A method and device for coordinating transmission side operation loss and transmission and distribution boundary power

Abstract

The application provides a power transmission side operation loss and power transmission and distribution boundary power coordination method and device, and relates to the technical field of power system operation and control. The method comprises the following steps: defining the loss in the power transmission side operation as conventional unit power generation loss, reserved standby loss and dynamic line expansion loss, and constructing a target function of the power transmission side operation loss; establishing a direct current flow constraint of the power transmission side operation loss; establishing a boundary power consistency constraint of the power transmission side and the power distribution side, constructing an optimization target function of the power transmission side and the power distribution side, and taking the optimization target function as an iteration basis to gradually approach the boundary power of the power transmission side and the power distribution side by means of a decoupling method and an iteration coordination mechanism, minimize the power transmission side operation loss, and realize power transmission side energy market clearing optimization. The application effectively balances the complexity of centralized optimization and the dispersion of distributed optimization, is helpful for better minimizing the power transmission side operation loss, and enables the collaborative optimization of the power transmission side and the power distribution side to be further deepened.

Description

Technical Field

[0001] This invention relates to the field of power system operation and control technology, specifically to a method and apparatus for coordinating transmission-side operating losses and transmission-distribution boundary power. Background Technology

[0002] In the current power system architecture, the operation of the transmission and distribution sides is gradually becoming the focus of industry attention. The transmission side plays a crucial role in large-scale power transmission and system dispatch, while the distribution side focuses on supplying power to end users and providing high-quality power services. With the deepening opening of the power market, competition has been fully integrated into market operations, making the coordinated optimization of the transmission and distribution sides particularly critical. This not only requires ensuring the security, stability, and efficiency of power transmission, but also achieving the scientific and rational allocation of power resources to meet the diverse needs of different market participants in areas such as power trading, supply and demand, and operational loss control.

[0003] In recent years, the rapid popularization of electric vehicles and the continuous innovation of virtual power plant technology have led to the emergence of electric vehicle virtual power plants (EVVs) as a new type of electricity market player. By integrating the battery resources of a large number of electric vehicles, EVVs construct massive energy storage systems and deeply participate in the dispatch and trading of electricity. This innovation has not only brought new vitality to the electricity market but has also triggered a series of new challenges. For example, the security and stability of power grid operation are impacted, and coordination between distributed energy resources and centralized power grids is required. Therefore, in the process of collaborative optimization of the transmission and distribution energy market, how to fully consider the profound impact of the bidding strategy of EVVs on the clearing results of the transmission-side energy market has become an important topic that urgently needs in-depth discussion and research.

[0004] Current research often employs centralized optimization methods, integrating the optimization problems of the transmission and distribution sides into a unified model for solution. While this method can achieve global optimum, it faces challenges in practical applications, including high computational complexity, large data requirements, and long solution times. Some studies have proposed distributed optimization methods, which decompose a large problem into multiple smaller problems for separate solving, and then achieve global optimization through iterative coordination. This method reduces computational complexity to some extent, but suffers from slow convergence or even non-convergence. In large-scale power systems, as the number of devices connected to the power system increases, the requirements for the model also rise to ensure the system's response speed. Given the continuous expansion of installed capacity, ensuring the coordination between the power market clearing models of the transmission and distribution sides, while allowing them to be solved independently to some extent, is undoubtedly beneficial to the response characteristics of the power system. Summary of the Invention

[0005] The purpose of this invention is to provide a method and apparatus for coordinating transmission-side operating losses and transmission-distribution boundary power, which is used to solve how to achieve coordinated optimization of the transmission side and the distribution side and minimize transmission-side operating losses. Existing optimization methods have problems such as high computational complexity and difficulty in solving. This invention can achieve coordinated optimization of the transmission side and the distribution side and minimize transmission-side operating losses, and the calculation process is simple and easy to solve.

