Evolutionary Maximization of Energy Amount Harvested by Means of Panel of Thermoelectric Modules

This work proposes the use of a specialized algorithm based on evolutionary computation to the global MPPT regulation of panel of thermoelectric modules connected serially in numerous string sections. Each section of the thermovoltaic panel is equipped with local DC/DC converter controlled by the proposed algorithm and finally this allows the optimization of the total efficiency of conversion. Evolutionary computations adjust PWM signals of switching waveforms of DC/DC sectional simple boost converters, which have outputs configured in parallel. It gives the chance to obtain the highest level of electric energy harvested, i.e., thanks to boost converting operational points precise adaptation to the system temperature profile as well as electric load level. The simulation results of the proposed evolutionary technique confirmed the high speed of the MPPT process that is much better than for perturbation and observation, as well as incremental conductance methods, and it assures concurrent optimization of numerous PWM signals. Next, the work shows practical optimization results achieved by the proposed algorithm implemented to microcontroller module controlling the DC/DC converter during thermal to electric conversion experiment. A laboratory thermovoltaic panel was constructed from a string of Peltier modules and radiator that assured passive cooling. The measurements obtained once more proved the MPPT evolutionary regulation properness and its adaptation effectiveness for different resistive test loads.

A Firework-Based GMPPT with Variable Sampling Time for PV Systems

Photovoltaic systems have a nonlinear characteristic in which there is one optimum operating point called Maximum Power Point (MPP). However, when PV panels are partially shaded by surrounding objects, there are several MPPs, of which one of them is Global MPP (GMPP). Therefore, conventional Maximum Power Point Tracking (MPPT) algorithms get trapped into local MPPs. As a result, a multitude of Global MPPT (GMPPT) algorithms have been proposed. An outstanding GMPPT algorithm as well as the fast-tracking speed should find GMPP in complicated shading patterns where not only there are lots of MPPs, but also the peaks are close together. Therefore, in this paper, a novel GMPPT based on firework algorithm is proposed which is able to find GMPP in complicated shading patterns with fast tracking speed. Moreover, the firework is combined with Perturb-and-Observe (P&O) algorithm to reduce the computational effort in a way that the firework is only used to recognize GMPP; afterwards, P&O algorithm completes the tracking. Furthermore, the variable sampling time technique, based on the system settling time, speeds up the tracking process considerably. Finally, the proposed method is compared with previous works, simulated, and implemented on an experimental setup to prove its superiority.