Photovoltaic cluster division method considering photovoltaic power generation and electricity-carbon coupling mode

Abstract

The invention discloses a photovoltaic cluster division method considering photovoltaic power generation and an electricity-carbon coupling mode, and belongs to the technical field of power grids, and the method comprises the following steps: S1, determining division indexes including photovoltaic regulation and control capacity, node carbon potential and node net power carbon flow rate; s2, carrying out normalization processing on the division indexes; s3, weighting the normalized division indexes by using an entropy weight method; s4, on the basis of the weighting result and the normalization processing result, constructing a similarity matrix of division indexes between the nodes; and S5, based on the similarity matrix of the division indexes between the nodes, dividing the photovoltaic cluster. By adopting the photovoltaic cluster division method considering photovoltaic power generation and an electricity-carbon coupling mode, multi-dimensional indexes such as photovoltaic regulation and control capacity, node carbon potential, net power carbon flow rate and the like are combined to evaluate and divide clusters, power grid load distribution can be balanced, and the stability and flexibility of a system are enhanced.

Description

Technical Field

[0001] The present invention relates to the field of power grid technology, and in particular to a photovoltaic cluster division method considering photovoltaic power generation and an electricity-carbon coupling mode. Background Art

[0002] A photovoltaic cluster refers to a combination of multiple photovoltaic power stations densely deployed in a specific geographical area, so as to achieve large-scale, integrated and coordinated management through centralized configuration. The photovoltaic power stations in the same cluster operate in coordination and share monitoring and maintenance resources, thereby improving the operating efficiency, stability and economy of the power system.

[0003] Wang Lei, Zhang Fan, Kou Lingfeng, etc. applied the community discovery algorithm to perform photovoltaic power cluster division in "Scaled Distributed Photovoltaic Power Cluster Division Based on Fast Unfolding Clustering Algorithm" to improve the accuracy and efficiency of cluster division.

[0004] Shi Bo, Xiao Chuanliang, Peng Ke et al. proposed a multi-index comprehensive distribution network cluster division method that considers electrical distance, cluster power balance and cluster size in the "Distribution Network-Source-Reservoir Two-Layer Joint Expansion Planning Strategy Based on Cluster Division".

[0005] Lu Junjie, Cai Tao, Lang Jianxun et al. proposed a photovoltaic cluster short-term power prediction method based on K-means clustering in "Short-term prediction method for photovoltaic power station cluster power generation based on cluster division" to improve the accuracy of short-term prediction of photovoltaic power station cluster power generation.

[0006] Ma Lubin, Pan Guobing, Jiang Qun et al. proposed an improved statistical upscaling photovoltaic cluster output prediction method based on EOF-DBSCAN cluster division in "Research on Distributed Photovoltaic Cluster Output Forecasting Method Based on EOF-DBSCAN-GRU".

[0007] It can be seen that the existing technology mainly studies the photovoltaic cluster division indicators and division methods from the perspectives of electrical distance, reactive power regulation capacity, etc., without considering the impact of system carbon flow distribution on the division of photovoltaic power generation clusters. Summary of the invention

[0008] The purpose of the present invention is to provide a photovoltaic cluster division method taking into account photovoltaic power generation and electricity-carbon coupling mode to solve the above technical problems.

[0009] To achieve the above object, the present invention provides a photovoltaic cluster division method considering photovoltaic power generation and electricity-carbon coupling mode, comprising the following steps:

[0010] S1. Determine the division indicators, which include photovoltaic control capacity, node carbon potential, and node net power carbon flow rate;

[0011] S2, normalizing the division index determined in step S1;

[0012] S3, using the entropy weight method to weight the division index after normalization processing in step S2;

[0013] S4, based on the weighting result described in step S3 and the normalization processing result described in step S2, constructing a similarity matrix of the partitioning indicators between nodes;

[0014] S5, based on the similarity matrix of the partitioning indexes between nodes constructed in step S4, the photovoltaic cluster is partitioned using the Fast Unfolding algorithm, and the optimal cluster partitioning result is output;