[0006] To achieve the above objectives, in a first aspect, the present invention provides a method for coordinating transmission-side operating losses and transmission-distribution boundary power, comprising:

[0007] The losses in transmission-side operation are defined as conventional unit generation losses, reserved reserve losses, and dynamic line expansion losses, and an objective function for transmission-side operation losses is constructed.

[0008] Establish DC power flow constraints for transmission-side operating losses;

[0009] Establish boundary power consistency constraints between the distribution side and the transmission side, construct optimization objective functions for the transmission side and the distribution side, and use them as the basis for iteration. Through decoupling methods and iterative coordination mechanisms, the boundary power of the transmission side and the distribution side gradually approach each other, minimize the operating loss of the transmission side, and achieve coordination between the operating loss of the transmission side and the boundary power of the transmission and distribution, that is, the optimization of the power market clearing of the transmission side.

[0010] According to the method for coordinating transmission-side operating losses and transmission-distribution boundary power provided by the present invention, the calculation formulas for conventional unit generation losses, reserved reserve losses, and dynamic line expansion losses are as follows:

[0011] (1)

[0012] (2)

[0013] (3)

[0014] in, For conventional unit power generation losses, For conventional units In time period of efforts, These are the fitting parameters; To reserve for backup losses, and They are conventional units In time period Reserve loss coefficients for upward and downward reserves; and They are conventional units In time period Provided upward and downward backup; All are coefficients; For dynamic line capacity expansion losses; The dynamic expansion factor represents the line capacity. In time period The capacity adjustment ratio; For the line The basic maximum transmission capacity; For the line In time period The actual transmission power; This represents the marginal loss coefficient for capacity expansion. For the line The load rate maintenance loss coefficient.

[0015] According to the present invention, a method for coordinating transmission-side operating losses and transmission-distribution boundary power is provided, wherein the objective function for transmission-side operating losses is:

[0016] (4)

[0017] In the formula, This represents the total number of time periods. This refers to the number of conventional generating units on the transmission side. This represents the number of lines on the transmission side.

[0018] According to the present invention, a method for coordinating transmission-side operating losses and transmission-distribution boundary power is provided, wherein the DC power flow constraints on transmission-side operating losses include:

[0019] (5)

[0020] (6)

[0021] (7)

[0022] (8)

[0023] (9)

[0024] (10)

[0025] (11)

[0026] (12)

[0027] in, This represents the boundary power on the transmission side. For access nodes A collection of conventional generating units, For nodes The set of connected transport boundaries, Ni Let i be the set of nodes directly connected to node i. For nodes The load demand, For the line The susceptance between them For nodes Voltage phase angle, For nodes Voltage phase angle, The set of all nodes; These are the lower and upper limits of output for conventional generating units, respectively. These are the lower and upper limits of the output ramp-up for conventional generating units, respectively. For conventional units In time period contribution; and They are conventional units The provided maximum upward and downward reserve values; These are the minimum and maximum values ​​of the dynamic expansion coefficient, respectively. For the line nodes The limit value of active power transmitted between them.

[0028] According to the present invention, a method for coordinating transmission-side operating losses and transmission-distribution boundary power is provided, wherein the boundary power consistency constraint between the distribution side and the transmission side is as follows:

[0029] (13)

[0030] In the formula, This refers to the boundary power on the distribution side. It is the set of all distribution boundaries.

[0031] According to the method for coordinating transmission-side operating losses and transmission-distribution boundary power provided by the present invention, the optimization objective function on the transmission side is:

[0032] (14)

[0033] The optimization objective function for the distribution side is:

[0034] (15)

[0035] in,

[0036] (16)

[0037] (17)

[0038] (18)

[0039] (19)

[0040] In the formula, and These represent the charging power and discharging power of charging station n, respectively. For the number of charging stations, N dist For the set of nodes on the distribution side, The day-ahead clearing marginal price for the node where charging station n is located. This is the penalty coefficient; The transmission and distribution boundary power represents the target value of power exchange between the transmission side and the distribution side at the boundary node k and the time period t. These are dual variables used to coordinate the boundary power consistency between the transmission and distribution sides. This represents the maximum charging power of the charging station. This represents the maximum discharge power of the charging station; when the charging station is in charging mode, , When the charging station is in a discharging state, , ; These are the minimum and maximum daily clearing marginal electricity prices of the node where charging station n is located, respectively.

