A method for coordinating P2P power market transactions using multi-regional power grids

Abstract

The present invention provides a method for coordinating P2P electric energy market transactions using multi-regional power grids, including: obtaining the initial operation state of the distribution network, the distribution network zoning plan, and obtaining the initial information of each regional distribution network based on the zoning plan; the distribution network operator sets a preset processing coordination ADMM algorithm and the global variables required by the two-layer P2P electric energy market, and each regional distribution network takes the convergence of the bilateral transaction volume of the two-layer P2P electric energy market as the optimization goal, and performs parallel optimization on each regional distribution network, and iterates k times to obtain optimization information; the two-layer P2P electric energy market includes an auxiliary service market and a P2P electric energy market; the distribution network operator determines whether the exchange power between each region is balanced, and when the exchange power between each region is balanced, the transaction is completed according to the optimization information. The present invention can realize P2P electric energy market transactions with the best local area and the best overall social benefits under the coordination of multi-regional distribution networks.

Description

Technical Field

[0001] The invention relates to a method for coordinating P2P electric energy market transactions by utilizing multi-regional power grids, and belongs to the technical field of regional P2P transaction negotiation. Background Art

[0002] At present, my country's distributed power generation is developing rapidly, the installed capacity of distributed power generation is increasing, and the proportion of distributed power generation capacity in the total installed capacity in the country is increasing. With the increase of the installed capacity of distributed energy in the distribution network, users play a more active role in energy management and the power market. Compared with the traditional monopoly distribution energy market, the next generation of energy delivery mechanism P2P market allows producers to adopt the grid-connected electricity price strategy and trade energy surplus with adjacent producers according to personal preferences. The P2P trading market is conducive to the absorption of renewable energy.

[0003] At present, there are in-depth studies on P2P market distributed transactions and P2P transaction distribution network usage fees at home and abroad, but there are few studies on multi-regional distribution network P2P coordinated transaction mechanisms. Based on the existing distribution network regional division principle combined with the ADMM algorithm, a P2P power market transaction method considering multi-regional distribution network coordination is established. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method for coordinating P2P power market transactions using multi-regional power grids, which can achieve P2P power market transactions with the best local area and the best overall social benefits under the coordination of multi-regional distribution networks. To achieve the above purpose, the present invention is implemented by adopting the following technical solutions:

[0005] In a first aspect, the present invention provides a method for coordinating P2P electric energy market transactions using a multi-regional power grid, comprising:

[0006] Obtaining the initial operating status of the distribution network and the distribution network zoning plan, and obtaining the initial information of the distribution network in each region based on the zoning plan;

[0007] Based on the acquired and obtained information, the distribution network operator sets a preset processing coordination ADMM algorithm and global variables required by the two-layer P2P power market. Each regional distribution network takes the convergence of the bilateral transaction volume of the two-layer P2P power market as the optimization goal, and uses the preset processing coordination ADMM algorithm to parallel optimize each regional distribution network, iterating k times to obtain the optimization information; wherein, the two-layer P2P power market includes ancillary service market and P2P power market;

[0008] The distribution network operator calculates the dual residual and local residual of the inter-regional exchange power based on the optimization information. If the residuals are greater than or equal to the preset values, the exchange power between regions is unbalanced. The distribution network operator resets the global variables and the regional distribution networks are re-optimized in parallel until the exchange power between regions is balanced. If the residuals are less than the preset values, the exchange power between regions is balanced and the transaction is completed according to the optimization information.

[0009] In combination with the first aspect, further, the upper regional power grid set Ω of each regional distribution network is obtained according to the distribution network zoning plan. A and the lower regional power grid set Ω C .

[0010] In combination with the first aspect, further, the initial information of each regional distribution network includes: an initial value of power exchanged between each regional distribution network and an upper-level regional distribution network, an initial value of power exchanged between each regional distribution network and a lower-level regional distribution network, and matrix information of each regional distribution network.

[0011] In combination with the first aspect, further, the matrix information of the distribution network in each region is obtained by the following steps:

[0012] Based on the initial operation status of the distribution network and the distribution network zoning plan, a power flow model based on the distribution network operators in each region is constructed;

[0013] The voltage sensitivity coefficient matrix and power transmission allocation coefficient matrix of each regional distribution network are obtained according to the power flow model;

[0014] The network loss sensitivity coefficient matrix of each regional distribution network is determined according to the initial operation point of the distribution network, where the power flow transmission allocation coefficient matrix M based on region n is n The regional active power flow matrix and reactive power flow matrix

[0015] The expression is:

[0016]

[0017] In formula (1), is the net active load matrix of nodes in region n, is the net reactive load matrix of nodes in region n; M n Medium ij When the loop formed between the starting node in region n and the node j at the electric energy seller includes the node i at the electric energy buyer, it is 1, otherwise it is 0; the node voltage of the node i at the electric energy buyer in region n can be expressed as:

[0018]

[0019] In formula (2), is the starting node voltage of region n, ψ i is the sensitivity coefficient matrix of node voltage to active power, is the sensitivity coefficient matrix of node voltage to reactive power.

