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结合多状态软开关调控与网络重构的配电网最优故障恢复
Optimal Fault Recovery in Distribution Networks with Multi-State SOP Regulation and Network Reconfiguration
【目的】柔性互联配电网遭遇故障停运后，通过软开关（soft open point，SOP）等设备可以快速、合理地进行功率转供或孤岛运行。然而现有研究暂未考虑柔性设备的不同控制状态对恢复结果的影响，常见孤岛预划分方法也难以确定柔性互联设备支撑的孤岛半径和恢复优先级。针对互联设备的可行控制方式，提出了基于SOP等效模型的故障恢复策略。【方法】首先设计含多种控制方式的SOP潮流交替迭代算法，以计算恢复后的功率与电压分布。其次以SOP控制方式选择以及非预设重构为优化手段，以最小化加权运行损失为目标，得到综合考虑潮流约束与多端口SOP模式约束的恢复模型。最后针对寻优范围增加，采用协同图拉普拉斯算子的遗传算法进行求解。基于互联的双IEEE 33系统算例进行了故障后恢复效果验证。【结果】结果表明：针对不同线路停运后的拓扑变动及分布式电源出力情况，所提方法能够形成相应的非预设重构方案，并灵活调整不同位置的SOP控制方式进行协同，负荷恢复比例较重构方式提升14%。【结论】非预设网络重构带来了更高的故障后负荷恢复比例，结合优化SOP的控制状态可取得更优的恢复后电压分布，从而支撑柔性互联配电网的高供电韧性。
[Objective] Following fault-induced outages in flexible interconnected distribution networks，devices such as Soft Open Points （SOPs） can enable rapid and coordinated power rerouting or support islanded operation. However，existing studies overlook the impact of different control states of flexible devices on restoration performance. Moreover，conventional predefined islanding schemes have limited capability in determining the effective support radius and restoration priority enabled by SOP. To address issues related to the feasible control strategies of interconnected devices，this paper proposes a fault restoration strategy based on the equivalent model of the SOP. [Methods] An alternating iterative power flow algorithm is developed to incorporate SOP with multiple control modes and to compute the post-restoration power and voltage distribution. By jointly optimizing SOP control mode selection and non-predefined network reconfiguration，a restoration model is established with the objective of minimizing weighted operational losses，while fully considering power flow constraints and multi-terminal SOP control limitations. To efficiently solve the resulting large-scale optimization problem，a genetic algorithm enhanced with a cooperative graph Laplacian operator is employed for efficient solution. Post-fault restoration performance was evaluated on an interconnected dual IEEE 33-bus test system. [Results] The results demonstrate that，in response to different topological changes and distributed generation outputs after line outages，the proposed method can dynamically generate appropriate non-predefined reconfiguration schemes. It also enables coordinated adjustment of SOP control strategies at different locations. Compared to conventional reconfiguration approaches，the proposed strategy improves the load restoration ratio by 14%. [Conclusions] The non-predefined network reconfiguration contributes to a higher post-fault load restoration ratio. When combined with optimized SOP control states，it yields a more favorable post-restoration voltage profile and supports high supply resilience in flexible interconnected distribution networks.
