Arvind Kumar

Voltage stability enhancement and voltage deviation minimization using BAT optimization algorithm

In this work, the most common problem of the modern power system named optimal power flow (OPF) is optimized using the novel meta-heuristic BAT Optimization Algorithm (BOA). BOA is inspired by the echolocation capability of micro-bats. BOA has a fast convergence rate. In order to solve the optimal power flow problem, standard IEEE-30 bus test system is used. BOA is implemented for the solution of proposed problem. The problems considered in the OPF problem are Fuel Cost Reduction, Voltage Deviation Minimization, and Voltage Stability Improvement. The results obtained by BOA is compared with other techniques such as Flower Pollination Algorithm (FPA) and Particle Swarm Optimizer (PSO). Results shows that BOA gives better optimization values as compared with FPA and PSO that confirms the effectiveness of the suggested algorithm.

Moth-Flame optimization Algorithm for solving real challenging constrained engineering optimization problems

In this paper, a novel nature-inspired optimization algorithm based on the navigation strategy of Moths in universe called the Moth-Flame optimization (MFO) Algorithm, is applied for constrained optimization and engineering design problems. A comparative analysis of MFO algorithm expresses the optimum functional value in term of accuracy and standard deviation over rest of well-known constraint optimization algorithms. Five constrained benchmark function of engineering problems have been calculated and gained solutions were compared with other recognized algorithms. The gained solution expresses that MFO algorithm provides better results in various design problems compared to other optimization algorithms.

Design and synthesis of 4-(4-ethyl-phenyl)-4-oxo-butyric acid (3-oxo-1, 3-diphenyl-propylidene)/[1-(4-chloro-phenyl)-ethylidene]-hydrazide as potential anticonvulsant agents

Some new substituted hydrazone derivatives were designed, synthesized, and evaluated for anticonvulsant activity and neurotoxicity. The anticonvulsant activity was established after intrapentoneal administration in one-seizure models, which include maximal electroshock seizure (MES) model. In the MES screen, the most active compounds were PK-1 and PK-2 which showed 100xa0% protection. None of these compounds showed neurotoxicity. A computational study was also performed including prediction of pharmacokinetic properties, bioactivity, toxicity, and docking studies. The result reveals from the computational studies as the protein–ligand interaction energies of derivatives PK-1 and PK-2 with established epilepsy receptor namely Na/H exchanger were −8.31 and −7.30xa0kcal/mol, which is slightly higher than the phenytoin as −6.71xa0kcal/mol. The percentage of absorption (%ABS) was calculated and observed that all titled compounds exhibited a better %ABS ranging 82–90. Therefore, all pharmacological parameters are almost similar to standard drug. The above observation suggested that these compounds would serve as better lead compounds for anticonvulsant screening for future drug design perspective.

Voltage stability enhancement and voltage deviation minimization using multi-verse optimizer algorithm

In this work, the most common problem of the modern power system named optimal power flow (OPF) is optimized using the novel meta-heuristic optimization technique Multi-Verse Optimizer (MVO). The main inspirations of this algorithm are based on three concepts in cosmology: white hole, black hole, and wormhole. MVO has a fast convergence rate. In order to solve the optimal power flow problem, standard IEEE-30 bus test system is used. MVO algorithm is implemented for the solution of proposed problem. The problems considered in the OPF problem are Fuel Cost Reduction, Voltage Deviation Minimization, and Voltage Stability Improvement. The results obtained by MVO is compared with other techniques such as Flower Pollination Algorithm (FPA) and Particle Swarm Optimizer (PSO). Results show that Multi-Verse Optimizer gives better optimization values as compared with FPA and PSO that confirms the effectiveness of the suggested algorithm.

An emission constraint environment dispatch problem solution with microgrid using Whale Optimization Algorithm

In this work, microgrid is modern small scale power system of the centralized electricity for a small community such as villages and commercial area. Microgrid consists of microsources like distribution generator, solar and wind units, etc., and different loads. In the microgrid, the energy management system (EMS) having a problem of Combined Economic Emission Dispatch (CEED) and it is optimized by metaheuristic techniques. The CEED is the procedure to scheduling the generating units within their bounds together with minimizing the fuel cost and emission values. The Whale Optimization Algorithm (WOA) is applied for the solution of CEED problem in the MATLAB environment. The minimization of total cost and total emission are obtained for all sources included. The result shows the comparison of WOA with the Gradient Method (GM), Ant Colony Optimization (ACO) and Particle Swarm Optimizer (PSO) technique for the two different cases which are Economic Load Dispatch (ELD) without emission and with emission. The results are calculated for different power demand of 24 hours. The results obtained with WOA gives better cost reduction in less iterations as compared to GM, ACO and PSO which shows the effectiveness of the given algorithm. The key objective of this work is to solve the CEED problem to obtained optimal system cost.

