Carbon Flow Analysis Method Of Distribution Network Considering High Proportion Of New Energy

This paper proposes a tracking method for the carbon flow intensity of the distribution network under a high proportion of new energy. Firstly, a power flow tracking model is proposed based on the proportional sharing principle. Then, considering network loss, a model on the ground of the carbon emission flow theory of the power system is established for analyzing carbon emissions in a distribution system with a high ratio of green power. Moreover, the availability and accuracy of the model are verified by the IEEE33 node example.


Introduction
Scientific and accurate carbon emission accounting is the basis for mastering the carbon emission status of electricity.The conventional method of calculating carbon emissions based on power generation ignores the principle of demand-generating supply, and cannot provide user-side power sources and accurate carbon emission coefficients.Therefore, researching the carbon footprint of distribution networks is highly important under the background of a high proportion of clean energy access to power systems.By analyzing the carbon emission flow of the distribution network, the power source of the user side can be clarified, and the distribution network's carbon footprint can be mastered, which provides a scientific basis for dividing the carbon emission responsibility and formulating carbon emission reduction measures.
In recent years, more and more experts and scholars have shifted the research on carbon emissions to the distribution network side.Davidson et al. [1] proposed a power flow carbon intensity calculation tracking method for distribution networks considering local power consumption and system loss.Li et al. [2] proposed a carbon flow tracing method to track the total energy usage of the entire network to define the carbon emission obligation generated by electricity consumption.Li et al. [3] established an evaluation model of the power carbon footprint of end-users by tracing the active source of the load.Gong et al. [4] established a carbon circuit tracking model resting on the complex power circuit tracking model considering network loss.Stemming from the conception of system node carbon potential balance, Kang et al. [5] proposed a recursive algorithm for power system carbon emission flow.Yuan et al. [6] proposed a method for allocating carbon emissions in power systems.From the perspective of secondary energy terminal consumption, Wang et al. [7] proposed a calculation method for carbon emissions from fossil energy consumption in China's provinces.Ma et al. [8] proposed a method to calculate the impact factor of wind power injection power on carbon emission flow.Zhang et al. [9] established a computing method for optimal carbon flux.From the perspective of the load side, Zhou et al. [10] analyzed and compared the Shapley value method and generalized nucleolus method based on cooperative game theory.In Wang's research [11], the actual power network is decomposed, and the power circuit tracking and carbon circuit reckon are carried out respectively, so as to overcome the difficulty in accurately measuring hidden carbon footprint.
In summary, the carbon emission flow principle advances a new idea for the analysis of carbon emissions in power systems, but the principle of carbon emission flow is still in the development stage, and the carbon emission calculation model for high-proportion renewable power access to the electric network is not perfect.Based on the power flow tracking model and carbon emission flow, this paper proposes a carbon circuit analysis model of a distribution network with a high proportion of new energy and verifies its correctness and applicability through the IEEE33 node example.

Power flow tracking model
The technical core of power flow tracing is the theory of proportional sharing, that is, the power flowing into the node is shared proportionally between the power supply and the branch.
For a multi-node system, the injection power of any node is : For investigating the carbon emissions on the distribution side, this downstream tracking method should be used to track the power circuit and carbon circuit.In the actual power grid, there is a loss because of the line resistance.In order to make it equivalent to a lossless network, a virtual node can be added to the branch, so that the node load is equal to the branch impedance loss.
The elements in the backtracking matrix ij A are defined as:

−
A exists, the relationship between node power and generator output is : The elements in the load coefficient matrix ij T are defined as: Therefore, the relationship between the power consumption on any load and the generator output can be linearly expressed as :