[0015] Step S5 specifically includes the following steps:

[0016] S51, treating each node of the photovoltaic power generation group connected to the equivalent lossless network as an independent cluster;

[0017] S52, matching any two nodes to form a new cluster;

[0018] S53, calculate the modularity function of the new cluster:

[0019]

[0020] Where Q is the modularity function value; is the judgment function; s i is the sum of similarities between node i and other nodes; s j is the sum of the similarities between node j and other nodes; s is the sum of the similarities between all nodes in the equivalent lossless network; s′ ij is the similarity between node i and node j;

[0021] S54, judging whether the modularity function value increases, if it increases, returning to step S52, otherwise outputting the optimal cluster division result.

[0022] Preferably, the photovoltaic control capacity described in step S1 includes active control capacity and reactive control capacity, and the active control capacity Q j and reactive power control capacity P j The calculation formula is as follows

[0023] Q j,min ≤Q j ≤Q j,max

[0024]

[0025] 0≤P j ≤P j,max (3);

[0026] In the formula, Q j,max , Q j,min are the upper and lower limits of the reactive power regulation capacity of the photovoltaic power generation system, in kVar; S j,max is the grid-connected capacity of the photovoltaic inverter, in kVA; P j,max It is the upper limit of the photovoltaic active power regulation capacity, and the lower limit of the photovoltaic active power regulation capacity is set to 0.

[0027] Preferably, the node carbon potential E in step S1 N The calculation formula is as follows:

[0028] E N =(P N -P B T ) -1 P Z T E G (4);

[0029] Where P N is the node active flux matrix, and P N =(P Nij ) N×N , P Nij represents the active power from node i to node j, i,j∈N, N represents the total number of grid nodes; P B is the branch power flow distribution matrix, and P B =(P Bij ) N×N , P Bij represents the active power flow from node i to node j; P Z The photovoltaic generator group is injected into the matrix, and P Z =(P Gkj ) K×N , P Gkj represents the active power injected by photovoltaic generator set k into node j; E G is the carbon emission intensity matrix of photovoltaic power generation units, and E G =(e Gi ) K×N , e Gi Represents the carbon emission intensity of the photovoltaic power generation group at the i-th node.

[0030] Preferably, the calculation formula for the node net power carbon flow rate in step S1 is as follows:

[0031]

[0032] In the formula, R Li is the equivalent lossless network node net power carbon flow rate; is the node power matrix of the equivalent lossless network; P i,pv is the active power output of the photovoltaic system at grid node i; e Ni is the carbon potential of the ith node.

[0033] Preferably, the normalization calculation formula described in step S2 is as follows:

[0034]

[0035] In the formula, x′ i,m is the mth partition index value of the ith node after normalization; x i,m is the original partition index value; max(x n,m ) is the maximum value of the mth partition index; min(x n,m ) is the minimum value of the mth partition index.

[0036] Preferably, the calculation formula for weighting the division index using the entropy weight method described in step S3 is as follows:

[0037]

[0038] Where V im is the value of the i-th node at the m-th partition index, and i∈n, n=N is the total number of grid nodes; φ m is the entropy value of the mth indicator, α m is the weight of the mth indicator.

[0039] Preferably, the similarity matrix calculation formula of the partitioning index between nodes described in step S4 is as follows:

[0040]

[0041] Where s′ ij is the similarity between node i and node j; x i,m ′ is the mth partition index value of the ith node after normalization; x j,m ′ is the mth partition index value of the jth node after normalization; R is the maximum inner product of the ith node and the jth node.

