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A Generic Convex Model for a Chance-Constrained Look-Ahead Economic Dispatch Problem Incorporating an Efficient Wind Power Distribution Modeling
IEEE Transactions on Power Systems ( IF 6.5 ) Pub Date : 2020-03-01 , DOI: 10.1109/tpwrs.2019.2940288
Benyamin Khorramdel , Alireza Zare , C. Y. Chung , Panagiotis Gavriliadis

Power systems with high penetration of wind resources must cope with significant uncertainties originated from wind power prediction error. This uncertainty might lead to wind power curtailment and load shedding events in the system as a big challenge. Efficient modeling and incorporation of wind power uncertainty in generation and reserve scheduling can prevent these events. This paper presents a new framework for wind power cumulative distribution function (CDF) modeling and its incorporation in a new chance-constrained economic dispatch (CCED) problem. The proposed CDF modeling uses few moments of wind power random samples. To validly capture the actual features of the wind power distribution such as main mass, high skewness, tails, and especially boundaries from the moments, an efficient moment problem is presented and solved using the beta kernel density representation (BKDR) technique. Importantly, a new polynomial cost function for efficient modeling of wind power misestimation costs is proposed for the CCED problem that eliminates the need for an analytical CDF and enables the use of an accurate piecewise linearization technique. Using this technique, the non-linear CCED problem is converted to a mixed-integer linear programming (MILP)-based problem that is convex with respect to the continuous variables of the problem. Therefore, it is solved via off-the-shelf mathematical programming solvers to reach more optimal results. Numerical simulations using the IEEE 118-bus test system show that compared with conventional approaches, the proposed MILP-based model leads to lower power system total cost, and thereby is suggested for practical applications.

中文翻译:

结合有效风电配电建模的机会约束前瞻经济调度问题的通用凸模型

具有高风资源渗透率的电力系统必须应对源自风电功率预测误差的重大不确定性。这种不确定性可能会导致系统中的风电限电和减载事件成为一个巨大的挑战。在发电和备用调度中有效建模和结合风力发电的不确定性可以防止这些事件。本文提出了一种新的风电累积分布函数 (CDF) 建模框架,并将其纳入新的机会约束经济调度 (CCED) 问题。建议的 CDF 建模使用了少量的风电随机样本矩。为了有效地捕捉风功率分布的实际特征,例如主要质量、高偏度、尾部,尤其是矩的边界,使用β核密度表示(BKDR)技术提出并解决了有效矩问题。重要的是,针对 CCED 问题提出了一种新的多项式成本函数,用于对风电错误估计成本进行有效建模,该函数消除了对分析 CDF 的需求,并能够使用精确的分段线性化技术。使用这种技术,非线性 CCED 问题被转换为基于混合整数线性规划 (MILP) 的问题,该问题相对于问题的连续变量是凸的。因此,它通过现成的数学规划求解器进行求解,以达到更优的结果。使用 IEEE 118 总线测试系统的数值模拟表明,与传统方法相比,所提出的基于 MILP 的模型可降低电力系统的总成本,
更新日期:2020-03-01
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