[0020] In combination with the first aspect, further, each regional distribution network takes the convergence of bilateral transaction volume in the double-layer P2P power market as the optimization target, and the regional distribution network optimization target is expressed by the following formula:

[0021]

[0022] In formula (3), Purchase active power from the upper regional distribution network for regional distribution network n, The reactive power purchased by regional distribution network n from the upper regional distribution network, P g To contribute to the ancillary service market participants, α is an auxiliary variable, which is expressed by the following formula:

[0023]

[0024] In formula (4), Ω A is the upper regional power grid set of the regional distribution network, Ω C It is the lower level regional power grid collection of the regional distribution network; is the dual variable of the power balance constraint between the regional distribution network n and the lower regional distribution network, is the dual variable of the power balance constraint exchanged between the regional distribution network n and the upper regional distribution network; Purchase active power from the lower regional distribution network for regional distribution network n, is the global variable for exchanging power between regional distribution network n and the lower-level regional distribution network, is the global variable for the power exchange between regional distribution network n and the upper regional distribution network, and ρ is the penalty factor.

[0025] In combination with the first aspect, preferably, when the preset processing coordination ADMM algorithm performs parallel optimization on the distribution networks of each region, in the kth iteration, the distribution network operator calculates the global variable of the inter-regional exchange power obtained in the k-1th iteration. and It is transmitted to the regional distribution network n through the virtual communication layer.

[0026] In combination with the first aspect, further, a preset processing coordination ADMM algorithm is used to perform parallel optimization on the distribution networks of each region, and optimization information is obtained by iterating k times, including:

[0027] The regional distribution network operators use the two-tier P2P power market to n Carry out optimized dispatch, including iteration of the ancillary service market and the P2P power market;

[0028] When the transmission fee coefficient is given, the P2P power market clearing is carried out by parallel optimization of a single producer and seller according to the ADMM distributed algorithm. The P2P power market clearing is:

[0029] The augmented Lagrangian function of node i, which is an electric energy buyer in the regional power grid n, is:

[0030]

[0031] The augmented Lagrangian function of node j, which is an electric energy seller, is:

[0032]

[0033] In formula (5) and (6), is the total amount of electricity purchased by node i, which is an electricity buyer. is the purchase price of electricity, is the amount of electricity purchased by node i, which is an energy buyer, from node j, which is an energy seller, ψ ij To handle global variables in the coordinated ADMM algorithm, is the total amount of electricity sold by node j, which is an electricity seller. The selling price of electricity; is the amount of electricity sold by node j, which is an electricity seller, to node i, which is an electricity buyer, and δ is the penalty factor; e ij is the cost of using the distribution network, which can be expressed as:

[0034] e ij =0.5(Π j -Π i ) ij (7)

[0035] In formula (7): p ij For trading electric energy between node i which is an electric energy buyer and node j which is an electric energy seller;

[0036] According to the optimization of equations (5) and (6), the optimal purchase amount of node i at the power buyer to node j at the power seller and the optimal sales amount of node j at the power seller to node i at the power buyer are obtained. It is judged whether the P2P power transaction converges under the transmission fee coefficient. If not, the global variables of the two-layer P2P power market are updated:

[0037]

[0038] In the ancillary service market of the two-layer P2P power market, the regional distribution network operator dispatches the ancillary service market to determine the node electricity price information according to the P2P power market clearing corresponding to equations (5) and (6), where Πi is the marginal electricity price of the distribution network node at the node i of the electricity buyer, expressed as:

[0039]

[0040] In formula (9): p is the dual coefficient of active power balance constraint of regional distribution network; q is the dual coefficient of reactive power balance constraint of regional distribution network; μ - is the dual coefficient of the lower limit constraint of the node voltage in the regional distribution network; μ + is the dual coefficient of the upper limit of the node voltage of the regional distribution network; τ b is the dual coefficient of the regional distribution network power flow constraint, and the marginal electricity price of the distribution network node is the net injected power P of the node i in the regional augmented Lagrangian function. i int The first partial derivative of ;

[0041] The regional distribution network operator determines whether the double-layer P2P energy market in the regional distribution network converges according to whether the P2P energy market clearing changes with the iteration of the double-layer P2P energy market, and determines the optimal exchange power of the regional distribution network at the kth iteration according to the double-layer P2P energy market clearing results.

