Particle Swarm Optimization technique has been improved by fractional order calculus to be used for photovoltaic (PV) modeling. The modified technique which is called Fractional Order Darwinian Particle Swarm Optimization (FODPSO) has been constructed to estimate the optimal electrical parameters of PV modules. Single and double diode models have been used to designate the PV modules. FODPSO and PSO algorithms have been designed and applied on two different PV modules at different irradiances and temperatures. In order to validate the proposed modeling technique, Root Mean Square Error (RMSE) of the current, RMSE of power and Summation of the Individual Absolute Error (SIAE) results obtained using FODPSO and traditional Particle Swarm Optimization (PSO) algorithms have been compared. Minimum RMSE and SIAE have been achieved using the FODPSO technique. To verify the FODPSO results accuracy, accurate measurements of short circuit current, open circuit voltage, and maximum power, voltage at maximum power and current at maximum power have been performed for both PV modules. FODPSO-estimated results show excellent agreement with the experimental ones at different irradiances and temperatures.

分数群算法已改进了粒子群优化技术，可用于光伏（PV）建模。构造了改进的技术，称为分数阶达尔文粒子群优化（FODPSO），以估算光伏组件的最佳电参数。单二极管和双二极管模型已用于指定PV模块。已经设计了FODPSO和PSO算法，并在不同的辐照度和温度下将其应用于两个不同的PV模块。为了验证所提出的建模技术，比较了使用FODPSO和传统粒子群优化（PSO）算法获得的电流均方根误差（RMSE），功率的均方根误差（RMSE）和个体绝对误差总和（SIAE）的结果。使用FODPSO技术已达到最低RMSE和SIAE。为了验证FODPSO结果的准确性，已对两个PV模块进行了短路电流，开路电压和最大功率，最大功率的电压以及最大功率的电流的精确测量。FODPSO估计的结果显示在不同的辐照度和温度下与实验结果极佳的一致性。