[0041] According to the present invention, a method for coordinating transmission-side operating losses and transmission-distribution boundary power is provided, wherein the decoupling method is the alternating direction multiplier method.

[0042] The present invention provides a method for coordinating transmission-side operating losses and transmission-distribution boundary power, which, as an iterative basis, uses decoupling methods and iterative coordination mechanisms to gradually bring the boundary power of the transmission side and the distribution side closer together, thereby minimizing transmission-side operating losses. The method includes:

[0043] Set initial values ​​for the transmission and distribution boundary power, dual variables, and penalty coefficients;

[0044] The boundary power of the transmission side and the distribution side is gradually brought closer by a preset iterative formula;

[0045] Calculate the difference between the boundary power on the transmission side and the distribution side. Stop the iteration when the difference is less than a predetermined value, and output the minimum value of the operating loss on the transmission side.

[0046] According to the present invention, a method for coordinating transmission-side operating losses and transmission-distribution boundary power is provided, wherein the preset iterative formula is:

[0047] (20)

[0048] (twenty one)

[0049] (twenty two)

[0050] (twenty three)

[0051] The formula for calculating the difference between the boundary power on the transmission side and the distribution side is:

[0052] (twenty four)

[0053] In the formula, This represents the boundary power on the transmission side after N+1 iterations. This represents the boundary power on the distribution side after N+1 iterations. The power at the transport boundary after N iterations. Let N be the dual variable after N iterations. The transport boundary power after N+1 iterations. Let N+1 be the dual variable. This represents the difference in boundary power between the transmission and distribution sides.

[0054] Secondly, the present invention provides a device for coordinating transmission-side operating losses and transmission-distribution boundary power, comprising:

[0055] The construction unit is used to define the losses in the operation of the transmission side as conventional unit generation losses, reserved reserve losses and dynamic line expansion losses, and to construct the objective function of the transmission side operation losses.

[0056] Establish a unit to establish DC power flow constraints for transmission-side operating losses;

[0057] The optimization unit is used to establish boundary power consistency constraints between the distribution side and the transmission side, construct optimization objective functions for the transmission side and the distribution side, and use them as the basis for iteration. Through decoupling methods and iterative coordination mechanisms, the boundary power of the transmission side and the distribution side gradually approaches each other, minimizing the operating loss of the transmission side.

[0058] The technical solution of the present invention has at least the following technical effects:

[0059] This invention provides a method and apparatus for coordinating transmission-side operating losses and transmission-distribution boundary power. The method includes: defining transmission-side operating losses as conventional unit generation losses, reserved reserve losses, and dynamic line expansion losses; constructing an objective function for transmission-side operating losses; establishing DC power flow constraints for transmission-side operating losses; establishing boundary power consistency constraints between the distribution and transmission sides; constructing optimization objective functions for both the transmission and distribution sides; and using these as iterative bases, employing decoupling methods and iterative coordination mechanisms to gradually bring the boundary power of the transmission and distribution sides closer together, minimizing transmission-side operating losses, and achieving coordination between transmission-side operating losses and transmission-distribution boundary power. This invention effectively balances the complexity of centralized optimization and the dispersion of distributed optimization, helping to better minimize transmission-side operating losses and allowing for deeper collaborative optimization between the transmission and distribution sides. It can achieve collaborative optimization between the transmission and distribution sides and minimize transmission-side operating losses, and the calculation process is simple and easy to solve. Attached Figure Description

[0060] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this invention. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0061] In the attached diagram:

[0062] Figure 1 This is a graph showing the variation of the boundary power difference between the transmission side and the distribution side, obtained by the alternating direction multiplier method of this invention.

