Power distribution network load green low-carbon benefit allocation method, system and equipment based on curve similarity and medium

Abstract

The invention discloses a curve similarity-based power distribution network load green low-carbon benefit allocation method, system, device and medium, and the method comprises the steps: calculating the total power generation amount and new energy unit power generation amount of a transformer area according to the generator set type and power generation amount of the transformer area; calculating the total input electric quantity and the input green electric quantity of each transformer area, calculating the total electric quantity balance value of each transformer area, and then calculating the green electric quantity balance value of each transformer area; calculating an average green power factor of the transformer area; calculating the curve similarity of the new energy power generation curve in the transformer area and the demand side user load power curve before aggregation; load aggregation is carried out on all users participating in demand side response, an aggregation load power curve is obtained, the curve similarity after aggregation of the aggregation load power curve and a new energy power generation curve is calculated, the green power distribution coefficient of the demand side users is calculated, the green power factor of the power distribution network station area users is calculated, and green power benefit allocation of demand side power utilization is achieved. The invention improves the enthusiasm of the user to participate in the demand side response.

Description

Technical Field

[0001] The present invention relates to the field of carbon peak and carbon neutrality technology, and specifically to a green and low-carbon benefit sharing method, system, equipment and medium for distribution network load based on curve similarity. Background Art

[0002] In the current electricity market, users' demand for green electricity is increasing. However, the existing power supply system and management mechanism have not been able to fully and accurately reflect and track users' actual green electricity usage and carbon emissions. The existing traceability methods mainly focus on the total amount analysis at the macro level, lacking the refined management and green electricity benefit allocation methods at the micro level, and it is difficult to meet users' refined demand for green electricity use.

[0003] Therefore, there is an urgent need for a method that can form a larger, controllable power load by aggregating the loads of multiple small power users based on real-time power data and new energy output, and accurately calculate the aggregated load and the green power usage of demand-side users and the corresponding carbon emissions. This will not only help improve the utilization rate of green power, but also provide users with more transparent and reliable power consumption information, and promote the consumption and popularization of green power. At the same time, load aggregation can reduce power consumption during peak hours through demand response measures, reduce the power generation costs of power companies and the operating pressure of the power grid. For users, by participating in load aggregation, they can obtain economic incentives and reduce electricity costs. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides a green and low-carbon benefit allocation method, system, equipment and medium for distribution network load based on curve similarity, aiming to achieve green electricity benefit allocation for demand-side electricity consumption through a comprehensive analysis of the power injection, carbon emissions and green power data of each substation in the power grid.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A green and low-carbon benefit allocation method for distribution network load based on curve similarity includes the following steps:

[0007] Obtain the topological structure and power data of the distribution network, and regard the area covered by the transformer nodes of the distribution network as a substation; calculate the total power generation of the substation and the power generation of the new energy units according to the type and power generation of the generator sets in the substation;

[0008] Calculate the total input electricity and input green electricity of each substation, calculate the total electricity balance value of the substation based on the total power generation and total input electricity of each substation, and then calculate the green electricity balance value of the substation based on the power generation of each new energy unit in the substation and the input green electricity of each substation; calculate the average green electricity factor of the substation based on the total electricity balance value and green electricity balance value of the substation;

[0009] Combined with the load data of the demand-side users in the substation, the similarity between the new energy power generation curve in the substation and the load power curve of the demand-side users before aggregation is calculated; load aggregation is carried out for all users participating in the demand-side response to obtain the aggregated load power curve, and the similarity between the aggregated load power curve and the new energy power generation curve after aggregation is calculated. The principle of load aggregation is that the similarity of the curve after aggregation is higher than the similarity of the curve before aggregation. According to the similarity of the curve after aggregation, the green electricity allocation coefficient of the demand-side user is calculated, and the green electricity factor of the users in the distribution network substation is calculated according to the average green electricity factor and the green electricity allocation coefficient, so as to realize the green electricity benefit sharing of the demand-side electricity consumption.

