P2P (Peer-to-Peer) energy interaction method considering production and disappearance differentiation contribution degree and voltage regulation and control

Abstract

The invention discloses a P2P energy interaction method considering production and disappearance differentiation contribution degree and voltage regulation and control, and the method comprises the steps: building an objective function and constraint conditions of a production and disappearance person output optimization model according to a current carbon emission penalty value when a production and disappearance person receives electric quantity from a superior power grid and supplies the electric quantity; constructing a producer and consumer consumer cluster energy consumption minimization sub-model, and solving the producer and consumer consumer cluster energy consumption minimization sub-model to obtain an electric energy optimal scheme of producer and consumer consumer energy consumption minimization; a DNO voltage maintenance model is established, and the DNO voltage maintenance model is utilized to carry out voltage safety inspection on the optimal scheme of the electric energy of the producer and the consumer; according to the optimal electric energy scheme for minimizing the energy consumption of the consumer, establishing a consumer differentiation model and obtaining negotiation weights of different consumers; and constructing a producer and consumer cluster differentiation negotiation sub-model and solving the sub-model to obtain the final power consumption. According to the method, the voltage safety can be ensured, and meanwhile, the difference of producers and diasters can be effectively quantified and distinguished, so that the energy interaction is more fair.

Description

Technical Field

[0001] The present invention relates to the technical field of interactive regulation of distribution networks, and particularly to a P2P energy interaction method considering the differential contribution degrees of prosumers and voltage regulation. Background Art

[0002] In recent years, with the access of flexible resources such as distributed renewable energy, energy storage systems, and electric vehicles, as well as the continuous improvement of communication and control technology levels, traditional passive distribution networks have gradually transformed into active distribution networks (ADNs). In an ADN, users with distributed energy are no longer passive energy consumers, but prosumers who integrate production and consumption. These prosumers can independently manage their available flexible resources and actively participate in energy interaction. The participation of prosumers in energy interaction can reduce their own energy consumption, improve the local consumption rate of distributed renewable energy, and reduce the impact of the uncertainty of renewable energy on the superior power grid.

[0003] Existing research on the interactive regulation of distribution networks mainly focuses on prosumer resource management and clearing algorithms, while ignoring the impact of interaction among prosumers on the security of distribution networks, and there is little research on the impact of prosumer differences on the fairness of energy interaction. Unrestricted interaction among prosumers is likely to have an adverse impact on the power grid, such as node voltages violating voltage constraints. In addition, ignoring the differences among prosumers will not be able to ensure the fairness of prosumers in energy interaction, limit the possibility for prosumers to further reduce their own energy consumption, and damage the sustainable development of local energy interaction. Summary of the Invention

[0004] The purpose of the present invention is to provide a P2P energy interaction method considering the differential contribution degrees of prosumers and voltage regulation, in order to utilize the differences in the different participation degrees of prosumers in energy interaction, and take into account the optimal operation of energy interaction on the premise of ensuring the security of the distribution network, so as to improve the enthusiasm and fairness of prosumers in energy interaction.

[0005] In order to achieve the above purpose, the present invention provides the following technical solutions:

[0006] A P2P energy interaction method considering the differential contribution degrees of prosumers and voltage regulation, comprising the following steps:

[0007] S1. Establish the objective function and constraint conditions of the prosumer output optimization model according to the current carbon emission penalty values of the electricity received from the superior power grid and the electricity supplied by the prosumer; the constraint conditions include: demand response constraint, energy storage constraint, prosumer P2P interaction constraint, and superior power grid interaction constraint;

[0008] S2. Based on the prosumer output optimization model, construct a sub-model for minimizing the energy consumption of the prosumer cluster, and solve the sub-model for minimizing the energy consumption of the prosumer cluster to obtain the optimal power plan with the minimum prosumer energy consumption;

[0009] S3. Establish a DNO voltage maintenance model, and use the DNO voltage maintenance model to conduct a voltage safety inspection on the optimal power plan of the prosumer. If the inspection passes, execute S4; otherwise, after updating the current carbon emission penalty value, return to S1 and execute in sequence;

[0010] S4. According to the optimal power plan with the minimum prosumer energy consumption, establish a prosumer differentiation model and obtain the negotiation weights of different prosumers;

[0011] S5. Construct and solve a prosumer cluster differentiation negotiation sub-model to obtain the final electricity consumption.

[0012] Preferably, the S1 step specifically includes:

[0013] S1-1. Use equations (1)-(2) to establish the objective function f of the output optimization model of prosumer j j :

[0014] min f j = f j load + f j ESS + f j P2P + f j grid + f j tran (1),

[0015]

[0016] In equations (1)-(2): min f j represents the minimization objective function of the output optimization model of prosumer j, and f j load is the energy consumption due to inconvenient load adjustment of prosumer j, and f j ESS is the energy consumption of charge and discharge loss of the energy storage of prosumer j, and f j P2P is the energy consumption of prosumer j participating in P2P interaction, and f j grid is the energy consumption of the interaction between prosumer j and the superior power grid, and f j tran is the energy consumption during the passing of the network when prosumer j conducts P2P power interaction, and α tran is the inconvenient load adjustment coefficient of the prosumer, and p j tranFor prosumer j, it is the set of all times. The total load transferred downward, represents the set of all times, and are the energy storage charging coefficient and discharge loss coefficient of prosumer j respectively, c j,h and d j,h are the charging power and discharging power of the energy storage of prosumer j at time h respectively, represents the P2P interaction volume between prosumer j and prosumer i at time h, represents the carbon emission penalty value per unit electric energy given when prosumer j and prosumer i interact with each other in terms of electricity at time h, represents the electricity supplied by prosumer j to the superior power grid at time h, represents the electricity received by prosumer j from the superior power grid at time h, and are the current carbon emission penalty values for the electricity received and supplied by prosumer j at time h respectively, β P2P is the cross - network energy consumption per unit electric energy, Ω N represents the set of all prosumers;

[0017] S1 - 2. Establish the demand response constraint of prosumer j using equations (3) - (4):

[0018]

[0019] In equations (3) - (4): ω is the ratio of adjustable load, is the load volume transferred by prosumer j at time h, p j,h represents the active power injected by prosumer j at time h;

[0020] S1 - 3. Establish the energy storage constraint of prosumer j using equations (5) - (8):

[0021]