[0063] Figure 2 This is a graph showing the change in transmission power of boundary node 1 on the transmission side of the present invention with the number of iterations;

[0064] Figure 3 This is a graph showing the change in transmission power of boundary node 2 on the transmission side of the present invention with the number of iterations;

[0065] Figure 4 This is a graph showing the change in transmission power of boundary node 1 on the power distribution side of the present invention with the number of iterations;

[0066] Figure 5 This is a graph showing the change in transmission power of boundary node 2 on the power distribution side of the present invention with the number of iterations;

[0067] Figure 6 This is a flowchart of the method for coordinating transmission-side operating losses and transmission-distribution boundary power according to the present invention. Detailed Implementation

[0068] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. All other embodiments obtained by those skilled in the art based on the embodiments of this invention without creative effort are within the scope of protection of this invention.

[0069] The following detailed description of some embodiments of the present invention will be provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0070] This invention combines the advantages of centralized and distributed optimization, introducing a hybrid collaborative optimization method that integrates decoupling and iterative coordination mechanisms. By setting boundary power consistency constraints, it can decompose the electricity price optimization problem on the transmission and distribution sides into independent sub-problems for separate solving. Specifically, the transmission network operator (TSO, i.e., the transmission side) uses conventional generating units, system reserve capacity, dynamic line expansion losses, and boundary exchange power with the distribution network operator (DSO, i.e., the distribution side) as decision variables. It clears the transmission-side electricity market by receiving bid information from various market participants to minimize total transmission-side operating losses. Then, the TSO sends the optimized cleared LMP (Learning Marginal Price) at the transmission-distribution boundary node to the DSO as the price at which the DSO purchases power from the TSO. This method effectively balances the complexity of centralized optimization and the dispersion of distributed optimization, helping to better minimize transmission-side operating losses and allowing for deeper collaborative optimization between the transmission and distribution sides. Meanwhile, in order to simplify the calculation while ensuring the accuracy of the model, based on the fact that the reactance of the high-voltage transmission network side circuit is much greater than the resistance, the resistance of the transmission line and its influence such as network loss are ignored in the calculation. The DC power flow model is directly used to constrain the power flow state. This is reasonable under the premise of minimizing system operating losses and solving quickly. It can improve the response speed of the model while keeping the error within a controllable range.

[0071] Please see Figure 6 This invention provides a method for coordinating transmission-side operating losses and transmission-distribution boundary power, comprising:

[0072] Step 1: Define the losses in operation on the transmission side as conventional unit generation losses, reserved reserve losses, and dynamic line expansion losses, and construct the objective function for transmission side operation losses.

[0073] The formulas for calculating conventional unit power generation losses, reserved reserve losses, and dynamic line expansion losses are as follows:

[0074] (1)

[0075] (2)

[0076] (3)

[0077] Equation (1) represents the generation loss of a conventional generating unit using an exponential function to simulate increasing marginal losses. For conventional units In time period of efforts, For the fitting parameters: The magnitude of the exponential term determines its influence; a larger exponential term indicates a greater influence. This will make the loss function grow more steeply; The rate used to control exponential growth must meet the following conditions. To maintain the characteristics of increasing loss; Represents fixed or linear losses, ensuring basic losses exist even under low loads. Equation (2) represents nonlinear reserved reserve capacity losses. and They are conventional units In time period Reserve loss coefficients for upward and downward reserves; and They are conventional units In time period Provided upward and downward reserves; coefficients It needs to be greater than 1 to reflect the increasing marginal loss characteristics of reserve capacity, and needs to be determined according to the actual situation. (3) Equation is the dynamic line expansion loss. It is the marginal loss term for capacity expansion. The dynamic expansion factor represents the line capacity. In time period The capacity adjustment ratio (e.g., (This indicates a 10% capacity expansion). For the line The basic maximum transmission capacity; For the line In time period The actual transmission power; The marginal loss coefficient for capacity expansion represents the cost of expanding capacity per unit. For load factor related loss items, For the line The load factor loss coefficient is determined by separating capacity expansion loss from load factor loss, ensuring that all terms are non-negative.

