引用本文:黄裕春,杨 燕,文福拴,李 力,王 珂,高 超.计及风险控制的多区域ATC概率优化协调决策模型与方法[J].电力自动化设备,2013,33(3):
HUANG Yuchun,YANG Yan,WEN Fushuan,LI Li,WANG Ke,GAO Chao.Coordinated probabilistic optimal decision-making model for multi-area ATC with risk control[J].Electric Power Automation Equipment,2013,33(3):
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计及风险控制的多区域ATC概率优化协调决策模型与方法
黄裕春1, 杨 燕2, 文福拴1, 李 力3, 王 珂3, 高 超3
1.浙江大学 电气工程学院,浙江 杭州 310027;2.华南理工大学 电力学院,广东 广州 510641;3.广东电网公司电力调度控制中心,广东 广州 510600
摘要:
在电力市场环境下进行多区域可用输电容量(ATC)决策时,需要在维持系统安全运行与风险可控的前提下优化分配和协调利用现有的输电网络资源。利用非序贯蒙特卡洛仿真导出指定子区域在各种不确定性因素影响下的ATC概率密度分布,在此基础上构造能够使得风险收益最大化的多区域ATC概率优化协调决策模型,并利用多目标非支配排序遗传算法(NSGA-Ⅱ)进行求解,由该模型得到的各区域ATC计及了系统运行中有关不确定性因素所引起的风险成本和区域间同步协调问题。以IEEE 118节点测试系统为例对所发展的模型与采用的算法的基本特征进行了说明。仿真结果表明,电力系统运行中的不确定性以及不同区域的相对重要程度影响多区域ATC的决策风险。
关键词:  可用输电容量  风险  收益  多目标协调决策  多目标非支配排序遗传算法  模型
DOI:
分类号:
基金项目:国家高科技研究发展计划(863计划)资助项目(2011-AA05A105);国家自然科学基金资助项目(51177145);广东电网公司重点科研项目(DK0010DT0008)
Coordinated probabilistic optimal decision-making model for multi-area ATC with risk control
HUANG Yuchun1, YANG Yan2, WEN Fushuan1, LI Li3, WANG Ke3, GAO Chao3
1.School of Electrical Engineering,Zhejiang University,Hangzhou 310027,China;2.South China University of Technology,Guangzhou 510641,China;3.Electric Power Dispatch and Control Center of Guangdong Power Grid Corporation,Guangzhou 510600,China
Abstract:
In the decision-making of multi-area ATC(Available Transfer Capacity) in electricity market environment,the existing resources of transmission network should be optimally dispatched and coordinately employed on the premise that the secure system operation is maintained and risk associated is controllable. The non-sequential Monte Carlo simulation is used to determine the ATC probability density distribution of specified areas under the influence of several uncertainty factors,based on which,a coordinated probabilistic optimal decision-making model with the maximal risk benefit as its objective is developed for multi-area ATC. The NSGA-Ⅱ is applied to calculate the ATC of each area,which considers the risk cost caused by relevant uncertainty factors and the synchronous coordination among areas. The essential characteristics of the developed model and the employed algorithm are illustrated by the example of IEEE 118-bus test system. Simulative result shows that,the risk of multi-area ATC decision-making is influenced by the uncertainties in power system operation and the relative importance degrees of different areas.
Key words:  available transfer capacity  risks  benefit  multi-objective decision-making  NSGA-Ⅱ  models

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