[0042] Therefore, the present invention adopts the above-mentioned photovoltaic cluster division method considering photovoltaic power generation and electricity-carbon coupling mode, which has the following beneficial effects:

[0043] 1. It combines multi-dimensional indicators such as photovoltaic control capacity, node carbon potential and net power carbon flow rate to evaluate and divide clusters, which helps to balance the load distribution of the power grid and enhance the stability and flexibility of the system, especially when a high proportion of renewable energy is connected, and can effectively cope with the challenges brought by intermittent power supply;

[0044] 2. Taking into account carbon emission factors (such as node carbon potential and net power carbon flow rate), it not only focuses on economic benefits and technical performance, but also emphasizes environmental friendliness, which is conducive to promoting green energy transformation and achieving emission reduction targets;

[0045] 3. Use the entropy weight method to objectively assign weights to each evaluation indicator, ensuring that the weight allocation is based on actual data rather than subjective judgment, which enhances the scientificity and accuracy of the decision-making process. At the same time, construct a similarity matrix and apply the FastUnfolding algorithm to further improve the rationality and practicality of the clustering results;

[0046] 4. By rationally dividing photovoltaic clusters, the power generation capacity of photovoltaic power stations can be better managed and scheduled, reducing the phenomenon of abandoned light, thereby improving the utilization efficiency of solar energy resources.

[0047] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 The present invention is a flow chart of a photovoltaic cluster division method in consideration of photovoltaic power generation and electricity-carbon coupling mode. DETAILED DESCRIPTION

[0049] In the description of the present invention, it should be noted that the terms "upper", "lower", "inside", "outside", etc. indicate positions or positional relationships based on the positions or positional relationships shown in the accompanying drawings, or the positions or positional relationships in which the invented product is usually placed when in use. They are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In the description of the present invention, it should also be noted that, unless otherwise clearly specified and limited, the terms "setting", "installation", and "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be an indirect connection through an intermediate medium, or it can be a connection between the two elements. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0050] The embodiments of the present invention are described in detail below in conjunction with the accompanying drawings.

[0051] like Figure 1 As shown, the photovoltaic cluster division method considering photovoltaic power generation and electricity-carbon coupling mode includes the following steps:

[0052] S1. Determine the division indicators, which include photovoltaic control capacity, node carbon potential, and node net power carbon flow rate;

[0053] The photovoltaic control capacity described in step S1 includes active control capacity and reactive control capacity, and the active control capacity Q j and reactive power control capacity P j The calculation formula is as follows

[0054] Q j,min ≤Q j ≤Q j,max

[0055]

[0056] 0≤P j ≤P j,max (3);

[0057] In the formula, Q j,max , Q j,min are the upper and lower limits of the reactive power regulation capacity of the photovoltaic power generation system, in kVar; S j,max is the grid-connected capacity of the photovoltaic inverter, in kVA; P j,max It is the upper limit of the photovoltaic active power regulation capacity, and the lower limit of the photovoltaic active power regulation capacity is set to 0.

[0058] In this embodiment, each photovoltaic power generation group in the cluster should have sufficient reactive power regulation capacity to ensure reactive power support in the event of an emergency in the power grid. When the grid voltage reaches the upper limit, the photovoltaic power generation group can be controlled to reduce reactive power output, thereby adjusting the grid voltage level and stabilizing the system. When the reactive power regulation capacity is close to the upper limit, the photovoltaic power generation group is controlled to increase reactive power output, thereby reducing the reactive power regulation capacity and further ensuring safe operation of the system.

[0059] Dividing the nodes with similar carbon potential into a cluster, that is, considering the carbon potential balance of each node, is conducive to achieving balanced distribution of carbon flow within the cluster. Therefore, in this embodiment, the node carbon potential is considered, and the node carbon potential E in step S1 is N The calculation formula is as follows:

[0060] E N =(P N -P B T ) -1 P Z T E G (4);

[0061] Where P N is the node active flux matrix, and P N =(P Nij ) N×N , P Nij represents the active power from node i to node j, i,j∈N, N represents the total number of grid nodes; PB is the branch power flow distribution matrix, and P B =(P Bij ) N×N , P Bij represents the active power flow from node i to node j; P Z The photovoltaic generator group is injected into the matrix, and P Z =(P Gkj ) K×N , P Gkj represents the active power injected by photovoltaic generator set k into node j; E G is the carbon emission intensity matrix of photovoltaic power generation units, and E G =(e Gi ) K×N , e Gi Represents the carbon emission intensity of the photovoltaic power generation group at the i-th node.

