面向低碳园区供需平衡的混杂负荷系统聚合和控制模型构建

Aggregation and Control Model Construction of Hybrid Load System for Supply and Demand Balance in Low-carbon Zone

随着“双碳”目标的持续推进,园区系统的低碳转型受到了广泛关注。低碳园区具备高比例的清洁能源,其间歇性和波动性问题给园区的安全稳定运行带来了挑战,传统增加储能设备的手段成本高且灵活性低。为此,该文提出了利用园区内丰富的可调节负荷资源,经过有效的聚合管控充分挖掘负荷调节潜力,提供功率转移容量以实现园区自身供需平衡。以园区内各种可调负荷组成的聚合系统为控制对象,针对负荷物理参数的异质混杂特性,提出包括设备嵌入控制、异质聚合控制、系统辨识控制以及混杂协同控制的分层控制算法,由设备嵌入控制自底而上形成稳定可控的异质集群,从混杂协同控制自上而下控制大量混杂负荷输出稳定收敛响应。在系统辨识控制层,构建基于径向基函数神经网络的系统参数辨识模型,辨识异质集群的聚合参数,从而构建稳定可控的异质聚合模型,能够适用于不同负荷种类的异质集群,具有通用性。在混杂协同控制层,构建异质集群协同管控模型,随机选取容量合适的集群参与清洁能源消纳。最后,通过提供清洁能源出力跟踪服务验证了方法的有效性。仿真结果表明,在该文的异质聚合模型下负荷聚合数量提高了11.2%,表明了该文的异质聚合方法能够有效提升负荷的聚合数量。此外,该文混杂负荷分层控制算法的跟踪误差在0.02%以内,验证了该文算法的准确性。

With the continuous promotion of carbon peak and neutrality targets,the low-carbon transformation of the zone systems has attracted broader attention.With a high proportion of clean energy,the intermittency and fluctuation of clean energy has brought great challenges to the stable operation of the low-carbon zone.However,the traditional methods of increasing the energy storage equipment has low flexibility and costs a lot.Therefore,through the effective aggregation and management of the adjustment potential of abundant load resources in the low-carbon zone,these adjustable loads may form the considerable power transfer capacity to realize the balance between supply and demand of the zone.This paper takes the aggregation system composed of various adjustable loads in the low-carbon zone as the control object.Aiming at the heterogeneity problem of the load parameters,the hierarchical control algorithm is proposed,which includes the device embedding control,the heterogeneous aggregation control,the system identification control and the hybrid cooperative control.On the device embedding control layer,the stable and controllable heterogeneous clusters are formed through the bottom-up aggregation;On the hybrid cooperative control layer,the abundant hybrid loads are managed to output the stable and convergent response through the top-down control;On the system identification control layer,the identification model is constructed based on the RBF neural network to identify the aggregation parameters of the heterogeneous cluster.Then a stable and controllable heterogeneous aggregation model is built,which can be applied to heterogeneous clusters of different load types with the universality;On the hybrid cooperative control layer,the collaborative management and control model of the heterogeneous clusters is structured to select randomly the clusters to participate in the consumption of the clean energy.Finally,the effectiveness of the proposed method is verified through a tracking simulation for smoothing the clean energy output.The simulation result shows that the number of the aggregated loads has increased by 11.2%,which indicates that the heterogeneous aggregation proposed in this paper is able to effectively increase the load aggregation number.In addition,the tracking error of the hierarchical control algorithm for the hybrid loads is within 0.02%,which verifies the accuracy of the algorithm in this paper.