Unit Commitment With Continuous-Time Generation and Ramping Trajectory Models
Unit Commitment With Continuous-Time Generation and Ramping Trajectory Models
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DOI：
10.1109/tpwrs.2015.2479644
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发表时间：
2016-07
影响因子：
6.6
通讯作者：
M. Parvania;A. Scaglione
中科院分区：
文献类型：
--
作者：
M. Parvania;A. Scaglione
在电力系统的实时运行中，越来越多的证据表明斜坡资源短缺。为了系统地解释和解决这一问题，本文对日前机组组合(UC)问题表示负荷、发电和匝道约束信息的方式进行了新的探讨。我们具体研究了将原始问题映射到实际求解的离散时间问题上所产生的逼近误差，该误差决定了所承诺的发电机组的连续时间生成和倾斜轨迹。我们首先证明，目前的做法相当于用线性样条线近似轨迹。然后，我们通过三次样条法提供了不同的表示，它提供了物理上可行的时间表，并通过捕捉前一天电力系统运行中的亚小时变化和负荷斜坡来提高连续时间发电和斜坡轨迹的精度。相应的前一天UC模型被表示为混合整数线性规划(MILP)的实例，具有与传统UC公式相同的二进制变量数。对加州ISO实际负荷数据的数值模拟表明，所提出的UC模型降低了总的提前天数和实时运行成本，并减少了实时运行中陡峭稀缺性事件的发生次数。
There is increasing evidence of shortage of ramping resources in the real-time operation of power systems. To explain and remedy this problem systematically, in this paper we take a novel look at the way the day-ahead unit commitment (UC) problem represents the information about load, generation and ramping constraints. We specifically investigate the approximation error made in mapping of the original problem, that would decide the continuous-time generation and ramping trajectories of the committed generating units, onto the discrete-time problem that is solved in practice. We first show that current practice amounts to approximating the trajectories with linear splines. We then offer a different representation through cubic splines that provides physically feasible schedules and increases the accuracy of the continuous-time generation and ramping trajectories by capturing sub-hourly variations and ramping of load in the day-ahead power system operation. The corresponding day-ahead UC model is formulated as an instance of mixed-integer linear programming (MILP), with the same number of binary variables as the traditional UC formulation. Numerical simulation over real load data from the California ISO demonstrate that the proposed UC model reduces the total day-ahead and real-time operation cost, and the number of events of ramping scarcity in the real-time operations.