Rank‐based energy scheduling strategy of networked microgrids in distribution systems

Microgrids (MGs) have emerged as a key platform for integrating distributed energy resources into distribution systems. However, a high penetration of renewable energy resources in an MG causes an imbalance frequently between energy generation and load. One solution to this problem is internal energy trading among MGs, where MGs trade (i.e. buy or sell) energy with other MGs in the network. In internal trading, multiple buyer MGs may compete to obtain energy from seller MGs with surplus energy. By contrast, seller MGs also compete to sell their surplus to those confronted with a deficit. Considering this scenario, we propose a novel rank‐based energy scheduling strategy for networked MGs in a distribution system to solve the competition between buyer and seller MGs. The technique for order of preference by similarity to the ideal solution method, which is a multi‐criteria decision‐making approach, is applied to prioritise the MGs. The proposed strategy determines the amount of internal energy to trade for each seller/buyer MG. Different from existing mechanisms, the proposed rank‐based approach evaluates each MG with respect to four criteria: ratio of energy, forecasting accuracy, contribution of supply, and historical performance. The proposed strategy is compared with existing no‐rank‐based scheduling and absolute contribution‐based method. Moreover, the effect of each criterion on the cost of each MG is illustrated by considering and disregarding the criterion in the proposed strategy that demonstrates the effectiveness of the proposed strategy in reducing the cost of MGs according to their rank in the network.