The management of active and reactive power has become more and more complex due to the increasing integration of distributed photovoltaic (PV) into the distribution network. To address this issue, the Multi-objective Probabilistic Group Search Optimizer (MPGSO) for coordinating active-reactive power in distribution networks with distributed PV is proposed in this paper. The MPGSO utilizes a crowding probabilistic operator to select producers, enabling the population to explore areas with higher potential but less crowding and reducing the number of fitness function calculations. Furthermore, a new parameter selection strategy based on chaotic sequences with limited computational complexity is employed to escape local optimal solutions. Simulation studies were conducted on a modified IEEE 33-bus system to verify the effectiveness of MPGSO. Metrics comparisons were made with the original GSOMP and NSGA-II, which demonstrated that MPGSO provides high quality Pareto solutions for decision-makers and effectively improves operational reliability and economics.