Carbon flow tracking model with a high proportion of new energy
Carbon flow is not real, but a virtual network flow based on power flow.Carbon flow relies on the power flow, and there is a numerical correspondence between them.By constructing the corresponding relationship between branch power flow and carbon emission, carbon flow will be received.The carbon flow diagram is shown in Fig. 1.To determine the network distribution of power carbon emissions, it is vital to trace the power of the distribution side, and the process is defined as carbon flow tracking.Carbon emissions are generated in the power generation link.By establishing a carbon flow tracking model, carbon emissions can be transferred from the power generation link to the distribution side, and the carbon emission intensity can be calculated by tracing the power source and quantity of the distribution side.In low-voltage distribution networks, if a carbon flow calculation model with a high proportion of new energy is to be established, it is necessary to consider the loss during power transmission to make sure that the result is exact.Among them, the carbon flow density is an indicator to measure the carbon emissions generated by power generation per unit of time, is merely influenced by the category and percentage of power generation, and is unrelated to the network formation.The generator with x groups of power g i P and carbon emission intensity of i Ω kg / (kWh).Moreover, both the clean capacity with y groups of power q i P and the carbon emission intensity of 0 are built to supply power to the distribution network.
The carbon flow density equation of node injection can be expressed as : ω , the carbon flow density can be expressed as : The expression of node carbon emission intensity considering network loss is : ( ) Because the power flow of the distribution network is different in different periods, according to the variation of load and clean power, the function of power injection power, load power, and network loss power about time is introduced to calculate the carbon emission of the node in a certain period of time.The carbon emission rate equation is: In the time integration of c U in a span, the calculation formula is as follows :

Example description
In this paper, the IEEE33 node standard distribution system shown in Fig. 2 is taken as an example to verify the correctness of the proposed power flow tracking and carbon flow tracking models.Node 1 is the balance node, and the other nodes are PQ nodes.The reference voltage at the head of the network is 12.66 KV, and the three-phase power reference value is 10 MVA.The power is converted into a unit value for calculation.Renewable energy as an effective means of carbon emission reduction is the key technology to achieve carbon neutrality.For analyzing the influence of carbon emission reduction after the introduction of green power, this paper sets up two scenarios.In Scenario 1, there is no clean power supply, and both the type of main network unit and the carbon emission intensity are shown in Fig. 3. Scenario 2 adds three different clean power sources to nodes 6,15, and 32 on the basis of Scenario 1, where nodes 6 and 32 are connected to 10 KV photovoltaic generators respectively, and node 15 is connected to 300 KV wind turbines.

Result analysis
According to the power flow tracking and carbon flow tracking model, the results obtained in Scenario 1 and Scenario 2 are as follows.Table 1 shows the network loss and carbon emission rate of each branch.4 and Fig. 5 show the carbon emission rate and emission reduction ratio of nodes and loads in two cases.It is obvious that the carbon emission rates of network loss and the panel point under Scenario 1 are 138.67 kg/h and 2404.23 kg/h, respectively.The sum of the two is the same as the carbon current rate of the root node revealed in Fig. 4, which manifests the accuracy of the pattern.Similarly, under Scenario 2, the carbon emission rate of network loss is 87.17 kg/h and the carbon emission rate of cargo is 2056.35kg/h, and the calculated result is 2143.52 kg/h.Linked to the carbon emission rate of the root node demonstrated in Fig. 4, the error is within the acceptable extent, which proves the practicability of the method.Linked to Scenario 1, the system carbon emission rate under Scenario 2 is reduced from 2542.90 kg/h to 2123.51 kg/h.It can be seen that after the introduction of clean power, all node loads have achieved different degrees of carbon emission reduction.

Figure 4 .
Figure 4. Node carbon emission rate Figure 5. Load carbon emission rate5.ConclusionsOn the basis of power flow tracking, this paper establishes a power flow tracking model of a distribution network with a high proportion of new energy by using carbon emission flow theory.The carbon emission reduction effect after the introduction of green energy is analyzed by the IEEE33 node distribution system, and the validity and practicability of the model are verified, which provides technical reference for the establishment of a perfect carbon accounting system.

Table 1 .
Network loss carbon emission rate tracking results.