[0010] To optimize the above technical solutions, the specific measures taken also include:

[0011] Furthermore, the topological structure of the distribution network includes: a geographical wiring diagram and an electrical connection diagram of the distribution network; the power data of the distribution network includes: the power generation of the distributed new energy units of the distribution network and the power generation of other units;

[0012] The specific process of calculating the total power generation of the substation and the power generation of the new energy units according to the type and power generation of the generator units in the substation is as follows:

[0013] The total power generation G of the operating generator sets in the ith area during the evaluation period t i The calculation formula is as follows:

[0014]

[0015] In the formula, G i，j represents the power generation power of the jth generator set in operation in the i-th area, and m represents the total number of generator sets;

[0016] The power generation of all renewable energy units in operation in the i-th area during the evaluation period t is GG i The calculation formula is as follows:

[0017]

[0018] In the formula, GG i，j represents the power generation power of the jth renewable energy unit among all renewable energy units running in the i-th area during the evaluation period t, Represents the total number of new energy units.

[0019] Furthermore, the total input power and input green power of each substation are calculated as follows:

[0020] For a distribution network with n substations, the total power input from other substations to the i-th substation during the evaluation period t is X i for:

[0021]

[0022] Where, X i，j represents the power input from area j to area i through the tie line; X i，a It represents the power input from the main grid to the station area i through the tie line;

[0023] The amount of green electricity GX input from other substations to the i-th substation during the evaluation period t i for:

[0024]

[0025] X i，j represents the power input from area j to area i through the tie line; GF j represents the green power factor of area j; X i，a Indicates the power input from the main grid to the station area i through the tie line; GF a Indicates the green power factor of the main grid.

[0026] Furthermore, the total power balance value of each substation is calculated based on the total power generation and total input power of each substation as follows:

[0027] The total power balance value of the substation area consists of two parts: the total power generation of all generators in the substation area G i , the total power input from other areas and the main grid to area i is X i , the calculation formula is as follows:

[0028] Q i =G i +X i

[0029] In the formula, Q i Indicates the power balance value of the area;

[0030] The green power balance value of each substation calculated based on the power generation of each substation's new energy units and the input green power of each substation is specifically:

[0031] The green electricity balance value of the area is also composed of two parts: the total power generation of all new energy generators in the area GG i , the green electricity GX input from other areas and the main grid to area i i , the calculation formula is as follows:

[0032] GQ i =GG i +GX i

[0033] In the formula, GQ i Indicates the green electricity balance value of the substation;

[0034] The calculation of the average green power factor of the area according to the total power balance value of the area and the green power balance value of the area is specifically:

[0035]

[0036] In the formula, GF i Represents the average green power factor of area i.

[0037] Furthermore, the calculation of the similarity before aggregation between the new energy generation curve in the substation area and the load power curve of the demand-side user is specifically as follows:

[0038] Define the shape of the new energy generation curve and the demand-side user load power curve within the total evaluation period T:

[0039]

[0040] Where, L i，g (t) is the new energy power generation curve of area i, YesL i，g (t) is normalized by the function f u (·) after the per unit value, L i,n (t) is the load power curve of a user n in the station area i; YesL i，n (t) is normalized by the function f u (·) after the per unit value;

[0041] Using indicator E i,n Evaluate the similarity before aggregation between the power curve of renewable energy generation and the power curve of demand-side user load, index E i,n The formula is as follows:

[0042] E i，n = i，n β i，n

[0043] α i,n =e -ε|D|

[0044]

[0045] In the formula, α i,nis the measurement index after the Euclidean distance D between the load power curve of user n and the renewable energy power curve of station i in time period t is mapped to the interval (0, 1], ε is a given constant value, e is a natural constant, β i，n is the proportion of the power consumption of user n in time period t to the renewable energy power generation in the same period, and D is the per unit value of the renewable energy power curve And the per unit value of the demand side user load power curve The Euclidean distance between them, T is the total evaluation period.

[0046] Furthermore, the specific process of carrying out load aggregation for all users participating in demand-side response is as follows:

[0047] The loads participating in the demand-side response through load aggregators and self-aggregation are collectively referred to as aggregated loads. The power consumption per unit curve of aggregated load a in distribution network area i is:

[0048]

[0049] In the formula, It is the power consumption per unit curve of the aggregated load a which is aggregated from load 1 to load n in the time period T. The principle of load aggregation is that after the user participates in a certain aggregated load, the similarity between the load power curve of the aggregated load and the aggregated curve of the new energy power generation curve is improved;

[0050] The calculation of the similarity between the load power curve of the aggregated load a and the aggregated curve of the new energy power generation curve is specifically:

[0051] E i，a = i，a β i，a

[0052] In the formula, E i,a Indicates the similarity between the load power curve of aggregated load a and the aggregated new energy power curve of station i in time period t, α i,a It represents the measurement index after the Euclidean distance D between the load power curve of aggregate load a and the new energy generation curve of station i in time period t is mapped to the interval (0, 1], β i，a It indicates the proportion of the power consumption of aggregate load a in time period t to the renewable energy power generation in the substation during the same period.

