Diminution of Real Power Loss by Hybridization of Particle Swarm Optimization with Extremal Optimization

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. Particle swarm optimization (PSO) has received increasing interest from the optimization community due to its simplicity in implementation and its inexpensive computational overhead. However, PSO has premature convergence, especially in complex multimodal functions. Extremal Optimization (EO) is a recently developed local-search heuristic method and has been successfully applied to a wide variety of hard optimization problems. To overcome the limitation of PSO, this paper proposes a novel hybrid algorithm, called hybrid PSO-EO algorithm, through introducing EO to PSO. The hybrid approach elegantly combines the exploration ability of PSO with the exploitation ability of EO. The proposed approach is shown to have superior performance and great capability of preventing pre- mature convergence across it comparing favourably with the other algorithms. We demonstrated that our proposed HPSOEO (hybrid particle swarm optimization – Extremal optimization) presents a better performance when compared to the other algorithms. In order to evaluate the proposed algorithm, it has been tested on IEEE 30 bus system and compared to other algorithms reported those before in literature. Results show that HPSOEO is more efficient than others for solution of single-objective Optimal Reactive Power Dispatch problem. Keywords: Modal analysis, optimal reactive power, Transmission loss, particle swarm, Particle swarm optimization, Extremal optimization, Numerical optimization, Metaheuristic

Voltage Profile Amplification and Attenuation of Real Power Loss by Using New Cuttlefish Algorithm

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. Global optimization methods play an important role to solve many real-world problems. However, the implementation of single methods is excessively preventive for high dimensionality and nonlinear problems, especially in term of the accuracy of finding best solutions and convergence speed performance. In this paper, a New Cuttlefish Algorithm (NCFA) is proposed to solve reactive power dispatch problem. The algorithm imitates the method of colour altering behaviour used by the cuttlefish .The patterns and colours seen in cuttlefish are produced by reflected light from different layers of cells including (chromatophores, leucophores and iridophores) heap together, and it is the amalgamation of certain cells at once that allows cuttlefish to acquire such a huge array of patterns and colours. The projected algorithm considers two key progressions: reflection and visibility. Reflection process is projected to replicate the light reflection mechanism used by these three layers, while the visibility is projected to replicate the visibility of matching pattern used by the cuttlefish. These two processes are used as a explore strategy to find the global optimal solution. The proposed New Cuttlefish Algorithm (NCFA) has been tested on standard IEEE 30 bus test system and simulation results show clearly the better performance of the proposed algorithm in enhancing the voltage stability and reducing the real power loss. Keywords: Optimal Reactive Power, Transmission loss, Cuttlefish algorithm, Reflection, Visibility, Optimization, Chromatophores, Iridophores, Leucophores

Social Emotional Optimization Algorithm for Solving Optimal Reactive Power Dispatch Problem

The main feature of solving Optimal Reactive Power Dispatch Problem (ORPD) is to minimize the real power loss and also to keep the voltage profile within the specified limits. Human society is a complex group which is more effective than other animal groups. Therefore, if one algorithm mimics the human society, the effectiveness maybe more robust than other swarm intelligent algorithms which are inspired by other animal groups. So in this paper Social Emotional Optimization Algorithm (SEOA) has been utilized to solve ORPD problem. The proposed algorithm (SEOA) has been validated, by applying it on standard IEEE 30 bus test system. The results have been compared to other heuristics methods and the proposed algorithm converges to best solution

Shrinkage of Active Power Loss by Hybridization of Flower Pollination Algorithm with Chaotic Harmony Search Algorithm

In this paper, Hybridization of flower pollination algorithm with chaotic harmony search algorithm (HFPCHS) is proposed to solve optimal reactive power dispatch problem. This method integrates the standard Flower Pollination algorithm (FP) with the chaotic Harmony Search (HS) algorithm to improve the searching accuracy. By using chaotic sequences in Harmony search Algorithm can be helpful to progress the consistency of the global optimality, and they also augment the quality of the results.   The proposed HFPCHS has been tested on standard IEEE 57 bus test system and simulation results show clearly the better performance of the proposed algorithm in reducing the real power loss.   Keywords: Flower pollination algorithm, Harmony search, chaotic sequences, optimal reactive power, Transmission loss

Hybrid - Particle Swarm Optimization and Differential Evolution for Reduction of Real Power Loss and Preservation of Voltage Stability Limits

