADIAL DISTRIBUTION SYSTEM USING FUZZY LOGIC

OPTIMAL VOLTAGE REGULATOR PLACEMENT IN A RADIAL DISTRIBUTION SYSTEM USING FUZZY LOGIC

Abstract:

The operation and planning studies of a distribution system require a steady state condition of the system for various load demands. Our aim is to obtain optimal voltage control with voltage regulators and then to decrease the total cost of voltage regulators and losses, to obtain the net saving. An algorithm is proposed which determines the initial selection and tap setting of the voltage regulators to provide a smooth voltage profile along the network. The same algorithm is used to obtain the minimum number of the initially selected voltage regulators, by moving them in such a way so as to control the network voltage at the minimum cost. The algorithm has been implemented using MATLAB along with Fuzzy Logic and the result of both conventional and Fuzzy Logic are compared.

Introduction:

General description of Distribution System

Distribution system is that part of the electric power system which connects the high voltage transmission network to the low voltage consumer service point
In any distribution system the power is distributed to various uses through feeders, distributors and service mains. Feeders are conductors of large current carrying capacity which carry the current in bulk to the feeding points. Distributors are conductors from which the current is tapped of from the supply to the consumer premises. A typical distribution system with all its elements is shown in figure
Diagram Of A Distribution System
Diagram Of A Distribution System 
Factors Effecting Distribution System Losses
Factors contributing to the increase in the line losses in primary and secondary distribution system are:
1. Inadequate size of conductor:
2. Feeder Length:
3. Location of Distribution Transformers:
4. Low Voltage:
5. Low Power Factor:

FUZZY LOGIC

Fuzzy logic, invented by Professor Lotfi Zadeh of UC-Berkeley in the mid 1960s, provides a representation scheme and a calculus for dealing with vague or uncertain concepts. It provides a mathematical way to represent vagueness in humanistic systems. The crisp set is defined in such a way as to dichotomize the individuals in some given universe of discourse into two groups as below:
a) Members (those who certainly belong to the set.)
b) Non-members (those who certainly do not belong to the set.)

Fuzzy Logic in Power Systems

Analytical approaches have been used over the years for many power system operation, planning and control problems. However, the mathematical formulations of real world problems are derived under certain restrictive assumptions and even with these assumptions, the solutions of large – scale power systems problems are not trivial. On the other hand, there are many uncertainties in various power system problems because power systems are large, complex, geographically widely distributed systems and influenced by unexpected events.
More recently, the deregulation of power utilities has introduced new issues into the existing problems. These facts make it difficult to effectively deal with many power systems problems through strict mathematical formulations alone. Although a large number of AI techniques have been employed in power systems, fuzzy logic is a powerful tool in meeting challenging problems in power systems. This is so because fuzzy logic is the only technique, which can handle in precise, vague or ‘fuzzy’ information.

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