Blocking decoupling management-based power distribution network economic dispatching method and system

Abstract

The present invention relates to the field of energy market analysis. Provided are a blocking decoupling management-based power distribution network economic dispatching method and system. The blocking decoupling management-based power distribution network economic dispatching method comprises: receiving competitive bidding information submitted by all prosumers; performing energy competitive bidding matching by means of the competitive bidding information submitted by all the prosumers; settling a result of the energy competitive bidding matching; and performing blocking management on the basis of a preset blocking management model, the blocking management model being established by settling the result of the energy competitive bidding matching. The method not only allows power distribution network operators to recover costs correctly, but also helps to motivate prosumers to perform nearby energy matching; the energy matching and decoupling dispatching of blocking management provide the prosumers with more profit room and matching opportunities while improving fairness, and greatly improve the solving efficiency of economic dispatching, thus adapting to the requirements of rapid and high-frequency economic dispatching of power distribution networks in an ultra-large-scale prosumer scenario.

Description

A distribution network economic dispatching method and system based on congestion decoupling management Technical Field

[0001] The present invention relates to the technical field of energy market analysis, and in particular to a distribution network economic dispatching method and system based on congestion decoupling management. Background Art

[0002] In the distribution market, due to the random nature of distributed renewable energy generation, long economic dispatch cycles can expose prosumers to default losses due to forecasting errors. Therefore, real-time economic dispatch of distribution networks generally requires fast, high-frequency operation. Therefore, in scenarios where a large number of prosumers exist within the distribution network, computational efficiency can become both a challenge and a key factor in the design of economic dispatch mechanisms. Furthermore, the distribution network's radial grid structure with its high r / x ratio renders simplified DC power flow models on the transmission side unsuitable, further increasing the model's complexity and imposing a greater computational burden.

[0003] Existing distribution network market clearing models primarily include the following two approaches: The core of this approach is the safety-constrained economic dispatch method, which is analogous to the node electricity price method in the wholesale market. Taking into account the particularities of the physical architecture of the distribution network, it uses similar safety-constrained unit commitment and economic dispatch models to clear the market. Furthermore, it uses duality theory to derive distribution network node electricity prices that include components such as energy cost, congestion cost, and voltage regulation cost. This method is essentially still solving a very large-scale flow-constrained optimization model with the participation of massive producers and consumers, and clearly suffers from certain disadvantages in solution efficiency.

[0004] The continuous double auction method ignores the security constraints of the distribution network at the beginning of the current dispatch cycle and uses simple double auction rules to conduct multiple rounds of rapid market clearing. Since the power flow constraints are temporarily ignored, all energy matching can be completed in a very short time. For the problem that the matching results may violate the power flow constraints, this technology mainly adopts a post-safety check and reduces or cancels orders according to certain principles. There are also related technologies that use a method of checking the matching results one by one until there are no more orders to be reached. Although this method can meet the needs of fast and high-frequency economic dispatch of the distribution network, the safety check method may cause a considerable number of energy orders to be unfulfilled, or to be reduced or even canceled.

[0005] On the one hand, the existing methods are not conducive to promoting the matching of local electricity supply and demand and the local consumption of new energy; on the other hand, there may be fairness disputes over the principles to be adopted for order reduction.

[0006] Summary of the Invention

[0007] (1) Technical problems solved

[0008] In response to the shortcomings of the existing technology, the present invention provides a distribution network economic dispatch method and system based on congestion decoupling management, which can not only enable distribution network operators to recover costs correctly, but also help to encourage producers and consumers to match energy nearby. The decoupled dispatch of energy matching and congestion management not only improves fairness but also gives producers and consumers more profit space and matching opportunities, and greatly improves the efficiency of economic dispatch solution, which can adapt to the needs of fast and high-frequency economic dispatch of distribution networks in ultra-large-scale producers and consumers scenarios.

[0009] (2) Technical solution

[0010] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0011] In a first aspect, a method for economic dispatch of a distribution network based on congestion decoupling management is provided, comprising the following steps:

[0012] An information receiving step of receiving bidding information submitted by each producer and consumer, wherein the bidding information includes bidding requirements, bidding prices, and bidding modes;

[0013] The matching step involves matching energy bids based on the bidding information submitted by each prosumer. The bidding requirements include: purchase / sale power requirements and the location of the prosumer node. The bidding price represents the declared price per kWh of electricity purchased / sold.