[0053] Furthermore, the green electricity allocation coefficient of the demand-side user is calculated based on the similarity of the aggregated curves as follows:

[0054]

[0055] In the formula, γ i，arepresents the green power allocation coefficient of aggregated load a in area i, m represents the number of aggregated loads participating in demand-side response in area i; E i,a It represents the similarity of the aggregated load power curve of aggregated load a and the aggregated new energy power curve of area i in time period t;

[0056] The green power factor of users in the distribution network area is calculated based on the average green power factor and the green power allocation coefficient, which specifically includes:

[0057] The amount of green electricity consumed by the aggregated load a under the station area i is distributed according to the green electricity distribution coefficient:

[0058] GQ i，a =GF i ×∫0 t L i，s (t)×γ i，a

[0059] Where, L i,s (t) is the power curve of all loads participating in demand-side response in distribution network area i during the evaluation period t, GQ i，a represents the amount of green electricity consumed by the aggregate load a, GF i represents the average green power factor of area i, γ i，a represents the green power allocation coefficient of aggregate load a under station area i;

[0060] The amount of green electricity consumed by user n participating in the aggregate load a under the station area i is calculated according to the curve similarity of user n to the aggregate load a.

[0061] distribute:

[0062]

[0063] GQ i，n =GQ i，a ×θ i，a，n

[0064] In the formula, θ i，a，n represents the green power allocation coefficient of user n under aggregate load a in area i, E i，a，n GQ represents the curve similarity of user n under aggregate load a in station i, i，n It represents the amount of green electricity consumed by user n under the aggregated load a in the substation i;

[0065] Green power factor GF of user n i,n The calculation formula is as follows:

[0066]

[0067] L i，n(t) is the power curve of user n participating in demand-side response in distribution network area i during the evaluation period t.

[0068] The present invention also proposes a green and low-carbon benefit sharing system for distribution network load based on curve similarity, comprising:

[0069] Data acquisition module, used to obtain the topological structure and power data of the distribution network;

[0070] The power generation calculation module is used to regard the area covered by the transformer node of the distribution network as a substation; according to the type and power generation of the generator set in the substation, the total power generation of the substation and the power generation of the new energy unit are calculated;

[0071] The average green power factor calculation module is used to calculate the total input power and input green power of each substation, calculate the total power balance value of the substation according to the total power generation and total input power of each substation, and then calculate the green power balance value of the substation according to the power generation of the new energy units in each substation and the input green power of each substation; calculate the average green power factor of the substation according to the total power balance value and green power balance value of the substation;

[0072] The green electricity allocation coefficient calculation module is used to calculate the similarity of the new energy power generation curve in the substation area and the load power curve of the demand-side user before aggregation in combination with the load data of the demand-side user in the substation area; load aggregation is carried out for all users participating in the demand-side response to obtain the aggregated load power curve, and the similarity of the aggregated load power curve and the new energy power generation curve after aggregation is calculated. The principle of load aggregation is that the similarity of the curve after aggregation is higher than the similarity of the curve before aggregation. According to the similarity of the curve after aggregation, the green electricity allocation coefficient of the demand-side user is calculated;

[0073] The green electricity benefit sharing module is used to calculate the green electricity factor of users in the distribution network area based on the average green electricity factor and the green electricity allocation coefficient, so as to realize the green electricity benefit sharing of electricity consumption on the demand side.

[0074] The present invention also proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the green and low-carbon benefit sharing method for distribution network load based on curve similarity as described above is implemented.

[0075] The present invention also proposes a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the green and low-carbon benefit allocation method for distribution network load based on curve similarity as described above.

