Analysis and Implementation of Artificial Neural Network Techniques for Power Quality Enhancement using DSTATCOM

This project shows how to use a back propagation BP control method to execute a three stage delivery static compensator DSTATCOM for its capabilities such as load balancing and zero voltage management of reactive power compensation under non linear loads. In this case, we utilize a BP based control method to determine the crucial dynamic weight. Furthermore, the BP based control method is often used to estimate the receptive power parts of the load streams required for estimating the reference source streams. The new topic of research in the field of power engineering is the regulation of power efficiency devices using neural networks. The output of the balancing instruments is defined by the extraction of the harmonic components. DSTATCOM and UPFC are used as balancing devices in this case. A DSTATCOM model is created with the help of a computerized signal processor, and its implementation is tailored to specific working circumstances. With the suggested control method, the execution of DSTATCOM is shown to be appropriate for a variety of workloads. The BP based control method is used to calculate the basic weighted value of the loads active and reactive power components. The sample trained back propagation method will identify the power quality signal problem in real time. This algorithms main characteristics include continuity, differentiability, and non decreasing momotomy. The UPFC procedure is similar to that of DSTATCOM, with the exception that the device is not turned off under adverse conditions. The simulation model is created using ANFIS, and its output is investigated under various operating circumstances. For various kinds of loads, the ANFIS output is determined to be acceptable using the suggested control method. The proposed technique must be validated using MATLAB Simulink findings. Amrendra Kumar | Pramod Kumar Rathore "Analysis and Implementation of Artificial Neural Network Techniques for Power Quality Enhancement using DSTATCOM" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-5 , August 2021, URL: https://www.ijtsrd.com/papers/ijtsrd45218.pdf Paper URL: https://www.ijtsrd.com/engineering/other/45218/analysis-and-implementation-of-artificial-neural-network-techniques-for-power-quality-enhancement-using-dstatcom/amrendra-kumar