Research on Voltage Flexibility Analysis and Governance Measures for Distribution Networks with High Proportion

In response to issues such as reduced voltage flexibility caused by the integration of a large number of high-proportion distributed photovoltaic (HPDP) and new energy electric vehicles (NEEV) into the distribution networks, this article proposes a method for evaluating the voltage flexibility (VF) of distributed PV distribution networks with high proportions and corresponding governance measures, which can effectively improve the VF of distribution networks and the absorption rate of photovoltaic (PV) systems. Firstly, we build an integrated system model for PV, electrochemical energy storage (EES), and distributed charging piles (DCP). Then, from a spatial perspective, a VF evaluation method for HPDP distribution networks is proposed. We analyze the impact of HPDP integration on the VF of each node in the distribution network and propose a governance measure that combines EES and DCP to enhance the VF of the distribution network. Finally, we take a typical 10 kV distribution network architecture in Jilin Province as an example for numerical analysis, so the effectiveness of the proposed method is verified.


Introduction
In recent years, with China's strong support for the new energy field, HPDPs and NEEVs have been widely applied [1][2][3].However, due to the randomness and intermittency of PV systems, as well as the impact of new energy electric vehicle loads, it has a huge impact on the VF of the distribution network.Therefore, to improve the VF of the distribution network, reduce the impact of NEEV loads on the distribution network, and promote the absorption of PV systems, it is urgent to carry out a VF analysis and governance measures research for distribution networks with HPDPs.
Currently, in terms of flexibility assessment, in [4], we categorize flexibility resources into three categories: transmission system flexibility, distribution system flexibility, and dual terminal flexibility of transmission and distribution systems.And traditional power sources and controllable new energy sources are generally divided into transmission system flexibility, but specific flexibility assessments have not been conducted for new energy sources such as the PV that has already existed in actual distribution networks.In terms of PV absorption, in [5], the time-shift characteristics of EES and the fast response of DC modulation are utilized to absorb grid-connected photovoltaics.In [6], the use of EES is proposed to solve the intermittent problem of solar energy resources and improve the photovoltaic absorption rate.However, the two scenarios did not effectively consider the impact of NEEV load integration on the distribution network.
Based on the research results above on VF and PV absorption in distribution networks, this article proposes a VF evaluation method for distribution networks from a spatial perspective.Through the analysis of the flexibility evaluation results, it is proposed to establish an integrated station of PV, EES, and DCP to improve the VF of distribution networks with HPDPs.Finally, an example analysis was conducted based on the actual distribution network structure to demonstrate the effectiveness of the VF evaluation method and governance measures proposed in the paper.

The PV model
The output power of the PV system is: pv pv pv ( 1) where C loss is the loss coefficient of the PV system.

The EES model
The state of charge (SOC) of EES can reflect the degree of stored electricity, which is expressed as: where Q n is the rated capacity of electrochemical energy storage; i(τ) is the charging and discharging current.

The DCP model
We configure EESs on each charging station and reduce the peak load of each charging station μ, and reduce the total peak load of the charging station μ%.The distributed charging station can be represented by the following equation: C, EES, limit 1 ( ) where P iC,t , P i, peak , and P iEES,t are the charging station power at time t, the actual daily charging peak power, and the energy storage power separately configured for the i-th charging station at time t.

Evaluation indicators for VF in distribution networks
When the HPDPs are connected to the distribution network, the phenomenon of power imbalance in the distribution network increases, and node voltages may cross the line.The VF of the distribution network reflects the ability of nodes to tolerate voltage fluctuations.This article will establish an evaluation index for the flexibility and adequacy of voltage nodes in distribution networks from a spatial perspective.

Evaluation indicators for node VF adequacy
ΔU i + represents the direction in which node voltage fluctuations increase, and ΔU i -represents the direction in which node voltage fluctuations decrease.Considering the actual load scenario of the distribution network while we take into account system safety constraints, the expression for the adequacy of voltage fluctuations that each node in the distribution network can withstand is: , : max , : min where M C, i is the VF evaluation indicators of node i, Pr{ } is the probability calculation equation, ΔU Li,t + is the upward fluctuation of voltage at node i at time t, and ΔU Li,t -is the downward wave momentum of the voltage at node i at time t.

Classification of evaluation indicators for node VF adequacy
According to Equation (7), the evaluation indicators M C, i for VF adequacy of distribution network nodes can be divided into the following four categories:  I: When 0.95≤M C and i ≤1.0, it indicates that the VF of the distribution network nodes is sufficient;  II: When 0.80≤M C and i ＜0.95, it indicates that the VF of the distribution network nodes slightly lacks;  III: When 0.70≤M C and i ＜0.80, it indicates that the VF of the distribution network nodes is insufficient;  IV: When 0≤M C and i ＜0.70, it indicates that the VF of the distribution network nodes is severely insufficient.

Constraint condition (1) Power balance constraint
The power balance equation for nodes containing HPDP is shown in Equation (8), and the power balance equation for nodes containing HPDP, EES, and DCP is shown in Equation (9): where P Gi and Q Gi are the active and reactive power of node i, respectively; P Li and Q Li are the active and reactive loads of node i, respectively; U i is the voltage of node i; P Ci and Q Ci are the active and reactive power of the charging station at node i, respectively; P ESSi and Q ESSi are the active and reactive power of electrochemical energy storage at node i, respectively; G ij , B ij , and θ ij refer to the conductivity, admittance, and phase angle difference between nodes i and j, respectively.
(2) Voltage safety constraint ,min ,max where U i, min , and U i, max are the lower and upper voltage limits at node i, respectively.