[0076] The beneficial effects of the present invention are as follows: the present invention collects the topological structure and power information of the distribution network, calculates the average green power factor of each substation of the distribution network, calculates the similarity between the load curve after the user response and the distributed new energy output curve according to the load response of the user participating in the demand side response, and according to the similarity result, performs load aggregation on the user, calculates the green power consumed by the aggregated load, calculates the green power allocated to the user, calculates the green power factor of the demand side user, completes the allocation of green power benefits from the network side to the demand side, and improves the enthusiasm of users to participate in the demand side response. Reduce the power generation cost of power companies and the operating pressure of the power grid. BRIEF DESCRIPTION OF THE DRAWINGS

[0077] Figure 1 This is a flow chart of a green and low-carbon benefit allocation method for distribution network load based on curve similarity.

[0078] Figure 2 Schematic diagram of the process of polymerizing load. DETAILED DESCRIPTION

[0079] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0080] Embodiment 1

[0081] The present invention proposes a method for allocating green and low-carbon benefits of distribution network loads based on curve similarity, which is applicable to distribution networks of 110kV and below that include distributed renewable energy. The flow chart of the method is as follows: Figure 1 As shown, the following steps are included:

[0082] Step 1: Obtain the topological structure and power data of the distribution network, and regard the area covered by the transformer node of the distribution network as a substation; the topological structure of the distribution network includes: the geographical wiring diagram and electrical connection diagram of the distribution network; the power data of the distribution network includes: the power generation of the distributed new energy units of the distribution network and the power generation of other units; according to the type and power generation of the generator units in the substation, calculate the total power generation of the substation and the power generation of the new energy units; the specific process of calculating the total power generation of the substation and the power generation of the new energy units according to the type and power generation of the generator units in the substation is:

[0083] The total power generation G of the operating generator sets in the ith area during the evaluation period t i The calculation formula is as follows:

[0084]

[0085] In the formula, G i，j represents the power generation power of the jth generator set in operation in the i-th area, and m represents the total number of generator sets;

[0086] The power generation of all renewable energy units in operation in the i-th area during the evaluation period t is GG i The calculation formula is as follows:

[0087]

[0088] In the formula, GG i，j represents the power generation power of the jth renewable energy unit among all renewable energy units running in the i-th area during the evaluation period t, Represents the total number of new energy units.

[0089] Step 2: Calculate the total input power and input green power of each substation; specifically:

[0090] For a distribution network with n substations, the total power input from other substations to the i-th substation during the evaluation period t is X i for:

[0091]

[0092] Where, X i，j represents the power input from area j to area i through the tie line; X i，a It represents the power input from the main grid to the station area i through the tie line;

[0093] The amount of green electricity GX input from other substations to the i-th substation during the evaluation period t i for:

[0094]

[0095] X i，j represents the power input from area j to area i through the tie line; GF j represents the green power factor of area j; X i，a Indicates the power input from the main grid to the station area i through the tie line; GF a Indicates the green power factor of the main grid.

[0096] Step 3: Calculate the total power balance value of each substation based on the total power generation and total input power of each substation, and then calculate the green power balance value of each substation based on the power generation of each new energy unit and the input green power of each substation; calculate the average green power factor of the substation based on the total power balance value and green power balance value of the substation;

[0097] The total power balance value of each substation area calculated based on the total power generation and total input power of each substation area is specifically:

[0098] The total power balance value of the substation area consists of two parts: the total power generation of all generators in the substation area G i , the total power input from other areas and the main grid to area i is X i , the calculation formula is as follows:

[0099] Q i =G i +X i

[0100] In the formula, Q i Indicates the power balance value of the area;

[0101] The green power balance value of each substation calculated based on the power generation of each substation's new energy units and the input green power of each substation is specifically:

[0102] The green electricity balance value of the area is also composed of two parts: the total power generation of all new energy generators in the area GG i , the green electricity GX input from other areas and the main grid to area i i , the calculation formula is as follows:

[0103] GQ i =GG i +GX i

[0104] In the formula, GQ i Indicates the green electricity balance value of the substation;

[0105] The calculation of the average green power factor of the area according to the total power balance value of the area and the green power balance value of the area is specifically:

[0106]

[0107] In the formula, GF i Represents the average green power factor of area i.

