Enriched Firefly Algorithm for Solving Reactive Power Problem

In this paper, Enriched Firefly Algorithm (EFA) is planned to solve optimal reactive power dispatch problem. This algorithm is a kind of swarm intelligence algorithm based on the response of a firefly to the light of other fireflies. In this paper, we plan an augmentation on the original firefly algorithm. The proposed algorithm extends the single population FA to the interacting multi-swarms by cooperative Models. The proposed EFA has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss

Rapid Particle Swarm Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem

In this paper Rapid Particle Swarm Optimization (RPSO) algorithm is proposed to solve the optimal    reactive    power     dispatch Problem. The Rapid Particle swarm Optimization (RPSO) algorithm is obtained by merging PSO with Cauchy mutation. Basic idea is to introduce the Cauchy mutation into PSO such that it prevents PSO from trapping into a local optimum through stretched jumps made by the Cauchy mutation. In order to evaluate the efficiency of the proposed algorithm, it has been tested on IEEE 30 bus system and compared other standard algorithms. Results show’s that RPSO is more efficient in reducing the real power loss and voltage index also improved

Wolf Search Algorithm for Solving Optimal Reactive Power Dispatch Problem

This paper presents a new bio-inspired heuristic optimization algorithm called the Wolf Search Algorithm (WSA) for solving the multi-objective reactive power dispatch problem. Wolf Search algorithm is a new bio – inspired heuristic algorithm which based on wolf preying behaviour. The way wolves search for food and survive by avoiding their enemies has been imitated to formulate the algorithm for solving the reactive power dispatches. And the speciality  of wolf is  possessing  both individual local searching ability and autonomous flocking movement and this special property has been utilized to formulate the search algorithm .The proposed (WSA) algorithm has been tested on standard IEEE 30 bus test system and simulation results shows clearly about the good performance of the proposed algorithm

Optimal Power Flow using Ant Colony Search Algorithm to Evaluate Load Curtailment Incorporating Voltage Stability Margin Criterion

This paper proposes a method to compute load curtailment evaluation using ACSA based optimal power flow incorporating voltage stability margin criterion. . In a deregulated environment, congestion alleviation could mean load curtailment in certain situations.  The utilities would definitely prefer to curtail a load as lower as possible during a viability crisis situation. A criterion based on the voltage stability indicator is them incorporated as an additional constraint into the optimal power flow using ACSA algorithm and it is evaluated in a WSCC 9-bus test system.DOI:http://dx.doi.org/10.11591/ijece.v3i5.2738  

Analysis of coupled and decoupled PWM techniques for induction motor drive

Dual inverter fed induction motor drive-in open-end winding gives more advantages than multilevel inverter fed induction motor drives. For better quality of output voltage with low common mode voltage (CMV), in this paper analysis of coupled and decoupled PWM techniques for open end winding induction motor are carried. The analysis is carried in MATLAB/simulink environment for vector controlled open end winding induction motor drive. The performance of drive and PWM techniques are evaluated both in transient, steady state and loaded conditions

Voltage Profile Index Enrichment and Dwindling of Real Power Loss by using Acclimatized Imperialist Competitive Algorithm

In this paper, Acclimatized Imperialist Competitive Algorithm (AICA) is proposed for solving reactive power dispatch problem. The Imperialist Competitive Algorithm (ICA) was recently introduced has shown its good performance in optimization problems. This novel optimization algorithm is enthused by socio-political progression of imperialistic competition in the real world .The ICA is straightforwardly stuck into a local optimum when solving numerical optimization problems. In the proposed algorithm, for an effective search, the amalgamation Policy changed dynamically to adapt the angle of colonies movement towards imperialist’s position. To overcome this inadequacy we use probabilistic model that make use of the information of colonies positions to balance the exploration and exploitation aptitude of the imperialistic competitive algorithm. Using this mechanism, ICA exploration capability will augmented. The proposed (AICA) algorithm has been tested on standard IEEE 57 bus test system and simulation results shows clearly about the good performance of the proposed algorithm in reducing the real power loss

Dolphin Echolocation Algorithm for Solving Optimal Reactive Power Dispatch Problem

This paper proposes Dolphin echolocation Algorithm (DEA) for solving the multi-objective reactive power dispatch problem. Echolocation is the genetic sonar used by dolphins and more than a few kinds of other animals for direction-finding and hunting in different environments. This aptitude of dolphins is mimicked in this paper to develop a new process for solving optimal reactive power dispatch problem. A detailed study has shown that meta-heuristic algorithms have certain overriding rules. These rules will facilitate to get enhanced results. Dolphin echolocation algorithm takes reward of these rules and outperforms many active optimization methods. The new approach DEA leads to outstanding results with little computational efforts. In order to evaluate the efficiency of the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other specified algorithms. Simulation results show that DEA is superior to other algorithms in tumbling the real power loss and enhancing the voltage stability.

A New charged system Search for Solving Optimal Reactive Power Dispatch Problem

This paper presents an algorithm for solving the multi-objective reactive power dispatch problem in a power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization and maximization of voltage stability margin are taken as the objectives. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. This paper presents a new optimization algorithm based on some principles from physics and mechanics, which will be called Charged System Search (CSS). We utilize the governing Coulomb law from electrostatics and the Newtonian laws of mechanics. CSS is a multi-agent approach in which each agent is a Charged Particle (CP). CPs can affect each other based on their fitness values and their separation distances. The quantity of the resultant force is determined by using the electrostatics laws and the quality of the movement is determined using Newtonian mechanics laws. CSS can be utilized in all optimization fields; especially it is suitable for non-smooth or non-convex domains. CSS needs neither the gradient information nor the continuity of the search space. Proposed algorithm has been tested in standard IEEE 30 bus test system.

Minimization of Active Power Loss and Voltage Profile Fortification by Using Differential Evolution – Harmony Search Algorithm

This paper presents DEHS (Differential Evolution-harmony Search) algorithm for solving the multi-objective reactive power dispatch problem .Harmony Search is a new heuristic algorithm, which mimics the procedure of a music player to search for an ideal state of harmony in music playing. Harmony Search can autonomously mull over each component variable in a vector while it generates a new vector. These features augment the flexibility of the Harmony Search algorithm and produce better solutions and overcome the disadvantage of Differential Evolution. Improved Differential Evolution method based on the Harmony Search Scheme, which we named it DEHS (Differential Evolution-harmony Search). The DEHS method has two behaviors. On the one hand, DEHS has the flexibility. It can adjust the values lightly in order to get a better global value for optimization. On the other hand,   DEHS can greatly boost the population’s diversity. It not only uses the DE’s strategies to search for global optimal results, but also utilize HS’s tricks that generate a new vector by selecting the components of different vectors randomly in the harmony memory and its outside. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms.

Diminution of Real Power Loss by Using Hybridization of Bat Algorithm with Harmony Search Algorithm

In this paper, a new Hybridization of Bat algorithm with Harmony search algorithm (BAHS) is proposed for solving reactive power dispatch problem. The enhancement includes the addition of pitch modification procedure in HS serving as a mutation operator during the procedure of the bat updating with the aim of speeding up convergence, thus making the approach more feasible for a wider range of real-world applications. The proposed Hybridization of Bat algorithm with Harmony search algorithm (BAHS) algorithm has been tested on standard IEEE 30, IEEE 57 bus test systems and simulation results show clearly the superior performance of the proposed algorithm in reducing the real power loss