基于混合随机算法的可用输电能力计算

AVAILABLE TRANSFER CAPABILITY DETERMINATION: A NOVEL STOCHASTIC APPROACH

提出了一个新颖的基于混合随机算法的互联网络截面可用传输能力的计算方法。由于电力系统中固有的不确定因素会显著影响可用传输能力水平 ,为得到一个可靠而尽可能精确的值 ,文中建立了一个随机计算模型。在该模型中 ,用二次分布函数来模拟发电机组和输电线的故障 ,并认为负荷预测误差符合正态分布。为了有效解决这样一个同时包含离散随机变量和连续随机变量的问题 ,文中提出了一个综合两阶段求索随机规划和概率约束规划优点的混合随机算法。对于 IEEE1 1 8节点系统的结果分析证明了在 ATC计算中考虑不确定因素的必要性。同时 ,计算结果表明所提出的方法新颖实用 ,具有工程应用价值。

From the viewpoint of short-term operational planning, this paper focuses on the steady-state ATC determination of interconnected systems. In order to reflect the physical realities of the transmission network, a stochastic ATC evaluation model is formulated, where the key uncertainties affecting ATC levels are modelled explicitly. Availability of generators and circuits are considered as discrete random variables following binomial distributions. In addition, load forecast errors are modelled as normally distributed variables. However, with the introduction of the probability distributions to each of the uncertain parameters, particularly continuous random variables, the equivalent deterministic model of a large-scale practical problem usually has huge and intractable dimensions. To deal with the complex problem presented with both discrete and continuous variables involved efficiently, a hybrid stochastic approach is proposed, which takes advantage of both two-stage stochastic programming with recourse (SPR) and chance constrained programming (CCP). Furthermore, the necessity to consider the impact of uncertainties on ATC assessment is demonstrated clearly by using the IEEE 118-bus standard system. The numerical results also illustrate the salient performance of the proposed methodology. This work is supported by National Key Basic Research Special Fund of China (No.G1998020310) and National Science Foundation of China for Overseas Youth R & D Cooperation.