Effect of Demand Response on transformer lifetime expectation

Johannes Jargstorf, K. Vanthournout, T. D. Rybel, D. Hertem
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引用次数: 40

Abstract

Demand Response is seen as important to support the integration of renewable energies into the grid. In Flanders, a residential Demand Response setup is realized in the Linear pilot. The aim is to assess the potential benefits and ways of technical realization of residential Demand Response. In this paper, household devices, like washing machines, are used to offer a flexible load. These are also devices which are used in the pilot. The effect of using flexible loads on the lifetime of a low-voltage transformer is assessed. An IEEE transformer model is used to calculate the lifetime. To calculate the effect of Demand Response, aging is first calculated based on the load of a group of customers and then based on their load being optimized by Demand Response. In this paper, devices are scheduled based on the transformer temperature. The temperature is optimized by using a simulation model based on a mixed integer quadratic programming (MIQP) scheduler. To assess the effect of Demand Response on the transformer lifetime, aging for the improved load curve is compared with aging for the initial load curve. To demonstrate the impact, realistic data for household load curves and the usage of household devices are employed. Results for this input data show reductions in aging of up to 75 % for transformers operating at rated load. The setup will be used to calculate a benchmark for the setup in the Linear pilot, which will use an on-line scheduler. It will be also used to determine potential outcome of a business case.
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需求响应对变压器寿命预期的影响
需求响应被认为是支持可再生能源并网的重要手段。在佛兰德斯,住宅需求响应设置在线性试点中实现。目的是评估住宅需求响应的潜在效益和技术实现方法。在本文中,家用设备,如洗衣机,被用来提供一个灵活的负载。这些也是飞行员使用的设备。评估了使用柔性负载对低压变压器寿命的影响。采用IEEE变压器模型计算其寿命。为了计算需求响应的影响,首先根据一组客户的负荷计算老化,然后根据他们的负荷被需求响应优化。在本文中,设备调度是基于变压器的温度。采用基于混合整数二次规划(MIQP)调度的仿真模型对温度进行了优化。为了评估需求响应对变压器寿命的影响,将改进负载曲线的老化与初始负载曲线的老化进行比较。为了证明这种影响,采用了家庭负荷曲线和家用设备使用情况的实际数据。该输入数据的结果表明,在额定负载下运行的变压器老化率可降低75%。该设置将用于计算Linear试点中设置的基准,该试点将使用在线调度器。它还将用于确定商业案例的潜在结果。
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