A nearest level control technique for an asymmetric source configuration of multi-level inverter topology

In this paper, an asymmetric source configuration of Multilevel Inverter (MLI) topology has been proposed. It consists of eight unidirectional switches, two bidirectional switches and four isolated DC sources. By considering 1:5 and 1:4 source configurations, the inverter produces 25-level and 21-level outputs respectively with the same switching action. For producing negative voltage levels, there is no requirement of separate backend H-bridge and inherently produces both positive and negative voltage levels. The main advantage of this topology is that in every state, only four switches are in ON mode and else are in OFF state. It also gives less per unit Total Standing Voltage (TSV) and thereby cost requirement of semiconductor devices can become decreases. For generating gate pulses, the simple Nearest Level Control (NLC) has been used by considering the round function. This technique is basically a fundamental switching frequency technique thereby switching losses are greatly reduces as compared with high switching frequency Pulse Width Modulation (PWM) techniques and it is particularly suitable for large number of levels. With this control technique, there is no inrush current has been developed at the input of DC sources. Finally, with step change in Modulation Index (MI) values the proposed topology with two different source configurations have been validated through MATLAB/Simulink platform

Multi-Objective Optimal Power Flow Solution Using a Non-Dominated Sorting Hybrid Fruit Fly-Based Artificial Bee Colony

A new optimization technique is proposed for solving optimization problems having single and multiple objectives, with objective functions such as generation cost, loss, and severity value. This algorithm was developed to satisfy the constraints, such as OPF constraints, and practical constraints, such as ram rate limits. Single and multi-objective optimization problems were implemented with the proposed hybrid fruit fly-based artificial bee colony (HFABC) algorithm and the non-dominated sorting hybrid fruit fly-based artificial bee colony (NSHFABC) algorithm. HFABC is a hybrid model of the fruit fly and ABC algorithms. Selecting the user choice-based solution from the Pareto set by the proposed NSHFABC algorithm is performed by a fuzzy decision-based mechanism. The proposed HFABC method for single-objective optimization was analyzed using the Himmelblau test function, Booth’s test function, and IEEE 30 and IEEE 118 bus standard test systems. The proposed NSHFABC method for multi-objective optimization was analyzed using Schaffer1, Schaffer2, and Kursawe test functions, and the IEEE 30 bus test system. The obtained results of the proposed methods were compared with the existing literature

Multi-Objective Optimal Power Flow Solution Using a Non-Dominated Sorting Hybrid Fruit Fly-Based Artificial Bee Colony

A new optimization technique is proposed for solving optimization problems having single and multiple objectives, with objective functions such as generation cost, loss, and severity value. This algorithm was developed to satisfy the constraints, such as OPF constraints, and practical constraints, such as ram rate limits. Single and multi-objective optimization problems were implemented with the proposed hybrid fruit fly-based artificial bee colony (HFABC) algorithm and the non-dominated sorting hybrid fruit fly-based artificial bee colony (NSHFABC) algorithm. HFABC is a hybrid model of the fruit fly and ABC algorithms. Selecting the user choice-based solution from the Pareto set by the proposed NSHFABC algorithm is performed by a fuzzy decision-based mechanism. The proposed HFABC method for single-objective optimization was analyzed using the Himmelblau test function, Booth’s test function, and IEEE 30 and IEEE 118 bus standard test systems. The proposed NSHFABC method for multi-objective optimization was analyzed using Schaffer1, Schaffer2, and Kursawe test functions, and the IEEE 30 bus test system. The obtained results of the proposed methods were compared with the existing literature