Sydulu Maheswarapu

Security Constraint Optimal Power Flow (SCOPF) – A Comprehensive Survey

This paper reviews the existing developments in Security Constrained Optimal Power Flow (SCOPF) from 1960‟s to till date. Diverse schemes and approaches on Single Area/Multiarea, Algorithms, Contingency Selection, Steady and Dynamic SCOPF, Artificial Intelligence based SCOPF, Real time and SCOPF using Parallel/Distributed Processing, Economic Dispatch with Security Constraints, Decentralized SCOPF, Voltage Constrained SCOPF (VSCOPF), Incorporation of FACTS on SCOPF studies and Literatures on Applications of SCOPF etc., are appraised in a structured manner chronologically with detailed reviews on the strategies and the test systems used for the analysis are reported. A brief summary of the existing stratagems and test system data which can be retrieved are given in the conclusion for easy access of researchers.

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.

A Music Based Harmony Search (MBHS) approach to Optimal Power Flow with reactive power loss optimization

This paper presents a new optimization algorithm, Music Based Harmony Search (MBHS) applied to the Optimal Power flow (OPF) problem with line constraints for minimizing the Fuel costs together with Generator Reactive power losses. The proposed method is compared with other optimization techniques like Simple Genetic Algorithm (SGA), Adaptive Genetic Algorithm (AGA) and Particle Swarm Optimization (PSO) to prove its supremacy. The algorithm is tested on a standard IEEE 30 bus test bed and numerous analyses viz., the effect on taps; shunt reactors etc., with different MBHS parameters are demonstrated. It is found that MBHS offers a computationally faster (75.83 times) and robust solution for OPF problem.

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.

Directional Search Genetic Algorithm Applications to Economic Dispatch of Thermal Units

This paper proposes a novel directional search genetic algorithm (DSGA) for solving the Economic Dispatch (ED) problem with fixed boundary conditions. In this paper, a new population generation technique has been employed by using Lambda Limits updation technique. The incremental cost of the generating unit is taken as the decision variable. The feasibility of the proposed method is demonstrated for three different systems, and is compared with various methods available in literature. The proposed algorithm works well for both small- and large-scale generating units and it remarkably reduces the computation time, number of iterations taken to converge, and population size.

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.

A novel approach to sustainable Power System Expansion planning with inclusion of Renewable Energy

The importance of Renewable Generation for sustainable growth must be recognized in Power System Expansion Studies. Inclusion of renewable energy generation in Power System Expansion ensures decreased dependency on fossil fuels in future. In this direction, we have developed a method for planning studies, by incorporating the selection of renewable energy generators, primarily wind and solar. The problem considered is a novel one and extensive literature is not available for the same. Thus, implementing the concept of inclusion of renewables in expansion studies is a great challenge. In this paper, wind and solar generators are defined similar to the conventional ones, to bring them to a common base. A constraint Emission Rate (ER) is introduced to ensure inclusion of renewable technologies with high costs and low Capacity Utilization Factor (CUF) in the expansion plan. This constraint guarantees a certain percentage of Renewables in the generation addition during expansion. Single Stage Multi-State Power System Expansion with Renewable Energy Inclusion was attempted using Genetic Algorithm. The authenticity of the solution obtained for inclusion of renewables during planning is ascertained by conducting a consistency check for an obvious case. Expansion studies for different percentages of renewable penetration are carried out and the results are compared. Matlab R2010a is used for the purpose of implementation.

Improved genetic and Harmony Search Algorithms for single and multi stage expansion planning of power system

Meta-heuristic algorithms are widely used to address optimization problems. However these methods give only suboptimal solutions in case of complex problems with constraints. This calls for modification in the algorithm in accordance with the problem to result in optimal solution with reasonable consistency. In this paper, Genetic Algorithm (GA) and Harmony Search Algorithm (HS) are discussed and compared. Improvements for HS and GA are suggested for Single and Multi stage expansion of Multi state Power System, which is an optimization problem with availability constraints. The modified HS employed for Single Stage expansion drastically improved the consistency and the time taken. Modification of GENITOR (a variant of GA) for Multi-Stage expansion resulted in achieving the solution in less number of iterations. This feature gives scope to the algorithm for application in real time complex problems with constraints. Also, the key feature of GENITOR is incorporated into HS for Multi-Stage expansion, in order to achieve the solution in lesser number of iterations. MatLab R2010a is used for the purpose of programming.

An efficient power flow method for distribution system studies under various load models

This paper presents a robust and direct method for solving the power flow problem of a radial and weakly meshed distribution systems. The proposed method uses the concept of partial network and system parameters to construct the network matrix which remains constant for a given distribution system. A simple matrix multiplication of network matrix and current injection vector offers solution vector for the both radial and meshed distribution networks. A computer coded program is developed in MATLAB environment. The validity of the proposed method is tested on IEEE 33 bus, IEEE 69 bus, Taiwan Power Company (TPC) 84 bus, 136 bus and 874 bus radial and weakly meshed distribution networks. The test results has shown that it is very effective for all case studies. To apprise its credibility, it is compared with Current Injection Method which works for radial and weakly meshed networks, on the basis of iteration count and CPU time. The proposed method is 5 to 6 times faster than the current injection method. This method finds potential applications in network reconfiguration, reactive power compensation studies and incorporation of renewable energy sources.