[0014] Settlement step, settling the results of energy bidding matching;

[0015] A model management step, performing congestion management based on a preset congestion management model, wherein the congestion management model is established by settling energy bidding matching results;

[0016] Model solving steps, solve the congestion management model, and complete the optimal economic dispatch of the distribution network under the market environment.

[0017] Preferably, the matching step specifically includes the following steps:

[0018] 2-1) Sort the sets of buyers and sellers, producers and consumers, by bidding price in descending order and descending order respectively;

[0019] 2-2) Determine the winning bidder* for the current matching round. The determination method can be expressed as follows:

[0020] Where m∈{1,2,3,...,M} and n∈{1,2,3,...,N} represent the sets of electricity buyers and sellers, respectively. and Represent the time-of-use electricity price and on-grid electricity price respectively, π m and π nRepresents the prosumer's quotation information. The closer the two are to the contract price, the greater the profit the prosumer makes. * Indicates the best bid in the current matching round;

[0021] 2-3) Calculate the additional transmission fee and network cost for the winning bidder * for any n energy matches. For example, the calculation method is as follows:

[0022] Where, They represent the transmission fee and network loss fee that should be paid for energy matching between the prosumers at two nodes a and b, They represent the additional transmission fee and network loss fee for energy matching between the prosumers at two nodes a and b, represents the active power sold by node a prosumer to node b prosumer, and 0.5 indicates that the additional cost is borne by both matching parties;

[0023] 2-4) For electricity sellers, the price is adjusted according to the Sort from low to high to form a list of electricity sellers to be matched. The case where * represents the electricity seller is similar and will not be repeated.

[0024] 2-5) Starting from the first table of the list to be matched, traverse the above list in order. For the current traversal object, if it satisfies Then the producer and consumer* matches the order with the current traversal object, records the matching result, and updates all waiting-for-matching lists according to the matching result. Otherwise, the current traversal object is removed from the waiting-for-matching list of the current round.

[0025] 2-6) Repeat steps 2-5). If no electricity seller can match *, *'s bid fails and * is moved from the pending matching list to the minimum and maximum guaranteed list or energy resale list according to the bidding mode.

[0026] 2-7) Repeat steps 2-2) to 2-6) until max(π m )<min(π n ) to form the energy bidding matching result.

[0027] Preferably, the matching step further comprises the following steps:

[0028] 2-8) The present invention adopts a network loss sensitivity iterative correction method. In each iteration process, it is considered that the distribution network line flow P ij , Q ij and each node voltage V i As a given value, the network loss additional cost is calculated based on this to perform energy matching. Then, based on the matching result, P ij , Q ij With Vi Make corrections and update the corresponding distribution network flow distribution based on equations (80)-(83) and ν represents the current iteration number, and the above process is repeated until convergence. When ν = 0, in order to reduce the algorithm error and improve the convergence performance, the matching algorithm is calculated by only considering the network fee and ignoring the network loss. and As the initial value of network loss sensitivity.

[0029] As the number of prosumers increases, the model scale becomes larger. The above iterative method may be difficult to ensure convergence within the required time. Considering that the network loss has little impact on the power flow results, and the network loss fee of the mechanism is only used as a price signal to guide each prosumer to match energy nearby. In order to ensure the solution speed, the present invention also sets the maximum number of iterations ν max As the criterion for the termination of iteration, it is considered that the modified ν max The matching result after subtracting the network loss coefficient can already meet the actual needs;

[0030] Since the network loss caused by energy matching depends on the power flow distribution, which is unknown before the energy matching is completed, the corresponding distribution network power flow distribution is updated based on the energy bidding matching results. and ν represents the current iteration number; when ν = 0, the power flow distribution is calculated by ignoring the network loss and only taking into account the energy bidding matching results of the network fee. The calculation of the power flow distribution is expressed as follows: i =∑ j G ij V j -∑ j B′ ij θ j Q i =-∑ j B ij V j -∑ j G′ ij θ j P ij =g ij (V i -V j )-b ij (θ i -θ j ) Q ij =-b ij (V i -V j )-g ij (θ i -θ j )

[0031] Where i and j represent the first and last nodes of the distribution line, P i , Q i 、P ij , Q ij They represent the net injection of node i and the active and reactive power of line ij, respectively. i ,θ i Respectively represent the voltage amplitude and phase angle of node i; Y ij =G ij +jB ij represents the node admittance matrix element. The superscript prime indicates that the node admittance matrix element value corresponding to the parallel branch to the ground is ignored. g ij +jb ij represents the admittance of the distribution line ij;

[0032] 2-9) If The energy bidding matching is completed, and the νth energy bidding matching result is the final result. Otherwise, ν=ν+1, and go to step 2-1) to continue iteration.