[0042] In combination with the first aspect, further, the optimization information includes:

[0043] In the kth iteration, the regional distribution network operator uses the preset processing obtained from the overall distribution network operator to coordinate the global variables used by the ADMM algorithm in the k-1th iteration and Node electricity price and voltage information obtained from the upper-level regional distribution network operator;

[0044] The P2P power market clearing volume, regional distribution network node electricity prices and voltage information determined by the convergence of the two-layer P2P power market.

[0045] In combination with the first aspect, preferably, in the kth processing coordinated ADMM algorithm starting from the regional power grid containing the slack nodes, according to the sensitivity coefficient matrix information of the region, the global variable and By conducting optimal economic analysis, the regional distribution network operator coordinates the ancillary service market and the P2P market to achieve bilateral trading market clearing based on the physical constraints of the distribution network.

[0046] In combination with the first aspect, preferably, the regional distribution network operator transmits the node price information and node voltage information of the regional distribution network to the lower-level regional distribution network operator, and at the same time transmits the optimized value in the kth iteration and passed to the distribution network operator.

[0047] In combination with the first aspect, preferably, when performing the optimal economic analysis for each regional distribution network in the kth iteration, the regional distribution network operator coordinates the ancillary service market and the P2P market in the region to achieve optimal utility, wherein the ancillary service market is dispatched by the regional distribution network operator according to the physical constraints of the distribution network, and the P2P market converges according to the distributed clearing algorithm.

[0048] In combination with the first aspect, preferably, the regional distribution network operator dispatches the ancillary service market according to the P2P market clearing and determines the node marginal electricity price, and transmits the transmission fee coefficient based on the node marginal electricity price to the P2P market participants.

[0049] In combination with the first aspect, further, the distribution network operator resets the global variables to update the global variables required by the k+1th preset processing coordination ADMM algorithm and

[0050]

[0051] In order to accelerate the convergence of the preset processing coordination ADMM algorithm, the distribution network operator uses the local residual SE and the dual residual TE, combined with the preset acceleration factor ω up and the deceleration factor ω down Update the penalty factor ρ(k+1) and calculate it as follows:

[0052]

[0053] In formula (12), ω up is the acceleration factor; ω down is the deceleration factor.

[0054] In combination with the first aspect, further, the distribution network operator calculates the dual residual and the local residual of the inter-regional exchange power according to the optimization information, including:

[0055] The optimal transaction value between each regional distribution network and the upper-level distribution network in the overall distribution network operator's collection and optimization information The optimal transaction value of the transmission power of the lower distribution network

[0056] The dual residual of the exchange power between the distribution networks in each region is calculated by the following formula:

[0057]

[0058] Calculate the local residual of the exchange power between the distribution networks in each region by the following formula:

[0059]

[0060] In formulas (13) and (14), is the global variable for exchanging power between regional distribution network n and the lower-level regional distribution network, It is a global variable for exchanging power between regional distribution network n and the upper-level regional distribution network.

[0061] In a second aspect, the present invention provides a system for coordinating P2P power market transactions using a multi-regional power grid, including a communication-connected distribution network operator in each region and a distribution network operator;

[0062] The regional distribution network operators are used to use a preset processing coordination ADMM algorithm to perform parallel optimization on the regional distribution networks, coordinate the exchange power between the regional distribution networks and their upper and lower distribution networks, coordinate P2P power market transactions, and complete the clearing of P2P power market transactions according to the optimization information;

[0063] The distribution network operator is used to obtain distribution network operation data and provide preset processing coordination ADMM algorithm and global variables required by the two-layer P2P power market.

[0064] Compared with the prior art, the method for coordinating P2P power market transactions using multi-regional power grids provided in the embodiment of the present invention has the following beneficial effects:

[0065] The present invention obtains the initial operation state of the distribution network and the distribution network zoning plan, and obtains the initial information of the distribution network in each region based on the zoning plan; based on the information obtained and obtained, the distribution network operator sets a preset processing coordination ADMM algorithm and global variables required by the two-layer P2P electric energy market, and each regional distribution network takes the convergence of the bilateral transaction volume of the two-layer P2P electric energy market as the optimization goal, and uses the preset processing coordination ADMM algorithm to parallel optimize the distribution network in each region, and iterates k times to obtain the optimization information; wherein, the two-layer P2P electric energy market includes an auxiliary service market and a P2P electric energy market; the present invention can coordinate the exchange power of the auxiliary service market and the P2P electric energy market in each regional distribution network;

