A cooperative game approach for energy management of interconnected microgrids

This paper proposes a cooperative game to schedule the day-ahead operation of multi-microgrid (MMG) systems. In the proposed model, microgrids are scheduled to achieve a global optimum for the cost of the multi-microgrid system. The minimum cost is achieved by transactions of microgrids with each other. Also, price-based demand response is implemented in the model to build a cost-reducing opportunity for consumers. Applying Shapley value, the optimum cost of the MMG system is fairly allocated between microgrids. To enhance the confidence level of results, data uncertainties are incorporated into the model. The uncertainties of renewable outputs, demand, and prices of trading with the main grid are applied into the model. The presented model is developed as a mixed-integer nonlinear programming problem, and its efficiency is evaluated on a standard test system containing three microgrids. The cost of the MMG system when microgrids form a cooperative game is compared with the isolated status that microgrids do not transact energy with each other. The results indicate that the cost of the MMG is declined using the proposed cooperative model in comparison with the isolated mode. Also, the cost of microgrid1, microgrid2, and microgrid3 are improved by 2.4, 2.7, and 11.8%, respectively.

Automated summary

This paper proposes a cooperative game model for scheduling the day-ahead operation of multi-microgrid systems. By integrating transactions between microgrids, the model aims to achieve a global optimum for system cost. Price-based demand response is implemented to provide cost-reducing opportunities for consumers. The model incorporates data uncertainties to enhance result reliability. The study shows that implementing the cooperative model can reduce overall system cost and improve performance of individual microgrids.