D. Sattianadan

Optimal Coordination of Directional Overcurrent Relays using Particle Swarm Optimization Technique

Abstract- The main function of the protective devices in the power system is to detect and remove the selected faulty parts as fast as possible. Directional over current relays are commonly used for the protection of interconnected sub transmission systems, distribution systems, or as a secondary protection of transmission systems. For the systems having more than one source connected, that is meshed or looped networks, directional over current relays become the suitable choice for better selectivity, since directional relays operate only when the fault current flows in the specific tripping direction desired. The most vital task when installing directional relays on the system is selecting their suitable current and time settings such that their fundamental protective functions are met under the requirements of sensitivity, selectivity, reliability and speed. The problem of setting Directional Over Current Relay(DOCR) is a highly constrained optimization problem that has been solved as a linear programming problem. The calculation of the time dial setting (TDS) and pick up current (IP) setting of the relays is the core of the coordination. This paper calculates the TDS by choosing one of the available pick up current settings as the predetermined value. The simplex two phase method is used to determine the optional TDS of the relays. Improvement in the solution is brought by using the particle swarm optimization technique to the co-ordination problem for reaching the global optimum value with less computational time. Sample 3 bus and 8 bus systems are utilized for comparing the results obtained by PSO with that of the simplex method. The optimization method used in the recent times minimizes the operating time of the relays much, when compared to the other methods. This method also enhances quicker solution of coordination process.

Optimal Placement of DG in Distribution System Using Genetic Algorithm

Power loss minimization is one of the important aspects in the distribution system..This paper deals with power loss minimization by the placement of distributed generators (DG) in the distribution system. The optimal location and sizing of DG for minimization of the power loss and cost of DG is found using GA. These two objectives power loss and cost are conflicting in nature. Moreover in such case only one compromised solution satisfying both objectives is obtained according to the choice of the decision maker. The Multi objective optimization algorithm (NSGA-II) is used to solve these two objectives to get a set of pareto optimal solutions. The simulation study is carried out on a 33 bus Distribution System for different load models.

Power loss minimization by the placement of DG in distribution system using GA

Power loss minimization is an important aspect of distribution System where the load variation is more compared to other systems. There are different methods to minimize the power loss like DG placement, capacitor placement, load balancing etc. Among those methods DG placement was much more beneficial because it is directly related to real power loss. This paper is based on power loss minimization by the placement of distributed generators (DG) in the distribution system. The location of DG is found with the help of voltage stability index (VSI) and DG size is varied in small steps and corresponding power loss is calculated by running the power flow and the result obtained is verified by Genetic Algorithm. The simulation study is carried out on a 33 bus Distribution System by considering different load models.

Maximum Loss Reduction and Voltage Profile Improvement with Placement of Hybrid Solar-Wind System

Distributed generators (DG) are much beneficial in reducing the losses effectively compared to other methods of loss reduction. It is expected to become more important in future generation. This paper deals with the multi DGs placement in radial distribution system to reduce the system power loss and improve the voltage profile by using the optimization technique of particle swarm optimization (PSO). The PSO provides a population-based search procedure in which individuals called particles change their positions with time. Initially, the algorithm randomly generates the particle positions representing the size and location of DG. The proposed PSO algorithm is used to determine optimal sizes and locations of multi-DGs. The objective function is the combination of real, reactive power loss and voltage profile with consideration of weights and impact indices with and without DG. Test results indicate that PSO method can obtain better results on loss reduction and voltage profile improvement than the simple heuristic search method on the IEEE33-bus and IEEE 90-bus radial distribution systems.

Optimal Operation Management of Transmission System with Fuel Cell Power Plant Using PSO

In this paper Particle Swarm Optimization PSO algorithm to solve the Optimal Operation Management OOM of transmission system is presented. The purpose of the OOM problem is to decrease the total electrical energy cost, real power losses in transmission system and the total pollutant emission produced by fuel cells. Fuel cell power plants FCPPs have been taken into a great deal of consideration in recent years. The continuing growth of the power demand together with environmental constraints is the great interest to use FCPPs in power system. One of the most important issues in the power system is optimal operation management which can be effected by FCPPs. The various objectives of OOM problem is solved as single and /or multi --- objective problem using PSO technique. Numerical results on IEEE 30 bus test system have been presented.

Optimum Allocation of Distributed Generation Based on Nodal Pricing for Profit and Social Welfare Maximization

This paper presents a method using nodal pricing for optimal allocating distribution generations (DG) for profit maximization, reduction of loss in distribution network along with social welfare maximization. Inclusion of distributed generation (DG) resources in power system changes the power flows and the magnitude of network losses at the distribution side. A detailed analysis has been simulated in MATLAB with 33 bus distribution system. The Genetic algorithm optimization is used in this work to find optimal location and size of DG in radial distribution system. Applying nodal pricing to a model distribution network, it shows significant price differences between buses reflecting high marginal losses and by finding optimal size of DG maximizes the profit of distribution companies that use DG in their networks for obtaining multiple benefits.

Reliability Improvement in a Radial Distribution System Using DG

Reliability analysis plays a very vital role in designing and planning of radial distribution systems that operate for minimal interruption of customer loads. The Distributed Generation (DG) in a radial distribution network has been slowly increasing for the last few years due to advancement of technologies and institutional changes in the electric power industry. This paper presents a reliability analysis for large scale, radial (with respect to substation) and reconfigurable electrical distribution systems. This paper evaluates the improvement in reliability over a time varying load curve.