[0066] The distribution network operator calculates the dual residual and local residual of the inter-regional exchange power according to the optimization information. If the residuals are greater than or equal to the preset values, the exchange power between the regions is unbalanced. The distribution network operator resets the global variables, and the regional distribution networks are re-optimized in parallel until the exchange power between the regions is balanced. If the residuals are less than the preset values, the exchange power between the regions is balanced, and the transaction is completed according to the optimization information. For a single regional power grid operator, the present invention can determine the coupling information from the upper power grid through the ADMM distributed algorithm, realize the internal P2P market convergence, and transmit the corresponding information to the lower power grid. The present invention can realize P2P power market transactions with the best local area and the best overall social benefits under the coordination of multi-regional distribution networks. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] Figure 1 is a flow chart of a method for coordinating P2P power market transactions using multi-regional power grids provided in Example 1 of the present invention;

[0068] Figure 2 is a topological diagram of IEEE-69 node area I in embodiment 2 of the present invention;

[0069] Figure 3 is a topological diagram of IEEE-69 node area II in embodiment 2 of the present invention;

[0070] Figure 4 is a topological diagram of IEEE-69 node area III in embodiment 2 of the present invention;

[0071] Figure 5 It is the marginal electricity price information of the distribution network nodes in each region in embodiment 2 of the present invention;

[0072] Figure 6 It is the voltage information of the node area II and the power flow information of the node area I in the second embodiment of the present invention. DETAILED DESCRIPTION

[0073] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0074] Embodiment 1:

[0075] like Figure 1 As shown, a method for coordinating P2P electric energy market transactions using multi-regional power grids includes:

[0076] Obtaining the initial operating status of the distribution network and the distribution network zoning plan, and obtaining the initial information of the distribution network in each region based on the zoning plan;

[0077] Based on the acquired and obtained information, the distribution network operator sets a preset processing coordination ADMM algorithm and global variables required by the two-layer P2P power market. Each regional distribution network takes the convergence of the bilateral transaction volume of the two-layer P2P power market as the optimization goal, and uses the preset processing coordination ADMM algorithm to parallel optimize each regional distribution network, iterating k times to obtain the optimization information; wherein, the two-layer P2P power market includes ancillary service market and P2P power market;

[0078] The distribution network operator calculates the dual residual and local residual of the inter-regional exchange power based on the optimization information. If the residuals are greater than or equal to the preset values, the exchange power between regions is unbalanced. The distribution network operator resets the global variables and the regional distribution networks are re-optimized in parallel until the exchange power between regions is balanced. If the residuals are less than the preset values, the exchange power between regions is balanced and the transaction is completed according to the optimization information.

[0079] The specific steps are as follows:

[0080] Step 1: Obtain the initial operating status of the distribution network and the distribution network zoning plan, and obtain the initial information of the distribution network in each area based on the zoning plan.

[0081] According to the distribution network zoning plan, the upper regional power grid set Ω of each regional distribution network is obtained A and the lower regional power grid set Ω C .

[0082] The initial information of each regional distribution network includes: the initial value of the power exchanged between each regional distribution network and the upper regional distribution network, the initial value of the power exchanged between each regional distribution network and the lower regional distribution network, and the matrix information of each regional distribution network.

[0083] Among them, the matrix information of the distribution network in each region is obtained through the following steps:

[0084] Based on the initial operation status of the distribution network and the distribution network zoning plan, a power flow model based on the distribution network operators in each region is constructed;

[0085] The voltage sensitivity coefficient matrix and power transmission allocation coefficient matrix of each regional distribution network are obtained according to the power flow model;

[0086] The network loss sensitivity coefficient matrix of each regional distribution network is determined according to the initial operation point of the distribution network, where the power flow transmission allocation coefficient matrix M based on region n is n The regional active power flow matrix and reactive power flow matrix

[0087] The expression is:

[0088]

[0089] In formula (1), is the net active load matrix of nodes in region n, is the net reactive load matrix of nodes in region n; M n Medium ij When the loop formed between the starting node in region n and the node j at the electric energy seller includes the node i at the electric energy buyer, it is 1, otherwise it is 0; the node voltage of the node i at the electric energy buyer in region n can be expressed as:

[0090]

[0091] In formula (2), is the starting node voltage of region n, ψ i is the sensitivity coefficient matrix of node voltage to active power, is the sensitivity coefficient matrix of node voltage to reactive power.

[0092] Step 2: The distribution network operator sets the preset processing coordination ADMM algorithm and the global variables required by the two-layer P2P power market. Each regional distribution network takes the convergence of the bilateral transaction volume of the two-layer P2P power market as the optimization goal, and uses the preset processing coordination ADMM algorithm to perform parallel optimization on each regional distribution network. The optimization information is obtained by iterating k times.

[0093] In combination with the first aspect, preferably, in the kth processing coordinated ADMM algorithm starting from the regional power grid containing the slack nodes, according to the sensitivity coefficient matrix information of the region, the global variable and By conducting optimal economic analysis, the regional distribution network operator coordinates the ancillary service market and the P2P market to achieve bilateral trading market clearing based on the physical constraints of the distribution network.

