基于模型预测控制算法的配电网源荷跟踪技术

Source-Load Tracking Technology of Distribution Network Based on Model Predictive Control

随着大量分布式能源接入配电网,功率波动的随机性对新能源消纳能力以及设备的利用率都产生了严重的影响。本文充分利用负荷侧功率的可调节特性,对馈线首端电压进行调节,使负荷功率能够跟踪新能源出力,实现对配电网公共连接点功率的平抑。为保证在配电网经济运行的基础上有效平抑波动性,并消除新能源随机性对控制效果的影响,本文建立了基于日内优化-实时控制框架的源荷跟踪模型。在日内优化层面,以相邻周期公共连接点功率差值和运行成本为目标函数建立优化模型,求解公共连接点功率最优值;在实时控制层面,基于模型预测控制算法并结合日内优化结果,滚动优化求解调压量,从而实现源荷跟踪。最后以广州某工业园区实测数据为例验证了该模型对功率波动平抑的有效性。

With a large amount of distributed energy accessing to the distribution network,the randomness of power fluctuations has a serious impact on the new energy consumption and equipment utilization.In this paper,the adjustable characteristics of the load side power are fully utilized,by adjusting the feeder voltage,the distributed energy output can be tracked by the load,thereby the suppression of the power at the point of common coupling (PCC) is achieved.In order to ensure the smooth suppression of fluctuations on the basis of economic operation of distribution network and to eliminate the influence of randomness of distributed energy on control,this paper establishes a source-load tracking model based on a framework of intraday optimization and real-time control.At the intraday optimization level,the optimization model is established with the adjacent period PCC power difference and operation cost as the objective function to solve the optimal PCC power.At the real-time control level,the voltage regulation is solved by rolling optimization based on the model predictive control algorithm and the results of the intraday optimization,so as to realize the source-load tracking.Finally,a case of the measured data from an industrial park in Guangzhou verifies the effectiveness of the model in suppressing the power fluctuation.