安全约束机组组合(security constrained unit commitment,SCUC)是电网出清场景中最为广泛使用的一类模型。建立了一种针对超大规模SCUC现货市场出清问题的求解框架,首先提出了SCUC问题的时间解耦求解方法,通过缩小问题的规模来加快求...安全约束机组组合(security constrained unit commitment,SCUC)是电网出清场景中最为广泛使用的一类模型。建立了一种针对超大规模SCUC现货市场出清问题的求解框架,首先提出了SCUC问题的时间解耦求解方法,通过缩小问题的规模来加快求解速度;其次针对时间解耦后模型的子问题提出了拉格朗日松弛求解技术,在不影响求解准确度的情况下,有效降低了关键困难约束的求解难度。数值实验证明,所提出的框架极大地提升了求解效率,且十分稳定。展开更多
随着电网规模的持续扩大,市场环境下考虑网络安全约束的机组组合(security-constrained unit commitment,SCUC)模型中的变量和约束显著增加,模型的求解性能变差。当模型规模过大时,会出现现有的商用求解器无法求解的状况,造成大规模模...随着电网规模的持续扩大,市场环境下考虑网络安全约束的机组组合(security-constrained unit commitment,SCUC)模型中的变量和约束显著增加,模型的求解性能变差。当模型规模过大时,会出现现有的商用求解器无法求解的状况,造成大规模模型求解困难的问题。为实现大规模机组组合模型的快速求解,从减少模型约束数量的角度出发,提出了一种基于边界法的线性约束简化方法。通过边界法剔除模型中冗余的线性约束,可以有效降低模型规模,实现模型的快速求解。基于IEEE-39、WECC 179和IEEE-118算例,在市场环境下进行日前SCUC测试。通过对比简化前后的求解时间,表明该方法能够显著提高模型的求解速率。展开更多
With increasing penetration of wind energy,the variability and uncertainty of wind resources have become important factors for power systems operation.In particular,an effective method is required for identifying the ...With increasing penetration of wind energy,the variability and uncertainty of wind resources have become important factors for power systems operation.In particular,an effective method is required for identifying the stochastic range of wind power output,in order to better guide the operational security of power systems.This paper proposes a metric to determine accurate wind power output ranges so that the probability of actual wind power outputs being out of the range would be less than a small pre-defined value.A mixed-integer linear programming(MILP)based chance-constrained optimization model is proposed for efficiently determining optimal wind power output ranges,which are quantified via maximum and the minimum wind generation levels with respect to a certain time interval.The derived wind power range is then used to construct dynamic uncertainty intervals for the robust securityconstrained unit commitment(SCUC)model.A comparison with the deterministic SCUC model and the traditional robust SCUC model with presumed static uncertainty interval demonstrates that the proposed approach can offer more accurate wind power variabilities(i.e.,different variability degrees with respect to different wind power output levels at different time periods).The proposed approach is also shown to offer more effective and robust SCUC solutions,guaranteeing operational security and economics of power systems.Numerical case studies on a 6-bus system and the modified IEEE 118-bus system with realworld wind power data illustrate the effectiveness of the proposed approach.展开更多
The Benders Decomposition method is widely used to manage large-scale problems in power system optimization.In this paper,a simple but effective method is proposed to improve the Benders Decomposition efficiency using...The Benders Decomposition method is widely used to manage large-scale problems in power system optimization.In this paper,a simple but effective method is proposed to improve the Benders Decomposition efficiency using the security constrained unit commitment(SCUC)problem as an example.The heuristic weights are introduced for constraint violations to accelerate their elimination,and thereby improving the Benders Decomposition efficiency.The validity of the proposed method is verified through case studies on multiple IEEE test systems.展开更多