[0033] Preferably, the settlement step specifically includes: π mn =0.5*(π m +π n )

[0034] Where, π mn With P mn Denote the transaction price and power of prosumers m and n respectively, C m 、C n and C DSO represent m, n and the expenditure costs of the distribution network operator respectively.

[0035] Preferably, the objective function of the congestion management model is as follows:

[0036] Where C M represents the congestion management cost of the distribution network operator, μ g P represents the declared compensation price for the unit of electricity regulated by the producer / consumer g in the distribution network, g represents the actual regulation capacity of the producer / consumer g, Q h With μ h They represent the power generated by the reactive power compensation device in the distribution network and the additional unit cost caused by its deployment. The third item represents the network loss cost of the distribution network.

[0037] The constraints of the congestion management model include, among which, P g , Q hThe following constraints should be met:

[0038] Where, represents the maximum flexibility available to prosumers participating in congestion management, Indicates the output limit of the reactive power compensation device owned by the distribution network operator;

[0039] Using the virtual node demand model, a load power of 0.5 times the line network loss is simulated at the nodes at both ends, so that the line can be considered as a lossless line; the network loss of each line is expressed as follows:

[0040] Where, Represent the active and reactive losses of line ij respectively Inject power P to each node δ , Q δ sensitivity;

[0041] The network loss correction power and line flow of each node based on the virtual node demand model are expressed as follows:

[0042] Where P′ i , Q′ i , P′ ij , Q′ ij They represent the corrected active and reactive power of each node and line after considering the compensation of the virtual node demand model, They represent the line power flow P ij , Q ij Inject power P into the node δ , Q δ sensitivity;

[0043] Then the power flow constraint that the congestion management model needs to satisfy is expressed as follows, ∑ i P′ i =0∑ i Q′ i =0

[0044] Where 1 is a unit vector, and its dimension is the same as the number of system nodes.

[0045] Preferably, the improvement of the efficiency of solving the congestion management model includes:

[0046] The power circle is approximately replaced by an inscribed regular L-gon, where L is an even number and the corresponding central angle is θ. The specific expression is as follows:

[0047] Where k l 、b l Represents the slope and longitudinal intercept of the straight line corresponding to the lth side of the inscribed regular L-gon.

[0048] Preferably, the bidding model specifically includes:

[0049] Minimum and maximum cap model: During the energy matching phase, all bidders that fail to match the bid will obtain / sell electricity directly from the distribution network operator at the contract electricity price, time-of-use electricity price and grid electricity price;

[0050] Energy resale model: In the energy matching stage, all bids that fail to match will be transferred to participate in the congestion management of the distribution network operator at a new bidding price, thereby obtaining new scheduling opportunities.

[0051] In a second aspect, a distribution network economic dispatch system based on congestion decoupling management is provided, the system comprising the following modules:

[0052] An information receiving module is used to receive bidding information submitted by each producer and consumer, wherein the bidding information includes bidding requirements, bidding prices and bidding modes;

[0053] A matching module is used to match energy bids using the bidding information submitted by each producer and consumer;

[0054] Settlement module, used to settle the results of energy bidding and matching;

[0055] A model management module, configured to perform congestion management based on a preset congestion management model, wherein the congestion management model is established by settling energy bidding matching results;

[0056] The model solving module is used to solve the congestion management model and complete the optimized economic dispatch of the distribution network under the market environment.

[0057] In a third aspect, a computer-readable storage medium is provided that stores one or more programs, wherein the one or more programs include instructions that, when executed by a computing device, cause the computing device to perform any of the methods described.

[0058] According to a fourth aspect, a computing device is provided, comprising:

[0059] One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the methods described. (3) Beneficial effects

[0060] (1) The present invention provides a distribution network economic dispatching method and system based on congestion decoupling management. Compared with the conventional continuous two-way auction mechanism, the sensitivity factor-based network loss and transmission fee accounting and correction method has a better guiding and promoting effect on the distribution network operator to correctly recover service costs and incentivize the energy matching of producers and consumers. Compared with the traditional contract price model, the method proposed in the present invention can guarantee the minimum income of producers and consumers and has a good incentive for market participants.

