Hybrid renewable energy systems (HRESs) can alleviate the grid dependence for power in rural and distant locations. The intermittent nature of renewable energy sources acting alone does not make the system reliable; however, combining one or more sources (like solar, wind, diesel, biomass, micro-hydel, etc.) with adequate storage options or intelligent control of hybrid systems ensures power availability to the end user. As a result, it is imperative that the technical aspects of such a hybrid system can be analyzed with respect to optimal sizing of sources, proper control design and mechanism for energy management, and adequate backup via the storage option that ascertain reliable power supply to the consumer/end user or at the distributed generation end. This paper presents an overview of the applications of Genetic Algorithms, Fuzzy logic, Particle Swarm optimization, and similar other evolutionary and nature inspired algorithms that have been employed for the optimization, control, and power management strategies for renewable energy studies involving hybrid power generation schemes. Analysis of the algorithms and the potential applications of new improved algorithms for optimization, control, and power management of HRES is discussed and reported.

This paper makes a comparative investigation of the three basic non-isolated dc-dc converters used as interface for maximum power point tracking (MPPT) application in photovoltaic generators using the direct duty ratio control tracking algorithm. Analysis of the buck, boost, and buck–boost converters has been undertaken to study the behavior of the converter's performance with respect to the changing atmospheric conditions and in-turn duty ratio variation (as a result of MPPT) and the tracking efficiency of each converter. Effect of different resistive loads on the output of the converter side has also been considered for the three topologies and it has been observed that the buck-boost converter is the only converter which is able to track the maximum power point under variation of insolation, temperature, and loading effect, with the highest tracking efficiency.

No abstract

No abstract

No abstract