Multilevel inverter plays an important role especially in solar based renewable energy sources due to its modularity in structure and medium or high power applications. It is well known that there are three types of inverters which are Diode clamped multilevel inverter, flying capacitor multilevel inverter and cascaded multilevel inverter. One of the drawback of these inverters are, more switching losses due to which quality of power get decreases. The main intention of this work is to improve the quality of power, thereby increasing the life and performance of the overall system at consumer side. One of the reduced switched multilevel inverters have been used to perform so called multilevel DC link inverter. In earlier days, Sinusoidal Pulse Width Modulation (SPWM) technique is used to reduce the switching losses of the inverter. Present work proposes a new Hybrid Pulse Width Modulation (HPWM) technique to control the switching losses in the system. In this HPWM technique, multi level DC link inverter having combination of SPWM (at level generation), and Fuzzy controller(at polarity generation) are used to reduce the losses, and the results are compared with conventional SPWM technique considering R and R-L load.
Distributed Generation (DG) plays a vital role in modern power systems to achieve the requirements and satisfaction of end users while transmitting and distributing power from one to another point. It is a small scale generation which is also known as the embedded generation, dispersed generation or the decentralized generation. The optimal allocation of distributed generation (DG) on distributed network plays a crucial role in maximizing the benefits such as reduction of network losses and voltage profile improvement. There are many techniques used for the optimal allocation and sizing of DG in Radial Distribution System (RDS). The paper presented an overview and review the techniques used in some of the most popular methods includes load flow based methods, numerical techniques, intelligent techniques and evolutionary techniques. The evolutionary techniques include various optimization techniques such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Artificial Bee Colony (ABC) and Ant Colony Optimization and so on. The paper also provides advantages and disadvantages of each method and useful guidelines for the further research in this area.
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