[0061] (2) The present invention provides a distribution network economic dispatching method and system based on congestion decoupling management. With the further penetration and configuration of distributed resources and distributed power sources in the distribution network, the congestion management method proposed by the present invention helps to encourage distribution-side producers and consumers to actively explore their own power generation and consumption flexibility and provide services to the distribution network, thereby restoring the distribution network to normal operating state.

[0062] (3) The present invention provides a distribution network economic dispatch method and system based on blocking decoupling management. Compared with the unified clearing mechanism with safety constraints represented by traditional economic dispatch, the method proposed by the present invention can further improve the matching degree between the overall benefits of producers and consumers and local electricity in terms of economy; in terms of solution efficiency, the decoupling effect of the method proposed by the present invention reduces the complexity of the model, which can meet the needs of fast and high-frequency operation of distribution network economic dispatch in the scenario of massive producers and consumers. BRIEF DESCRIPTION OF THE DRAWINGS

[0063] FIG1 is a flow chart of a method for economic dispatching of a distribution network based on congestion decoupling management according to the present invention;

[0064] FIG2 is a schematic diagram of the overall implementation flow of the distribution network economic dispatch method based on congestion decoupling management of the present invention. DETAILED DESCRIPTION

[0065] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0066] Example

[0067] As shown in FIG1-2 , an embodiment of the present invention provides a method for economic dispatch of a distribution network based on congestion decoupling management, comprising the following steps:

[0068] An information receiving step of receiving bidding information submitted by each producer and consumer, wherein the bidding information includes bidding requirements, bidding prices, and bidding modes;

[0069] The matching step involves matching energy bids based on the bidding information submitted by each prosumer. The bidding requirements include: purchase / sale power requirements and the location of the prosumer node. The bidding price represents the declared price per kWh of electricity purchased / sold.

[0070] Settlement step, settling the results of energy bidding matching;

[0071] A model management step, performing congestion management based on a preset congestion management model, wherein the congestion management model is established by settling energy bidding matching results;

[0072] Model solving steps: solve the congestion management model, restore the distribution network to normal operation by purchasing flexibility resources from prosumers, and complete the optimized economic dispatch of the distribution network under the market environment.

[0073] Furthermore, the matching step specifically includes the following steps:

[0074] 2-1) Sort the sets of buyers and sellers, producers and consumers, by bidding price in descending order and descending order respectively;

[0075] 2-2) Determine the winning bidder* for the current matching round. The determination method can be expressed as follows:

[0076] Where m∈{1,2,3,...,M} and n∈{1,2,3,...,N} represent the sets of electricity buyers and sellers, respectively. and Represent the time-of-use electricity price and on-grid electricity price respectively, π m and π n Represents the prosumer's quotation information. The closer the two are to the contract price, the greater the profit the prosumer makes. * Indicates the best bid in the current matching round;

[0077] 2-3) Calculate the additional transmission fee and network cost for the winning bidder * for any n energy matches. For example, the calculation method is as follows:

[0078] Where, They represent the transmission fee and network loss fee that should be paid for energy matching between the prosumers at two nodes a and b, They represent the additional transmission fee and network loss fee for energy matching between the prosumers at two nodes a and b, represents the active power sold by node a prosumer to node b prosumer, and 0.5 indicates that the additional cost is borne by both matching parties;

[0079] The distribution network power flow sensitivity factor can be expressed as follows,

[0080] Ignoring the conductivity of the distribution line to the ground, the matrix form of equations (80) and (81) can be expressed as follows:

[0081] Delete the rows and columns where the coefficient matrix balance node of formula (84) is located, and calculate the inverse matrix of formula (84):

[0082] Where K, L, M, and N are (N-1)-order matrices. The rows and columns where the balance nodes are located are padded with 0 elements, so K, L, M, and N are n-order matrices, and N represents the number of nodes in the distribution system.

[0083] The energy matching between different producers and consumers affects the injected power of each node in the distribution network, which in turn affects the node voltage and line power of the distribution network. The power flow sensitivity factor based on the injected power of the distribution network node is derived as follows:

[0084] 1. Voltage sensitivity factor

[0085] Voltage sensitivity is defined as the voltage at each node V i Inject power P into the node δ , Q δ The partial derivative of . Specifically, it can be expressed as follows,

[0086] Where, They represent the sensitivity of node voltage amplitude and phase angle to active and reactive power injected into the node, respectively.

