Jiangang Lu ¹ Hongwei Du ² Ruifeng Zhao ^1* Haobin Li ¹ Yonggui Tan ² Wenxin Guo ¹

• ¹ Power Dispatching and Control Center of Guangdong Power Grid, Guangzhou, China
• ² NARI Group Co. Ltd, Nanjing, China; NARI Technology Nanjing Control Systems Co, Ltd, Nanjing, China, Nanjing, China

Integrating distributed generations (DGs) into distribution networks poses a challenge for active distribution networks (ADNs) when managing distributed resources for optimal scheduling. To address this issue, this paper proposes a hierarchical scheduling approach based on a multi-microgrid system. It starts with a CNN-LSTM-based source-load forecasting model to address the impact of source-load uncertainties on the power grid scheduling. Then, an optimal two-layer dispatching framework for ADNs and microgrids is introduced using predicted source-load information. The upper layer is responsible for optimizing the power interactions between the main grid and the connected microgrids, while the lower layer focuses on minimizing the operational costs of microgrids. The effectiveness of the proposed scheduling strategy is verified via case studies performed on a modified IEEE 33-node distribution network. The results show that the network loss of the main grid and the operation costs of microgrids are reduced by 17.31% and 32.81% after the microgrid is integrated into the active distribution network. And Peak-valley difference of microgrid decreased by 13.12%. The simulation shows a significant reduction in operational costs and load fluctuations after implementing the proposed two-layer scheduling strategy. The seamless coordination between the upper and lower layer allows for the precise adjustment of transfer power, alleviating peak load demand and minimizing network losses in the ADN system.