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The government’s support for rooftop photovoltaic systems has significantly increased their installed capacity, leading to the creation of numerous independent microgrids (MGs). However, multi-microgrids (MMGs), which comprise these MGs, often do not share operational data with neighboring microgrids. This lack of information can lead to congestion at the common coupling point, particularly at midnight when energy prices are low, an issue that this paper addresses for the first time. This paper will break the day into two scales: daytime and nighttime. Then, to manage the congestion, it will introduce a nighttime energy storage charging market managed by an aggregator. This charging market has two levels: at the first level, each MG will optimize its energy storage charging bids, and at the second level, the aggregator will form a supply curve to settle the nighttime charging market to minimize the costs of MMGs while managing congestion. To allocate congestion costs, the aggregator will form supply and bid curves for all possible coalitions. Then based on the ’pay as cleared’ market concept, it will allocate these costs/profits using a developed Shapley value. A comparison of the proposed method with the centralized method indicates that the proposed methodology yields an optimal solution while the privacy of MGs is required. The effectiveness of this methodology is validated through a case study using real data from Australia.