[0022] S j,H ≥S j,0 (8),

[0023] In equations (5) - (8): represents the maximum charge and discharge power of the energy storage owned by prosumer j, represents the charge and discharge efficiency of the energy storage owned by prosumer j, represents the maximum state of charge allowed for the energy storage owned by prosumer j, represents the minimum state of charge allowed for the energy storage owned by prosumer j, S j,h represents the state of charge of the energy storage owned by prosumer j at time h, S j,h-1Indicates the state of charge of the energy storage owned by prosumer j at time h-1. Δh represents the time scale at h, and Δh-1 represents the time scale at h-1. S j,0 Indicates the initial state of charge of the energy storage owned by prosumer j. S j,H Indicates the final state of charge of the energy storage owned by prosumer j;

[0024] S1-4. Establish the P2P interaction constraints of prosumer j using Equations (9)-(14):

[0025]

[0026]

[0027] In Equations (9)-(14): Ω j Is the set of adjacent prosumers of prosumer j, Is the P2P power supplied by prosumer j at time h, Is the P2P power received by prosumer j from prosumer i at time h, And Are the maximum values of the P2P power that prosumer j is allowed to receive and supply at time h, respectively, Represents the electrical energy interaction amount between prosumer j and prosumer i in time period h. M j,h Is the total energy consumption for power sharing that prosumer j needs to bear at time h;

[0028] S1-5. Establish the interaction constraints between prosumer j and the upstream power grid using Equations (15)-(16):

[0029]

[0030] In Equations (15)-(16): Is the net load of prosumer j at time h.

[0031] Preferably, the S2 step specifically includes:

[0032] S2-1: Establish the objective function of the sub-model for minimizing the energy consumption of the prosumer cluster using Equation (17)

[0033]

[0034] In Equation (17): Represents the total energy consumption of prosumer j;

[0035] S2-2: Use Equations (3)-(4), (5)-(8), (9)-(14), and (15)-(16) as the constraint conditions of the sub-model for minimizing the energy consumption of the prosumer cluster;

[0036] S2-3: Establish the augmented Lagrangian function of the energy consumption minimization sub-model for prosumer j using Equation (18).

[0037]

[0038] In Equation (18): λ i-j is the Lagrangian multiplier between prosumer i and prosumer j, and ρ j is the penalty parameter for prosumer j. is the auxiliary variable of the P2P interaction volume between prosumer j and prosumer i;

[0039] S2-4: Use the distributed ADMM algorithm to perform iterative solution to obtain the optimal power plan for minimizing the energy consumption of prosumer j, including: the optimal interaction volume with the upstream power grid, the optimal charging and discharging power of the energy storage, the optimal P2P interaction volume, and the optimal power of the adjustable load.

[0040] Preferably, the step S3 includes:

[0041] S3-1: Construct the DNO voltage maintenance model using Equations (19)-(20):

[0042]

[0043] In Equations (19)-(22): P j,h and Q j,h represent the active power and reactive power flowing from the upstream prosumer of prosumer j to prosumer j at time h, p j,h and q j,h represent the active power and reactive power injected by prosumer j at time h, U j,h represents the square of the bus voltage at prosumer j at time h, C j ∈Ω N represents the set of downstream prosumers of prosumer j, m represents the downstream prosumer of prosumer j, r m and x m are the resistance and reactance of the line between downstream prosumer m of prosumer j and prosumer j, P m,h and Q m,h represent the active power and reactive power flowing from the upstream prosumer of prosumer m to prosumer m at time h, p j,m and q j,m represent the active power and reactive power injected by prosumer m at time h, U0 represents the node voltage, and V0 represents the square of the node voltage;

[0044] S3-2: Determine whether formula (23) holds. If it holds, it indicates that the verification is passed; otherwise, it indicates that there are voltage violation nodes, and execute S3-3;

[0045] U min ≤U j,h ≤U max (23),

[0046] In formula (23): U min represents the minimum value of the allowable prosumer node voltage, U max represents the maximum value of the allowable prosumer node voltage, U j,h represents the node voltage of prosumer j at time h;

[0047] S3-3: Use formulas (24)-(25) to construct an update formula for the carbon emission penalty value:

[0048]

[0049] In formulas (24)-(25): γ is the regulation coefficient of the carbon emission penalty value, λ buy,min and λ buy,max are the minimum and maximum values of the power received from the superior power grid, λ sell,min and λ sell,max are the minimum and maximum values of the power supplied to the superior power grid, U j,h represents the carbon emission penalty value of the received power of prosumer j after update at time h, represents the carbon emission penalty value of the received power of prosumer j after update at time h, represents the carbon emission penalty value of the supplied power of prosumer j after update at time h.

[0050] Preferably, the S4 step specifically includes:

[0051] S4-1: Use formulas (26)-(29) to establish an energy interaction participation model in the prosumer differentiation model:

[0052]

[0053] In formulas (26)-(29): represents the P2P power received by prosumer j under the set of all times , represents the P2P power supplied by prosumer j under the set of all times , represents the ratio of the P2P power received by prosumer j under the set of all times to the P2P received by all prosumers, represents the set of all times for prosumer j The ratio of the P2P power supplied from below to the P2P power supplied by all prosumers, represents the energy interaction participation degree of prosumer j, represents the optimal P2P interaction quantity received by prosumer j from prosumer i, represents the optimal P2P interaction quantity supplied by prosumer j to prosumer i;

[0054] S4-2: Establish a voltage regulation contribution degree model in the prosumer differentiation model by using Equation (30);

[0055]

[0056] In Equation (30): represents the number of voltage violation nodes regulated by prosumer j, represents the maximum number of voltage violation nodes regulated among all prosumers, represents the voltage regulation contribution degree of prosumer j;

[0057] S4-3: Obtain the negotiation weight r of prosumer j by using Equation (31) j ;

[0058]

[0059] Preferably, the step S5 specifically includes:

[0060] S5-1: Establish an objective function of the prosumer cluster differentiation negotiation sub-model by using Equation (32)

[0061]

[0062] In Equation (32): represents the total energy consumption of prosumer j not participating in the cluster energy cooperation and sharing under the constraints of Equations (3)-(4), (5)-(8), and (15)-(16); represents the total energy consumption of prosumer j participating in the cluster energy cooperation and sharing, and there is:

[0063]

[0064] S5-2: Use Equation (13) as the constraint condition of the prosumer cluster differentiation negotiation sub-model;

[0065] S5-3: Establish an equivalent model of the prosumer cluster differentiation negotiation sub-model by using Equation (34):

[0066]

[0067] S5-4: Establish the constraint condition of the equivalent model by using Equation (35):​​

[0068]

[0069] S5-5: Solve the equivalent model using the distributed ADMM algorithm, and obtain the final power consumption by combining the optimal power plan, including: the total power consumption of the prosumers participating in the cluster energy cooperation and sharing, and the power consumption of each prosumer when the prosumer cluster power consumption is minimized.

