There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

This paper presents a new method to solve the network reconfiguration problem in the presence of distributed generation (DG) with an objective of minimizing real power loss and improving voltage profile in distribution system. A meta heuristic Harmony Search Algorithm (HSA) is used to simultaneously reconfigure and identify the optimal locations for installation of DG units in a distribution network. Sensitivity analysis is used to identify optimal location s for installation of DG units. Different scenarios of DG placement and reconfiguration of network are considered to study the performance of the proposed method. The constraints of voltage and branch current carrying capacity are included in the evaluation of the objective function. The method has been tested on 33-bus and 69-bus radial distribution systems at three different load levels to demonstrate the performance and effectiveness of the proposed method. The results obtained are encouraging.

Power Loss Minimization in Distribution System Using Network Reconfiguration in the Presence of Distributed Generation

Optimal reactive power dispatch problem in power systems has thrown a growing influence on secure and economical operation of power systems. However, this issue is well known as a nonlinear, multimodal and mixed-variable problem. In the last decades, computation intelligence-based techniques, such as genetic algorithms (GAs), differential evolution (DE) algorithms and particle swarm optimization (PSO) algorithms, etc., have often been used for this aim. In this work, a seeker optimization algorithm (SOA)-based reactive power dispatch method is proposed. The SOA is based on the concept of simulating the act of human searching, where the search direction is based on the empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple Fuzzy rule. In this study, the algorithm's performance is evaluated on benchmark function optimization. Then, the SOA is applied to optimal reactive power dispatch on standard IEEE 57- and 118-bus power systems, and compared with conventional nonlinear programming method, two versions of GAs, three versions of DE algorithms and four versions of PSO algorithms. The simulation results show that the proposed approach is superior to the other listed algorithms and can be efficiently used for optimal reactive power dispatch.

Seeker Optimization Algorithm for Optimal Reactive Power Dispatch

http://ardeshir20.persiangig.com/document/noandishaan/azar/alex1.pdf

Optimal dynamic economic dispatch of generation: A review

Optimal capacitor placement in a radial distribution system using Plant Growth Simulation Algorithm

This paper presents a novel approach that determines the optimal location and size of capacitors on radial distribution systems to improve voltage profile and reduce the active power loss. Capacitor placement & sizing are done by loss sensitivity factors and particle swarm optimization respectively. The concept of loss sensitivity factors and can be considered as the new contribution in the area of distribution systems. Loss sensitivity factors offer the important information about the sequence of potential nodes for capacitor placement. These factors are determined using single base case load flow study. particle swarm optimization is well applied and found to be very effective in radial distribution systems. The proposed method is tested on 10,15, 34, 69 and 85 bus distribution systems.

Particle Swarm Optimization Based Capacitor Placement on Radial Distribution Systems

Multi-Objective Invasive Weed Optimization – An application to optimal network reconfiguration in radial distribution systems

Congestion management is one of the technical challenges in power system deregulation. This paper presents single objective and multi-objective optimization approaches for optimal choice, location and size of Static Var Compensators (SVC) and Thyristor Controlled Series Capacitors (TCSC) in deregulated power system to improve branch loading (minimize congestion), improve voltage stability and reduce line losses. Though FACTS controllers offer many advantages, their installation cost is very high. Hence Independent System Operator (ISO) has to locate them optimally to satisfy a desired objective. Genetic Algorithms (GA) are best suitable for solution of combinatorial optimization and multi-objective optimization problems. This paper presents optimal location of FACTS controllers considering branch loading (BL), voltage stability (VS) and loss minimization (LM) as objectives at once using GA. It is observed that the locations that are most favorable with respect to one objective are not suitable locations with respect to other two objectives. Later these competing objectives are optimized simultaneously considering two and three objectives at a time using multi-objective Strength Pareto Evolutionary Algorithms (SPEA). The developed algorithms are tested on IEEE 30 bus system. Various cases like i) uniform line loading ii) line outage iii) bilateral and multilateral transactions between source and sink nodes have been considered to create congestion in the system. The developed algorithms show effective locations for all the cases considered for both single and multi-objective optimization studies.

Congestion management in deregulated power system by optimal choice and allocation of FACTS controllers using multi-objective genetic algorithm

This paper discusses the modeling of nonlinear electrical loads used in domestic and small scale industrial distribution systems Harmonic analysis of the distribution system is essential to study the behavior of equipments connected in the non-sinusoidal system environment for designing and optimal location of filters Simulation models are developed for various nonlinear loads based on practical waveforms of voltage and current obtained in the laboratory Analysis of voltage and current harmonics is performed for these loads individually These models are used for harmonic analysis of typical domestic and industrial loads THD is used as the harmonic index to study the effect of these nonlinear loads at the utility Validation of the load models is done by performing case study for an industrial supply system and comparing the THDs obtained from simulation using PSCAD/EMTDC package with the THD values obtained by measurement

Maheswarapu Sydulu

Papers

Particle Swarm Optimization Based Capacitor Placement on Radial Distribution Systems

Multi-Objective Invasive Weed Optimization – An application to optimal network reconfiguration in radial distribution systems

Congestion management in deregulated power system by optimal choice and allocation of FACTS controllers using multi-objective genetic algorithm

Modelling of Nonlinear Loads and Estimation of Harmonics in Industrial Distribution System

Unit Commitment by improved pre-prepared power demand table and Muller method