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Improved WOA-Based Multilevel Resource Coordinated Scheduling Strategy for Active Distribution Network

Rongyi Niu1,2, Chong Li1,2,*, Gang Gu1,2, Qunhui Hu1,2
1 NARI Technology Co., Ltd., Nanjing, China
2 NARI Nanjing Control System Co., Ltd., Nanjing, China
* Corresponding Author: Chong Li. Email: email

Energy Engineering https://doi.org/10.32604/ee.2026.076567

Received 22 November 2025; Accepted 09 January 2026; Published online 29 January 2026

Abstract

To address the operational complexity caused by the high proportion of new energy integration into distribution networks, a multilevel resource-coordinated operation strategy based on an improved whale optimization algorithm (improved WOA) is proposed for active distribution networks (ADNs). A bilevel optimization model is established to ensure the economic and safe operation of ADNs. The upper level is used to minimize the total system operation cost, while the lower level is used to optimize the power balance. Subsequently, the improved WOA, integrated with an adaptive weight and chaotic disturbance mechanisms, is used to solve the bilevel model and obtain a multi-resource coordinated operation strategy. This framework can help to enhance convergence and avoid local optima. In the simulation section, the IEEE 33-bus system is used to test the performance of the multilevel resource coordinated operation strategy. The simulation results reveal that the proposed approach can reduce the total system operation cost to 9.72 × 104 CNY. Moreover, the fossil fuel consumption of the diesel generator and the charging cost of electric vehicles are reduced by 15% and 18%, respectively. In addition, the power supply–demand matching accuracy is increased to 99.8%. Compared with the multi-element heuristic algorithm, the improved WOA shows significant superiority and robustness. This research provides an economical and stable multi-resource coordinated scheduling solution for distribution networks with a high proportion of renewable energy.

Keywords

Active distribution network; multilevel resources; whale optimization algorithm; comprehensive scheduling
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