[0070] Preferably, an electronic device includes a memory and a processor. The memory is used to store a program that supports the processor to execute the P2P energy interaction method considering prosumer differentiation contribution and voltage regulation. The processor is configured to execute the program stored in the memory.

[0071] Preferably, a computer-readable storage medium stores a computer program. When the computer program is run by a processor, it executes the steps of the P2P energy interaction method considering prosumer differentiation contribution and voltage regulation.

[0072] The beneficial effects of the present invention are as follows:

[0073] (1) The P2P energy interaction method of the present invention considering prosumer differentiation contribution and voltage regulation adopts a P2P energy interaction method considering prosumer differentiation contribution and voltage regulation, uses the differences of prosumers in energy interaction to maintain the voltage safety of the distribution network, and uses a distributed solution algorithm to solve it. Finally, a prosumer differentiation negotiation model is constructed, which effectively improves the fairness of prosumers in energy interaction and ensures the optimality of prosumer power consumption.

[0074] (2) The P2P energy interaction method of the present invention considering prosumer differentiation contribution and voltage regulation proposes a DNO-assisted voltage safety maintenance strategy. While the DNO does not interfere with the prosumer interaction objects, it effectively achieves the purpose of voltage safety by changing the carbon emission penalty value of the grid interaction.

[0075] (3) The P2P energy interaction method of the present invention considering prosumer differentiation contribution and voltage regulation proposes a prosumer differentiation model. For the contributions made by prosumers in energy interaction and voltage safety maintenance, different negotiation weights are given to prosumers, so that different prosumers are in different positions in the negotiation, effectively improving the fairness of prosumers in the whole energy interaction and being beneficial to the sustainable development of local energy interaction.

[0076] (4) The P2P energy interaction method of the present invention considering the differential contribution of prosumers and consumers and voltage regulation carefully considers the flexible resources that can be optimized in the energy interaction of prosumers. By timely adjusting the flexible resources, prosumers effectively maintain the voltage safety of the distribution network, reduce their own electricity consumption, and improve the local consumption rate of distributed renewable energy. Description of the Drawings

[0077] Figure 1 is the flowchart of the method of the present invention;

[0078] Figure 2 is and E s,bit / E b,bit relationship diagram;

[0079] Figure 3 is the IEEE 33-node test system diagram;

[0080] Figure 4 is the prosumer bus voltage diagram before regulation;

[0081] Figure 5 is the prosumer bus voltage diagram after regulation;

[0082] Figure 6 is the interactive carbon emission penalty value diagram of the prosumer and the superior power grid before and after voltage regulation;

[0083] Figure 7 is the power optimization situation diagram inside prosumer 6 and prosumer 10;

[0084] Figure 8 is the prosumer negotiation diagram of Example 4 and Example 1;

[0085] Figure 9 is the consumer energy consumption diagram of 4 examples. Detailed Implementation Modes

[0086] The following further describes the present invention in conjunction with embodiments. It should be noted that this is only an example and explanation of the inventive concept. Those skilled in the art of the present technology can make various modifications or supplements or use similar methods to replace the specific embodiments described, as long as they do not deviate from the inventive concept or exceed the scope defined by the claims of the present invention, they should be regarded as falling within the protection scope of the present invention.

[0087] Example 1:

[0088] Figure 1 is the flowchart of the method of the present invention. As Figure 1 shown, the P2P energy interaction method of the present invention considering the differential contribution of prosumers and consumers and voltage regulation includes the following steps:

[0089] S1: Establish the objective function and constraint conditions of the prosumer output optimization model based on the current carbon emission penalty values of the electricity received from and supplied to the upstream power grid by the prosumer; the constraint conditions include: demand response constraint, energy storage constraint, prosumer P2P interaction constraint, and upstream power grid interaction constraint. The specific steps are as follows:

[0090] S1-1: Use Equations (1)-(2) to establish the objective function f of the output optimization model for prosumer j j :

[0091] min f j = f j load + f j ESS + f j P2P + f j grid + f j tran (1),

[0092]

[0093] In Equations (1)-(2): min f j represents the minimization objective function of the output optimization model for prosumer j, and f j load is the inconvenience energy consumption for load adjustment of prosumer j, and f j ESS is the energy consumption of charge and discharge losses of the energy storage of prosumer j, and f j P2P is the energy consumption of prosumer j participating in P2P interaction, and f j grid is the interaction energy consumption between prosumer j and the upstream power grid, and f j tran is the energy consumption for passing through the grid during P2P electricity interaction between prosumer j and others, α tran is the inconvenience coefficient for load adjustment of the prosumer, p j tran is the total load transferred by prosumer j under the set H of all moments, and H represents the set of all moments, and are the charge coefficient and discharge loss coefficient of the energy storage of prosumer j respectively, c j,h and d j,h are the charge power and discharge power of the energy storage of prosumer j at moment h respectively, represents the P2P interaction volume between prosumer j and prosumer i at moment h, represents the carbon emission penalty value per unit of electric energy given when prosumer j and prosumer i interact with each other at moment h, Denotes the electricity quantity supplied by prosumer \(j\) to the upper-level power grid at time \(h\). Denotes the electricity quantity received by prosumer \(j\) from the upper-level power grid at time \(h\). And Are respectively the current carbon emission penalty values for the electricity received and supplied by prosumer \(j\) at time \(h\), and \(\beta\) P2P Is the grid-crossing energy consumption per unit of electric energy, and \(\Omega\) N Denotes the set of all prosumers.

[0094] S1-2: All prosumers have a certain proportion of flexible resources that can be transferred when needed, but the transferred load needs to meet certain constraints. Use equations (3)-(4) to establish the demand response constraints for prosumer \(j\):

[0095]

[0096] In equations (3)-(4): \(\omega\) is the ratio of the adjustable load, Is the amount of load transferred by prosumer \(j\) at time \(h\), and \(p\) j,h Denotes the active power injected by prosumer \(j\) at time \(h\). Equation (3) represents the range of load that prosumer \(j\) can transfer at each moment, and equation (4) represents that the total load transfer of prosumer \(j\) in a day must be balanced.

