Traditional algorithms, such as Perturb and Observe (P&O), Incremental Conductance (IC), Beta and others, have commonly been used to perform the maximum power point tracking (MPPT) in photovoltaic (PV) system. On the other hand, the overall system performance can be largely impaired when PV systems are subjected to partial shading conditions, once, usually, traditional algorithms operate at the local MPP (LMPP) instead of the global MPP (GMPP). Therefore, to deal with partial shading conditions in PV arrays, this paper presents a comparative analysis involving MPPT algorithms bio-inspired on the Bat-based optimization technique, which are able to reach the GMPP. However, in most metaheuristic algorithms, the methodology employed to achieve the GMPP can lead the system to present high PV power oscillations, even for small variations on solar irradiation. Thus, to reduce power oscillations and improve the PV systems performances, combinations of the Bat-based algorithm with traditional algorithms (P&O, IC and Beta) are proposed. The proposed MPPT algorithms, named in this paper as Bat-P&O, Bat-Beta and Bat-IC, are evaluated and compared to each other by employing a dc-dc Boost converter. Finally, by means of experimental and simulation results, the performance and effectiveness of the Bat-based MPPT techniques are evaluated.

传统算法（例如扰动和观测（P＆O），增量电导（IC），Beta等）通常用于在光伏（PV）系统中执行最大功率点跟踪（MPPT）。另一方面，当PV系统处于部分阴影条件下时，整个系统的性能可能会大大受损，通常，传统算法通常在本地MPP（LMPP）而非全局MPP（GMPP）下运行。因此，为了应对光伏阵列中的部分阴影条件，本文提出了一种比较分析，涉及基于Bat优化技术的生物启发式MPPT算法，该算法能够达到GMPP。但是，在大多数元启发式算法中，用于实现GMPP的方法可能导致系统呈现高PV功率振荡，即使是太阳辐射的微小变化。因此，为了减少功率振荡并提高光伏系统的性能，提出了基于Bat的算法与传统算法（P＆O，IC和Beta）的组合。通过使用DC-DC Boost转换器对本文中命名的MPPT算法（在本文中命名为Bat-P＆O，Bat-Beta和Bat-IC）进行了评估并进行了比较。最后，通过实验和仿真结果，评估了基于蝙蝠的MPPT技术的性能和有效性。通过使用dc-dc Boost转换器评估和相互比较。最后，通过实验和仿真结果，评估了基于蝙蝠的MPPT技术的性能和有效性。通过使用dc-dc Boost转换器评估和相互比较。最后，通过实验和仿真结果，评估了基于蝙蝠的MPPT技术的性能和有效性。