[0108] Step 4: Combined with the load data of the demand-side users in the substation, calculate the similarity of the new energy power generation curve in the substation and the load power curve of the demand-side users before aggregation; the calculation of the similarity of the new energy power generation curve in the substation and the load power curve of the demand-side users before aggregation is specifically:

[0109] Define the shape of the new energy generation curve and the demand-side user load power curve within the total evaluation period T:

[0110]

[0111] Where, L i，g (t) is the new energy power generation curve of area i, YesL i，g(t) is normalized by the function f u (·) after the per unit value, L i，n (t) is the load power curve of a user n in the station area i; YesL i,n (t) is normalized by the function f u (·) after the per unit value;

[0112] Using indicator E i,n Evaluate the similarity before aggregation between the power curve of renewable energy generation and the power curve of demand-side user load, index E i,n The formula is as follows:

[0113] E i，n = i，n β i，n

[0114] α i,n =e -ε|D|

[0115]

[0116] In the formula, E i,n It is an indicator that comprehensively considers the user's electricity consumption curve and the matching degree of the user's electricity consumption with the new energy generation curve, which is defined as the curve similarity, α i,n is the measurement index after the Euclidean distance D between the load power curve of user n and the renewable energy power curve of station i in time period t is mapped to the interval (0, 1], ε is a given constant value, e is a natural constant, β i，n is the proportion of the power consumption of user n in time period t to the renewable energy power generation in the same period, and D is the per unit value of the renewable energy power curve And the per unit value of the demand side user load power curve The Euclidean distance between them, T is the total evaluation period.

[0117] Step 5: Aggregate the loads of all users participating in the demand-side response to obtain the aggregated load power curve. The process diagram of the aggregated load is shown in the figure below: Figure 2 The similarity of the aggregated load power curve and the new energy power generation curve after aggregation is calculated. The principle of load aggregation is that the similarity of the curve after aggregation is higher than the similarity of the curve before aggregation. According to the similarity of the curve after aggregation, the green electricity allocation coefficient of the demand-side user is calculated. According to the average green electricity factor and the green electricity allocation coefficient, the green electricity factor of the distribution network users is calculated to realize the green electricity benefit sharing of the demand-side electricity consumption.

[0118] The specific process of carrying out load aggregation for all users participating in demand-side response is as follows:

[0119] The loads participating in the demand-side response through load aggregators and self-aggregation are collectively referred to as aggregated loads. The power consumption per unit curve of aggregated load a in distribution network area i is:

[0120]

[0121] In the formula, It is the power consumption per unit curve of the aggregated load a which is aggregated from load 1 to load n in the time period T. The principle of load aggregation is that after the user participates in a certain aggregated load, the similarity between the load power curve of the aggregated load and the aggregated curve of the new energy power generation curve is improved;

[0122] The calculation of the similarity between the load power curve of the aggregated load a and the aggregated curve of the new energy power generation curve is specifically:

[0123] E i，a = i，a β i，a

[0124] In the formula, E i，a Indicates the similarity between the load power curve of aggregated load a and the aggregated new energy power curve of station i in time period t, α i,a It represents the measurement index after the Euclidean distance D between the load power curve of aggregate load a and the new energy generation curve of station i in time period t is mapped to the interval (0, 1], β i，a It indicates the proportion of the power consumption of aggregate load a in time period t to the renewable energy power generation in the substation during the same period.

[0125] The green electricity allocation coefficient of the demand-side user is calculated based on the similarity of the aggregated curves as follows:

[0126]

[0127] In the formula, γ i，a represents the green power allocation coefficient of aggregated load a in area i, m represents the number of aggregated loads participating in demand-side response in area i; E i,a It represents the similarity of the aggregated load power curve of aggregated load a and the aggregated new energy power curve of area i in time period t;

[0128] The green power factor of users in the distribution network area is calculated based on the average green power factor and the green power allocation coefficient, which specifically includes:

[0129] The amount of green electricity consumed by the aggregated load a under the station area i is distributed according to the green electricity distribution coefficient:

[0130] GQ i，a =GF i ×∫0 t L i，s (t)×γi，a

[0131] Where, L i,s (t) is the power curve of all loads participating in demand-side response in distribution network area i during the evaluation period t, GQ i，a represents the amount of green electricity consumed by the aggregate load a, GF i represents the average green power factor of area i, γ i，a represents the green power allocation coefficient of aggregate load a under station area i;

[0132] The amount of green electricity consumed by user n participating in the aggregate load a under the station area i is calculated according to the curve similarity of user n to the aggregate load a.

