Photovoltaic (PV) power generation can considerably reduce the consumption of traditional fossil energy and improve environmental problems. Reliable photovoltaic (PV) cell modelling owns great significance to the following output characteristics analysis and optimal operation of the whole PV system, while there are several unknown physical parameters within different PV cell models. Thus, the identification of the internal parameters of the PV cell model is the first and foremost step for PV cell modelling, nevertheless, the intrinsic highly complex and non-linear and multi-modal features make traditional approaches, such as analytical methods hard to achieve satisfactory performance in solving this problem. Hence, this work aims to employ a powerful tool to effectively and efficiently overcome this thorny problem based on the most advanced optimization method. A recently developed meta-heuristic algorithm called peafowl optimization algorithm (POA) is employed in this work for PV cell modelling parameter identification. For comprehensive validation, two different PV cell models, i.e., double diode model (DDM) and triple diode model (TDM) are utilized. Simulation results demonstrate that POA can more accurately identify the unknown parameters of PV cell models in a higher convergence speed compared against other algorithms.

In view of the low efficiency of thermoelectric generation systems in different regions, this paper designs an optimization and reconfiguration of thermoelectric power generation system under heterogeneous temperature difference (HTD) based on particle swarm optimization (PSO) algorithm, so as to make full use of various thermal energy resources and obtain higher electrical output power, which realize multi-directional utilization of energy. In addition, PSO algorithm is a simple optimization strategy with a straightforward operation mechanism and fewer parameters to control during calculation. The research shows that when TEG array is in multiple HTD states, PSO algorithm has a stronger ability to get rid of local optimization, which can reduce power loss and improve energy conversion efficiency. On this basis, PSO algorithm is used to reconfigure the 15 × 15 symmetric TEG array. The experimental simulation analysis based on MATLAB platform is carried out to verify the feasibility of PSO algorithm.