[0087] 2. Line flow sensitivity factor

[0088] Line power flow sensitivity is defined as line power flow P ij , Q ij Inject power P into the node δ , Q δ Combined with equations (82)(86)(88), the sensitivity of the line active power flow to the node injected active power can be expressed as follows:

[0089] Similarly, the power flow sensitivity factors of the remaining lines can be expressed as follows,

[0090] Where, They represent the line power flow P ij , Q ij Inject power P into the node δ , Q δsensitivity.

[0091] 3. Network loss sensitivity factor

[0092] The network loss sensitivity is defined as the system network loss P loss , Q loss Inject power P into the node δ , Q δ The partial derivative of . Specifically, it can be expressed as follows,

[0093] Similarly, the remaining network loss sensitivity factors can be expressed as follows,

[0094] Where, Represents the active and reactive losses of the entire distribution system P loss , Q loss Inject power P to each node δ , Q δ The sensitivity, r ij 、x ij They represent the resistance and reactance of line ij respectively.

[0095] Obviously, the sensitivity of each line loss to the injected power of each node can be expressed as follows:

[0096] Where, Represent the active and reactive losses of line ij respectively Inject power P to each node δ , Q δ sensitivity.

[0097] The line flow sensitivity factor quantifies the change in line flow caused by the unit of electrical energy injected or outflowed from the node. The calculation method of the transmission fee based on the line flow sensitivity factor can be expressed as follows:

[0098] Where, represents the transmission fee that should be paid for energy matching between prosumers located at two nodes a and b; p , σ q Respectively represent the active and reactive power transmission rates of unit power distribution resources; They represent the occupancy of the distribution line capacity by the unit active and reactive power transmitted between nodes a and b, They represent the active and reactive power sold by the prosumer at node a to the prosumer at node b respectively.

[0099] in, The calculation method can be expressed as follows:

[0100] Similarly, the calculation method of network loss cost can be expressed as follows,

[0101] Where, It represents the network loss fee that should be paid for energy matching between prosumers located at two nodes a and b; Respectively represent the compensation costs for unit active and reactive network losses; They represent the network losses caused by the transmission of unit active and reactive power between nodes a and b respectively.

[0102] in, The calculation method can be expressed as follows:

[0103] In the formula, the coefficient of 0.5 indicates that the network loss calculated by the approximate method of formulas (94)-(101) is twice the actual network loss, so it is compensated.

[0104] Assuming that each producer or consumer produces or consumes electricity at a fixed power factor, reactive power is considered a by-product of active energy matching. Producers and consumers do not quote reactive power. The cost per kilowatt-hour of network transmission fees and network losses can be calculated as follows:

[0105] In the formula, 0.5 means that the additional cost is borne by both parties. and After calculating the bidding information of all potential matching objects, if the adjusted price does not cause losses to both matching parties, that is, when the adjusted price is between the time-of-use electricity price and the on-grid electricity price, the two parties will complete energy matching.

[0106] 2-4) For electricity sellers, the price is adjusted according to the Sort from low to high to form a list of electricity sellers to be matched. The case where * represents the electricity seller is similar and will not be repeated.

[0107] 2-5) Starting from the first table of the list to be matched, traverse the above list in order. For the current traversal object, if it satisfies Then the producer and consumer* matches the order with the current traversal object, records the matching result, and updates all waiting-for-matching lists according to the matching result. Otherwise, the current traversal object is removed from the waiting-for-matching list of the current round.

[0108] 2-6) Repeat steps 2-5). If no electricity seller can match *, *'s bid fails and * is moved from the pending matching list to the minimum and maximum guaranteed list or energy resale list according to the bidding mode.

[0109] 2-7) Repeat steps 2-2) to 2-6) until max(π m )<min(π n ) to form the energy bidding matching result.

[0110] Furthermore, the matching step further includes the following steps:

[0111] 2-8) The present invention adopts a network loss sensitivity iterative correction method. In each iteration process, it is considered that the distribution network line flow P ij , Q ij and each node voltage V i As a given value, the network loss additional cost is calculated based on this to perform energy matching. Then, based on the matching result, P ij , Q ij With V i Make corrections and update the corresponding distribution network flow distribution and ν represents the current iteration number, and the above process is repeated until convergence. When ν = 0, in order to reduce the algorithm error and improve the convergence performance, the matching algorithm is calculated by only considering the network fee and ignoring the network loss. and As the initial value of network loss sensitivity.

