Hybrid-cloud-based data processing for power system monitoring in smart grids

This paper presents the design of planar four-bar linkages free of order, branch and circuit defects, for the purpose of path generation, having clearances at one, two, three or all of its joints. Joint clearance is treated as a massless virtual link and its direction is known by the direction of the joint force. A Particle Swarm Optimization based algorithm is given here to solve this highly nonlinear optimization problem with some constraints, namely; the Grashof’s and free of the foregoing defects conditions. An example is included in which the optimal problem is solved for different cases; namely planar four-bar linkage having clearances at one, two, three, all of the joints and without clearance. For all the designs, the generated paths, the errors and the directions of the virtual links are plotted and are compared. Finally, we compare the optimal designs with reality.

Optimal free-defect synthesis of four-bar linkage with joint clearance using PSO algorithm

A Improved Archimedes Optimization Algorithm for multi/single-objective Optimal Power Flow

The economic load dispatch (ELD) is one of the most complex optimization problems of electrical power system. Classically, it is to identify the optimal combination of generation level of all power generating units in order to minimize the total fuel cost while satisfying the loads and losses in power transmission system. In view of the sharply increasing nature of cost of fossil fuel, energy management has gained lot of significance nowadays. Herein lies the relevance of continued research on improving the solution of ELD problem. A lot of research work have been carried out on this problem using several optimization techniques including classical, linear, quadratic, and nonlinear programming methods. The objective function of the ELD problem being of highly nonlinear and non-convex nature, the classical optimization methods cannot guarantee convergence to the global optimal solution. Some soft computing techniques like Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Clonal Selection Algorithm (CSA), Ant Colony Optimization (ACO), Simulated Annealing (SA), Genetic Algorithm (GA), etc. are now being applied to find even better solution to the ELD problem. An interesting trend in this area is application of hybrid approaches like GA-PSO, ABC-PSO, CSA-SA, etc. and the results are found to be highly competitive. In this book chapter, we focus on the hybrid soft computing approaches in solving ELD problem and present a concise and updated technical review of systems and approaches proposed by different research groups. To depict the differences in technique of the hybrid approaches over the basic soft computing methods, the individual methods are introduced first. While the basic working principle and case studies of each hybrid approach are described briefly, the achievements of the approaches are discussed separately. Finally, the challenges in the present problem and some of the most promising approaches are highlighted and the possible future direction of research is hinted.

https://www.springer.com/cda/content/document/cda_downloaddocument/9788132225430-c2.pdf?SGWID=0-0-45-1522874-p177560038

Study of Economic Load Dispatch by Various Hybrid Optimization Techniques

This paper presents an economic operation considered renewable energy which is optimized using thunderstorm algorithm. The problem is constrained by an emission standard and various technical limits implemented on the 62-bus system model. Simulations showed that the renewable energy inclusion penetrates to the unit commitment of generating units with strongly approach for the computational solution. This inclusion also affects to the individual power production in accordance to the fuel cost and pollutant discharge.

http://journal.portalgaruda.org/index.php/EECSI/article/download/984/548

Renewable energy inclusion on economic power optimization using thunderstorm algorithm

This paper deals with particle swarm optimization (PSO) method to solve Combined Economic emission Dispatch Problem (CEEDP)of thermal units while satisfying the constraints such as generator capacity limits, power balance and line flow limits. PSO is a stochastic optimization process based on the movement and intelligence of swarms. The objective is to minimize the total fuel cost of generation and environmental pollution caused by fossil based thermal generating units. The bi-objective problem is converted into single objective problem by introducing price penalty factor to maintain an acceptable system performance in terms of limits on generator real power outputs, transmission losses with minimum emission dispatch. The proposed approach has been evaluated on an IEEE 30-bus test system with six generators. The results obtained with the proposed approach are compared with results of genetic algorithm and other technique. Keywords

