2 power sharing strategies have considered the impacts of DG output impedances, feeders and local loads. However, in a networked (multi-bus) microgrid, besides above mismatched factors, the networked structure is also an important factor that affects the system reactive power sharing. Without a complete consideration of these mismatched factors, previous methods can't work properly as desired in networked microgrids.To solve the reactive power sharing issue in networked microgrids, communication based solutions become shortcuts. In [19], [20], intercommunication among DG units is utilized to improve the reactive power sharing accuracy. However, this manner is subject to the DG install locations. Synchronizing signals are utilized in [21]-[23] to trigger an extra regulation for reactive power sharing, but the control performance is easy to be influenced if load changes during the regulation period. With the communication between microgrid central controller (MCC) and DG units, reactive power sharing methods based on set-point regulation, also known as secondary control [24]-[28], can be well applied in networked microgrids. With a similar communication mechanism, virtual impedances can also be adjusted to realize reactive power sharing [29]-[31]. However, it seems that the communication based virtual impedance methods have no significant benefits compared with set-point regulation methods.Although communication can help improving the reactive power sharing accuracy, it also introduces some new issues, such as cost increase and expansion capability decrease. In this paper, a wireless reactive power sharing control strategy that employs optimized virtual impedance controllers and local load measurements is proposed for networked microgrids. Based on the microgrid network modeling, the cause of reactive power sharing issue is revealed. Meanwhile, an estimation method for network reactive power sharing error is proposed. Through the estimation method based network feature analyses, virtual impedance controller is designed accordingly; then detailed controller parameters are optimized by using genetic algorithm (GA), which is to introduced to minimize the system global reactive power sharing error. The optimization process is performed offline in microgrid configuration stage. With the optimized virtual impedance controllers, DG units can well share the loads in microgrid. Throughout the whole strategy, communication is not used; instead, local load measurement is added for the virtual impedance control, which has no effect on the wireless manner of droop control. Finally, simulation and experimental results are provided to verify the proposals. 0885-8993 (c)