[0097] S1-3: Use equations (5)-(8) to establish the energy storage constraints for prosumer \(j\):

[0098]

[0099] S j,H ≥S j,0 (8),

[0100] In equations (5)-(8): Denotes the maximum charge and discharge power of the energy storage owned by prosumer \(j\), Denotes the charge and discharge efficiency of the energy storage owned by prosumer \(j\), Denotes the maximum allowable state of charge of the energy storage owned by prosumer \(j\), Denotes the minimum allowable state of charge of the energy storage owned by prosumer \(j\), and \(S\) j,h Denotes the state of charge of the energy storage owned by prosumer \(j\) at time \(h\), and \(S\) j,h-1 Denotes the state of charge of the energy storage owned by prosumer \(j\) at time \(h - 1\). \(\Delta h\) represents the time scale at time \(h\), and \(\Delta h - 1\) represents the time scale at time \(h - 1\), and \(S\) j,0 Denotes the initial state of charge of the energy storage owned by prosumer \(j\), and \(S\) j,HIndicates the final state of charge of the energy storage owned by prosumer j. Equation (7) indicates that the power level at any time period must ensure that the state of charge of the battery energy storage is within the rated range, and Equation (8) indicates that the power at the end of the scheduling period cannot be lower than the initial power.

[0101] S1-4: Use Equations (9)-(14) to establish the P2P interaction constraints for prosumer j:

[0102]

[0103] In Equations (9)-(14): Ω j is the set of adjacent prosumers of prosumer j, is the P2P power supplied by prosumer j at time h, is the P2P power received by prosumer j from prosumer i at time h, and are the maximum values of the P2P power that prosumer j is allowed to receive and supply at time h, respectively, represents the electrical energy interaction amount between prosumer j and prosumer i at time period h, M j,h is the total energy consumption for power consumption that prosumer j needs to bear when participating in power sharing at time h. Equations (10)-(12) mean that the electrical energy transmission power output or received by the prosumer at each time period h should be within the power limit range, and Equations (13) and (14) determine the balance of the total P2P interaction power and the total P2P power consumption value of all prosumers.

[0104] S1-5: Use Equations (15)-(16) to establish the interaction constraints between prosumer j and the upstream power grid:

[0105]

[0106] In Equations (15)-(16): is the net load of prosumer j at time h. Equation (15) means that at any time, the carbon emission penalty value received by the prosumer from the upstream power grid should be greater than the carbon emission penalty value for feeding power back to the upstream power grid.

[0107] S2: Based on the prosumer output optimization model, construct a sub-model for minimizing the energy consumption of the prosumer cluster, and solve the sub-model for minimizing the energy consumption of the prosumer cluster to obtain the optimal power plan for minimizing the prosumer energy consumption. The specific steps include:

[0108] S2-1: It can be seen from Equation (14) that the mutual settlement of carbon emission consumption values between prosumers is always balanced, that is, the sum is zero. Therefore, the energy consumption f j P2P in the P2P energy settlement does not affect the energy consumption of the prosumer cluster and can be ignored during the solution, that is, f j P2P= 0; Use Equation (17) to establish the objective function of the prosumer cluster energy consumption minimization sub-model

[0109]

[0110] In Equation (17): f j P1 represents the total energy consumption of prosumer j.

[0111] S2-2: Use Equations (3)-(4), (5)-(8), (9)-(14), and (15)-(16) as the constraint conditions of the prosumer cluster energy consumption minimization sub-model.

[0112] S2-3: It can be seen that the objective function of Equation (17) can be decomposed into sub-objective functions for each prosumer. Considering the privacy and communication resources among prosumers, a distributed algorithm is used to solve this optimization problem. Since ADMM combines the decomposability of dual ascent with the superior convergence of the multiplier method and still has good convergence performance in the presence of non-strictly convex objective functions, the ADMM algorithm is used to solve it. Use Equation (18) to establish the augmented Lagrangian function of the energy consumption minimization sub-model of prosumer j

[0113]

[0114] In Equation (18): λ i-j is the Lagrange multiplier between prosumer i and prosumer j, and ρ j is the penalty parameter of prosumer j, is the auxiliary variable of the P2P interaction volume between prosumer j and prosumer i.

[0115] S2-4: Use the distributed ADMM algorithm to perform iterative solution to obtain the optimal power plan for the minimum energy consumption of prosumer j, including: the optimal interaction volume with the superior power grid, the optimal charging and discharging power of energy storage, the optimal P2P interaction volume, and the optimal power of adjustable load.

[0116] S3: Establish a DNO voltage maintenance model and use the DNO voltage maintenance model to conduct a voltage safety inspection on the optimal power plan of prosumers. If the inspection passes, execute S4; otherwise, after updating the current carbon emission penalty value, return to S1 and execute sequentially. The specific steps include:

[0117] S3-1: Prosumers upload the power interaction volume between themselves and the superior power grid and the P2P interaction volume at each moment to the DNO. The DNO calculates the node voltage of each prosumer through the following model and constructs the DNO voltage maintenance model using Equations (19)-(20):

[0118]

[0119] In equations (19) - (22): P j,h and Q j,h represent the active and reactive power flowing from the upstream prosumer of prosumer j to prosumer j at time h, p j,h and q j,h represent the active and reactive power injected by prosumer j at time h, U j,h represents the square of the bus voltage at prosumer j at time h, represents the set of downstream prosumers of prosumer j, m represents the downstream prosumer of prosumer j, r m and x m are the resistance and reactance of the line between downstream prosumer m of prosumer j and prosumer j, P m,h and Q m,h represent the active and reactive power flowing from the upstream prosumer of prosumer m to prosumer m at time h, p j,m and q j,m represent the active and reactive power injected by prosumer m at time h, U0 represents the node voltage, and V0 represents the square of the node voltage.

[0120] S3 - 2: Determine whether equation (23) holds. If it holds, it means the verification passes; otherwise, it means there are voltage violation nodes, and execute S3 - 3;

[0121] U min ≤U j,h ≤U max (23),

[0122] In equation (23): U min represents the minimum allowable node voltage of the prosumer, U max represents the maximum allowable node voltage of the prosumer, U j,h represents the node voltage of prosumer j at time h.

[0123] S3 - 3: Use equations (24) - (25) to construct the updated formula for the carbon emission penalty value:

[0124]

[0125] In equations (24) - (25): γ is the regulation coefficient of the carbon emission penalty value, λ buy,min and λ buy,max are the minimum and maximum values of the electricity received from the superior power grid, λ sell,min and λ sell,max are the minimum and maximum values of the electricity supplied to the superior power grid, U j,hDenote the carbon emission penalty value of the received electricity of prosumer j after update at time h. Denote the carbon emission penalty value of the received electricity of prosumer j after update at time h. Denote the carbon emission penalty value of the supplied electricity of prosumer j after update at time h.