/pdf/combined-economic-emission-dispatch-problem-using-particle-seo6vsm415.pdf

Combined Economic Emission Dispatch Problem using Particle Swarm Optimization

The complexity of the geometrical configuration of a product box and source rack demands an efficient and straightforward methodology for positioning dosimeters in desired planes of the product box to optimise its dose profile. The gamma dose profile generated in the Y-set of commissioning dosimetry depends on the geometry of the selected planes of the product box. The present work attempts to model a product box using a Voronoi diagram-based algorithm for optimising the number of dosimeters in the desired planes of the product box. Discrete dosimeter positions in vertical planes of the product box were used to construct the Voronoi diagram and Delaunay triangulation to model the product box. The Voronoi vertices were computed using a perpendicular bisector algorithm from the discrete coordinates of positions of dosimeters. The Voronoi vertices of the plane of the product box were chosen to optimise the position of dosimeters. The ceric-cerous dosimeters were used to measure the absorbed doses in the product box to validate the algorithm. The overdose ratio calculated was estimated as the average maximum dose and the average minimum dose from the vertices of the Voronoi diagram, and the position of dosimeters put as per conventional strategy in the plane of the product box. The results estimated from the proposed methodology are very close to the conventional dosimetry with a better dose uniformity ratio. The overdose ratio calculated from the Voronoi approach (DUR = 1.06) was found to be improved compared to the estimated overdose ratio (1.07) of the conventional Z-set dosimetry. The present work established the advantages of using the Voronoi Diagram in commissioning dosimetry to ease the dosimetry process. 

Modelling and optimization of dosimeters in the product box for commissioning dosimetry at gamma irradiator using Voronoi Diagram algorithm

E-drive technology is demanded for regulatory and climate protection reasons, and it comes with many advantages compared to ICE-based technology. Battery pack, e-motor controller, and e-motor are the key components of an electric powertrain that helps in propelling the electric vehicle (EV). The e-motor is the heart of an EV that delivers the required torque and speed continuously to meet the driving demand. To ensure that an e-motor continuously drives a specific vehicle over a specific geographical condition, the proper power rating of an electrical machine must be selected. This research paper has demonstrated the mathematical procedure to determine the power rating of an electrical machine for a particular vehicle based on the acceleration and drive cycle requirements by determining the various important parameters of the e-motor, such as peak torque, peak power, peak speed, base speed, etc. for different architectures of the drive-train. It has also presented a comparison among different architectures of drivetrain: front-wheel drive, rear-wheel drive, and a four-Wheel drive vehicle by comparing their important performance parameters such as torque requirement, acceleration, top-speed of the vehicle on the flat road surface and on the gradient road surface, etc. by using the simulation results of MATLAB.

Procedure to Select the Power Rating of Electrical Machines for an EV and Comparison with Different Drivetrain Configurations

Electric Vehicles (EV) are one of the best alternatives to conventional IC engines in the present scenario due to various problems such as depletion of fossil fuels, global warming, emissions, engine efficiency etc. A smooth driving pattern by an electric vehicle is one of the most desired needs in the current automotive industry. To ensure a smooth driving pattern, the torque ripple produced by the electric motor should be at its minimum. Motors in an EV must be able to perform well in all four quadrants as they act like a motor as well as a generator during driving based on the road conditions. To conduct this study, a mathematical model of motor controller, inverter and PMSM plant model has been developed entirely on Simulink, MathWorks without using any additional toolboxes, as it saves cost by eliminating the use of other toolboxes for modeling purposes. All the dynamics have been modeled only by using mathematical equations. Two, three and five levels of inverter have been developed for the purpose of comparison. The models have been validated by comparing the simulation results of the requested signal with the actual signal for torque and speed in each level of inverter separately over all the four quadrants of operation. Simulation results demonstrated better performance of multi-level inverters over the conventional two-level inverters in all the quadrants for an EV application.

Anurag Gupta

Papers

Combined Economic Emission Dispatch Problem using Particle Swarm Optimization

Modelling and optimization of dosimeters in the product box for commissioning dosimetry at gamma irradiator using Voronoi Diagram algorithm

Procedure to Select the Power Rating of Electrical Machines for an EV and Comparison with Different Drivetrain Configurations

Mathematical Modeling of PMSM for Simulation of Electric Drives and Comparison with Multi Level Inverters