Enhancing stochastic multi-microgrid operational flexibility with mobile energy storage system and power transaction

With the increased uncertainty and variability of net load induced from high penetrations of renewable energy, independent operation of single microgrid (MG) is facing great operational problems such as high operation cost, low self-consumption of local renewable energy and exacerbating peak and valley load. In this paper, a mobile energy storage system (MESS) and power transaction-based flexibility enhancement strategy is proposed for interconnecting multi-microgrid (MMG) considering uncertain renewable generation. The MESS can move between different microgrids by a truck, and we use this temporal-spatial flexibility to provide charging/discharging service for MMG. Then, the Aumann-Shapley is developed for expenses allocating in MMG system with MESS and power transaction due to ensuring the fairness and reasonableness is of the utmost important in collaborative operation. After that, the expected power not served (EPNS) and expected power curtailment (EPC) are derived as the risk measure to evaluate the uncertain renewable energy from the perspective of risk aversion. Numerical studies show that MESS for MMG operation enables the reduction in total operational cost of diesel generator by 23.58%, the improvement in total grid connection volumes of wind and solar by 7.17%, and the improvement in smoothness of the total load curve by 0.92%. Besides, interconnected system for MMG operation enables the improvement in total grid connection volumes of wind and solar by 6.69%, and the improvement in smoothness of the total load curve by 1.50% in comparison with the unconnected system.

Automated summary

This paper proposes a flexibility enhancement strategy based on a mobile energy storage system and power transactions for interconnecting multiple microgrids, addressing the uncertainty issues caused by renewable energy penetration. Numerical studies demonstrate the effectiveness of the approach in reducing operational costs and improving system performance.