[0094] The optimization target of each regional distribution network is the convergence of bilateral transaction volume in the two-layer P2P power market. The optimization target of the regional distribution network is expressed by the following formula:

[0095]

[0096] In formula (3), Purchase active power from the upper regional distribution network for regional distribution network n, The reactive power purchased by regional distribution network n from the upper regional distribution network, P g To contribute to the ancillary service market participants, α is an auxiliary variable, which is expressed by the following formula:

[0097]

[0098] In formula (4), Ω A is the upper regional power grid set of the regional distribution network, ΩC It is the lower level regional power grid collection of the regional distribution network; is the dual variable of the power balance constraint between the regional distribution network n and the lower regional distribution network, is the dual variable of the power balance constraint exchanged between the regional distribution network n and the upper regional distribution network; Purchase active power from the lower regional distribution network for regional distribution network n, is the global variable for exchanging power between regional distribution network n and the lower-level regional distribution network, is the global variable for the power exchange between regional distribution network n and the upper regional distribution network, and ρ is the penalty factor.

[0099] When the preset processing coordination ADMM algorithm performs parallel optimization on the distribution networks of each region, in the kth iteration, the distribution network operator calculates the global variable of the inter-regional exchange power obtained in the k-1th iteration. and It is transmitted to the regional distribution network n through the virtual communication layer.

[0100] The preset processing coordination ADMM algorithm is used to optimize the distribution networks in each region in parallel, and the optimization information is obtained after k iterations, including:

[0101] The regional distribution network operators use the two-tier P2P power market to n Carry out optimized dispatch, including iteration of the ancillary service market and the P2P power market;

[0102] When the transmission fee coefficient is given, the P2P power market clearing is carried out by parallel optimization of a single producer and seller according to the ADMM distributed algorithm. The P2P power market clearing is:

[0103] The augmented Lagrangian function of node i, which is an electric energy buyer in the regional power grid n, is:

[0104]

[0105] The augmented Lagrangian function of node j, which is an electric energy seller, is:

[0106]

[0107] In formula (5) and (6), is the total amount of electricity purchased by node i, which is an electricity buyer. is the purchase price of electricity, is the amount of electricity purchased by node i, which is an energy buyer, from node j, which is an energy seller, ψ ij To handle global variables in the coordinated ADMM algorithm, is the total amount of electricity sold by node j, which is an electricity seller. The selling price of electricity; is the amount of electricity sold by node j, which is an electricity seller, to node i, which is an electricity buyer, and δ is the penalty factor; e ij is the cost of using the distribution network, which can be expressed as:

[0108] e ij =0.5(Π j -Π i ) ij (7)

[0109] In formula (7): p ij For trading electric energy between node i which is an electric energy buyer and node j which is an electric energy seller;

[0110] According to equations (5) and (6), the optimal amount of electricity purchased from node i, which is an energy buyer, to node j, which is an energy seller, is obtained: and the optimal power sales from node j, which is an energy seller, to node i, which is an energy buyer, to determine whether the P2P energy transaction converges under the transmission fee coefficient. If not, update the global variables of the two-layer P2P energy market:

[0111]

[0112] In the ancillary service market of the two-layer P2P power market, the regional distribution network operator dispatches the ancillary service market to determine the node electricity price information according to the P2P power market clearing corresponding to equations (5) and (6), where Π i is the marginal electricity price of the distribution network node at the node i of the electricity buyer, expressed as:

[0113]

[0114] In formula (9): p is the dual coefficient of active power balance constraint of regional distribution network; q is the dual coefficient of reactive power balance constraint of regional distribution network; μ - is the dual coefficient of the lower limit constraint of the node voltage in the regional distribution network; μ + is the dual coefficient of the upper limit of the node voltage of the regional distribution network; τ b is the dual coefficient of the regional distribution network power flow constraint, and the marginal electricity price of the distribution network node is the net injected power P of the node i in the regional augmented Lagrangian function. i int The first partial derivative of ;

[0115] The regional distribution network operator determines whether the double-layer P2P energy market in the regional distribution network converges according to whether the P2P energy market clearing changes with the iteration of the double-layer P2P energy market, and determines the optimal exchange power of the regional distribution network at the kth iteration according to the double-layer P2P energy market clearing results.

[0116] Optimization information includes:

[0117] In the kth iteration, the regional distribution network operator uses the preset processing obtained from the overall distribution network operator to coordinate the global variables used by the ADMM algorithm in the k-1th iteration and Node electricity price and voltage information obtained from the upper-level regional distribution network operator;

[0118] The P2P power market clearing volume, regional distribution network node electricity prices and voltage information determined by the convergence of the two-layer P2P power market.