[0126] As shown in the flowchart Figure 1 shown, when the prosumer j is over-voltage at time period h before update, then reduce the grid-connected carbon emission penalty value of prosumer j at this time in the next update iteration and the received carbon emission penalty value to guide prosumer j to transfer the load at other times to time h, increase the electricity consumption load at time h, reduce the electricity injected into the grid by it, and alleviate the over-voltage violation; on the contrary, when the prosumer j is under-voltage at time period h before gen update, then increase the grid-connected carbon emission penalty value of prosumer j at this time in the post-update iteration and the received carbon emission penalty value to guide prosumer j to transfer the load at time h to other times, reduce the electricity consumption load at this time, and alleviate the under-voltage violation; if there is no violation for prosumer j at time period h before update, then the interaction voltage between prosumer j and the superior power grid at this time remains unchanged in the next iteration.

[0127] S4: According to the optimal power plan for minimizing the energy consumption of prosumers, establish a prosumer differentiation model and obtain the negotiation weights of different prosumers. The specific steps include:

[0128] S4-1: The energy interaction participation degree specifically refers to the degree of prosumer participation in local energy interaction. Different identities and different P2P interaction amounts will result in different energy interaction participation degrees for each prosumer; use a non-linear logarithmic function to quantify and establish an energy interaction participation degree model in the prosumer differentiation model using equations (26)-(29):

[0129]

[0130] In equations (26)-(29): Denote the P2P electricity received by prosumer j under the set of all times Denote the P2P electricity supplied by prosumer j under the set of all times Denote the ratio of the P2P electricity received by prosumer j under the set of all times to the total P2P electricity received by all prosumers, Denote the ratio of the P2P electricity supplied by prosumer j under the set of all times to the total P2P electricity supplied by all prosumers, ​​Indicates the energy interaction participation degree of prosumer j, Indicates the optimal P2P interaction quantity received by prosumer j from prosumer i, Indicates the optimal P2P interaction quantity supplied by prosumer j to prosumer i.

[0131] Equation (29) depicts the energy interaction participation degrees of different prosumers, which changes with the prosumer acceptance ratio and prosumer supply ratio as Figure 2 shown.

[0132] From Figure 2 part (a), it can be seen that the energy interaction participation degree is positively correlated with the prosumer P2P acceptance ratio E b,bit and the prosumer P2P supply ratio E s,bit , that is, it increases with the increase of E b,bit and E s,bit . In particular, it is pointed out that in Equation (27) will increase sharply when E s,bit approaches 1. However, in the energy interaction constructed in the present invention, there are multiple new energy suppliers among the prosumers. Therefore, the value of E s,bit will be at most below 0.9 at its most conservative. Therefore, the problems appearing in Equation (27) above will not affect the quantification of the energy participation degree in the present invention; from Figure 2 part (b), it can be seen that under the same ratio, the energy interaction participation degree of new energy suppliers is greater than that of new energy receivers.

[0133] S4-2: The voltage regulation contribution degree defines the differential contribution made by prosumers to the voltage security of the distribution system; similar to the energy interaction participation degree, a non-linear logarithmic function is used for quantification, and the voltage regulation contribution degree model in the prosumer differential model is established using Equation (30);

[0134]

[0135] In Equation (30): Indicates the number of voltage violation nodes regulated by prosumer j, Indicates the maximum number of voltage violation nodes regulated among all prosumers, Indicates the voltage regulation contribution degree of prosumer j.

[0136] Equation (30) indicates that all prosumers have a basic voltage regulation contribution degree value of 1 (i.e., the voltage regulation contribution degree of prosumers that do not participate in voltage regulation). In addition, the more voltage violation nodes a prosumer regulates, the greater its voltage regulation contribution degree and the greater the negotiation value it has.

[0137] The first aspect of differentiation is implemented in the P2P interaction stage. The DNO updates the interaction carbon emission penalty value between it and the superior power grid according to the differentiated voltage conditions of prosumers, that is, the interaction carbon emission penalty value between the prosumer and the superior power grid is affected by its voltage. Specifically, at the moment when the prosumer has overvoltage, the carbon emission penalty value supplied by the prosumer to the superior power grid and the carbon emission penalty value received are reduced, encouraging the prosumer to increase the power consumption load at this moment and improving the overvoltage violation situation; at the moment when the prosumer has undervoltage, the carbon emission penalty value supplied by the prosumer to the superior power grid and the carbon emission penalty value received are increased, encouraging the prosumer to reduce the power consumption load at this moment and improving the undervoltage violation situation; through the update of the differentiated carbon emission penalty value, the prosumer can improve the voltage violation situation through demand response.

[0138] S4-3: The latter two aspects of differentiation are implemented in the negotiation stage, constituting the differentiated negotiation weights in the negotiation stage. The negotiation weight r of prosumer j is obtained using Equation (31) j ;

[0139]

[0140] S5: Construct a differentiated negotiation sub-model for the prosumer cluster and solve it to obtain the final power consumption. The specific steps include:

[0141] S5-1: Use Equation (32) to establish the objective function of the differentiated negotiation sub-model for the prosumer cluster

[0142]

[0143] In Equation (32): represents the total power consumption when prosumer j does not participate in the cluster energy cooperation and sharing under the constraints of Equations (3)-(4), (5)-(8), and (15)-(16); represents the total power consumption when prosumer j participates in the cluster energy cooperation and sharing, and there is:

[0144]

[0145] S5-2: Use Equation (13) as the constraint condition of the differentiated negotiation sub-model for the prosumer cluster. S5-3: Use Equation (34) to establish an equivalent model of the differentiated negotiation sub-model for the prosumer cluster:

[0146]

[0147] S5-4: Use Equation (35) to establish the constraint conditions of the equivalent model:

[0148]

[0149] S5-5: Solve the equivalent model using the distributed ADMM algorithm, and obtain the final power consumption by combining the optimal power plan, including: the total power consumption of the prosumers participating in the cluster energy cooperation and sharing, and the power consumption of each prosumer when the prosumer cluster energy consumption is minimized.

[0150] In this embodiment, an electronic device includes a memory and a processor. The memory is used to store a program that supports the processor to execute the above P2P energy interaction method considering the prosumer differentiation contribution degree and voltage regulation. The processor is configured to execute the program stored in the memory.

[0151] In this embodiment, a computer-readable storage medium stores a computer program. When the computer program is run by a processor, it executes the steps of the above P2P energy interaction method considering the prosumer differentiation contribution degree and voltage regulation.

