电气技术  2020, Vol. 21 Issue (10): 15-20    DOI:
研究与开发 |
基于网损估计的系统恢复新方法
唐晓健, 林济铿, 郭其一
同济大学电信学院电气工程系,上海 201804
A new system recovery algorithm based on network loss estimation
Tang Xiaojian, Lin Jikeng, Guo Qiyi
College of Electronic and Information Engineering, Tongji University, Shanghai 201804
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摘要 黑起动系统恢复是电网停电情况下尽快恢复系统且减少经济损失的最关键技术之一,如何合理有效地制定最优黑起动系统恢复方案一直是电力系统领域十分重要的研究课题。本文提出一种完整的系统恢复新算法,首先构建以停电损失最小为目标函数的完整恢复新模型,并计及相关约束;然后为得到最优系统恢复方案且防止最优潮流不收敛,提出基于网损估计的两阶段求解策略,第一阶段建立并求解考虑网损的系统恢复线性模型,第二阶段利用以网损最小为目标函数的最优潮流优化并调整上层所得方案;最后本文以IEEE 39节点算例验证了本文算法的有效性。
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关键词 黑起动系统恢复网损线性规划最优潮流    
Abstract:Blackstart system recovery is one of the most critical technologies to recover as quickly as possible and reduce economic losses in the event of a power outage. How to formulate an optimal blackstart system recovery plan reasonably and effectively has been a very important research topic in power systems. This paper presents a complete new algorithm for system recovery. First, a new model of complete recovery with the minimum power outage as the objective function is constructed, taking into account the relevant constraints. In order to obtain the optimal system recovery plan and prevent the optimal power flow from converging, a two-stage solution strategy based on network loss estimation is proposed: the first stage establishes and solves the system recovery linear model considering the network loss; the second stage uses the network loss The minimum is the optimal power flow optimization of the objective function and adjustment of the upper-level program. Finally, an IEEE 39 node example is used to verify the effectiveness of the algorithm.
Key wordsblackstart    system recovery    network loss    linear programming    optimal power flow (OPF)   
收稿日期: 2020-04-14     
基金资助:国家自然科学基金资助项目(51177107); 国网福建省电力有限公司科技项目(SGFJDK00DWJS1800211)
作者简介: 唐晓健(1996-),男,上海市人,硕士研究生,主要从事电力系统黑起动研究工作。
引用本文:   
唐晓健, 林济铿, 郭其一. 基于网损估计的系统恢复新方法[J]. 电气技术, 2020, 21(10): 15-20. Tang Xiaojian, Lin Jikeng, Guo Qiyi. A new system recovery algorithm based on network loss estimation. Electrical Engineering, 2020, 21(10): 15-20.
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