SOC SOC SOC  
(11) where SOC min and SOC max are the lower and upper limits of the electrochemical energy storage state of charge, respectively.

Governance measures
Based on the classification results of the evaluation indicators for voltage flexibility adequacy of distribution network nodes, the current VF situation of the distribution network can be effectively analyzed.Based on the analysis results, and considering the insufficient or severe VF of the distribution network and the number of NEEVs in the vicinity of nodes, this article proposes governance measures for connecting EESs and DCPs to nodes or nearby nodes with insufficient or severely insufficient VF in distribution network nodes.

Basic architecture of 10 kV distribution network with HPDPs
This article takes a typical 10 kV distribution network architecture in Jilin Province (as shown in Figure 1) as an example and uses simulation software for example analysis.The working range of the node voltage set in the text is [0.95, 1.05], with a reference power of 10 kW, a reference voltage of 12.66 kV, and a maximum load power of 300 kW.

Analysis of VF in distribution networks with HPDP
This article analyzes the VF of the distribution network when the penetration rate of a high proportion of distributed PV in the distribution network reaches 70% as an example.At this time, the maximum annual total power generation of distributed PV connected to the distribution network is 210 kW (among which the maximum annual power generation of PV at node 7 is 15.2 kW, at node 15 is 16 kW, at node 16 is 14.15 kW, at node 17 is 9.5 kW, at node 18 is 9.5 kW, at node 21 is 25.5 kW, at node 22 is 19 kW, at node 23 is 11 kW, at node 24 is 30.15kW, at node 33 is 18.5 kW, at node 39 is 20.3 kW, and at node 41 is 21.2 kW).The VF evaluation results of the distribution network with HPDPs are shown in Figure 2.
From Figure 2, it can be seen that the M C, i values at the nodes connected to and adjacent to the HPDPs significantly decrease (M C, i at node 7 is 0.62, M C, i at node 15 is 0.58, M C, i at node 16 is 0.62, M C, i at node 17 is 0.66, M C, i at node 18 is 0.66, M C, i at node 21 is 0.61, M C, i at node 22 is 0.66, M C, i at node 23 is 0.66, M C, i at node 24 is 0.44, M C, i at node 33 is 0.44, M C, i at node 38 is 0.40, and M C, i at node 41 is 0.44), and the VF of these nodes are severely insufficient.The closer the M C, i value is to the PV access nodes, the lower the VF is, while the closer the M C, i value is to the balance node, the higher the VF is.In addition, the distribution of M C, i varies among different nodes, indicating that the VF of distribution networks have spatial characteristics.

Analysis of governance measures
According to the evaluation results of VF, EESs and DCPs will be connected to nodes with insufficient or severe VF, and the specific access nodes and capacities are shown in Table 1.After connecting to EESs and DCPs, the VF evaluation results of the distribution network with HPDPs are shown in Figure 3.  Figure 3 shows the M C, i values of each node after connecting EES and DCP in the distribution network with HPDP.M C, i at node 7 is 0.78, M C, i at node 15 is 0.73, M C, i at node 16 is 0.75, M C, i at node 17 is 0.78, M C, i at node 18 is 0.78, M C, i at node 21 is 0.75, M C, i at node 22 is 0.78, M C, i at node 23 is 0.78, M C, i at node 24 is 0.67, M C, i at node 33 is 0.67, M C, i at node 38 is 0.63, and M C, i at node 41 is 0.68.Through the comparative analysis of Figure 2 and Figure 3, it can be seen that after the EESs and DCPs are connected, the VF of each node in the distribution network with HPDP has been significantly improved, fully verifying the effectiveness of the governance measures proposed in this article.

Conclusion
This article first constructs a model of PV, ESS, and DCP systems.Then, from a spatial perspective, a method for evaluating the voltage flexibility of distribution network nodes was proposed.We analyzed the impact of HPDPs access on the VF of the distribution network, and proposed governance measures for integrating EESs and DCPs into the distribution network.Finally, taking a typical 10 kV distribution network basic architecture in Jilin Province as an example, a numerical analysis was conducted to verify the effectiveness of the evaluation method and governance measures proposed in this article, and the following conclusions were drawn: (1) By analyzing the distribution network from a spatial perspective, it can be seen that nodes connected to HPDPs and nodes at the end of the line in the distribution network are prone to insufficient operational flexibility; (2) According to the M C, i results, EESs and DCPs are connected at nodes with insufficient or severe VF in the distribution network.Not only can it improve the VF of the distribution network and promote HPDP consumption, but it can also improve the operational efficiency and benefit of the distribution network, and assist in the promotion and use of NEEVs in the Northeast region.
6) where K C,i + represents the adequacy of the node to withstand upward voltage fluctuations, and K C, i represents the adequacy of the node to withstand downward voltage fluctuations.The evaluation index of node VF adequacy refers to the probability that the fluctuation of node voltage does not exceed the range of voltage fluctuation adequacy within one operating cycle.It can effectively reflect the VF of each node in the distribution network.The expression is:

Figure 2 .
Figure 2. M C, i values for different nodes Figure 3. M C, i values for different nodes

Table 1 .
ESS and DCP access capacity of each node