基于AGC预测指令的火电机组控制策略
摘要：新能源发电本身具有的不确定性和波动性势必会对电网安全造成影响。在火电机组调峰调频能力足够的情况下，通过改变火电机组的出力可平抑电网波动，减小新能源并网造成的冲击。为了电网的安全经济稳定运行，使火电机组具备足够的调节能力，提出了一种基于AGC指令预测的火电机组前馈预测控制方法。首先搭建BP神经网络模型对风电场、光伏电站的出力以及电力系统负荷进行预测，得到基于源荷分析的厂级AGC预测曲线，并根据该预测指令对火电厂负荷进行分配，所得的变负荷趋势作为前馈信息引入到火电机组控制系统中，以修正火电机组的AGC指令曲线，对机组进行优化前馈预测控制。经验证，所提控制方法使火电机组提前做出响应，可有效提升机组的响应能力。与常规控制方法相比，所提方法在控制精度和响应效率上均有一定程度上的提升，提高火电机组的调节能力。
Abstract:The uncertainty and volatility of new energy power generation itself is bound to affect the security of power grid. In the case of enough peak load and frequency regulation capacity of thermal power units, by means of changing the output of thermal power unit the fluctuation in power grid can be stabilized, and the impact caused by grid-connection of new energy power units can also be mitigated. To ensure secure, economic and stable operation of power grid and to make thermal power units possessing enough regulation capability, an AGC command prediction-based feedforward predictive control method for thermal power units was proposed. Firstly, a BP neural network model was constructed to predict the output of wind farm and photovoltaic (abbr. PV) power station as well as the load of power grid to obtain the source load analysis-based plant level AGC prediction curve. According to this prediction command the load of thermal power plant was distributed, and the obtained variable load trend was taken as the feedforward information led into the control system of thermal power units to revise the AGC command curve of thermal power units, and to perform the optimal feedforward predictive control of the units. It is verified that the proposed control method can make thermal power units responded in advance, so the response capability of the units can be effectively improved. Comparing with conventional control methods, the proposed method improves both control accuracy and response efficiency to a certain extent, thus the regulation capacity of thermal power units is enhanced.
标题：基于AGC预测指令的火电机组控制策略
英文标题：A Control Strategy of Thermal Power Unit Based on AGC Prediction Command
作者：邢峰, 褚文超, 苏智东, 冀洋, 韩仲雅, 牛玉广, 何青波,
关键词：火电机组, BP神经网络, 负荷分配, AGC预测曲线, 前馈控制,
发表日期：2023-09-26
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