Multi-objective Collaborative Optimization Control Method of Composite Function Grid Connected Inverters Considering Variable Weight Hybrid Decision Evaluation

Multi-functional grid connected inverter (MFGCI) has the ability to solve various power quality problems in the distribution network while fulfilling the power tracking task simultaneously, but this ability is often limited by its compensation capacity that can be used for power quality management. Based on the control structure of MFGCI, this paper provides the current compensation order and grid connection tracking current order without PLL. A multi-objective collaborative optimization method based on variable weight hybrid decision evaluation is proposed to better adapt to the fluctuations in power quality indicators caused by uncertainty in new energy and nonlinear load integration. A multi-objective function is constructed to achieve the best power quality compensation effect and the minimum required compensation capacity, an optimization algorithm based on the multi-objective artificial hummingbird algorithm (MOAHA) update mechanism is employed to solve the optimal capacity allocation coefficient for compensating various power quality problems. The correctness and effectiveness of the proposed method are verified through simulations in various scenarios.