[0152] To enable those skilled in the art to better understand the present invention, the case analysis includes the following components:

[0153] Simulation settings: Figure 3 The structure of the IEEE 33-bus system with 10 prosumers (5 consumers and 5 prosumers) is given. Each prosumer may have a certain capacity of photovoltaic or energy storage, so as to participate in local energy interaction. Compared with the standard situation, the line impedance is amplified by 1.5 times to highlight the voltage violation problem. The length of each time slot is Δh = 1h, the nominal distribution voltage is 12.66 kV, and the feasible bus voltage range is 1 ± 5% p.u. The initial interaction carbon emission penalty value between the prosumer and the superior power grid The reactive power of the prosumer is uniformly set to 0 kVAr. In the inner-loop ADMM algorithm, the penalty factor ρ j = 1.5×10 -3 . The energy storage parameters of the prosumer are shown in Table 1 below.

[0154] Table 1 Energy storage parameter table of prosumers

[0155] Prosumer Pr6 Pr10 Charge / discharge power (kW) 80 / 80 80 / 80 Charge / discharge efficiency 0.95 / 0.95 0.95 / 0.95 Charge / discharge loss (CNY / kWh) 0.01 0.01 Minimum / maximum value of SoC 0.3 / 0.9 0.3 / 0.9 Energy storage capacity (KVA) 400 500

[0156] To verify the effectiveness of the method of the present invention, comparative studies are carried out with several other cases:

[0157] Example 2:

[0158] The method of this embodiment does not consider P2P interaction. The specific steps are as follows: S1. According to the current carbon emission penalty values of the electricity received from the superior power grid and the electricity supplied by the prosumer, establish the objective function and constraint conditions of the prosumer output optimization model; the constraint conditions include: demand response constraint, energy storage constraint, superior power grid interaction constraint; S2. Solve the prosumer output optimization model in combination with the prosumer output constraint conditions to obtain the optimal electricity plan for minimizing the prosumer energy consumption and the final electricity consumption.

[0159] Embodiment 3:

[0160] The method of this embodiment is based on the distributed optimization of ADMM, supports P2P interaction, but does not consider voltage regulation. The specific steps are as follows: S1. According to the current carbon emission penalty values of the electricity received from the superior power grid and the electricity supplied by the prosumer, establish the objective function and constraint conditions of the prosumer output optimization model; the constraint conditions include: demand response constraint, energy storage constraint, prosumer P2P interaction constraint, superior power grid interaction constraint; S2. Solve the prosumer output optimization model in combination with the prosumer output constraint conditions to obtain the optimal electricity plan for minimizing the prosumer energy consumption and the final electricity consumption; S3. Construct and solve the prosumer cluster negotiation sub-model to obtain the final electricity consumption.

[0161] Embodiment 4:

[0162] The method of this embodiment is based on the distributed optimization of ADMM, supports P2P interaction, considers voltage regulation, but there is no differential negotiation. The specific steps are basically the same as those of Embodiment 1, except that: step S4 is omitted; in step S5, construct and solve the prosumer cluster negotiation sub-model to obtain the final electricity consumption.

[0163] The simulation is solved using the YALMIP toolbox and the commercial solver MOSEK in the MATLAB environment, and the computing device is a computer configured with Intel(R) Core(TM) i7-8700@3.2GHz.

[0164] Through the P2P energy interaction management of Embodiment 1, Embodiment 2, Embodiment 3, and Embodiment 4, the specific results are as follows:

[0165] Figure 4 and Figure 5 are the voltage curves of 10 prosumer nodes in Embodiment 2 or Embodiment 3 and Embodiment 1 or Embodiment 4 respectively. The voltage distribution diagram of Embodiment 2 or Embodiment 3 is as Figure 4 shown. It can be seen from the figure that the prosumer 6 has overvoltage violation situations at multiple moments in the second period, and the most serious overvoltage can reach 1.06 p.u. In the third period, multiple prosumers have undervoltage violation situations, and the prosumer 10 has the most serious undervoltage violation situation, and the voltage at the most serious moment is close to 0.92 p.u. And inFigure 5 After each prosumer executes the proposed voltage regulation scheme, the voltages of all prosumers are between 0.95 - 1.05 p.u., indicating that the voltage regulation scheme proposed by the present invention can effectively alleviate voltage violations.

[0166] Figure 6 It is a graph of the interactive carbon emission penalty values between prosumers and the upstream power grid before and after voltage regulation. From Figure 6 it can be seen that at the moments when prosumers violate voltage constraints, the interactive carbon emission penalty values between prosumers and the upstream power grid have changed. Taking the change in the carbon emission penalty value in the second period of prosumer 6 and the change in the carbon emission penalty value in the third period of prosumer 10 as examples, when prosumer 6 has overvoltage in the second period, the carbon emission penalty value for supplying new energy to the upstream power grid decreases, and the carbon emission penalty value for purchasing electricity from the upstream power grid decreases, encouraging prosumer 6 to increase load and consume more new energy at the overvoltage moment, reducing the electricity injected into the grid, thereby alleviating its overvoltage violation. When prosumer 10 has undervoltage in the third period, the carbon emission penalty value for supplying new energy to the upstream power grid increases, and the carbon emission penalty value for purchasing electricity from the grid increases, encouraging prosumer 10 to cut the electricity load at the undervoltage moment, reducing the purchased electricity, thereby alleviating its undervoltage violation.

[0167] Figure 7 It shows the internal power optimization of prosumer 6 and prosumer 10. It can be seen that the consumption of new energy has the highest priority. On the premise that prosumers first achieve the optimization of their own internal power dispatching, they participate in the overall power coordination and optimization process of prosumers. After optimization, both prosumer 6 and prosumer 10 transfer the loads in the first and third periods to the second period. For prosumer 6, on the one hand, there is sufficient photovoltaic power in the second period, and it can make full use of its own photovoltaic power to reduce its own energy consumption; on the other hand, the DNO punishes its acceptance / supply carbon emission penalty values in these two periods, reducing the acceptance / supply carbon emission penalty values of prosumer 6 during the overvoltage period and increasing the acceptance / supply carbon emission penalty values of prosumer 6 during the undervoltage period. In order to reduce energy consumption, prosumer 6 cuts the load at the undervoltage moment and increases the load at the overvoltage moment, effectively alleviating the voltage violation and maintaining the voltage safety of the distribution system. For prosumer 10, after load optimization, it transfers the load in the third period to noon. On the one hand, it fully consumes its own new energy, reduces its own energy consumption, and at the same time participates in P2P local energy interaction to help improve the overall consumption rate; on the other hand, it cuts the load volume at the moment punished by the DNO, effectively alleviating the undervoltage violation of prosumer 10.