QSAR model development for studying carbonic anhydrase inhibitors as anticonvulsant agents

The objective of this work was to develop quantitative structure activity relationship (QSAR) models from sulfonamide derivatives against anticonvulsant activity. For developing the model, multiple linear regression and artificial neural network (ANN) have been employed as effective and efficient methods and these models have been validated with statistical analysis such as fraction of variance, cross-validation test, quality factor, Fischer’s test, and internal validation test (Y-randomization test), where applicable. A regression-based QSAR model (linear model) has been developed with cross-validation test q2u2009=u20090.8324 and fraction of variance r2u2009=u20090.8327, all the statistical tests have validated this model. An ANN (nonlinear model)-based model has also been developed with fraction of variance r2u2009=u20090.8710 and cross validation test q2u2009=u20090.7032. So, with the help of the developed models we can predict the logKi values of novel designed molecules and alter their structural properties accordingly before synthesizing them.

Whale Optimization Algorithm for Constrained Economic Load Dispatch Problems—A Cost Optimization

This paper presents an optimization approach, population-based meta-heuristics algorithm, known as whale optimization algorithm (WOA) for constrained economic load dispatch problems. An overall solution of constrained economic load dispatch problems is providing a continuous and reliable supply of electricity while maintaining the optimal cost of production and operation for the system. The proposed whale optimization algorithm (WOA), which is based on the concept of bubble-net hunting strategy, is applied to standard benchmark test function and both IEEE test systems with the number of 6 thermal units, and 15 thermal units including ramp rate limits and prohibited operation zones. The WOA results have been compared with PSO and Lagrange’s algorithm. The proposed algorithm is considerably fast and provides feasible near-optimal solutions. Simulation results have proved the performance of the proposed WOA algorithm to solve ELD problem within a faster convergence and reasonable execution time.

Design, molecular docking, synthesis, characterization, biological activity evaluation (against MES model), in-silico biological activity spectrum (PASS analysis), toxicological and predicted oral rat LD50 studies of novel sulphonamide derivatives

BackgroundAmong the reported potential agents to treat the epilepsy, sulphonamides are important and their significance cannot be ignored. A series of substituted 4-amino-benzene sulfonamides were designed, keeping in view the structural requirement of pharmacophore.MethodsLipinski rule of five has been calculated; failure to Lipinski rule was not observed. Docking was performed through AutoDock Vina. Molecules have been screened out through docking. Compounds were synthesized and characterized through IR, 1HNMR, 13C NMR, Mass and elemental analysis. The anticonvulsant activity of the synthesized compounds was assessed using the Maximal Electroshock Seizure (MES) model. In-silico biological activity spectrum, toxicological studies, predicted oral rats LD50 were performed.ResultsDocking studies showed good interaction with lyase (Oxo-acid) - human carbonic anhydrase-I (1AZM). The in-silico studies proved them to be with good drug-likeness properties, especially 4-(3-Acetyl-phenylamino)-methyl)-benzenesulfonamide (2g). These results revealed that the synthesized compounds (1a-1c, 2a-2q) exhibited promising anticonvulsant effect against MES model for inhibition of Lyase- Human Carbonic Anhydrase-I.ConclusionAfter investigating all the results, the compound 4-(3-Acetyl-phenylamino)-methyl)-benzenesulfonamide (2g) is found to be best in the series. A comparatively good activity of compound 2g suggests us that sulphonamide can be leads to further optimization for building potent and chemically diversified anti-convulsant agents.

Price penalty factors based approach for emission constrained economic dispatch problem solution using whale optimization algorithm

In The main ambition of utility is to provide continuous reliable supply to customers, satisfying power balance, transmission loss while generators are allowed to be operated within rated limits. Meanwhile, achieve this purpose emission value and fuel cost should be as less as possible. An allowable deviation in fuel cost and feasible tolerance in fuel cost has been called emission constrained economic dispatch (ECED) problem. A new nature-inspired Whale optimization algorithm (WOA) is based on concept of bubble-net hunting strategy is applied to solve ECED problem. ECED is a multi-criteria problem can transformed to single criteria using price penalty factor method. In this paper quadratic function together with emission value and fuel cost are considered as individual objective makes it multi-criteria problem. The effect of six penalty factors like “Min-Max”, “Max-Max”, “Min-Min”, “Max-Min”, “Average”, “Common” price penalty factors and emission value of various pollutants gases exhalation are included. The emission constrained economic dispatch (ECED) problem is analysed for an IEEE-30 Bus system with six operational generator units. Results prove capability of WOA in solving ECED problem with different penalty factors.