[0112] As the number of prosumers increases, the model scale becomes larger. The above iterative method may be difficult to ensure convergence within the required time. Considering that the network loss has little impact on the power flow results, and the network loss fee of the mechanism is only used as a price signal to guide each prosumer to match energy nearby. In order to ensure the solution speed, the present invention also sets the maximum number of iterations ν max As the criterion for the termination of iteration, it is considered that the modified ν max The matching result after subtracting the network loss coefficient can already meet the actual needs;

[0113] Since the network loss caused by energy matching depends on the power flow distribution, which is unknown before the energy matching is completed, the corresponding distribution network power flow distribution is updated based on the energy bidding matching results. and ν represents the current iteration number; when ν = 0, the power flow distribution is calculated by ignoring the network loss and only taking into account the energy bidding matching results of the network fee. The calculation of the power flow distribution is expressed as follows: i =∑ j G ij Vj -∑ j B′ ij θ j Q i =-∑ j B ij V j -∑ j G′ ij θ j P ij =g ij (V i -V j )-b ij (θ i -θ j ) Q ij =-b ij (V i -V j )-g ij (θ i -θ j )

[0114] Where i and j represent the first and last nodes of the distribution line, P i , Q i 、P ij , Q ij They represent the net injection of node i and the active and reactive power of line ij, respectively. i ,θ i Respectively represent the voltage amplitude and phase angle of node i; Y ij =G ij +jB ij represents the node admittance matrix element. The superscript prime indicates that the node admittance matrix element value corresponding to the parallel branch to the ground is ignored. g ij +jb ij represents the admittance of the distribution line ij;

[0115] The energy bidding matching is completed, and the νth energy bidding matching result is the final result. Otherwise, ν=ν+1, and go to step 2-1) to continue iteration.

[0116] Furthermore, the settlement steps specifically include: π mn =0.5*(π m +π n )

[0117] Where, π mn With P mn Denote the transaction price and power of prosumers m and n respectively, C m 、C nand C DSO represent m, n and the expenditure costs of the distribution network operator respectively.

[0118] Furthermore, the objective function of the congestion management model is as follows,

[0119] Where C M represents the congestion management cost of the distribution network operator, μ g P represents the declared compensation price for the unit of electricity regulated by the producer / consumer g in the distribution network, g represents the actual regulation capacity of the producer / consumer g, Q h With μ h They represent the power generated by the reactive power compensation device in the distribution network and the additional unit cost caused by its deployment. The third item represents the network loss cost of the distribution network.

[0120] The constraints of the congestion management model include, among which, P g , Q h The following constraints should be met:

[0121] Where, represents the maximum flexibility available to prosumers participating in congestion management, Indicates the output limit of the reactive power compensation device owned by the distribution network operator;

[0122] Using the virtual node demand model, a load power of 0.5 times the line network loss is simulated at the nodes at both ends, so that the line can be considered as a lossless line; the network loss of each line is expressed as follows:

[0123] Where, Represent the active and reactive losses of line ij respectively Inject power P to each node δ , Q δ sensitivity;

[0124] The network loss correction power and line flow of each node based on the virtual node demand model are expressed as follows:

[0125] Where P′ i , Q′ i , P′ ij , Q′ ij They represent the corrected active and reactive power of each node and line after considering the compensation of the virtual node demand model, They represent the line power flow Pij , Q ij Inject power P into the node δ , Q δ sensitivity;

[0126] The power flow constraints that the congestion management model needs to satisfy are expressed as follows, ∑ i P′ i =0∑ i Q′ i =0

[0127] Where 1 is a unit vector, and its dimension is the same as the number of system nodes.

[0128] Further improvements to the efficiency of solving the congestion management model include:

[0129] To improve the efficiency of the model solution, the following formula can be used to replace the linear constraint corresponding to the regular polygon in the power circle: The power circle is approximately replaced by an inscribed regular L-gon, where L is an even number and the corresponding central angle is θ. The specific expression is as follows:

[0130] Where k l 、b l Represents the slope and longitudinal intercept of the straight line corresponding to the lth side of the inscribed regular L-gon.

[0131] Furthermore, the bidding model specifically includes:

[0132] Minimum and maximum cap model: During the energy matching phase, all bidders that fail to match the bid will obtain / sell electricity directly from the distribution network operator at the contract electricity price, time-of-use electricity price and grid electricity price;

[0133] Energy resale model: In the energy matching stage, all bids that fail to match will be transferred to participate in the congestion management of the distribution network operator at a new bidding price, thereby obtaining new scheduling opportunities.

