Optimal Control and Dynamic Stability of Power Injection Based on Fuzzy Intelligent Controller

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Abstract

Many countries are witnessing nice developments in construction, urban planning, technological development moreover as grid management the increasing demand for energy of every kind and totally different generation strategies as well because the want for low and medium voltage distribution altogether areas. The assembly of this energy varies per user needs, initial requirements, capacity, supposed use, waste generation, and economic potency. The improvement of those different energies depends on the number of synchronization achieved within the injection of power into the mains together with force control, tool stability, voltage quality, efficiency - and redundant power return. During this paper, a proposal is given for associate intelligent management unit supported the modeling and stabilization of the alarm force system. So as to satisfy the challenges of the planned overvoltage of the presented system, it’s doable to feed the plentiful power from the surplus power of the private households into the grid. Use and profit economically from star collectors through good grid smart control systems. So as to review and analyze the practicableness of the proposed grid coordination and energy storage privately PV networks based on solar energy, a mathematical model was created consisting of 4 main parts: simulation, correlation, stability, and evaluation. An Adaptive Neuro-Fuzzy Inference System (ANFIS) to assess the impact of those basic limitations in sensible application. The simulation of the planned system is dispensed with the most powerful system with a capability of 600 V which will be operated with this power. The proposed system was evaluated from Matlab simulation bars and graphs for every part of the system, and therefore the overall system simulation results were taken into account.

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APA

Al Mashhadany, Y. I., Ulutagay, G., & Abdulelah, B. J. (2022). Optimal Control and Dynamic Stability of Power Injection Based on Fuzzy Intelligent Controller. In Lecture Notes in Networks and Systems (Vol. 504 LNNS, pp. 895–904). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-09173-5_103

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