[0119] The regional distribution network operator transmits the node price information and node voltage information of the regional distribution network to the lower-level regional distribution network operator, and at the same time transmits the optimized value in the kth iteration to the lower-level regional distribution network operator. and passed to the distribution network operator.

[0120] When conducting the optimal economic analysis for each regional distribution network in the kth iteration, the regional distribution network operator coordinates the ancillary service market and the P2P market in the region to achieve optimal utility. The ancillary service market is dispatched by the regional distribution network operator according to the physical constraints of the distribution network, and the P2P market converges according to the distributed clearing algorithm.

[0121] The regional distribution network operator dispatches the ancillary service market and determines the node marginal electricity price based on the P2P market clearing, and passes the transmission fee coefficient based on the node marginal electricity price to the P2P market participants.

[0122] Step 3: The distribution network operator calculates the dual residual and local residual of the inter-regional exchange power based on the optimization information. If the residuals are greater than or equal to the preset values, the exchange power between regions is unbalanced. The distribution network operator resets the global variables and the regional distribution networks are re-optimized in parallel until the exchange power between regions is balanced. If the residuals are less than the preset values, the exchange power between regions is balanced and the transaction is completed according to the optimization information.

[0123] The distribution network operator resets the global variables to update the global variables required by the k+1th preset processing coordination ADMM algorithm and

[0124]

[0125] In order to accelerate the convergence of the preset processing coordination ADMM algorithm, the distribution network operator uses the local residual SE and the dual residual TE, combined with the preset acceleration factor ω up and the deceleration factor ω down Update the penalty factor ρ(k+1) and calculate it as follows:

[0126]

[0127] In formula (12), ω up is the acceleration factor; ω down is the deceleration factor.

[0128] The distribution network operator calculates the dual residual and local residual of the inter-regional exchange power based on the optimization information, including:

[0129] The optimal transaction value between each regional distribution network and the upper-level distribution network in the overall distribution network operator's collection and optimization information The optimal transaction value of the transmission power of the lower distribution network

[0130] The dual residual of the exchange power between the distribution networks in each region is calculated by the following formula:

[0131]

[0132] Calculate the local residual of the exchange power between the distribution networks in each region by the following formula:

[0133]

[0134] In formulas (13) and (14), is the global variable for exchanging power between regional distribution network n and the lower-level regional distribution network, It is a global variable for exchanging power between regional distribution network n and the upper-level regional distribution network.

[0135] Embodiment 2:

[0136] The IEEE 69 node system is selected for specific analysis and description. The schematic diagram of IEEE-69 node area division in the embodiment of the present invention is as follows: Figure 2-Figure 4 As shown. The DER of the ancillary service market participants are set at 32, 40, 7, 60, 21 and 68 nodes respectively. For DLMP, it can be divided into the upper regional grid power price part, the network loss energy price part, the active power flow congestion price part, the voltage support price part and the dual coefficient part. The cost coefficients of the ancillary service market participants are shown in Table 1.

[0137] Table 1 Cost coefficients of ancillary service market participants in different scenarios

[0138]

[0139] When the overall distribution network reaches an agreement on the exchange power between the regional power grids, the regional power grid DLMP price information is as follows: Figure 5 As shown in the figure, the marginal electricity prices of the interconnection nodes of the distribution networks in each region are consistent and the marginal electricity price of node 1 is the main grid electricity price. The marginal electricity prices of each node are positively correlated with the corresponding sensitivity coefficients.

[0140] For node area I where power congestion may occur and node area II where voltage over-limit may occur, it can be seen that their power flows and voltages are respectively as follows: Figure 6 As shown in the figure, since the power transmission allocation coefficients of the corresponding nodes of some branches in area I are all 1, it can be seen that power congestion is prone to occur, so it is necessary to respond and adjust according to the regional ancillary service market; considering that the adjustment cost of the ancillary service market in area II is higher than that in other areas, the corresponding adjustment values ​​are relatively small and voltage over-limit is prone to occur.

[0141] Using the method described in Example 1 for coordinating P2P power market transactions using multi-regional power grids, the ancillary service market clearing volumes in different regional power grids are obtained as shown in Table 2.

[0142] Table 2: Clearing information of ancillary service market participants in different scenarios

[0143]

[0144] As shown in Table 2, for a single regional power grid operator, the present invention can determine coupling information from the upper power grid through the ADMM distributed algorithm, achieve internal P2P market convergence, and transmit corresponding information to the lower power grid. The present invention can realize P2P electricity market transactions with the best local regional and overall social benefits under the coordination of multi-regional distribution networks.