[0133] distribute:

[0134]

[0135] GQ i , n = GQ i ,a×ɑi,a,n

[0136] In the formula, ɑ i，a，n represents the green power allocation coefficient of user n under aggregate load a in area i, E i，a，n GQi represents the curve similarity of user n under aggregate load a in station area i, n It represents the amount of green electricity consumed by user n under the aggregated load a in the substation i;

[0137] Green power factor GF of user n i,n The calculation formula is as follows:

[0138]

[0139] L i，n (t) is the power curve of user n participating in demand-side response in distribution network area i during the evaluation period t.

[0140] Embodiment 2

[0141] The present invention proposes a green and low-carbon benefit sharing system for distribution network load based on curve similarity corresponding to the method of embodiment 1, comprising:

[0142] Data acquisition module, used to obtain the topological structure and power data of the distribution network;

[0143] The power generation calculation module is used to regard the area covered by the transformer node of the distribution network as a substation; according to the type and power generation of the generator set in the substation, the total power generation of the substation and the power generation of the new energy unit are calculated;

[0144] The average green power factor calculation module is used to calculate the total input power and input green power of each substation, calculate the total power balance value of the substation according to the total power generation and total input power of each substation, and then calculate the green power balance value of the substation according to the power generation of the new energy units in each substation and the input green power of each substation; calculate the average green power factor of the substation according to the total power balance value and green power balance value of the substation;

[0145] The green electricity allocation coefficient calculation module is used to calculate the similarity of the new energy power generation curve in the substation area and the load power curve of the demand-side user before aggregation in combination with the load data of the demand-side user in the substation area; load aggregation is carried out for all users participating in the demand-side response to obtain the aggregated load power curve, and the similarity of the aggregated load power curve and the new energy power generation curve after aggregation is calculated. The principle of load aggregation is that the similarity of the curve after aggregation is higher than the similarity of the curve before aggregation. According to the similarity of the curve after aggregation, the green electricity allocation coefficient of the demand-side user is calculated;

[0146] The green electricity benefit sharing module is used to calculate the green electricity factor of users in the distribution network area based on the average green electricity factor and the green electricity allocation coefficient, so as to realize the green electricity benefit sharing of electricity consumption on the demand side.

[0147] The implementation methods of each module and module function in the system are completely consistent with the steps of the method in Example 1, so they will not be repeated here.

[0148] Embodiment 3

[0149] The present invention proposes an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the green and low-carbon benefit sharing method for distribution network load based on curve similarity as described in Example 1 is implemented.

[0150] Embodiment 4

[0151] The present invention proposes a computer-readable storage medium storing a computer program, wherein the computer program enables a computer to execute the green and low-carbon benefit allocation method for distribution network load based on curve similarity as described in Example 1.

[0152] In the embodiments disclosed in the present application, the computer storage medium can be a tangible medium that can contain or store a program for use by or in conjunction with an instruction execution system, device or equipment. The computer storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, devices or equipment, or any suitable combination of the above. More specific examples of computer storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above.

[0153] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in this application can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0154] The above are only preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. It should be pointed out that for ordinary technicians in this technical field, some improvements and modifications without departing from the principle of the present invention should be regarded as the protection scope of the present invention.

Claims

1. A green and low-carbon benefit allocation method for distribution network load based on curve similarity, characterized in that: The following steps are involved: Obtain the topological structure and power data of the distribution network, and regard the area covered by the transformer nodes of the distribution network as a substation; calculate the total power generation of the substation and the power generation of the new energy units according to the type and power generation of the generator sets in the substation; Calculate the total input electricity and input green electricity of each substation, calculate the total electricity balance value of the substation according to the total power generation and total input electricity of each substation, and then calculate the green electricity balance value of the substation according to the power generation of new energy units in each substation and the input green electricity of each substation; calculate the average green electricity factor of the substation according to the total electricity balance value of the substation and the green electricity balance value of the substation; combine the load data of the demand-side users in the substation, calculate the similarity of the new energy power generation curve in the substation and the load power curve of the demand-side users before aggregation; carry out load aggregation for all users participating in the demand-side response to obtain the aggregated load power curve, and calculate the similarity of the aggregated load power curve and the new energy power generation curve after aggregation. The principle of load aggregation is that the similarity of the curve after aggregation is higher than the similarity of the curve before aggregation. According to the similarity of the curve after aggregation, calculate the green electricity allocation coefficient of the demand-side users, and calculate the green electricity factor of the users in the distribution network substation according to the average green electricity factor and the green electricity allocation coefficient, so as to realize the green electricity benefit sharing of the demand-side electricity consumption.

