文章摘要
王智冬,娄素华,范臻,等.基于机会约束规划的含大规模风电电力系统阻塞调度优化[J].电力系统自动化,2019,43(23):147-154. DOI: 10.7500/AEPS20181219003.
WANG Zhidong,LOU Suhua,FAN Zhen, et al.Chance-constrained Programming Based Congestion Dispatching Optimization of Power System with Large-scale Wind Power Integration[J].Automation of Electric Power Systems,2019,43(23):147-154. DOI: 10.7500/AEPS20181219003.
基于机会约束规划的含大规模风电电力系统阻塞调度优化
Chance-constrained Programming Based Congestion Dispatching Optimization of Power System with Large-scale Wind Power Integration
DOI:10.7500/AEPS20181219003
关键词: 阻塞调度  运行风险  机会约束规划  风电接入  再度阻塞
KeyWords: congestion dispatching  operational risk  chance constrained programming  integration of wind power  re-congestion
上网日期:2019-08-27
基金项目:国家重点研发计划资助项目(2016YFB0900100);国家电网公司科技项目(5102-201956304A-0-0-00);国家自然科学基金资助项目(51677076)
作者单位E-mail
王智冬 国网经济技术研究院有限公司, 北京市 102206 shlou@mail.hust.edu.cn 
娄素华 华中科技大学电气与电子工程学院, 湖北省武汉市 430074
强电磁工程与新技术国家重点实验室(华中科技大学), 湖北省武汉市 430074 
 
范臻 国网重庆市电力公司检修分公司, 重庆市 400039  
吴耀武 华中科技大学电气与电子工程学院, 湖北省武汉市 430074
强电磁工程与新技术国家重点实验室(华中科技大学), 湖北省武汉市 430074 
 
杨印浩 华中科技大学电气与电子工程学院, 湖北省武汉市 430074
强电磁工程与新技术国家重点实验室(华中科技大学), 湖北省武汉市 430074 
 
摘要:
      电力市场环境下,接入风电的不确定性增大了系统输电阻塞出现的概率。采用现有的确定性方法进行输电阻塞调度,会导致部分重载线路接近热稳定极限;若风电出力预测产生偏差,系统在实时运行中可能再度出现阻塞。为解决阻塞问题并使系统具备一定的抵御再度阻塞的能力,提出一种新的阻塞调度模型,该模型将风电出力预测误差作为随机变量,形成了模拟实时运行不确定性的机会约束条件;同时,模型计及了期望缺电、弃风风险指标,实现了阻塞调度中功率调整与旋转备用的联合优化。基于蒙特卡洛方法提出了不确定性风电并网导致的系统再度阻塞的量度方法和指标,通过IEEE RTS 24节点系统算例证明了所提模型的有效性。
Abstract:
      In the power market, the uncertainty of wind power integration increases the probability of system transmission congestion. The existing deterministic methods for transmission congestion dispatching will lead to some transmission lines close to the thermal stability limit. Furthermore, when the forecasting errors of wind power exist, the system would be re-blocked in real-time operation. In order to eliminate the system transmission congestion and make the system be able to resist re-congestion, a new congestion dispatching model is put forward, in which the forecasting errors of wind power are considered as random variables, and chance-constrained conditions for simulating the uncertainty is formed in real-time operation. Meanwhile, the indices of expected demand not supplied and risk of abandoning wind power are taken into account for co-optimizing power adjustment and spinning reserves in congestion dispatching. Based on Monte Carlo method, method and indices are presented for measuring the system re-congestion caused by the uncertainty of wind power integration. Based on IEEE RTS 24-bus system, the effectiveness of the proposed model is illustrated.
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