[0078] The objective function for transmission-side operating losses is:

[0079] (4)

[0080] In the formula, This represents the total number of time periods. This refers to the number of conventional generating units on the transmission side. Let be the number of lines in the transmission side. By solving equation (4), the minimum loss required for transmission side operation can be obtained without considering interaction with the distribution side for the time being. By integrating the above loss terms, an objective function for transmission side operation loss is constructed, with the goal of minimizing operation loss, providing an economic model basis for subsequent optimization.

[0081] Step 2: Establish DC power flow constraints for transmission-side operating losses;

[0082] Based on the parameters given in step 1, the DC power flow constraint is established as follows:

[0083] (5)

[0084] (6)

[0085] (7)

[0086] (8)

[0087] (9)

[0088] (10)

[0089] (11)

[0090] (12)

[0091] Equation (5) is the node power balance equation, which ensures that power generation, transmission and load demand are matched. This represents the boundary power on the transmission side. For access nodes A collection of conventional generating units, For nodes The set of connected transport boundaries, N i Let i be the set of nodes directly connected to node i. For nodes The load demand, For the line The susceptance between them For nodes Voltage phase angle, For nodes Voltage phase angle, This is the set of all nodes. It should be noted that... Includes all lines In step 1, the method used is... This parameter represents a line; here, nodes i and j are used to represent a line. Since node power is used here, but the line... and lines They are essentially the same.

[0092] Equations (6) and (7) are constraints on the operation of conventional generating units, where equation (6) is the upper and lower limit constraint on the unit's output, and equation (7) is the limit on the unit's output ramp-up. Equations (8) and (9) are constraints on reserve capacity, where equation (8) is the upper limit on reserve capacity, and equation (9) is the lower limit on reserve capacity. Equation (10) is a constraint on the dynamic expansion coefficient. By limiting the expansion range, excessive adjustments can be prevented from causing equipment overload or resource waste. Equation (11) is a constraint on the actual transmission power of the line. Equation (12) is a constraint on the transmission power of the line, which controls the active power transmitted by each line within a certain range. These are the lower and upper limits of output for conventional generating units, respectively. These are the lower and upper limits of the output ramp-up for conventional generating units, respectively. For conventional units In time period contribution; and They are conventional units The provided maximum upward and downward reserve values; These are the minimum and maximum values ​​of the dynamic expansion coefficient, respectively. For the line nodes The limit value of active power transmitted between them.

[0093] The calculation is simplified by using a DC power flow model (ignoring resistance), ensuring that the optimized model conforms to the actual power grid operation rules and setting physical constraints for power system operation.

[0094] Step 3: Establish boundary power consistency constraints between the distribution side and the transmission side, construct optimization objective functions for the transmission side and the distribution side, and use them as the basis for iteration. Through decoupling methods and iterative coordination mechanisms, the boundary power of the transmission side and the distribution side gradually approach each other, minimizing the transmission side operating loss and achieving coordination between the transmission side operating loss and the transmission and distribution boundary power, i.e., the optimization of the power market clearing on the transmission side.

[0095] Specifically, the boundary power consistency constraints between the distribution side and the transmission side are as follows:

[0096] (13)

[0097] In the formula, This refers to the boundary power on the distribution side. It is the set of all distribution boundaries.

[0098] After decoupling the transmission and distribution sides so that they can be solved independently, the alternating direction multiplier method is used, and the boundary power is continuously updated through an iterative coordination mechanism until the required convergence is achieved.