2. The green and low-carbon benefit allocation method for distribution network load based on curve similarity according to claim 1, characterized in that: The topological structure of the distribution network includes: a geographical wiring diagram and an electrical connection diagram of the distribution network; the power data of the distribution network includes: the power generation of the distributed new energy units of the distribution network and the power generation of other units; The specific process of calculating the total power generation of the substation and the power generation of the new energy units according to the type and power generation of the generator units in the substation is as follows: The total power generation G of the operating generator sets in the ith area during the evaluation period t i The calculation formula is as follows: In the formula, G i,j represents the power generation power of the jth generator set in operation in the i-th area, and m represents the total number of generator sets; The power generation of all renewable energy units in operation in the i-th area during the evaluation period t is GG i The calculation formula is as follows: In the formula, GG i,j represents the power generation power of the jth renewable energy unit among all renewable energy units running in the i-th area during the evaluation period t, Represents the total number of new energy units.

3. The green and low-carbon benefit allocation method for distribution network load based on curve similarity according to claim 1, characterized in that: The calculation of the total input power and input green power of each area is specifically as follows: For a distribution network with n substations, the total power input from other substations to the i-th substation during the evaluation period t is X i for: Where, X i，j represents the power input from area j to area i through the tie line; X i，a It represents the power input from the main grid to the station area i through the tie line; The amount of green electricity GX input from other substations to the i-th substation during the evaluation period t i for: X i，j represents the power input from area j to area i through the tie line; GF j represents the green power factor of area j; X i，a Indicates the power input from the main grid to the station area i through the tie line; GF a Indicates the green power factor of the main grid.

4. The green and low-carbon benefit allocation method for distribution network load based on curve similarity according to claim 1, characterized in that: The total power balance value of each substation area calculated based on the total power generation and total input power of each substation area is specifically: The total power balance value of the area consists of two parts: the total power generation of all generators in the area G i , the total power input from other areas and the main grid to area i is X i , the calculation formula is as follows: Q i =G i +X i In the formula, Q i Indicates the power balance value of the area; The green power balance value of each substation calculated based on the power generation of each substation's new energy units and the input green power of each substation is specifically: The green electricity balance value of the area is also composed of two parts: the total power generation of all new energy generators in the area GG i , the green electricity GX input from other areas and the main grid to area i i , the calculation formula is as follows: GQ i =GG i +GX i In the formula, GQ i Indicates the green electricity balance value of the substation; The calculation of the average green power factor of the area according to the total power balance value of the area and the green power balance value of the area is specifically: In the formula, GF i Represents the average green power factor of area i.

5. The green and low-carbon benefit allocation method for distribution network load based on curve similarity according to claim 1, characterized in that: The calculation of the similarity before aggregation between the new energy generation curve in the area and the load power curve of the demand-side user is specifically as follows: Define the shape of the new energy generation curve and the demand-side user load power curve within the total evaluation period T: Where, L i，g (t) is the new energy power generation curve of area i, YesL i，g (t) is normalized by the function f u (·) after the per unit value, L i,n (t) is the load power curve of a user n in the station area i; YesL i,n (t) is normalized by the function f u (·) after the per unit value; Using indicator E i,n Evaluate the similarity before aggregation between the power curve of renewable energy generation and the power curve of demand-side user load, index E i,n The formula is as follows: E i，n =ɑ i，n b i，n α i,n ＝e -ε|D| In the formula, α i,n is the measurement index after the Euclidean distance D between the load power curve of user n and the renewable energy power curve of station i in time period t is mapped to the interval (0, 1], ε is a given constant value, e is a natural constant, β i，n is the proportion of the power consumption of user n in time period t to the renewable energy power generation in the same period, and D is the per unit value of the renewable energy power curve And the per unit value of the demand side user load power curve The Euclidean distance between them, T is the total evaluation period.