[0134] Another embodiment of the present invention provides a distribution network economic dispatch system based on congestion decoupling management, the system including the following modules:

[0135] An information receiving module is used to receive bidding information submitted by each producer and consumer, including bidding requirements, bidding prices and bidding modes;

[0136] A matching module is used to match energy bids using the bidding information submitted by each producer and consumer;

[0137] Settlement module, used to settle the results of energy bidding and matching;

[0138] A model management module is used to perform congestion management based on a preset congestion management model, where the congestion management model is established by settling the results of energy bidding and matching;

[0139] The model solving module is used to solve the congestion management model and complete the optimized economic dispatch of the distribution network under the market environment.

[0140] The embodiments of the present application can be provided as methods or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code. The scheme in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming language Java and translated scripting language JavaScript, etc.

[0141] The present application is described with reference to the flow chart and / or block diagram of the method, device (system), and computer program product according to the embodiment of the present application. It should be understood that each flow process and / or box in the flow chart and / or block diagram and the combination of the flow process and / or box in the flow chart and / or block diagram can be realized by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processing machine or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device produce a device for realizing the function specified in one flow chart flow or multiple flows and / or one box or multiple boxes of the block diagram.

[0142] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce a product including an instruction device that implements the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0143] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in one or more processes in the flowchart and / or one or more boxes in the block diagram.

[0144] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply the existence of any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article, or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or device. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, method, article, or device comprising the element.

Claims

1. A distribution network economic dispatching method based on congestion decoupling management, characterized in that: The following steps are involved: An information receiving step, receiving bidding information submitted by each producer and consumer, wherein the bidding information includes bidding requirements, bidding prices and bidding modes; The matching step is to match the energy bidding through the bidding information submitted by each producer and consumer; Settlement step, settling the results of energy bidding and matching; A model management step, performing congestion management based on a preset congestion management model, wherein the congestion management model is established by settling the results of energy bidding matching; Model solving steps, solve the congestion management model, and complete the optimal economic dispatch of the distribution network under the market environment.

2. The method for economic dispatching of distribution network based on blocking decoupling management according to claim 1, characterized in that: The matching step specifically includes the following steps: 2-1) Sort the buyer and seller producers and consumers according to the bidding prices from high to low and from low to high respectively; 2-2) Determine the winner of the current matching round*. The determination method can be expressed as follows: In the formula, m∈{1,2,3,...,M} and n∈{1,2,3,...,N} represent the sets of electricity buyers and sellers, respectively. and Respectively represent the time-of-use electricity price and the on-grid electricity price, π m With π n Represents the quotation information of the producer and consumer. The closer the two are to the contract price, the more profit the producer and consumer will make. * Indicates the best bid in the current matching round; 2-3) Calculate the additional grid-connection fee and network cost for the winning bidder * and any n energy matching. The calculation method is as follows, taking * as the electricity buyer as an example: In the formula, They represent the network transmission fee and network loss fee that should be paid for energy matching between the prosumers at two nodes a and b, respectively. They represent the additional transmission fee and network loss fee for energy matching between producers and consumers at two nodes a and b, respectively. Indicates that node a prosumer sells to node b prosumer The active power output, 0.5 means the additional cost is borne by both matching parties; 2-4) Collectively charge the electricity sellers a revised price Sort from low to high to form a list of electricity sellers to be matched; 2-5) Starting from the head of the list to be matched, traverse the above list in order. For the current traversal object, if it satisfies Then the producer and consumer* matches the order with the current traversal object, records the matching result, and updates all waiting-to-match lists according to the matching result. Otherwise, the current traversal object is removed from the waiting-to-match list of the current round. 2-6) Repeat step 2-5). If there is no electricity seller that can match with *, *'s bidding fails, and * is moved from the waiting list to the minimum and maximum list or energy resale list according to the bidding mode; 2-7) Repeat steps 2-2) to 2-6) until max(π m )<min(π n ) to form the energy bidding matching result.

