DG-Embedded Radial Distribution System Planning Using Binary-Selective PSO
📝 Abstract
With the increasing rate of power consumption, many new distribution systems need to be constructed to accommodate connecting the new consumers to the power grid. On the other hand, the increasing penetration of renewable distributed generation (DG) resources into the distribution systems and the necessity of optimally place them in the network can dramatically change the problem of distribution system planning and design. In this paper, the problem of optimal distribution system planning including conductor sizing, DG placement, alongside with placement and sizing of shunt capacitors is studied. A new Binary-Selective Particle Swarm Optimization (PSO) approach which is capable of handling all types of continuous, binary and selective variables, simultaneously, is proposed to solve the optimization problem of distribution system planning. The objective of the problem is to minimize the system costs. Load growth rate, cost of energy, cost of power, and inflation rate are all taken into account. The efficacy of the proposed method is tested on a 26-bus distribution system.
💡 Analysis
With the increasing rate of power consumption, many new distribution systems need to be constructed to accommodate connecting the new consumers to the power grid. On the other hand, the increasing penetration of renewable distributed generation (DG) resources into the distribution systems and the necessity of optimally place them in the network can dramatically change the problem of distribution system planning and design. In this paper, the problem of optimal distribution system planning including conductor sizing, DG placement, alongside with placement and sizing of shunt capacitors is studied. A new Binary-Selective Particle Swarm Optimization (PSO) approach which is capable of handling all types of continuous, binary and selective variables, simultaneously, is proposed to solve the optimization problem of distribution system planning. The objective of the problem is to minimize the system costs. Load growth rate, cost of energy, cost of power, and inflation rate are all taken into account. The efficacy of the proposed method is tested on a 26-bus distribution system.
📄 Content
DG-Embedded Radial Distribution System Planning Using Binary-Selective PSO
Ahvand Jalali University of Melbourne, Melbourne, Australia ajalali@student.unimelb.edu.au S K. Mohammadi Islamic Azad University, Boukan Branch, Iran s_kadkhoda63@yahoo.com H. Sangrody Binghamton University, New York, USA habdoll1@binghamton.edu A. Rahim-Zadegan Karlsruhe Institute of Technology, Karlsruhe, Germany aso.rahimzadegan@student.kit.edu
Abstract –With the increasing rate of power consumption, many new distribution systems need to be constructed to accommodate connecting the new consumers to the power grid. On the other hand, the increasing penetration of renewable distributed generation (DG) resources into the distribution systems and the necessity of optimally place them in the network can dramatically change the problem of distribution system planning and design. In this paper, the problem of optimal distribution system planning including conductor sizing, DG placement, alongside with placement and sizing of shunt capacitors is studied. A new Binary-Selective Particle Swarm Optimization (PSO) approach which is capable of handling all types of continuous, binary and selective variables, simultaneously, is proposed to solve the optimization problem of distribution system planning. The objective of the problem is to minimize the system costs. Load growth rate, cost of energy, cost of power, and inflation rate are all taken into account. The efficacy of the proposed method is tested on a 26-bus distribution system.
Index Terms- Distribution system planning, conductor sizing, capacitor placement, DG placement, binary-selective PSO.
I. INTRODUCTION
Distribution system, responsible for transferring electrical
energy to the end users, plays a determining role in the
power system economics. Operating at low voltages, and
high currents, it suffers from high power loss which is
considered as a continuous cost for the distribution system
and relates reversely with the size of the system conductors.
Besides, keeping the voltage profile and current flows of the
system in the acceptable operating range constrains the
problem of conductor sizing since the small conductors have
less current flow capability and also lead to more voltage
drops across the system. This necessitates an economic
viewpoint in selecting the system conductors. The problem
of conductor sizing is addressed in many papers using a
variety of methods including analytical [1], evolutionary [2,
3], and other creative approaches [4, 5]. The common
objective for this problem has been to minimize the system
costs which include loss cost and conductors cost.
Maintaining system’s voltages and currents within their
desired margins are also the prevalent restrictions for such
problem.
In addition, installing shunt capacitors is widely used for
power flow control, power factor correction, voltage profile
management and losses reduction [6]. Again, an optimal
placement and sizing of capacitors is necessary to make the
most of their capability. Shunt capacitor placement problem
has also been addressed in the literature using heuristic
approaches [7, 8], sensitivity analysis [8], fuzzy [9], etc.
With the increasing penetration of renewable DGs into
the power systems, optimal placement of DG units in the
distribution network is becoming more important [10]. DG
placement has been addressed in [11] for the purpose of
minimizing the consumer’s cost.
Supplying active and reactive loads locally, DGs and
capacitors alter the power flow of the system; hence, play the
same role as the supplementary conductors. Thus, both
problems of DG and capacitor sizing and placement are of
close correlation with the conductor sizing problem. If taking
into account all these problems simultaneously, more
desirable results, i.e. less investment cost and more loss
reduction, can be achieved.
Particle swarm optimization is proved to be one of the
most computation-efficient heuristic approaches. Ref. [12]
has shown that PSO, compared to GA and conventional
methods, has a better performance on capacitor placement
problem. Binary versions of the PSO has also been
developed [13, 18] which are of high advantages for solving
optimization problems such as DG and capacitor placement.
The combination of conductor sizing and capacitor
placement has been addressed in several references using
PSO [14], GA [15] and other creative methods [16]. In this
paper, a sub-problem of renewable DG placement is also
included in the problem. Furthermore, the multi-objective
optimization problem of conductor sizing is solved with the
weighting factors being assigned to the elements of the
objective function and meaningful conductor profiles are
obtained. A new PSO procedure is proposed which is
capable of choosing the variables from a selective space.
This is useful since the available cond
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