In this paper, a Hybrid algorithm based on - Particle Swarm Optimization (PSO) and Differential Evolution (DE) is used for solving reactive power dispatch problem. It needs progressing the population to create the individual optimal positions by means of the PSO algorithm, and then the algorithm come in DE phase and progresses the individual optimal positions by smearing the DE algorithm. In order to comprehend co-evolution of DE and PSO algorithm, an information-sharing mechanism is presented, which progresses the capability of the algorithm to fence out of the local optimum. Additionally, in optimization procedure, we espouse the hybrid inertia weight stratagem, time-varying acceleration coefficients tactic and arbitrary scaling factor stratagem. The proposed Hybrid algorithm based on - Particle Swarm Optimization and Differential Evolution (H-PSDE) has been tested on standard IEEE 30, 57,118 bus test systems and simulation results show clearly about the better performance of the proposed algorithm in reducing the real power loss. Keywords:Optimal Reactive Power; Transmission loss; Particle Swarm Optimization; Differential Evolution; Global Search; Local Search; Inertia Weight

Ant colony search algorithm for optimal reactive power optimization

The paper presents an (ACSA) Ant colony search Algorithm for Optimal Reactive Power Optimization and voltage control of power systems. ACSA is a new co-operative agents’ approach, which is inspired by the observation of the behavior of real ant colonies on the topic of ant trial formation and foraging methods. Hence, in the ACSA a set of co-operative agents called "Ants" co-operates to find good solution for Reactive Power Optimization problem. The ACSA is applied for optimal reactive power optimization is evaluated on standard IEEE, 30, 57, 191 (practical) test bus system. The proposed approach is tested and compared to genetic algorithm (GA), Adaptive Genetic Algorithm (AGA)

Reduction of Real Power Loss by Improved Evolutionary Algorithm

This paper presents an Improved Evolutionary Algorithm (IEA), to solve optimal reactive power dispatch problem. In IEA objective space is disintegrated into a set of sub objective spaces by a set of route vectors. In the evolutionary procedure, each sub objective space has a solution. In such a way, the diversity of achieved solutions can be upheld. In addition, if a solution is conquered by other solutions, the solution can produce more newfangled solutions than those solutions, which makes the solution of each sub objective space converge to the optimal solutions as far as conceivable. The planned IEA has been tested in standard IEEE 30, 118 bus test systems and simulation results show clearly the improved performance of the planned algorithm in declining the real power loss. Keywords: Evolutionary Algorithm, genetic operators, optimal reactive power, Transmission loss

Effect of Glomus intraradices and Rhizobium on the Growth of Groundnut (Arachis hypogaea L.).

AbstractArbuscular mycorrhizal (AM) fungi can increase the capability of the root systems to absorb and translocate phosphorus (P) and minor elements through an extensive network of mycelium.  AM fungi are commonly associated with legumes and can increase nutrient uptake of plants growing in high phosphate fixing soils.  The present study the efforts of AM fungi Glomus intraradices and Rhizobium on groundnut Arachis hypogaea L. The AM fungi Glomus intraradices and Rhizobium inoculation plants resulted in production of highest biomass such as plant, shoot length, root length, number of leaves, total number of root nodules, fresh and dry weight of plants and the biochemical content such as chlorophyll ‘a’ and ‘b’, total sugar, starch content, proline, carbohydrates and protein contents. The inoculation of Glomus intraradices + Rhizobium showed an enhanced biomass when compared to other treatments. Department of Botany, Annamalai University, Annamalai Nagar – 608 002  Please Cite This Article As:  K. Ramakrishnan and M. Lenin. 2010. Effect of Glomus intraradices and Rhizobium on the Growth of Groundnut (Arachis hypogaea L.). J. Ecobiotechnol. 2(5):01-08.Â

They Said: A Global Perspective on Access to Assistive Technology

International experts in assistive technology from five global regions (South America, Asia Pacific, Europe, Africa, and Australia) and with affiliation to the World Health Organization (WHO) Global Cooperation on Assistive Technology (GATE) community were invited to share their perspectives on the delivery of assistive technology and provision of assistive products in their regions. Four common topics emerged from the experts: (a) user and environmental barriers; (b) policy, funding, and product access; (c) professional training, collaboration, and service delivery; and (d) occupational justice (i.e., empowerment, participation, and progress)