In electrical distribution systems, shunt capacitors are installed in order to reduce system losses, to enhance the voltage profile, and to free up system capacity. Nevertheless, the installation of shunt capacitors in distribution systems with distorted waveforms will magnify the distortion level of harmonics if they are not set at appropriate locations relative to the harmonics. This paper proposes a hybrid method to determine the placement and sizing of shunt capacitors in distorted radial distribution systems, taking into account the presence of harmonic distortion with consideration of ambient temperature effects, (this technique consists of the fuzzy expert system approach and the Genetic Algorithm method). This hybrid technique is applied to an IEEE 34-bus radial standard distribution system as well as a real distribution system in the Saudi Electricity Company. The simulation results show that harmonic distortion considerably reduces and the efficiency of distribution systems increases with a reduction in power loss and enhancement of voltage regulation.

In distribution systems, supplying a reactive power along the distribution lines is essential in order to bring benefits such as power loss reduction, the voltage profile improvement, and maximizing cost saving. Shunt capacitors have been used for this purpose but the scope of these benefits depends on an appropriate location, and size of these capacitors. This paper proposes a hybrid technique consist of a Fuzzy Expert System (FES) and Dragonfly Algorithm (DA) methods to determine capacitors placement and their sizing in radial distribution system level of smart grids. The fuzzy expert system is utilized to determine the suitable locations placement of capacitors and dragonfly algorithm is utilized to find their size. This proposed method is tested at IEEE 69-bus distribution system. The obtained simulation results are compared with an existing optimization algorithm.

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An effective maximum power point tracking (MPPT) technique plays a crucial role in improving the efficiency and performance of grid-connected renewable energy sources (RESs). This paper uses the African Vulture Optimization Algorithm (AVOA), a metaheuristic technique inspired by nature, to tune the proportional–integral (PI)-based MPPT controllers for hybrid RESs of solar photovoltaic (PV) and wind systems, as well as the PI controllers in a storage system that are used to smooth the output fluctuations of those RESs in a hybrid system. The performance of the AVOA is compared with that of the widely used the particle swarm optimization (PSO) technique, which is commonly acknowledged as the foundation of swarm intelligence. As a result, this technique is introduced in this study to draw a comparison. It is observed that the proposed algorithm outperformed the PSO algorithm in terms of the tracking speed, robustness, and best convergence to the minimum value. A MATLAB/Simulink model was built, and optimization and simulation for the proposed system were carried out to verify the introduced algorithms. In conclusion, the optimization and simulation results showed that the AVOA is a promising method for solving a variety of engineering problems.

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