[0168] (3) Differential voltage control

[0169] Table 2 Prosumers' differential negotiation values

[0170]

[0171] Table 2 shows the differential negotiation values of 10 prosumers. It can be seen that the more P2P interactions a prosumer has, the greater its participation in the interaction of natural energy. The prosumers providing new energy have a greater participation than those receiving new energy. The more the number of regulated illegal voltage nodes of a prosumer, the greater its contribution to the entire node system, and the greater the negotiation value it has. In the negotiation stage, the party with a larger differential negotiation value dominates the negotiation process.

[0172] Figure 8 It is a negotiation result diagram for the prosumer negotiation stage. Figure 8 Part (a) in it shows the negotiation results of the non-differential scheme in Embodiment 4. All negotiation results are between the carbon emission penalty values for selling and purchasing electricity from the upstream power grid. Figure 8 Part (b) in it shows the negotiation results of the differential scheme in Embodiment 1. Taking Figure 8 the curves of the interactive carbon emission penalty values between prosumers 5-6 and prosumers 3-9 in part (b) as an example, the two carbon emission penalty value curves are higher than Figure 8 the carbon emission penalty value curve in part (a) because the differential negotiation values of prosumers 6 / 9 are higher than those of prosumers 5 / 3, dominating the negotiation process. As suppliers, prosumers 6 / 9 will raise the P2P interactive carbon emission penalty value to increase their own benefits. The differential negotiation ability effectively differentiates the local energy participation degrees of each prosumer and their contributions to the voltage security of the distribution system, making the interest distribution more fair, and helping to encourage prosumers to actively participate in the local energy consumption of excess new energy and maintain the voltage security of the distribution system.

[0173] Figure 9 It is a comparison of the energy consumption of 10 prosumers in 4 embodiments. From the comparison of the energy consumption between Embodiment 2 and Embodiment 3, it can be seen that except for prosumer 7 not participating in local energy, the energy consumption of all other prosumers participating in P2P energy sharing has been reduced. Among them, the largest reduction is for prosumer 5, with an energy consumption reduction of 46.75%, and the smallest reduction is for prosumer 10, with an energy consumption reduction of 2.83%. From the comparison of the energy consumption between Embodiment 3 and Embodiment 4, it can be seen that the energy consumption of almost all prosumers increases slightly after participating in voltage regulation because prosumers need to sacrifice some of their own interests for the safety of the distribution network. From the comparison of the energy consumption between Embodiment 4 and Embodiment 1, it can be seen that after differential negotiation, the prosumer with a larger negotiation value has greater dominance in the negotiation process. The supplier with a larger negotiation value in the negotiation process will increase the carbon emission penalty value to increase its own benefits, and the receiver with a larger negotiation value will lower the carbon emission penalty value to reduce its own energy consumption.

[0174] The above is an exemplary description of the invention. Obviously, the specific implementation of the present invention is not limited by the above methods. As long as such non-substantial improvements are made by adopting the method concept and technical solution of the present invention, or the concept and technical solution of the invention are directly applied to other occasions without improvement, they are all within the protection scope of the present invention.

Claims

1. A P2P energy interaction method considering the differential contribution of prosumers and voltage regulation, characterized in that, It includes the following steps: S1. Based on the current carbon emission penalty values of the electricity received from the upstream power grid and the electricity supplied by the prosumer, establish the objective function and constraint conditions of the prosumer output optimization model; The constraint conditions include: demand response constraint, energy storage constraint, prosumer P2P interaction constraint, and upstream power grid interaction constraint; S2. Based on the prosumer output optimization model, construct a sub-model for minimizing the energy consumption of the prosumer cluster, and solve the sub-model for minimizing the energy consumption of the prosumer cluster to obtain the optimal power plan with the minimum prosumer energy consumption; S3. Establish a DNO voltage maintenance model, and use the DNO voltage maintenance model to conduct a voltage safety inspection on the optimal power plan of the prosumer. If the inspection passes, execute S4; otherwise, after updating the current carbon emission penalty value, return to S1 and execute sequentially; S4. According to the optimal power plan with the minimum prosumer energy consumption, establish a prosumer differentiation model and obtain the negotiation weights of different prosumers; S5. Construct and solve a prosumer cluster differentiation negotiation sub-model to obtain the final electricity consumption.

2. The P2P energy interaction method considering the differential contribution of prosumers and voltage regulation according to claim 1, characterized in that, The specific content of step S1 includes: S1-1. Establish the objective function \(f\) of the output optimization model of prosumer \(j\) using equations (1) - (2) j : minf j = f j load + f j ESS + f j P2P + f j grid + f j tran (1) In formulas (1)-(2): minf j represents the minimization objective function of the output optimization model of prosumer j, and f j load is the inconvenient energy consumption for load adjustment of prosumer j, and f j ESS is the energy consumption of charge and discharge losses of the energy storage of prosumer j, and f j P2P is the energy consumption of prosumer j participating in P2P interaction, and f j grid is the interaction energy consumption between prosumer j and the upstream power grid, and f j tran is the network passing energy consumption when prosumer j conducts P2P power interaction, α tran is the inconvenient coefficient for load adjustment of the prosumer, p j tran is the set of all time instants for prosumer j is the total transferred load under represents the set of all time instants, and are respectively the energy storage charging coefficient and discharge loss coefficient of prosumer j, c j,h and d j,h are respectively the charging power and discharging power of the energy storage of prosumer j at time h, represents the P2P interaction volume between prosumer j and prosumer i at time h, represents the carbon emission penalty value per unit of electric energy given when prosumer j and prosumer i exchange electric energy at time h, represents the electric energy supplied by prosumer j to the upstream power grid at time h, represents the electric energy received by prosumer j from the upstream power grid at time h, and are respectively the current carbon emission penalty values for the received and supplied electric energy of prosumer j at time h, β P2P is the network passing energy consumption per unit of electric energy, Ω N represents the set of all prosumers; S1-2. Use equations (3)-(4) to establish the demand response constraint of prosumer j: In Formula (3) - Formula (4): ω is the ratio of the adjustable load, is the amount of load transferred by prosumer j at time h, p j,h represents the active power injected by prosumer j at time h; S1-3. Use equations (5)-(8) to establish the energy storage constraint of prosumer j: S j,H ≥S j,0 (8), In formulas (5)-(8): represents the maximum charge and discharge power of the energy storage owned by prosumer j, represents the charge and discharge efficiency of the energy storage owned by prosumer j, represents the maximum allowed state of charge of the energy storage owned by prosumer j, represents the minimum allowed state of charge of the energy storage owned by prosumer j, S j,h represents the state of charge of the energy storage owned by prosumer j at time h, S j,h-1 represents the state of charge of the energy storage owned by prosumer j at time h - 1. Δh represents the time scale at time h, and Δh - 1 represents the time scale at time h - 1, S j,0 represents the initial state of charge of the energy storage owned by prosumer j, S j,H represents the final state of charge of the energy storage owned by prosumer j; S1-4. Use equations (9)-(14) to establish the P2P interaction constraint of prosumer j: In equations (9) - (14): Ω j is the set of adjacent prosumers of prosumer j, is the P2P power supplied by prosumer j at time h, is the P2P power received by prosumer j from prosumer i at time h, and are the maximum values of the P2P power that prosumer j is allowed to receive and supply at time h, respectively, represents the electrical energy interaction amount between prosumer j and prosumer i at time period h, M j,h is the total energy consumption for power consumption that prosumer j needs to bear when participating in electrical energy sharing at time h; S1-5. Use equations (15)-(16) to establish the interaction constraint between prosumer j and the upstream power grid: In formulas (15) - (16): is the net load of prosumer j at time h.

