Wind farms are introduced in larger and larger quantities in power systems all over the world. Hence, it becomes more and more vital to be able to perform power system studies, including wind farm behavior, and it demands modeling of wind farms. This paper deals with the implementation of FACTS controller called static synchronous compensator STATCOM to improve the performance of the grid connected wind farms. The essential feature of the STATCOM is that it has the ability to absorb or inject fastly the reactive power with power grid . Therefore the voltage regulation of the power grid with STATCOM FACTS device is achieved. Moreover restoring the system stability after severe disturbance is achieved by using the STATCOM. to validate the usage of STATCOM a simulated model is designed when subjected to sudden load variation.The results prove the effectiveness of the controller in restoring the system stability.

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<span lang="EN-US">Nowadays, renewable energy sources turned into a choice to fulfill the expanding load need since they are ecological inviting and furthermore accessible bountiful in nature. Due to the easy availability of solar-powered vitality, the photovoltaic (PV) system is gaining popularity as a renewable energy option. Most of the energy from a PV array may be dissipated by using the maximum power point tracking (MPPT) method. The force quality problems, the real and responsive force stream problems, are a major concern when transferring a mass measure of intensity from a PV array to the power grid. This research proposes a unique control technique for regulating the power flow and resolving power quality concerns brought on by the integration of PV arrays into an existing power infrastructure. For effective management of real and receptive force stream in matrix related photovoltaic framework, it includes a PI-GA, fuzzy-GA based flowed regulator dealt with adaptable AC transmission framework gadget, specifically static synchronous compensator (STATCOM). As a result, the fuzzy rationale regulator creates a control vector, which is in this way tweaked utilizing a standard calculation.</span>

The present state of sequenced programs requires the assignment of gene product functions in a timely, accurate and trustworthy manner. Many approaches to large-scale label designs have been developed. On the other hand, these approaches can only be used on a limited number of sub-sets. Their conclusions are not formalized. On the other hand, such approaches can only be used on a limited number of subsets, as their conclusions are not standardized. Annotation was supplied using Gene Ontology (GO) or categorization of valid or incorrect prediction using Support Vector Machines (SVM). A large database was used to assess the system's overall effectiveness. Reliability prediction was cross-validated organization by organization, yielding an average accuracy of 74% of all test cycles and 80%. The verification results revealed that the predictive efficacy was not dependent on the micro-organism because it could duplicate the high-quality automatic manual annotation. We used our trained categorization method to annotate Xenopuslaevis sequences, and greater than half of the known expressed genome was functionally annotated. We gave more than double the number of contigs with excellent annotations of high brightness compared to the already accessible annotations, and we also allocated a confidence score to each anticipated Gene Ontology (GO).

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