The purpose using capacitors in distribution networks is to reduce the total losses of the network. Capacitors help regulate the power factor and voltage in the electrical distribution system, and can be controlled remotely, in and out of the system. Capacitor placement depends on the objective function, which is usually single objective or multi objective. In this paper, the amount of capacitor at minimum load is determined using a genetic algorithm. The calculation is done at peak load to determine the sensitivity of power losses. By using this method, the increase of the voltage caused by the lead phase of the system is prevented in the minimum load. A multi-purpose objective function to simultaneously reduce losses and improve the voltage profile of the optimal capacitor size in each section is detected by a genetic algorithm. To show the efficiency of the method, the capacitor placement results are compared using DIGSIENT software.
The air fuel ratio (AFR) control is one of the effective methods to reduce emission and fuel consumption in spark ignition (SI) engines. Due to the hard nonlinearities existing in the engine dynamics model, a nonlinear controller should be designed for AFR control. In this Paper, an optimization-based nonlinear control law is developed for injected fuel mass flow to maintain AFR in the stoichiometric value. Simulation results show that the AFR in the controlled system is very close to the desired value, unlike the uncontrolled system in which the AFR has intensive fluctuations.
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