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Reliability constraint stochastic UC by considering the correlation of random variables with Copula theory

机译:考虑随机变量与Copula理论的相关性的可靠性约束随机UC

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摘要

This essay performs a reliability constraint stochastic model for unit commitment problem by considering generation and transmission constraints with high wind penetration and volatility of load demands. This query is expressed as a MILP that is based on the linear direct current model. The proposed approach models uncertainty of wind generators output power, load demand fluctuations and stochastic elements outage of the system like generators and transmission lines. In this paper, stochastic interdependence between random variables like wind speed and load demand is recognized. To establish the probability distribution of these correlated random variables, Copula theory is applied. Correlation structure between wind speed of different locations and a group of loads existing in the same area is investigated and studied based on historical data. For representing these uncertainties in the stochastic unit commitment problem, possible scenarios are generated with Monte Carlo simulation method. The reliability constraints are utilized in each scenario to evaluate the feasibility of solutions from a reliability point. The introduced stochastic UC is executed on the RTS 96-bus test system. Numerical results demonstrate the advantages of implementing stochastic programming on the UC problem by taking into account the intermittent behavior of wind energy and load inconstancy.
机译:本文通过考虑具有高风速和负荷需求波动性的发电和输电约束条件,为机组承诺问题建立了可靠性约束随机模型。该查询表示为基于线性直流模型的MILP。所提出的方法模拟了风力发电机输出功率的不确定性,负载需求波动以及系统(例如发电机和输电线路)的随机元件故障。在本文中,认识到风速和负荷需求等随机变量之间的随机相互依赖关系。为了建立这些相关随机变量的概率分布,应用了Copula理论。基于历史数据,研究并研究了不同位置的风速与同一地区存在的一组负荷之间的相关结构。为了表示随机单元承诺问题中的这些不确定性,使用蒙特卡洛模拟方法生成了可能的方案。在每种情况下都使用可靠性约束来从可靠性角度评估解决方案的可行性。引入的随机UC在RTS 96总线测试系统上执行。数值结果表明,通过考虑风能的间歇性行为和负荷不稳定性,对UC问题实施随机规划的优势。

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