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Multi-Objective Hierarchical Optimal Control of Active Distribution Network with Wind， Solar， and Energy Storage
XU Yanchun, LI Jialou, XI Lei, ZHANG Tao, WANG Lingyun, MI Lu
Electric Power Construction ›› 2026, Vol. 47 ›› Issue (11) : 128-147.
PDF(2230 KB)
PDF(2230 KB)
Multi-Objective Hierarchical Optimal Control of Active Distribution Network with Wind， Solar， and Energy Storage
[Objective] To address severe net load fluctuations， high renewable curtailment， and voltage deviations in active distribution networks caused by penetration of distributed generation （DG）， this paper proposes a hierarchical coordinated multi-objective optimization method that integrates energy storage system （ESS） scheduling with active distribution network operational optimization. [Methods] A hierarchical optimization framework based on an iterative coordination mechanism was established. In the upper layer， a composite objective considering ESS economic benefits and net load peak-shaving performance was formulated. A dynamic weighting adjustment mechanism based on load fluctuation characteristics was introduced， and an improved whale optimization algorithm （IWOA） was employed to determine the day-ahead charging and discharging strategies of the ESS. In the lower layer， a multi-objective model aimed at minimizing network power losses， node voltage deviations， and renewable energy curtailment was constructed. An improved multi-objective particle swarm optimization （IMOPSO） algorithm was adopted to coordinate reactive power compensation devices， distributed generation outputs， and ESS power allocation. Coordination between the two layers was achieved through alternating iterations and information feedback. [Results] Simulation results on an improved IEEE 33-node active distribution network system using MATLAB demonstrate that the proposed method yields a daily energy storage revenue of RMB 427.4 and a peak-shaving and valley-filling rate of 15.1%. It reduces total network loss to 1，796.3 kWh， total renewable energy curtailment to 1，725.2 kWh， and the sum of squared voltage limit violations to 0.001， thereby effectively alleviating voltage deviations. The method exhibits strong adaptability and outstanding comprehensive benefits under diverse load fluctuation conditions. [Conclusions] The proposed hierarchical coordinated optimization framework effectively addresses the operational challenges introduced by high DG penetration， significantly enhancing the operational efficiency and renewable energy accommodation capability in active distribution networks. The method features satisfactory computational efficiency and practical applicability， providing robust technical support for optimal operation under complex conditions.
active distribution network / energy-storage system / peak shaving and valley filling / reactive power optimization / hierarchical optimization / dynamic weighting mechanism
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In order to get the accurate scheme of optimal islanding partition in distribution network and accurately evaluate the beneficial effect of distributed generation access on improving the reliability of distribution network. A multi-time dynamic islanding model based on mixed-integer linear programming （MILP） is proposed. On the basis of sequential Monte Carlo simulation， a reliability evaluation process considering dynamic islands under fault conditions is proposed. The dynamic islanding partition model takes into account the fluctuation of distributed generation and load， and establishes the power sequential model of distributed generation and load. The radial topology of islands during fault is guaranteed by establishing linear logic constraints of branch power and node state. Taking the improved RBTS-BUS6 system as example， the reliability of active distribution network（ADN）with distributed solar power and energy storage is analyzed. The results show that the proposed power island model can restore power supply to a maximum extent and effectively improve the reliability level of distribution network.
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为响应“碳达峰、碳中和”的号召,兼顾分布式能源（DG）参与下配电网运行的经济性和环保性,该文构建一种含DG的配电网双层优化模型。该模型以DG投资运行成本及环境效益为上层目标对DG进行优化配置,并以网损和电压偏移度成本为下层目标对配电网进行无功优化。针对模型特点,提出改进麻雀算法进行模型求解,增加Tent混沌映射初始化种群,引入萤火虫扰动机制改进操作算子并优化越界处理机制维持种群多样性。仿真结果表明,该模型能有效提高配电网运行的经济环保性,并验证了改进麻雀算法在求解复杂非线性非凸含离散变量的复杂组合优化问题上的优势。
In response to the call of "carbon peaking, carbon neutralization", considering the economy and environmental protection of distribution network operation with distributed generation（DG）, this paper constructs a bi-level optimization model of distribution network with DG. In this model, DG investment and operation cost and environmental benefits are taken as the upper objectives to optimize the configuration of DG, and network loss and voltage offset cost are taken as the lower objectives to optimize the reactive power of distribution network. According to the characteristics of the model, an improved sparrow search algorithm is proposed to solve the model, adding tent chaotic map to initialize the population, introducing firefly disturbance mechanism to improve the operator, and optimizing the cross-border processing mechanism to maintain the population diversity. The simulation results show that the model can effectively improve the economic and environmental protection of distribution network operation, and verify the advantages of the improved sparrow search algorithm in solving complex high-dimensional nonlinear non-convex combinatorial optimization problems with discrete variables.
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利益冲突声明（Conflict of Interests）： 所有作者声明不存在利益冲突。
作者贡献声明（Authors' Contributions）： 徐艳春进行了研究设计；李家楼进行对比实验、文献调研与整理并完成实验和数据分析；席磊确定研究对象范围、收集数据；张涛参与了论文写作和修订；王凌云参与撰写论文、绘制图谱；Mi Lu参与修订论文、审核论文。所有作者均阅读并同意了论文终稿内容。
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