6. The green and low-carbon benefit allocation method for distribution network load based on curve similarity according to claim 1, characterized in that: The specific process of carrying out load aggregation for all users participating in demand-side response is as follows: The loads participating in the demand-side response through load aggregators and self-aggregation are collectively referred to as aggregated loads. The power consumption per unit curve of aggregated load a in distribution network area i is: In the formula, It is the power consumption per unit curve of the aggregated load a which is aggregated from load 1 to load n in the time period T. The principle of load aggregation is that after the user participates in a certain aggregated load, the similarity between the load power curve of the aggregated load and the aggregated curve of the new energy power generation curve is improved; The calculation of the similarity between the load power curve of the aggregated load a and the aggregated curve of the new energy power generation curve is specifically: E i，a =ɑ i，a b i，a In the formula, E i,a Indicates the similarity between the load power curve of aggregated load a and the aggregated new energy power curve of station i in time period t, α i,a It represents the measurement index after the Euclidean distance D between the load power curve of aggregate load a and the new energy generation curve of station i in time period t is mapped to the interval (0, 1], β i，a It indicates the proportion of the power consumption of aggregate load a in time period t to the renewable energy power generation in the substation during the same period.

7. The green and low-carbon benefit allocation method for distribution network load based on curve similarity according to claim 1, characterized in that: The green electricity allocation coefficient of the demand-side user is calculated based on the similarity of the aggregated curves as follows: In the formula, γ i，a represents the green power allocation coefficient of aggregated load a in area i, m represents the number of aggregated loads participating in demand-side response in area i; E i,a It represents the similarity of the aggregated load power curve of aggregated load a and the aggregated new energy power curve of area i in time period t; The green power factor of users in the distribution network area is calculated based on the average green power factor and the green power allocation coefficient, which specifically includes: The amount of green electricity consumed by the aggregated load a under the station area i is distributed according to the green electricity distribution coefficient: Where, L i,s (t) is the power curve of all loads participating in demand-side response in distribution network area i during the evaluation period t, GQ i，a represents the amount of green electricity consumed by the aggregate load a, GF i represents the average green power factor of area i, γ i，a represents the green power allocation coefficient of aggregate load a under station area i; The amount of green electricity consumed by user n participating in the aggregated load a under the station area i is distributed according to the similarity of user n to the curve of the aggregated load a: GQ i ,n=GQ i ,a×ɑi,a, n In the formula, θ i，a，n represents the green power allocation coefficient of user n under aggregate load a in area i, E i，a，n G Qi represents the curve similarity of user n under aggregate load a in station area i, n It represents the amount of green electricity consumed by user n under the aggregated load a in the substation i; Green power factor GF of user n i,n The calculation formula is as follows: L i,n (t) is the power curve of user n participating in demand-side response in distribution network area i during the evaluation period t.

8. A green and low-carbon benefit sharing system for distribution network load based on curve similarity, characterized in that: include: Data acquisition module, used to obtain the topological structure and power data of the distribution network; The power generation calculation module is used to regard the area covered by the transformer nodes of the distribution network as a substation; According to the type and power generation of the generator sets in the substation, calculate the total power generation of the substation and the power generation of new energy units; The average green power factor calculation module is used to calculate the total input power and input green power of each substation, calculate the total power balance value of the substation according to the total power generation and total input power of each substation, and then calculate the green power balance value of the substation according to the power generation of the new energy units in each substation and the input green power of each substation; calculate the average green power factor of the substation according to the total power balance value and green power balance value of the substation; The green electricity allocation coefficient calculation module is used to calculate the similarity of the new energy power generation curve in the substation area and the load power curve of the demand-side user before aggregation in combination with the load data of the demand-side user in the substation area; load aggregation is carried out for all users participating in the demand-side response to obtain the aggregated load power curve, and the similarity of the aggregated load power curve and the new energy power generation curve after aggregation is calculated. The principle of load aggregation is that the similarity of the curve after aggregation is higher than the similarity of the curve before aggregation. According to the similarity of the curve after aggregation, the green electricity allocation coefficient of the demand-side user is calculated; The green electricity benefit sharing module is used to calculate the green electricity factor of users in the distribution network area based on the average green electricity factor and the green electricity allocation coefficient, so as to realize the green electricity benefit sharing of electricity consumption on the demand side.

9. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the green and low-carbon benefit sharing method for distribution network load based on curve similarity as described in any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: The computer program enables the computer to execute the green and low-carbon benefit allocation method for distribution network load based on curve similarity as described in any one of claims 1 to 7.

Images