Sailaja Kumari Matam

Optimal placement and sizing of the DER in distribution systems using Shuffled Frog Leap Algorithm

Electrical power consumption is increasing day by day, complicating the operation of distribution systems. Distributed Energy Resource (DER) integration in distribution system is one of the options which give benefits like loss minimization, peak shaving, over load relieving and improved reliability. This paper presents an algorithm for optimal placement and size of the DER considering system loss minimization and voltage profile improvement as objective functions. This work is tested on IEEE 15, 33, 69 and 85 bus distribution systems. For all cases studied, a new heuristic optimization technique Shuffled Frog Leaping Algorithm (SFLA) is applied and current injection based distribution load flow method is employed. Further the results are compared with those results obtained by Particle swarm optimization (PSO) method and found to be encouraging.

Optimal placement and sizing of DER's with load models using BAT algorithm

This paper presents an algorithm for optimal placement and size of the Distributed energy resources (DERs) considering system loss minimization and voltage profile improvement as objective functions. DERs are the energy resources which contain renewable energy resources such as wind, solar and fuel cell and some artificial models like micro turbines, gas turbines, diesel engines, sterling engines, and internal combustion reciprocating engines. Combinations of DER studies and for every combination, indices, active and reactive losses and voltage profiles are studied. To optimize the objective function, new optimization technique called Bat algorithm(BA) is proposed. The Bat algorithm is tested on 37-bus distribution system with different load models like residential, Industrial, Commercial and Mixed loads. For all cases current injection based distribution load flow method is used.

Optimal placement and sizing of DER's with load models using a modified teaching learning based optimization algorithm

In this paper, a method which employs Modified Teaching-Learning Based Optimization (MTLBO) algorithm is proposed to determine the optimal placement and size of Distributed Energy Resources (DERs) units in distribution systems. DERs are commonly connected near the load in electric power distribution systems and include renewable energy sources such as wind and solar, fossil-fuel-based generation such as micro turbines, and other distributed energy storage elements. Loss minimization and voltage profile improvement as objective function and for every combination of DERs, impact indices, active and reactive losses and voltage profiles is studied on different load models. For all cases current injection distribution load flow method is used and tested on 84-bus Taiwan Power Company distribution system using MTLBO algorithm.

Optimal placement and sizing of multi Distributed generations with renewable bus available limits using Shuffled Bat algorithm

In this paper a new optimization algorithm is proposed for optimal planning of the Distributed generation (DGs) with renewable bus available limit constraint. Distribution system objectives considered for optimization are Active and reactive power losses minimization, bus voltage profile improvement, and line flow capacity limits. Power system modeled Distributed generations such as wind, solar and fuel cell and some artificial models like micro turbines are used to study the proposed algorithm. To optimize the objective function with voltage limits and renewable DG bus available limit constraints, Shuffled Bat algorithm (ShBAT) is proposed and compared with Genetic Algorithm (GA) and Bat Algorithm (Bat). 84-bus distribution system testing with proposed algorithm is presented with results.

Optimal placement and sizing of DGs at various load conditions using Shuffled Bat algorithm

In this paper a new and efficient hybrid optimization algorithm is proposed for optimal placement and sizing of the Distributed Generations (DGs). Bus voltage profile improvement, line flow capacity, active and reactive power loss minimization are considered as multi-objectives to optimize under various distribution load conditions. Renewable energy resources such as wind, solar, fuel cell and micro turbines are considered in power system modeling for finding the optimal placement and sizing. Current injection based distribution load flow is considered in DGs modeling in power systems. To optimize the objective function, a new optimization technique called Shuffled Bat algorithm (ShBAT) is proposed. The proposed methodology is tested on 84-bus Taiwan power company distribution systems with 90%, 100% and 120% of base load conditions to demonstrate its performance and effectiveness. Results show that the planned methodology is superior to existing strategies in terms of multi-objectives considered.