安全约束机组组合(Security-constrained Unit Commitment,SCUC)问题作为制定发电计划的核心环节,在电力系统优化调度等方面具有十分重要的意义。针对考虑故障态约束后SCUC问题规模庞大、难以求解的情况,提出了一种基于辅助优化问题的...安全约束机组组合(Security-constrained Unit Commitment,SCUC)问题作为制定发电计划的核心环节,在电力系统优化调度等方面具有十分重要的意义。针对考虑故障态约束后SCUC问题规模庞大、难以求解的情况,提出了一种基于辅助优化问题的故障态安全约束削减方法。首先引入与具体故障态安全约束相关的辅助优化问题,从而建立判别相应故障态安全约束是否冗余的充分必要条件。然后探究冗余故障态安全约束辨识过程的具体加速方法,包括松弛辅助优化问题方法,使用可行性判据进行故障态安全约束预分类方法,以及多线程并行计算方法。最后,在IEEE118测试系统上对所提方法的正确性和有效性进行了仿真验证。展开更多
文摘安全约束机组组合(security constrained unit commitment,SCUC)是电网出清场景中最为广泛使用的一类模型。建立了一种针对超大规模SCUC现货市场出清问题的求解框架,首先提出了SCUC问题的时间解耦求解方法,通过缩小问题的规模来加快求解速度;其次针对时间解耦后模型的子问题提出了拉格朗日松弛求解技术,在不影响求解准确度的情况下,有效降低了关键困难约束的求解难度。数值实验证明,所提出的框架极大地提升了求解效率,且十分稳定。
文摘随着电网规模的持续扩大,市场环境下考虑网络安全约束的机组组合(security-constrained unit commitment,SCUC)模型中的变量和约束显著增加,模型的求解性能变差。当模型规模过大时,会出现现有的商用求解器无法求解的状况,造成大规模模型求解困难的问题。为实现大规模机组组合模型的快速求解,从减少模型约束数量的角度出发,提出了一种基于边界法的线性约束简化方法。通过边界法剔除模型中冗余的线性约束,可以有效降低模型规模,实现模型的快速求解。基于IEEE-39、WECC 179和IEEE-118算例,在市场环境下进行日前SCUC测试。通过对比简化前后的求解时间,表明该方法能够显著提高模型的求解速率。
基金supported in part by the U.S.National Science Foundation under Grant ECCS-1254310.
文摘With increasing penetration of wind energy,the variability and uncertainty of wind resources have become important factors for power systems operation.In particular,an effective method is required for identifying the stochastic range of wind power output,in order to better guide the operational security of power systems.This paper proposes a metric to determine accurate wind power output ranges so that the probability of actual wind power outputs being out of the range would be less than a small pre-defined value.A mixed-integer linear programming(MILP)based chance-constrained optimization model is proposed for efficiently determining optimal wind power output ranges,which are quantified via maximum and the minimum wind generation levels with respect to a certain time interval.The derived wind power range is then used to construct dynamic uncertainty intervals for the robust securityconstrained unit commitment(SCUC)model.A comparison with the deterministic SCUC model and the traditional robust SCUC model with presumed static uncertainty interval demonstrates that the proposed approach can offer more accurate wind power variabilities(i.e.,different variability degrees with respect to different wind power output levels at different time periods).The proposed approach is also shown to offer more effective and robust SCUC solutions,guaranteeing operational security and economics of power systems.Numerical case studies on a 6-bus system and the modified IEEE 118-bus system with realworld wind power data illustrate the effectiveness of the proposed approach.
基金supported by National Natural Science Foundation of China(Grant No.51707146,U1766205).
文摘The Benders Decomposition method is widely used to manage large-scale problems in power system optimization.In this paper,a simple but effective method is proposed to improve the Benders Decomposition efficiency using the security constrained unit commitment(SCUC)problem as an example.The heuristic weights are introduced for constraint violations to accelerate their elimination,and thereby improving the Benders Decomposition efficiency.The validity of the proposed method is verified through case studies on multiple IEEE test systems.
文摘安全约束机组组合(Security-constrained Unit Commitment,SCUC)问题作为制定发电计划的核心环节,在电力系统优化调度等方面具有十分重要的意义。针对考虑故障态约束后SCUC问题规模庞大、难以求解的情况,提出了一种基于辅助优化问题的故障态安全约束削减方法。首先引入与具体故障态安全约束相关的辅助优化问题,从而建立判别相应故障态安全约束是否冗余的充分必要条件。然后探究冗余故障态安全约束辨识过程的具体加速方法,包括松弛辅助优化问题方法,使用可行性判据进行故障态安全约束预分类方法,以及多线程并行计算方法。最后,在IEEE118测试系统上对所提方法的正确性和有效性进行了仿真验证。
