Advanced dynamic stability system developed for nonlinear load

Abstract

The conventional production of electrical energy gives rise to environmental problems and involves high production costs. To cope with the increasing demand for electrical loads and to optimize power transmission on the grid, it is imperative to shift towards renewable energies and their hybrid utilization. This planning study assesses the impact of fluctuating electric loads on bus voltages and frequency, with the objective of distributing energy in a more efficient and dynamic manner. Moreover, we delve into the implementation of artificial intelligence (IAPS) to curtail operations, minimize losses (GED), optimize production plans (EMSO), and synchronize decentralized multi-machine power systems (MMSA). Our study scrutinizes power dispatching on dynamic models of purely consuming loads, which are subject to dynamic constraints, by utilizing educational software that encompasses 13 cycles for 24 hours of frequency studies for multisource production in a standardized electrical system (EPSS). The control outcomes obtained through validation on an IEEE30 bus network display a resilient model for planned productions.