柔性互联配电网 / 故障恢复 / 多状态软开关 / 韧性 / 图拉普拉斯算子
flexible interconnected distribution network / fault restoration / multi-state soft open point / resilience / graph Laplacian operator
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A two-stage, recovery strategy for distribution networks pre- and post-disasters is proposed to address the issue of transmission-line failures caused by extreme events (such as extremely cold weather and typhoons) which result in a significant loss of power in the distribution network, considering the coordination of battery-charging switching stations (BCSS) for electric vehicles. We analyzed the feasibility of the BCSS participation in the pre-to post-disaster distribution-network restoration and two-stage, restoration architecture and constructed a refined energy-transfer link model for BCSS; a thermal-management system was constructed considering the impact of a low-temperature environment. We proposed a two-stage, recovery strategy for a distribution network that considers the BCSS before and after a disaster. In the pre-disaster stage, the allocation of battery packs was decided. In the post-disaster stage, based on the remaining resource power-supply potential—the objective function was the maximization of the overall economic optimization to ensure a stable load operation. Finally, numerical simulations were conducted using the improved IEEE33 node and 123 node-distribution networks as examples. The results indicated that the proposed strategy is both feasible and superior and could improve the recovery rate of important loads in the distribution network while ensuring lower recovery costs. |
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近年来台风、暴雨等极端天气对电力系统的安全造成巨大影响,电力系统的弹性成为人们关注的热点。配电系统弹性是系统应对极端事件的预防、抵御、响应及快速恢复供电的能力。提出了一种考虑智能软开关(soft open point,SOP)和分布式电源(distributed generation, DG)的配电系统弹性提升方法,在多阶段弹性提升过程中考虑了DG规划、主动孤岛运行、SOP快速故障隔离和供电恢复。首先建立了SOP数学控制模型和考虑SOP的配电网供电恢复模型;然后提出了多阶段弹性评估指标和方法,建立了含SOP的多阶段混合整数线性规划模型,并考虑了每个阶段的网络拓扑和操作约束;最后在IEEE 33标准算例上进行分析计算,验证了所提弹性提升方法的有效性。
In recent years, extreme weather events, such as typhoons and rainstorms, have greatly impacted the security of power systems, and the resilience of power systems has gradually become the focus of attention. The resilience of a distribution system is its ability to prevent, resist, respond to, and quickly restore power supply in response to extreme events. This paper proposes a method to improve the resilience of a distribution system by considering the soft open point (SOP) and distributed generation (DG). The DG planning, active islanding, SOP fast fault isolation, and power supply recovery capability are considered in the multi-stage power supply recovery process. First, an SOP mathematical control model and a distribution network fault recovery model considering the SOP are established. Second, a multi-stage resilience evaluation index and method are proposed, a multistage mixed integer linear programming model with SOP is established, and the network topology and operation constraints of each stage are considered. Finally, the effectiveness of the proposed resilient lifting method is verified using the IEEE 33 standard example. |
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电网公司已形成了输变配电设备资产运维检修标准成本体系,为适应成本监审、科学配置资源投入奠定了基础。由于配电网设备资产规模大,运维检修作业内容及频次繁琐,运维检修成本结构模糊,导致运维检修成本配置合理性仍存在不足,尚无法支撑成本精益管理。针对配电网运维检修成本配置问题,提出了基于层次分析法(analytic hierarchy process,AHP)-熵权法的配电网设备资产运维检修成本优化配置模型。基于配电网运维检修成本关键影响因素,建立了成本优化配置评价指标体系;兼顾成本投入合理性和有效性,采用熵权法对优化配置评价指标赋权重,构建区域配电网设备资产运维检修成本优化配置模型,合理有效分配各区域运维检修成本;以某省14家地市单位为例,验证了该模型的有效性及实用性。该模型能够较为合理地对配电网运维检修成本分配进行优化,并对比发现现有分配比例存在的问题,对配电网实际运维检修成本策略的制定有一定的参考借鉴作用。
In recent years, power grid companies have formed a standard cost system for the operation and maintenance of transmission, transformation and distribution equipment assets, which lays the foundation for adapting to cost supervision and auditing and scientifically allocating resource input. However, the assets of distribution network equipment are large, the content and frequency of operation and maintenance work are cumbersome, and the cost structure of operation and maintenance is ambiguous. As a result, the rationality of operation and maintenance cost allocation is still insufficient, and it is still unable to support lean cost management. Aiming at the problem of distribution network operation and maintenance cost allocation, an optimal allocation model of operation and maintenance cost of distribution network equipment asset, which is based on AHP and entropy weight method, is proposed. Firstly, according to the key influencing factors of the distribution network operation and inspection cost, an evaluation index system for cost optimization configuration is established. Then, taking into account the rationality and effectiveness of the cost input, the entropy weight method is used to weight the optimal configuration evaluation index, and an optimal configuration model of operation and maintenance cost of equipment assets in the regional distribution network is constructed to reasonably and effectively allocate the regional operation and maintenance cost. Finally, taking 14 prefecture-level units in a province as an example, the validity and practicability of the model are verified. The model can reasonably optimize the distribution of operation and maintenance cost in the distribution network, and find the problems in the existing distribution ratio, which has a certain reference for the formulation of the actual operation and maintenance cost strategy of the distribution network. |
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