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海岛配电网应对风灾灵活资源动态应急优化调控OA

Dynamic Emergency Optimization and Control of Flexible Resources for Island Distribution Network to Cope With Wind Disasters

中文摘要英文摘要

在台风天气影响下,海岛受地理位置的制约,更容易受灾害影响,并且海岛的可再生能源更丰富,因此如何保证海岛微电网的可靠并且经济性运行尤为重要.考虑台风对于海岛地区的配电网影响,并根据海岛地区的负荷分布情况、可再生能源储备发电情况和移动应急电源车调配情况,在保证配电网稳定运行的前提下,结合维修团队的调度,以海岛配电网负荷损失最小、配电网电压稳定性更高为目标进行灵活资源应急调控,建立了考虑台风天气下海岛微电网的多目标优化调度模型.并采用改进粒子群算法来求得全局最优解,通过对算法中的惯性因子和学习因子进行优化,为避免陷入局部最优解,采用动态密集距离排序方式更新非劣解集,提高该算法的求解精度和全局寻优能力.将改进粒子群算法运用到实际算例中,算例结果表明该优化调度模型的可行性和有效性.

Under the influence of typhoon weather,islands,constrained by geographical conditions,are more vulnerable to disasters.Moreover,islands possess richer renewable energy resources,making it particularly crucial to ensure the reliable and economical operation of island microgrids.Considering the impact of typhoons on island power distribution networks,and based on the load distribution,renewable energy reserves,and mobile emergency power supply vehicle deployment in island areas,a multi-objective optimal scheduling model is established for island microgrids under typhoon conditions.The model aims to minimize load loss and enhance voltage stability in the distribution network while ensuring stable operation.By coordinating maintenance teams,flexible emergency resource regulation is implemented.An improved particle swarm optimization algorithm is employed to obtain the global optimal solution.Through optimization of inertia and learning factors in the algorithm,dynamic dense distance sorting is used to update the non-dominated solution set,improving the algorithm's accuracy and global optimization capability.Applied to practical case studies,the results demonstrate the feasibility and effectiveness of the optimized scheduling model.

郭乾;吴龙腾;吴杰康;张彬

广东电网有限责任公司电力调度控制中心,广州 510060广东电网有限责任公司电力调度控制中心,广州 510060广东工业大学自动化学院,广州 510006广东工业大学自动化学院,广州 510006

信息技术与安全科学

台风灾害海岛电网灵活资源动态应急优化调控改进粒子群算法

typhoon disastersisland distribution networkflexible resourcesdynamic emergency optimization and controlimproved particle swarm optimization algorithm

《南方电网技术》 2026 (7)

35-45,11

广东省基础与应用基础研究基金区域联合基金项目--粤港澳研究团队项目(2020B1515130001)中国南方电网有限责任公司科技项目(036000KK52222036(GDKJXM20222392)). Supported by Guangdong Basic and Applied Basic Research Foundation(2020B1515130001)the Seience and Technology Project of China Southern Power Grid Co.,Ltd.(036000KK52222036(GDKJXM20222392)).

10.13648/j.cnki.issn1674-0629.2026.07.004

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