In photovoltaic systems, the output power curve of solar battery has multiple peaks, under the partially shaded condition. Traditional maximum power point tracking (MPPT) search method often traps in local extremum, which causes the loss of the global maximum power point even generates oscillation and leads to instability of output. An improved bat algorithm (IBA) is proposed and used to find global optimal point, by introducing chaos search strategy in initial arrangement which can improve the uniformity and ergodicity. The self-adapting weight is introduced to enhance the global searching ability of previous processing and the local searching ability of late processing, and Levy flight is introduced in the same time to create the saltation velocity to jump out the local extremum. Dynamic contraction is also used to decrease the search section more effectively, so as to avoid premature convergence of the population affected by the local extremum. The simulation shows that modified bat algorithm can find the global optimal point fast, with high precision, under the partially shaded condition.