[0099] The optimization objective function on the transmission side is:

[0100] (14)

[0101] The optimization objective function for the distribution side is:

[0102] (15)

[0103] in,

[0104] (16)

[0105] (17)

[0106] (18)

[0107] (19)

[0108] In the formula, and For the charging power and discharging power of charging station n, For the number of charging stations, N dist For the set of nodes on the distribution side, The day-ahead clearing marginal price for the node where charging station n is located. This is the penalty coefficient; The transmission and distribution boundary power represents the target value of power exchange between the transmission side and the distribution side at the boundary node k and the time period t. These are dual variables used to coordinate the boundary power consistency between the transmission and distribution sides. This represents the maximum charging power of the charging station. This represents the maximum discharge power of the charging station; when the charging station is in charging mode, , When the charging station is in a discharging state, , ; These are the minimum and maximum daily clearing marginal electricity prices of the node where charging station n is located, respectively.

[0109] Equations (14) and (15) are the objective functions for optimizing TSO and DSO after considering the boundary exchange power between TSO and DSO. Equations (16), (17), (18), and (19) are the constraints on these variables, where... and To represent whether a charging station is charging or discharging, a 0-1 variable is used to ensure that the same charging station does not charge or discharge simultaneously.

[0110] In some embodiments, step 3, using decoupling methods and iterative coordination mechanisms as the basis for iteration, gradually brings the boundary power of the transmission side and the distribution side closer together, minimizing the transmission side operating losses, including:

[0111] Set initial values ​​for the transmission and distribution boundary power, dual variables, and penalty coefficients;

[0112] The boundary power of the transmission side and the distribution side is gradually brought closer by a preset iterative formula;

[0113] Calculate the difference between the boundary power of the transmission side and the distribution side. Stop the iteration when the difference is less than a predetermined value, and output the minimum value of the operating loss of the transmission side.

[0114] The preset iterative formula is:

[0115] (20)

[0116] (twenty one)

[0117] (twenty two)

[0118] (twenty three)

[0119] The formula for calculating the difference between the boundary power on the transmission side and the distribution side is:

[0120] (twenty four)

[0121] In the formula, This represents the boundary power on the transmission side after N+1 iterations. This represents the boundary power on the distribution side after N+1 iterations. The power at the transport boundary after N iterations. Let N be the dual variable after N iterations. The transport boundary power after N+1 iterations. Let N+1 be the dual variable. This represents the difference in boundary power between the transmission and distribution sides.

[0122] Equations (20), (21), (22), and (23) are iterative formulas. First, initial shared variables are set. Dual variables Penalty coefficient Then, through iteration, the boundary power of the transmission side and the distribution side can be gradually made closer. Equation (24) is used to calculate the difference between the two. If the value is less than a predetermined value, the iteration will stop and the optimized value will be output. and Both TSO and DSO include a quadratic penalty term for the bias of shared variables in their optimization objectives, ensuring that the global optimum is gradually approached during the iteration process.

[0123] By establishing boundary power consistency constraints, the exchange power between the transmission and distribution sides at boundary node k is forced to be equal. The Alternating Direction Multiplier Method (ADMM) is used to decompose the optimization problems of the transmission and distribution sides into independent subproblems (Equations 14 and 15), which are solved separately. The boundary power is iteratively updated (Equation 23) to coordinate the optimization results of both sides until convergence (Equation 24). A penalty term is introduced. ) and dual variables ( This ensures that the boundary power gradually approaches consistency.

[0124] It should be noted that the loss function constructed in step 1 (Equation 4) serves as the optimization objective, and the DC power flow constraint added in step 2 (Equation 5) serves as the physical constraint, together constituting the optimization model for the transmission side. The boundary consistency constraint in step 3 (Equation 13) links the optimization problems of the transmission and distribution sides, ensuring that the transmission and distribution sides are coordinated and consistent in terms of boundary power. Furthermore, step 3 decomposes the global optimization into independent sub-problems of the transmission and distribution sides through ADMM (steps 1 and 2 provide the objective function and constraints for them), and uses an iterative mechanism (Equations 20-24) to achieve distributed computing, avoiding the high complexity of centralized optimization. The DC power flow model in step 2 simplifies the calculation, and the decomposition method in step 3 reduces the solution scale. The combination of the two improves the calculation speed while ensuring the accuracy of the model, adapting to the real-time needs of large-scale power systems. Steps 1 to 3 form a closed loop: step 1 defines the economic objective, step 2 adds physical constraints, and step 3 achieves global optimization through boundary coordination, ultimately minimizing the operating losses of the transmission side while ensuring the safety and stability of the power grid.