3. The method for economic dispatching of distribution network based on blocking decoupling management according to claim 2 is characterized in that: The matching step further comprises the following steps: 2-8) Since the network loss caused by energy matching depends on the power flow distribution, which is unknown before the energy matching is completed; based on the energy bidding matching results, update the corresponding distribution network power flow distribution With V i (ν+1) , ν represents the current iteration number; when ν = 0, the power flow distribution is calculated by ignoring the network loss and only taking into account the network fee. The calculation of the power flow distribution is expressed as follows: P.S i (∑) j G ij V j -∑ j B′ ij θ j Q i =-∑ j B ij V j -∑ j G′ ij θ j P ij =g ij (V i -V j )-b ij (i i -θ j ) Q ij =-b ij (V i -V j )-g ij (i i -θ j ) In the formula, i and j represent the first and last nodes of the distribution line, P i , Q i , P ij , Q ij They represent the net injection of node i and the active and reactive power of line ij, respectively, V i ,θ i Respectively represent the voltage amplitude and phase angle of node i; Y ij =G ij +jB ij represents the node admittance matrix element. The superscript prime indicates that the node admittance matrix element value corresponding to the parallel branch to the ground is ignored. ij +jb ij represents the admittance of the distribution line ij; 2-9) If The energy bidding matching is completed, and the result of the νth energy bidding matching is the final result, otherwise ν=ν+1, and go to step 2-1) to continue the iteration.

4. The method for economic dispatching of distribution network based on blocking decoupling management according to claim 3 is characterized by: The settlement steps specifically include: mn =0.5*(π m +π n ) In the formula, π mn With P mn denote the transaction price and power of prosumers m and n respectively, C m , C n and C DSO Represent m, n and the expenditure cost of the distribution network operator respectively.

5. The method for economic dispatching of distribution network based on blocking decoupling management according to claim 4 is characterized in that: The objective function of the congestion management model is as follows: In the formula, C M represents the congestion management cost of the distribution network operator, μ g P represents the declared compensation price for the unit of electric energy regulated by the producer / consumer g in the distribution network, g represents the actual regulation capacity of producer-consumer g, Q h With μ h They represent the power generated by the reactive power compensation device in the distribution network and the additional unit cost caused by its call. The third item represents the network loss cost of the distribution network. The constraints of the congestion management model include, among which, P g , Q h The following constraints should be met: In the formula, represents the maximum flexibility that can be provided to prosumers participating in congestion management, Indicates the output limit of the reactive power compensation device owned by the distribution network operator; The virtual node demand model is used to simulate the load power of 0.5 times the line network loss at the two end nodes. The line can be considered as a lossless line; the network loss of each line is expressed as follows: In the formula, Respectively represent the active and reactive losses of line ij Inject power P to each node δ , Q δ Sensitivity; The network loss corrected power and line flow of each node based on the virtual node demand model are expressed as follows: Where P i ', Q′ i , P′ ij , Q′ ij They represent the corrected active and reactive power of each node and line after considering the compensation of the virtual node demand model, They represent the line power flow P ij , Q ij Inject power P into the node δ , Q δ Sensitivity; Then the power flow constraints that the congestion management model needs to satisfy are expressed as follows: ∑ i P i '＝0 ∑ i Q′ i ＝0 In the formula, 1 is a unit vector, and its dimension is consistent with the number of system nodes.

6. A distribution network economic dispatching method based on blocking decoupling management according to claim 5, characterized in that: The improvement of the efficiency of solving the blocking management model includes: The power circle is approximately replaced by an inscribed regular L-gon, where L is an even number and the corresponding central angle is θ. It is expressed as follows, In the formula, k l 、b l Represents the slope and y-intercept of the straight line corresponding to the lth side of an inscribed regular L-gon.

7. A distribution network economic dispatching method based on blocking decoupling management according to claim 1, characterized in that: The bidding model specifically includes: Minimum guaranteed and maximum capped mode: In the energy matching stage, all bidders that fail to match will obtain / sell electricity directly from the distribution network operator at the contract electricity price, time-of-use electricity price and grid-connected electricity price; Energy resale model: In the energy matching stage, all failed bids will be transferred to participate in the congestion management of the distribution network operator at a new bidding price, thereby obtaining new scheduling opportunities.

8. A distribution network economic dispatching system based on blocking decoupling management, characterized in that: The system includes the following modules: An information receiving module, used to receive bidding information submitted by each producer and consumer, wherein the bidding information includes bidding requirements, bidding prices and bidding modes; A matching module, used for matching energy bids through bidding information submitted by various prosumers; Settlement module, used to settle the results of energy bidding and matching; A model management module, used for performing congestion management based on a preset congestion management model, wherein the congestion management model is established by settling energy bidding matching results; The model solving module is used to solve the congestion management model and complete the optimal economic dispatch of the distribution network under the market environment.

9. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions which, when executed by a computing device, cause the computing device to perform any one of the methods according to claims 1-7.

10. A computing device, characterized in that include: One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include instructions for executing any of the methods according to claims 1-7.

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