Optimal Scheduling Strategy for Microgrid Clusters: Under the Cloud-Edge Collaborative Control Architecture
Manying Zhang, Mohan Lin, Zhesheng Hu, Mingyang Tu, Ling Lin, Zao Tang · 2023
The discrete access of many distributed resources makes collaborative management difficult. The effective management of distributed resources in the form of microgrid can significantly improve the consumption capacity of renewable energy and the economic level of the system. Therefore, this paper studies the optimal management strategy of multi-microgrids (MGs) taking into account the cloud-edge collaborative (CEC) control. First, MG cluster is divided into subregions around the CEC architecture system. The power gain/loss is also analyzed and a CEC control mode is established. Subsequently, based on the proposed architecture, centralized control of multi-MGs is performed to reduce the energy demand of the whole system from the external distribution network and improve the economic operation of the system. Then, a model of distributed microgrid dispatch is built. The objective is to minimize the operational costs of the MG cluster while considering unit output constraints and power balance constraints. Finally, a case study is conducted to verify the model. The results indicate that the proposed approach facilitates the optimal energy management among MG clusters, ensuring the economic viability of the comprehensive energy system in multi-MGs.