# Distributed Generation Cluster Division Method Considering Frequency Regulation Response Speed
## 1 Introduction  
With the continuous development of DG, the distribution network has been transformed from a traditional radial passive network to an active network containing a large number of distributed generation sources [1], which has increased the pressure on the voltage regulation of the power grid. Voltage regulation and peak shifting in the power grid [2; 3; 4] have emerged, along with complicated problems such as voltage overruns at local nodes, increased network losses, and the backward transmission of power across voltage levels [5]. In addition, distributed renewable energy sources are usually characterized by small standalone capacity, decentralized access points, and diverse access methods, which obviously increases the difficulty of centralized control [6]. Therefore, in order to ensure that large-scale distributed generation can be connected to the power grid in an orderly, safe, reliable, and cost-effective manner, as well as to realize friendly coordination between large-scale renewable energy sources and the power grid and to maximize grid-connected consumption and absorption of distributed generation, a forward-looking solution has been developed to divide distributed generation into clusters and carry out planning, scheduling, and control based on the clusters [7]. Scholars have conducted research on the division and regulation of distributed generation clusters (DGCs), which were defined by [PERSON] et al. as a collection of branch circuits that are electrically close to each other, with locally balanced reactive power and complementary active power timing [8]. Studies [9; 10] have proposed an index system combiningfunctional indexes of dissipation capacity and structural indexes of modularity which used a genetic algorithm [11] to divide DGCs. Another study [12] performed cluster division based on the electrical distance, cluster size, number, and connectivity and combined traditional graph division algorithms with evolutionary algorithms to optimize grid transmission planning and rotational inertia reserve capacity. Another study [13] proposed a hierarchical voltage control strategy based on active-reactive clusters. Other authors [14] established a cluster division methodology that considered flexibility balancing based on the concept of flexibility. To date, most DGC division studies have started with satisfying the voltage regulation and control needs [15; 16; 17; 18]. These studies mainly focused on reactive power and voltage control for distributed generation cluster division. There is a lack of discussion on the active power balance to realize renewable energy consumption and frequency regulation. In order to understand how DGCs can have friendly grid connection characteristics and regulation capabilities similar to those of traditional generators with respect to the external grid, a series of index sets has been proposed from the perspective of cluster power balance, such as the active balance degree [6] and the consumption capacity index [19]. Although the cluster division method based on planning classes proposed in a previous study [20] takes into account the complementary power characteristic relationship between nodes and solves the problem of source-load matching, the regulation capability of source-network-load-storage, etc., has not been sufficiently considered in cluster division [21; 22]. In another study [23; 24; 25], the authors differentiated the distribution network from the perspective of either reducing the control complexity or increasing the capacity of DG consumption. These types of indexes reflect the static power balance characteristics of power complementarity between nodes in clusters in a certain time period, but the power regulation of energy storage, load, and other control devices in a short time period has not yet been clarified, and the active response capacity has not been fully utilized to improve frequency regulation control performance.