Genetic k-means algorithm based RBF network for photovoltaic MPP prediction

Design optimization of insulation usage and space conditioning load using energy simulation and genetic algorithm

“…For instance, Mossolly studied the optimal control strategy for a multi-zone air conditioning system using GA [21]. Liao applied the so-called genetic k-means algorithm to predict the maximum power point of photovoltaic systems [22]. In addition to MOGA, there are other optimization algorithms available.…”

New silicon thin-film technology associated with original DC–DC converter: An economic alternative way to improve photovoltaic systems efficiencies

“…In order to improve the output efficiency of photovoltaic panels, it is important to operate the energy conversion systems near the maximum power point [37], so the objective of the control scheme is to track the maximum power point of both cells whatever the load requirements and the environmental conditions. For that purpose, the control algorithm can settle the PWM commands u S1 (t) and u S2 (t).…”

Photovoltaic Multiple Peaks Power Tracking Using Particle Swarm Optimization with Artificial Neural Network Algorithm

“…The widely used techniques include Perturb and Observe (P&O) [7][8][9][10], Incremental Conductance (IC) [11,12], Hill Climbing (HC) [8,13], open-circuit voltage [13,14], and short-circuit current algorithm [13,15]. Recently, several artificial intelligent methods, i.e., Fuzzy Logic Controller (FLC) [16][17][18][19][20][21], Artificial Neural Network (ANN) [16,22,23] are explored. The above-mentioned conventional MPPT algorithms are not capable of tracking the true maximum power point (MPP) if the PV array is partially shaded, such as covered by heavy clouds, falling tree leaves, birds' litters on the array or shaded by buildings [24].…”