[0145] Embodiment 3:

[0146] This embodiment provides a system for coordinating P2P power market transactions using a multi-regional power grid, including a communication-connected distribution network operator in each region and a distribution network operator;

[0147] The regional distribution network operators are used to use a preset processing coordination ADMM algorithm to perform parallel optimization on the regional distribution networks, coordinate the exchange power between the regional distribution networks and their upper and lower distribution networks, coordinate P2P power market transactions, and complete the clearing of P2P power market transactions according to the optimization information;

[0148] The distribution network operator is used to obtain distribution network operation data and provide preset processing coordination ADMM algorithm and global variables required by the two-layer P2P power market.

[0149] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for coordinating P2P electric energy market transactions using multi-regional power grids, characterized in that: include: Obtaining the initial operating status of the distribution network and the distribution network zoning plan, and obtaining the initial information of the distribution network in each region based on the zoning plan; Based on the acquired and obtained information, the distribution network operator sets a preset processing and coordination ADMM algorithm and the global variables required by the two-layer P2P power market. Each regional distribution network takes the convergence of the bilateral transaction volume of the two-layer P2P power market as the optimization goal, and uses the preset processing and coordination ADMM algorithm to parallel optimize each regional distribution network, and iterates k times to obtain optimization information; wherein, the two-layer P2P power market includes ancillary service market and P2P power market; the optimization information includes: in the kth iteration, the regional distribution network operator uses the global variables used in the k-1th iteration of the preset processing and coordination ADMM algorithm obtained from the overall distribution network operator and Node electricity prices and voltage information obtained from the upper-level regional distribution network operator; P2P electricity market clearing volume, regional distribution network node electricity prices and voltage information determined by double-layer P2P electricity market convergence; The distribution network operator calculates the dual residual and local residual of the inter-regional exchange power based on the optimization information. If the residuals are greater than or equal to the preset values, the exchange power between regions is unbalanced. The distribution network operator resets the global variables and the regional distribution networks are re-optimized in parallel until the exchange power between regions is balanced. If the residuals are less than the preset values, the exchange power between regions is balanced and the transaction is completed according to the optimization information.

2. The method for coordinating P2P electric energy market transactions using multi-regional power grids according to claim 1, characterized in that: According to the distribution network zoning plan, the upper regional power grid set Ω of each regional distribution network is obtained A and the lower regional power grid set Ω C .

3. The method for coordinating P2P electric energy market transactions using multi-regional power grids according to claim 1, characterized in that: The initial information of each regional distribution network includes: the initial value of the power exchanged between each regional distribution network and the upper regional distribution network, the initial value of the power exchanged between each regional distribution network and the lower regional distribution network, and the matrix information of each regional distribution network.

4. The method for coordinating P2P electric energy market transactions using multi-regional power grids according to claim 3, characterized in that: The matrix information of the distribution network in each region is obtained through the following steps: Based on the initial operation status of the distribution network and the distribution network zoning plan, a power flow model based on the distribution network operators in each region is constructed; The voltage sensitivity coefficient matrix and power transmission allocation coefficient matrix of each regional distribution network are obtained according to the power flow model; The network loss sensitivity coefficient matrix of each regional distribution network is determined according to the initial operation point of the distribution network, where the power flow transmission allocation coefficient matrix M based on region n is n The regional active power flow matrix and reactive power flow matrix The expression is: In formula (1), is the net active load matrix of nodes in region n, is the net reactive load matrix of nodes in region n; M n Medium ij When the loop formed between the starting node in region n and the node j at the electric energy seller includes the node i at the electric energy buyer, it is 1, otherwise it is 0; the node voltage of the node i at the electric energy buyer in region n can be expressed as: In formula (2), is the starting node voltage of region n, ψ i is the sensitivity coefficient matrix of node voltage to active power, is the sensitivity coefficient matrix of node voltage to reactive power.

5. The method for coordinating P2P electric energy market transactions using multi-regional power grids according to claim 1, characterized in that: The optimization target of each regional distribution network is to converge the bilateral transaction volume of the two-layer P2P power market. The optimization target of the regional distribution network is expressed by the following formula: In formula (3), Purchase active power from the upper regional distribution network for regional distribution network n, The reactive power purchased by regional distribution network n from the upper regional distribution network, P g To contribute to the ancillary service market participants, α is an auxiliary variable, which is expressed by the following formula: In formula (4), Ω A is the upper regional power grid set of the regional distribution network, Ω C It is the lower level regional power grid collection of the regional distribution network; is the dual variable of the power balance constraint between the regional distribution network n and the lower regional distribution network, is the dual variable of the power balance constraint exchanged between the regional distribution network n and the upper regional distribution network; Purchase active power from the lower regional distribution network for regional distribution network n, is the global variable for exchanging power between regional distribution network n and the lower-level regional distribution network, is the global variable for the power exchange between regional distribution network n and the upper regional distribution network, and ρ is the penalty factor.