3. The P2P energy interaction method considering the differential contribution of prosumers and voltage regulation according to claim 2, characterized in that The specific content of step S2 includes: S2-1: Establish the objective function of the prosumer cluster energy consumption minimization sub-model using Equation (17) In formula (17): represents the total energy consumption of prosumer j; S2-2: Use equations (3)-(4), equations (5)-(8), equations (9)-(14), and equations (15)-(16) as the constraint conditions of the sub-model for minimizing the energy consumption of the prosumer cluster; S2-3: Establish the augmented Lagrangian function of the energy consumption minimization sub-model of prosumer j using Equation (18) In formula (18): λ i-j is the Lagrange multiplier between prosumer i and prosumer j, and ρ j is the penalty parameter of prosumer j, is the auxiliary variable of the P2P interaction volume between prosumer j and prosumer i; S2-4: Use the distributed ADMM algorithm to perform iterative solution to obtain the optimal power plan for minimizing the energy consumption of prosumer j, including: the optimal interaction volume with the superior power grid, the optimal charging and discharging power of the energy storage, the optimal P2P interaction volume, and the optimal power of the adjustable load.

4. The P2P energy interaction method considering the differential contribution of prosumers and voltage regulation according to claim 3, wherein The content of step S3 includes: S3-1: Use equations (19)-(20) to construct the DNO voltage maintenance model: In formulas (19) - (22): P j,h and Q j,h represent the active power and reactive power flowing from the upstream prosumer of prosumer j to prosumer j at time h, p j,h and q j,h represent the active power and reactive power injected by prosumer j at time h, U j,h represents the square of the bus voltage at prosumer j at time h, represents the set of downstream prosumers of prosumer j, m represents a downstream prosumer of prosumer j, r m and x m are the resistance and reactance of the line between downstream prosumer m of prosumer j and prosumer j, P m,h and Q m,h represent the active power and reactive power flowing from the upstream prosumer of prosumer m to prosumer m at time h, p j,m and q j,m represent the active power and reactive power injected by prosumer m at time h, U0 represents the node voltage, and V0 represents the square of the node voltage; S3-2: Judge whether equation (23) holds. If it holds, it means the verification passes; otherwise, it means there are voltage violation nodes, and execute S3-3; U min ≤U j,h ≤U max (23), In formula (23): U min represents the minimum value of the allowable prosumer node voltage, U max represents the maximum value of the allowable prosumer node voltage, U j,h represents the node voltage of prosumer j at time h; S3-3: Use equations (24)-(25) to construct the update formula of the carbon emission penalty value: In formulas (24)-(25): γ is the regulation coefficient of the carbon emission penalty value, λ buy,min and λ buy,max are the minimum and maximum values of the electricity received from the superior power grid, λ sell,min and λ sell,max are the minimum and maximum values of the electricity supplied to the superior power grid, U j,h represents the carbon emission penalty value of the electricity received by prosumer j after update at time h, represents the carbon emission penalty value of the electricity received by prosumer j after update at time h, represents the carbon emission penalty value of the electricity supplied by prosumer j after update at time h.

5. The P2P energy interaction method considering the contribution degree of prosumer differentiation and voltage regulation according to claim 4, characterized in that, The specific content of step S4 includes: S4-1: Use equations (26)-(29) to establish the energy interaction participation degree model in the prosumer differentiation model: In Equations (26) - (29): represents the set of all times for prosumer j under which the P2P power received represents the set of all times for prosumer j under which the P2P power supplied represents the set of all times for prosumer j the ratio of the P2P power received by prosumer j to the P2P received by all prosumers represents the set of all times for prosumer j the ratio of the P2P power supplied by prosumer j to the P2P supplied by all prosumers represents the energy interaction participation degree of prosumer j represents the optimal P2P interaction amount received by prosumer j from prosumer i, represents the optimal P2P interaction amount supplied by prosumer j to prosumer i; S4-2: Use equation (30) to establish the voltage regulation contribution degree model in the prosumer differentiation model; In formula (30): represents the number of voltage violation nodes adjusted by prosumer j, represents the maximum number of voltage violation nodes adjusted among all prosumers, represents the voltage regulation contribution degree of prosumer j; S4-3: Obtain the negotiation weight r of prosumer j using Equation (31) j ; 6. The P2P energy interaction method considering the differential contribution of prosumers and voltage regulation according to claim 5, characterized in that The specific content of step S5 includes: S5-1: Establish the objective function of the prosumer cluster differentiation negotiation sub-model using Equation (32) In formula (32): represents the total energy consumption when prosumer j does not participate in the cluster energy cooperation and sharing under the constraints of formulas (3)-(4), (5)-(8), and (15)-(16); represents the total energy consumption when prosumer j participates in the cluster energy cooperation and sharing, and there is: S5-2: Use equation (13) as the constraint condition of the prosumer cluster differentiation negotiation sub-model; S5-3: Use equation (34) to establish an equivalent model of the prosumer cluster differentiation negotiation sub-model: S5-4: Use equation (35) to establish the constraint condition of the equivalent model: S5-5: Use the distributed ADMM algorithm to solve the equivalent model, and combine the optimal power plan to obtain the final electricity consumption, including: the total electricity consumption of the cluster when the prosumer participates in the cluster energy cooperation and sharing, and the energy consumption of each prosumer when the energy consumption of the prosumer cluster is minimized.

7. An electronic device, comprising a memory and a processor, characterized in that, The memory is used to store a program that supports the processor to execute the P2P energy interaction method considering the production-consumption differential contribution degree and voltage regulation as described in any one of claims 1-6, and the processor is configured to execute the program stored in the memory.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is run by the processor, it executes the steps of the P2P energy interaction method considering the production-consumption differential contribution degree and voltage regulation as described in any one of claims 1-6.

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