Solar Energy is one of the key solutions to future electrical power generation. Photovoltaic Plants (PV) are fast growing to satisfy electrical power demand. Different maximum power point tracking techniques (MPPT) are used to maximize PV systems generated power. In this paper, on grid PV system model in MATLAB SIMULINK is tested under sudden irradiance and cell temperature variations. Incremental Conductance MPPT is used to maximize generated power from the PV system with the help of new adaptive controller to withstand these heavy disturbances. The new adaptive controller is tuned for optimal operation using two different optimization techniques (Invasive weed and Harmony search).Optimization results for the two techniques are compared. .A robustness test is made to check system stability to withstand different random irradiance and cell temperature patterns without failure to track the maximum power point.Finally, a brief comparison is made with a previous literature and the new adaptive controller gives better results.
This paper applies two reliable and efficient evolutionary-based methods named Shuffled Frog Leaping Algorithm (SFLA) and Grey Wolf Optimizer (GWO) to solve Optimal Power Flow (OPF) problem. OPF is one of the essential functions of electrical power generation control and operation. It aims to estimate the optimal settings of real generator output power, bus voltage, reactive power compensation devices, and transformer tap setting. The objective function of OPF is to minimize total production cost while maintaining the power system operation within its security limit constrains. SFLA and GWO are meta-heuristic evolutionary-based methods. SFLA mimics the frogs' behavior while searching for food. GWO mimics the grey wolfs behavior while hunting for prey. These methods are simulated and tested on the standard IEEE 30-bus and 57-bus test systems. Moreover, the performances of the applied algorithms are analyzed and compared with each other as well as with other existing optimization techniques. The obtained results show the strengths of the two applied methods and the superiority of them in comparison to the other methods.
The Fourier transform spectrometer based on cascaded Fabry-Perot interferometers is analyzed, where one of the interferometers has a fixed length, while the other is scanning. We propose a method to reconstruct the spectrum correctly based on solving the integral equation of the overall response of the cascaded interferometers. The method is tested for different design parameters and noise conditions. Low reconstruction error below -80 dB is found to be achievable.
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