6. The method for coordinating P2P electric energy market transactions using multi-regional power grids according to claim 5, characterized in that: The preset processing coordination ADMM algorithm is used to optimize the distribution networks in each region in parallel, and the optimization information is obtained after k iterations, including: The regional distribution network operators use the two-tier P2P power market to n Carry out optimized dispatch, including iteration of the ancillary service market and the P2P power market; When the transmission fee coefficient is given, the P2P power market clearing is carried out by parallel optimization of a single producer and seller according to the ADMM distributed algorithm. The P2P power market clearing is: The augmented Lagrangian function of node i, which is an electric energy buyer in the regional power grid n, is: The augmented Lagrangian function of node j, which is an electric energy seller, is: In formula (5) and (6), is the total amount of electricity purchased by node i, which is an electricity buyer. is the purchase price of electricity, is the amount of electricity purchased by node i, which is an energy buyer, from node j, which is an energy seller, ψ ij To handle global variables in the coordinated ADMM algorithm, is the total amount of electricity sold by node j, which is an electricity seller. The selling price of electricity; is the amount of electricity sold by node j, which is an electricity seller, to node i, which is an electricity buyer, and δ is the penalty factor; e ij is the cost of using the distribution network, which can be expressed as: e ij =0.5(Π j -P i )p ij (7) In formula (7): p ij For the trade of electric energy between producers and sellers i and j; According to equations (5) and (6), the optimal amount of electricity purchased from node i, which is an energy buyer, to node j, which is an energy seller, is obtained: and the optimal amount of electricity sold from node j, which is an energy seller, to node i, which is an energy buyer Determine whether P2P power trading converges under the transmission fee coefficient. If not, update the global variables of the two-layer P2P power market: In the ancillary service market of the two-layer P2P power market, the regional distribution network operator dispatches the ancillary service market to determine the node electricity price information according to the P2P power market clearing corresponding to equations (5) and (6), where Π i is the marginal electricity price of the distribution network node at node i, expressed as: In formula (9): p is the dual coefficient of active power balance constraint of regional distribution network; q is the dual coefficient of reactive power balance constraint of regional distribution network; μ - is the dual coefficient of the lower limit constraint of the node voltage in the regional distribution network; μ + is the dual coefficient of the upper limit of the node voltage of the regional distribution network; τ b is the dual coefficient of the regional distribution network power flow constraint, and the marginal electricity price of the distribution network node is the net injected power P of the node i in the regional augmented Lagrangian function. i int The first partial derivative of ; The regional distribution network operator determines whether the double-layer P2P energy market in the regional distribution network converges according to whether the P2P energy market clearing changes with the iteration of the double-layer P2P energy market, and determines the optimal exchange power of the regional distribution network at the kth iteration according to the double-layer P2P energy market clearing results.

7. The method for coordinating P2P electric energy market transactions using multi-regional power grids according to claim 1, characterized in that: The distribution network operator resets the global variables to update the global variables required by the k+1th preset processing coordination ADMM algorithm and In order to accelerate the convergence of the preset processing coordination ADMM algorithm, the distribution network operator uses the local residual SE and the dual residual TE, combined with the preset acceleration factor ω up and the deceleration factor ω down Update the penalty factor ρ(k+1) and calculate it as follows: In formula (12), ω up is the acceleration factor; ω down is the deceleration factor.

8. The method for coordinating P2P electric energy market transactions using multi-regional power grids according to claim 1, characterized in that: The distribution network operator calculates the dual residual and local residual of the inter-regional exchange power according to the optimization information, including: The optimal transaction value between each regional distribution network and the upper-level distribution network in the overall distribution network operator's collection and optimization information The optimal transaction value of the transmission power of the lower distribution network The dual residual of the exchange power between the distribution networks in each region is calculated by the following formula: Calculate the local residual of the exchange power between the distribution networks in each region by the following formula: In formulas (13) and (14), is the global variable for exchanging power between regional distribution network n and the lower-level regional distribution network, It is a global variable for exchanging power between regional distribution network n and the upper-level regional distribution network.

9. A system for coordinating P2P electric energy market transactions using multi-regional power grids, executing the method for coordinating P2P electric energy market transactions using multi-regional power grids as described in any one of claims 1 to 8, characterized in that: Including the regional distribution network operators and distribution network operators connected by communications; The regional distribution network operators are used to use a preset processing coordination ADMM algorithm to perform parallel optimization on the regional distribution networks, coordinate the exchange power between the regional distribution networks and their upper and lower distribution networks, coordinate P2P power market transactions, and complete the clearing of P2P power market transactions according to the optimization information; The distribution network operator is used to obtain distribution network operation data and provide preset processing coordination ADMM algorithm and global variables required by the two-layer P2P power market.

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