Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques

To extract the maximum potential advantages in light of environmental, economical and technical aspects, the optimum installation and sizing of Distributed Generation (DG) in distribution network has always been challenging for utilities as well as customers. The installation of DG would be of maximum benefit where setting up of central power generating units are not practical, or in remote and small areas where the installation of transmission lines or availability of unused land is out of question. The objective of optimal installation of DG in distribution system is to achieve proper operation of distribution networks with minimization of the system losses, improvement of the voltage profile, enhanced system reliability, stability and loadability etc. In this respect analytical (classical) methods, although well-matched for small systems, perform adversely for large and complex objective functions. Unlike the analytical (classical) methods, the intelligent techniques for optimal sizing and siting of DGs are speedy, possess good convergence characteristics, and are well suited for large and complex systems. However, to find a global optimal solution of complex multi-objective problems, a hybrid of two or more meta-heuristic optimization techniques give more effective and reliable solution. This paper presents the fundamentals of DG and DG technologies review the classical and heuristic approaches for optimal sizing and placement of DG units in distribution networks and study their impacts on utilities and customers. An attempt has also been made to compare the analytical (classical) and meta-heuristic techniques for optimal sizing and siting of DG in distribution networks. The present study can contribute meaningful knowledge and assist as a reference for investigators and utility engineers on issues to be considered for optimal sizing and siting of DG units in distribution systems.

Optimal sizing and siting techniques for distributed generation in distribution systems: A review

A new meta-heuristic optimizer: Pathfinder algorithm

Distributed generation can be defined as power generation by small scale generating units that are installed at distribution systems. The penetration of distributed generation (DG) units in electric distribution systems is continually increasing. The process of finding optimal type, location and size of DG units is called “DG allocation”. DG allocation is a hot area of research and represents a difficult problem in electrical power engineering. In this paper, the existing research works on DG allocation problem are reviewed from viewpoint of their used optimisation algorithms, objectives, decision variables, DG type, applied constraints and kind of uncertainty modelling. Based on the review of existing research works, the research gaps are identified and some helpful recommendations for future research on DG allocation will be provided. The author strongly believes that this paper can be helpful for researchers and engineers in the related field.

Allocation of distributed generation units in electric power systems: A review

State-of-the-art techniques for modelling of uncertainties in active distribution network planning: A review

Optimal location and sizing determination of Distributed Generation and DSTATCOM using Particle Swarm Optimization algorithm

Optimal location and sizing of Distribution Static Synchronous Series Compensator using Particle Swarm Optimization

This paper proposes the optimal location of Thyristor Controlled Series Capacitor TCSC to reduce the active power loss in radial distribution system using Particle Swarm Optimization PSO algorithm. Also in this work, reactance characteristics curve of a TCSC device is drawn between effective reactance of TCSC XTCSC and firing angle 'α' from the optimal output obtained from the PSO algorithm. This gives the effective value of the firing angle 'α' and the main parameters of TCSC such as XC and XL are also designed. This analysis is done by degree of series compensation 'k'. The feasibility and effectiveness of the optimization methods proposed have been demonstrated on 12, 34 and 69 bus radial distribution system consisting of 11, 33 and 68 sections respectively. MATLAB, Version 7.10 software is used for simulation.

S. Devi

Papers

Optimal location and sizing determination of Distributed Generation and DSTATCOM using Particle Swarm Optimization algorithm

Optimal location and sizing of Distribution Static Synchronous Series Compensator using Particle Swarm Optimization

Optimal Location and Parameter Selection of Thyristor Controlled Series Capacitor Using Particle Swarm Optimization