10-04-2017, 08:59 PM
DG Allocation Using an Analytical Method to Minimize Losses and to Improve Voltage Security
Abstract
This paper proposes an analytical method for
optimal allocation and sizing of Distributed Generation
(DG) units in order to minimize losses and to improve the
voltage profile in distribution systems. The evaluation of
losses and voltage profile is based on a power flow method
for radial networks. The approach, which is based on the
calculation of losses sensitivity factor, has been applied to
IEE 13 and 37 bus distribution test systems. The proposed
method has better results than the results obtained from
other methods.
Keywords Distributed Generation, losses minimization,
Optimum Allocation, Sensitivity factors, Voltage Security
Improvement.
I. INTRODUCTION
The share of Distributed Generators (DGs) in power
systems has been slowly increasing in the last few years.
Electric Power Research Institute s (EPRI) study
forecasts that 25% of the new generation will be
Distributed by 2010 and a similar study by the Natural
Gas Foundation believes that the share of DG in new
generation will be 30% by the year 2010 [1]. Studies have
indicated that inappropriate selection of location and size
of DG, may lead to greater system losses than the losses
without DG. Utilities already facing the problem of high
power losses and poor voltage profile. Especially, the
developing countries cannot tolerate any increase in
losses. By optimum allocation, utilities take advantage of
reduction in system losses; improve voltage regulation
and improvement in reliability of supply [2]. The
planning of the electric distribution system, considering
the presence of Distributed Generation (DG), requires the
definition of several factors. The most important factors
are the number and the capacity of the units, the
installation location, the type of network connection and
etc. The most important indices are electric losses,
voltage profile, stability and reliability. These DG sources
are normally placed close to consumption centers and
they are relatively small in size and modular in structure.
The effect of adding a DG on network security will vary
depending on its type and position. It is supposed that one
or more sites on a given network may be optimal. Several
methods have been proposed to address the viability of
DGs in power system. An approach for optimal design of
grid connected DG systems in relation to its size and type
to satisfy on-site reliability and environmental
requirements, is presented in [3]. An optimization
approach using GA for minimizing the cost of network
investment and losses for a defined planning horizon is
presented in [4]. GA has been used to obtain penetration
level of DG and to minimize the total cost of operation
including fixed and variable cost [5]. The method for
optimal placement of DG to minimize real power losses
in power distribution system using GA is proposed in [6].
The gradient and second order methods, to determine the
optimal location and losses is employed in [7]. An
iterative method that provides an approximation for the
optimal placement of DG for loss minimization is
demonstrated in [8]. Analytical methods for determining
optimal location of DG with the aim of minimizing power
losses are proposed in [9]. Placement and penetration of
distributed generation under LMP based standard market
design with the objective of generation cost minimization
is proposed in [10]. Present study finds the best
placement of DG by proposed method which is based on
the analytical approaches [11-12]. In this paper an
analytical approach which is based on sensitivity factors
is presented. This new approach minimizes the electrical
network losses and improves the voltage security.
Simulation results show that the proposed method can
result in a better design. The paper is organized as
follows: Section 2 explain the loss sensitivity factor
method and its algorithm. Section 3 introduces the
proposed method. Test systems and Analytical tools are
presented in section 4. Section 5 is the simulation results.
The comparison of results is presented in section 6 and
section 7.
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