考虑预测误差的风热系统日前发电计划

A. I.
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摘要

一般情况下,电力系统会预留一定的备用容量来平衡负荷预测或风电的偏差。如果不准备好备用容量,电力系统可能处于危险状态。为了保证该备用容量的安全性,本文提出了考虑风电和负荷预测误差的风热系统日前发电计划,有效地协调了日前发电计划的经济性和安全性。本文方法将实际值视为风电和负荷预测值及其偏差之和。其中,由自动发电控制(AGC)单元对预测偏差进行平衡和跟踪,并对其输出有功功率和预留备用容量进行建模。AGC具有足够的可调上限和下限,通过施加约束来平衡电力,并具有跟踪预测偏差波动的能力。进一步,由于预测偏差为随机数,通过鲁棒点对点模型将具有随机参数的模型转化为确定性模型,验证其在极端场景下的效果,并引入分布式储能装置,促进风电消纳,优化系统运行经济性。最后,在ieee30节点系统中,设置风电并网比例高的背景,通过本文提出的方法分析极端场景下备用容量的安全性和经济性。
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Day-Ahead Generation Schedule of Wind-Thermal-Storage System Considering Prediction Error
In general, the power system reserves some reserve capacity to balance the deviation of load forecast or wind power. If this reserve capacity is not properly prepared, the power system may be in a dangerous state. In this paper, a day-ahead generation schedule of wind-thermal-storage system considering prediction error of wind power and load is proposed to ensure the security of this reserve capacity, as well as, which effectively coordinates the economy and safety of the day-ahead generation schedule. The actual value is regarded as the sum of the predicted value and its deviation for wind power and load in the proposed method. Among them, the predicted deviation is balanced and tracked by the automatic generation control (AGC) unit, and its output active power and reserved reserve capacity are modeled. What's more, the AGC has sufficient adjustable upper and lower limits to balance the electric power by applying constraints, and has the ability to track the fluctuation of the prediction deviation. Furthermore, since the prediction deviation is a random number, the model with random parameters is transformed into a deterministic model through a robust peer-to-peer model to verify the effect in the extreme scenario, as well as, a distributed energy storage device is introduced to promote wind power consumption and optimize the system operation economy. Finally, in an IEEE 30 node system, the background of high proportion of wind power connected to the power system is set, and the security and economy of reserve capacity under the extreme scenario are analyzed through the method proposed in this paper.
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