[0062] In order to clarify the impact of different photovoltaic power stations on the system carbon emissions after being connected to the grid nodes, and to use photovoltaic power stations with similar impact as reference indicators for cluster division; the node net power carbon flow rate is considered, and the calculation formula of the node net power carbon flow rate described in step S1 is as follows:

[0063]

[0064] In the formula, R Li is the equivalent lossless network node net power carbon flow rate; is the node power matrix of the equivalent lossless network; P i,pv is the active power output of the photovoltaic system at grid node i; e Ni is the carbon potential of the ith node.

[0065] In this embodiment, in order to accurately calculate the node carbon flow rate index, the node net power value can also be calculated based on formula (5). The node net power value is the difference between the node power value in the equivalent lossless network and the photovoltaic power generation output connected to the point.

[0066] S2. In order to distinguish the effects of different partitioning indicators in cluster partitioning, the partitioning indicators are weighted using the entropy weight method, and the partitioning indicators determined in step S1 are normalized;

[0067] The normalization calculation formula described in step S2 is as follows:

[0068]

[0069] In the formula, x′ i,m is the mth partition index value of the ith node after normalization; x i,m is the original partition index value; max(x n,m) is the maximum value of the mth partition index; min(x n,m ) is the minimum value of the mth partition index.

[0070] S3, using the entropy weight method to weight the division index after normalization processing in step S2;

[0071] The calculation formula for weighting the division index using the entropy weight method described in step S3 is as follows:

[0072]

[0073] Where V im is the value of the i-th node at the m-th partition index, and i∈n, n=N is the total number of grid nodes; φ m is the entropy value of the mth indicator, α m is the weight of the mth indicator.

[0074] S4, based on the weighting result described in step S3 and the normalization processing result described in step S2, constructing a similarity matrix of the partitioning indicators between nodes;

[0075] The similarity matrix calculation formula of the partition index between nodes described in step S4 is as follows:

[0076]

[0077] Where s′ ij is the similarity between node i and node j; x i,m ′ is the mth partition index value of the ith node after normalization; x j,m ′ is the mth partition index value of the jth node after normalization; R is the maximum inner product of the ith node and the jth node.

[0078] S5, based on the similarity matrix of the partitioning indexes between nodes constructed in step S4, the photovoltaic cluster is partitioned using the Fast Unfolding algorithm, and the optimal cluster partitioning result is output;

[0079] Step S5 specifically includes the following steps:

[0080] S51, treating each node of the photovoltaic power generation group connected to the equivalent lossless network as an independent cluster;

[0081] S52, matching any two nodes to form a new cluster;

[0082] S53, calculate the modularity function of the new cluster:

[0083]

[0084] Where Q is the modularity function value; is the judgment function; s i is the sum of the similarities between node i and other nodes; s is the sum of the similarities between all nodes in the equivalent lossless network;

[0085] S54, judging whether the modularity function value increases, if it increases, returning to step S52, otherwise outputting the optimal cluster division result.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that they can still modify or replace the technical solution of the present invention with equivalents, and these modifications or equivalent replacements cannot cause the modified technical solution to deviate from the spirit and scope of the technical solution of the present invention.