[0125] Based on the same inventive concept, another embodiment of the present invention provides a device for coordinating transmission-side operating losses and transmission-distribution boundary power. This device corresponds to the method of the aforementioned embodiment and includes:

[0126] The construction unit is used to define the losses in the operation of the transmission side as conventional unit generation losses, reserved reserve losses and dynamic line expansion losses, and to construct the objective function of the transmission side operation losses.

[0127] Establish a unit to establish DC power flow constraints for transmission-side operating losses;

[0128] The optimization unit is used to establish boundary power consistency constraints between the distribution side and the transmission side, construct optimization objective functions for the transmission side and the distribution side, and use them as the basis for iteration. Through decoupling methods and iterative coordination mechanisms, the boundary power of the transmission side and the distribution side gradually approaches each other, minimizing the transmission side operating loss and achieving coordination between the transmission side operating loss and the transmission and distribution boundary power, i.e., the optimization of the power market clearing on the transmission side.

[0129] The following is a specific embodiment of the present invention.

[0130] In this embodiment, there are 5 nodes on both the transmission side and the distribution side, of which 2 nodes are boundary nodes. Boundary node 1 on the transmission side corresponds to boundary node 1 on the distribution side, and boundary node 2 on the transmission side corresponds to boundary node 2 on the distribution side. Two time periods are set: time period 1 and time period 2. The load of each node is different in the two time periods, and the corresponding boundary transmission power is also different.

[0131] Figure 1 This illustrates the changes in the boundary power difference between the transmission and distribution sides as the Alternating Directional Multiplier Method (ADMM) iterates. Figure 2 The diagram shows the change in transmission power of boundary node 1 on the transmission side with the number of iterations. Figure 3 The diagram shows the change in transmission power at boundary node 2 on the transmission side with the number of iterations. Figure 4 The diagram shows the change in transmission power of boundary node 1 on the distribution side with the number of iterations. Figure 5 The variation of transmission power at boundary node 2 on the distribution side with the number of iterations is shown. The iteration process ends when the difference in transmission power between the corresponding boundary nodes on the transmission and distribution sides becomes less than a set value.

[0132] After iteration, the optimized boundary power value is obtained as follows:

[0133] Boundary node 1 has a capacity of 25.893662MW in time period 1 and 33.124933MW in time period 2. Boundary node 2 has a capacity of 24.106324MW in time period 1 and 33.125049MW in time period 2.

[0134] The transmission power at the transmission side boundary is:

[0135] Boundary node 1 has a capacity of 25.893673MW in time period 1 and 33.124945MW in time period 2. Boundary node 2 has a capacity of 24.106327MW in time period 1 and 33.125055MW in time period 2.

[0136] The power transmission power at the distribution side boundary is:

[0137] Boundary node 1 has a capacity of 25.893652MW in time period 1 and 33.124922MW in time period 2. Boundary node 2 has a capacity of 24.106321MW in time period 1 and 33.125042MW in time period 2.

[0138] The final output shows that the transmission and distribution sides continuously update the boundary power through an iterative coordination mechanism until the boundary power gap is reduced and the required convergence level is reached. In this embodiment, the boundary power gap is less than 0.0001MW.

