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Assessing wind uncertainty impact on short term operation scheduling of coordinated energy storage systems and thermal units

机译:评估风的不确定性对协调的储能系统和热力单元的短期运行计划的影响

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摘要

Renewable resources, especially wind power, are widely integrated into the power systems nowadays. Managing uncertainty of the large scale wind power is often known as one of the most challenging issues in the power system operation scheduling. Additionally, energy storage systems (ESSs) have been widely investigated in the power systems owing to their valuable applications, especially renewable energy smoothing and time shift. In this paper, a stochastic unit commitment (UC) model is proposed to assess the impact of the wind uncertainty impact on ESSs and thermal units schedule in UC problem. Wind uncertainty is modeled based on the two measures. First, the wind penetration level is changed with respect to the basic level. Second, the wind forecasting error is modeled through a normal probability distribution function with different variances. The ESSs are modeled based on several technical characteristics and optimally scheduled considering different levels of the wind penetration and forecasting accuracies. The proposed formulation is a stochastic mixed integer linear programming (SMILP) and solved using GAMS software. Simulation results demonstrate that the wind uncertainty have a considerable impact on operation cost and ESSs schedule while proposed optimum storage scheduling through the stochastic programming will reduce the daily operational cost considerably. (C) 2016 Elsevier Ltd. All rights reserved.
机译:如今,可再生资源(尤其是风能)已广泛集成到电力系统中。大型风力发电的不确定性管理通常是电力系统运行调度中最具挑战性的问题之一。另外,由于储能系统(ESS)的宝贵应用,尤其是可再生能源的平滑和时移,已经在电力系统中进行了广泛的研究。在本文中,提出了一个随机单位承诺(UC)模型来评估风的不确定性影响对ESS和UC问题中的热力单元计划的影响。基于这两种方法对风的不确定性进行建模。首先,相对于基本水平改变了风的渗透水平。其次,通过具有不同方差的正态概率分布函数对天气预报误差建模。 ESS是基于几种技术特征进行建模的,并考虑了不同级别的风渗透和预测精度进行了优化调度。所提出的公式是随机混合整数线性规划(SMILP),并使用GAMS软件进行了求解。仿真结果表明,风的不确定性对运行成本和ESSs调度有相当大的影响,而通过随机规划提出的最优存储调度将大大降低日常运营成本。 (C)2016 Elsevier Ltd.保留所有权利。

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