DG-Embedded Radial Distribution System Planning Using Binary-Selective PSO

TL;DR

This paper introduces a novel Binary-Selective PSO method for optimizing distribution system planning, including conductor sizing, DG placement, and capacitor sizing, considering economic factors and renewable integration.

Contribution

It presents a new PSO algorithm capable of handling mixed variable types for comprehensive distribution system planning optimization.

Findings

Effective in minimizing system costs

Successfully applied to a 26-bus system

Handles continuous, binary, and selective variables simultaneously

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.