元一平, 王建学, 周锟, 王秀丽, 王学斌, 张舒捷. 协同短期调度的新能源电力系统月度机组组合模型与快速求解方法[J]. 中国电机工程学报, 2019, 39(18): 5336-5345,5580. DOI: 10.13334/j.0258-8013.pcsee.182075
引用本文: 元一平, 王建学, 周锟, 王秀丽, 王学斌, 张舒捷. 协同短期调度的新能源电力系统月度机组组合模型与快速求解方法[J]. 中国电机工程学报, 2019, 39(18): 5336-5345,5580. DOI: 10.13334/j.0258-8013.pcsee.182075
YUAN Yi-ping, WANG Jian-xue, ZHOU Kun, WANG Xiu-li, WANG Xue-bin, ZHANG Shu-jie. Monthly Unit Commitment Model Coordinated Short-term Scheduling and Efficient Solving Method for Renewable Energy Power System[J]. Proceedings of the CSEE, 2019, 39(18): 5336-5345,5580. DOI: 10.13334/j.0258-8013.pcsee.182075
Citation: YUAN Yi-ping, WANG Jian-xue, ZHOU Kun, WANG Xiu-li, WANG Xue-bin, ZHANG Shu-jie. Monthly Unit Commitment Model Coordinated Short-term Scheduling and Efficient Solving Method for Renewable Energy Power System[J]. Proceedings of the CSEE, 2019, 39(18): 5336-5345,5580. DOI: 10.13334/j.0258-8013.pcsee.182075

协同短期调度的新能源电力系统月度机组组合模型与快速求解方法

Monthly Unit Commitment Model Coordinated Short-term Scheduling and Efficient Solving Method for Renewable Energy Power System

  • 摘要: 为实现多时间尺度下新能源电力系统经济、灵活运行与发电资源最优性配置,该文考虑月度机组组合与短期调度之间的层次衔接关系,提出协同短期调度的月度机组组合模型与高效求解算法。首先,结合风电短期随机不确定性与长期相关不确定性之间的概率统计规律,提出基于非参数核密度估计与自回归滑动平均分析的新能源出力模拟方法;在此基础上,通过协调月度机组群开停机计划与短期调度的互动关系,构建协同短期调度的多场景月度机组组合模型。其次,针对该混合整数线性规划模型的计算复杂性问题,利用约束转换技术与松弛诱导技术,提出一种基于分支—定界原理的改进求解策略。最后,结合某省区电网进行实际算例对比分析,论证协同短期调度的月度机组组合模型与求解算法的有效性。

     

    Abstract: In order to realize the economic and flexible operation of renewable energy power system and the global optimality allocation of generation resources, a novel monthly security-constrained unit commitment which considers the hierarchical relationship between monthly unit commitment and short-term scheduling, was presented in this paper. Firstly, by taking the probability information of short-term randomness uncertainty and long-term correlation uncertainty characteristic of renewable energy into account, a simulation method of renewable output based on the non-parametric kernel density estimation(N-KDE) and ARMA regression analysis was put forward. On this basis, a stochastic scenario based monthly unit commitment coordinating short-term scheduling was constructed. Secondly, in response to the computational intractable of the proposed model, both of the constrained transformation and relaxation induction technology were employed to provide an improved solving strategy according to the popular branch and bound principle. Finally, the result of the actual system shows the validity and advantage of the presented model and solution method.

     

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