[0139] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. It should be understood that the invention is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A method for coordinating transmission-side operating losses and transmission / distribution boundary power, characterized in that, The application relates to a power transmission side operation loss and power transmission and distribution boundary power coordination method. The power transmission side operation loss is defined as conventional unit generation loss, reserved standby loss and dynamic line expansion loss, and a target function of the power transmission side operation loss is constructed; A direct current flow constraint of the power transmission side operation loss is established; A boundary power consistency constraint of the power distribution side and the power transmission side is established, an optimization target function of the power transmission side and the power distribution side is constructed, and the power transmission side and the power distribution side are gradually close to each other in boundary power through a decoupling method and an iterative coordination mechanism, so that the power transmission side operation loss is minimized; The calculation formulae of the conventional unit generation loss, the reserved standby loss and the dynamic line expansion loss are as follows: (1) (2) (3) wherein, is the loss of the conventional generating units, is the output of the conventional generating units in the time period , is the fitting parameter; is the loss of the reserved standby, and are the outputs of the conventional generating units in the time period respectively; and are the outputs of the conventional generating units in the time period respectively; are the coefficients; is the loss of the dynamic line expansion; is the dynamic expansion coefficient, indicating the capacity adjustment ratio of the line in the time period ; is the basic maximum transmission capacity of the line ; is the actual transmission power of the line in the time period ; is the expansion marginal loss coefficient; is the load rate maintenance loss coefficient of the line ; The target function of the power transmission side operation loss is as follows: (4) In the formula, is the total number of time periods, is the number of conventional units on the power transmission side, is the number of lines in the power transmission side; The direct current flow constraint of the power transmission side operation loss comprises: (5) (6) (7) (8) (9) (10) (11) (12) wherein, is the boundary power of the transmission side; is the set of conventional generating units of the access node , is the set of transmission and distribution boundaries connected with the node N i is the set of nodes directly connected with the node i, is the load demand of the node , is the susceptance between the line , is the voltage phase angle of the node , is the voltage phase angle of the node , is the set of all nodes; are respectively the lower limit and the upper limit of the conventional generating unit output; are respectively the lower limit and the upper limit of the conventional generating unit output ramping; is the output of the conventional generating unit in the time period ; and are respectively the maximum upward reserve and the maximum downward reserve provided by the conventional generating unit ; are respectively the minimum value and the maximum value of the dynamic expansion coefficient; is the active power transmission limit value between the nodes of the line .

2. The method of claim 1, wherein, The boundary power consistency constraint of the power distribution side and the power transmission side is as follows: (13) wherein is the boundary power on the distribution side, is the set of all transmission and distribution boundaries.

3. The method of claim 2, wherein, The optimization target function of the power transmission side is as follows: (14) The optimization target function of the power distribution side is as follows: (15) The decoupling method is an alternating direction multiplier method. (16) (17) (18) (19) wherein, and are the charging power and discharging power of charging station n, respectively, is the number of charging stations, N dist is the set of nodes on the distribution side, is the day-ahead marginal price of the node where charging station n is located, is the penalty coefficient; is the transmission-distribution boundary power, representing the target value of power exchange between the transmission side and the distribution side at boundary node k and time period t; is the dual variable used to coordinate the boundary power consistency between the transmission side and the distribution side; is the maximum charging power of the charging station, is the maximum discharging power of the charging station; when the charging station is in the charging state, , ; when the charging station is in the discharging state, , ; are the minimum and maximum values of the day-ahead marginal price of the node where charging station n is located, respectively.

4. The method of claim 3, wherein, The decoupling method is an alternating direction multiplier method.

5. The method of claim 4, wherein, The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method.

6. The method of claim 5, wherein, The decoupling method is an alternating direction multiplier method. (20) (21) (22) (23) The decoupling method is an alternating direction multiplier method. (24) wherein denotes the boundary power on the transmission side after the iteration number N + 1, denotes the boundary power on the distribution side after the iteration number N + 1, is the transmission-distribution boundary power after the iteration number N, is the dual variable after the iteration number N, is the transmission-distribution boundary power after the iteration number N + 1, is the dual variable after the iteration number N + 1, is the difference between the boundary powers on the transmission side and on the distribution side.

7. A device for coordinating operation loss of a power transmission side and power at a power transmission and distribution boundary, characterized by, The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The decoupling method is an alternating direction multiplier method. The

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