Claims

1. A photovoltaic cluster division method considering photovoltaic power generation and electricity-carbon coupling mode, characterized by: The following steps are involved: S1. Determine the division indicators, which include photovoltaic control capacity, node carbon potential, and node net power carbon flow rate; S2, normalizing the division index determined in step S1; S3, using the entropy weight method to weight the division index after normalization processing in step S2; S4, based on the weighting result described in step S3 and the normalization processing result described in step S2, constructing a similarity matrix of the partitioning indicators between nodes; S5, based on the similarity matrix of the partitioning indicators between nodes constructed in step S4, the photovoltaic cluster is partitioned using the Fast Unfolding algorithm, and the optimal cluster partitioning result is output; Step S5 specifically includes the following steps: S51, treating each node of the photovoltaic power generation group connected to the equivalent lossless network as an independent cluster; S52, matching any two nodes to form a new cluster; S53, calculate the modularity function of the new cluster: Where Q is the modularity function value; is the judgment function; s i is the sum of similarities between node i and other nodes; s j is the sum of the similarities between node j and other nodes; s is the sum of the similarities between all nodes in the equivalent lossless network; s i ' j is the similarity between node i and node j; S54, judging whether the modularity function value increases, if it increases, returning to step S52, otherwise outputting the optimal cluster division result.

2. The photovoltaic cluster division method considering photovoltaic power generation and electricity-carbon coupling mode according to claim 1 is characterized in that: The photovoltaic control capacity described in step S1 includes active control capacity and reactive control capacity, and the active control capacity Q j and reactive power control capacity P j The calculation formula is as follows 0≤P j ≤P j,max (3); In the formula, Q j,max , Q j,min are the upper and lower limits of the reactive power regulation capacity of the photovoltaic power generation system, in kVar; S j,max is the grid-connected capacity of the photovoltaic inverter, in kVA; P j,max It is the upper limit of the photovoltaic active power regulation capacity, and the lower limit of the photovoltaic active power regulation capacity is set to 0.

3. The photovoltaic cluster division method considering photovoltaic power generation and electricity-carbon coupling mode according to claim 2 is characterized in that: The node carbon potential E in step S1 N The calculation formula is as follows: AND N =(P N -P B T ) -1 P Z T AND G (4); Where P N is the node active flux matrix, and P N =(P Nij ) N×N , P Nij represents the active power from node i to node j, i,j∈N, N represents the total number of grid nodes; P B is the branch power flow distribution matrix, and P B =(P Bij ) N×N , P Bij represents the active power flow from node i to node j; P Z The photovoltaic generator group is injected into the matrix, and P Z =(P Gkj ) K×N , P Gkj represents the active power injected by photovoltaic generator set k into node j; E G is the carbon emission intensity matrix of photovoltaic power generation units, and E G =(e Gi ) K×N , e Gi Represents the carbon emission intensity of the photovoltaic power generation group at the i-th node.

4. The photovoltaic cluster division method considering photovoltaic power generation and electricity-carbon coupling mode according to claim 3 is characterized in that: The calculation formula of the node net power carbon flow rate in step S1 is as follows: In the formula, R Li is the equivalent lossless network node net power carbon flow rate; is the node power matrix of the equivalent lossless network; P i,pv is the active power output of the photovoltaic system at grid node i; e Ni is the carbon potential of the ith node.

5. The photovoltaic cluster division method considering photovoltaic power generation and electricity-carbon coupling mode according to claim 4 is characterized in that: The normalization calculation formula described in step S2 is as follows: In the formula, x i ' ,m is the mth partition index value of the ith node after normalization; x i,m is the original partition index value; max(x n,m ) is the maximum value of the mth partition index; min(x n,m ) is the minimum value of the mth partition index.

6. The photovoltaic cluster division method considering photovoltaic power generation and electricity-carbon coupling mode according to claim 5 is characterized in that: The calculation formula for weighting the division index using the entropy weight method described in step S3 is as follows: Where V im is the value of the i-th node at the m-th partition index, and i∈n, n=N is the total number of grid nodes; φ m is the entropy value of the mth indicator, α m is the weight of the mth indicator.

7. The photovoltaic cluster division method considering photovoltaic power generation and electricity-carbon coupling mode according to claim 6 is characterized in that: The similarity matrix calculation formula of the partition index between nodes described in step S4 is as follows: In the formula, s i ' j is the similarity between node i and node j; x i,m ′ is the mth partition index value of the ith node after normalization; x j,m ′ is the mth partition index value of the jth node after normalization; R is the maximum inner product of the ith node and the jth node.

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