A new energy carrying capacity calculation method and system based on main distribution and micro-coordinated operation

Abstract

The present invention relates to a method and system for calculating the carrying capacity of new energy based on the coordinated operation of main-distribution-microgrid. The first carrying capacity data is obtained by mutual verification of the open capacity component and the total installed capacity of the target-level power grid; then, it is determined whether there is a microgrid participating in the coordinated operation according to the judgment index. When it is determined that there is a microgrid participating in the coordinated operation of the target-level power grid, the carrying capacity improvement value of the microgrid to the distribution network is obtained, and the first carrying capacity data is corrected based on the carrying capacity improvement value to obtain the new energy carrying capacity. The present invention establishes a new energy access carrying capacity calculation method based on the dimensions of substation, main transformer, feeder, and distribution transformer, and a new energy access carrying capacity calculation method based on the regional level dimension. It provides qualitative and quantitative analysis of access points and capacity of new energy in transit, and provides decision support and data reference for project planning and construction.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid operation, and in particular to a method and system for calculating new energy carrying capacity based on coordinated operation of main, distribution and micro-grids. Background Art

[0002] Microgrid refers to a small power generation and distribution system composed of distributed energy, energy storage devices, energy conversion devices, etc. With the continuous acceleration of energy transformation, key technologies such as microgrid planning and design, operation control, modeling and simulation are becoming more mature, and the cost of key equipment such as energy storage and photovoltaics continues to decline. As an effective means of efficiently absorbing large-scale distributed new energy nearby, microgrids are showing a large-scale development trend and the penetration rate is gradually increasing.

[0003] The assessment of renewable energy carrying capacity in the power grid system aims to comprehensively analyze the maximum power generation and the stable operation capacity of the power grid, so as to optimize energy distribution and ensure that the power grid remains safe and stable while accommodating more renewable energy power generation methods.

[0004] The existing new energy carrying capacity assessment only analyzes and measures the single main grid system, the single distribution grid system and the main and distribution coordinated system. Currently, most microgrids are independent systems located at high altitudes, islands, remote areas or areas without electricity. Therefore, there is a lack of carrying capacity measurement and optimal carrying capacity assessment under the coordinated operation of microgrids, main grids and distribution grids. Summary of the invention

[0005] To this end, the technical problem to be solved by the present invention is to overcome the technical difficulty of the lack of new energy carrying capacity evaluation under the coordinated operation of the main, distribution and micro networks in the prior art, and to provide a new energy carrying capacity calculation method and system based on the coordinated operation of the main, distribution and micro networks, and to establish the calculation and evaluation of the new energy access carrying capacity based on the analysis of the interactive operation characteristics of the microgrid composed of the source, grid, load and storage and the main grid and distribution network.

[0006] In the first aspect, in order to solve the above technical problems, the present invention provides a method for calculating the new energy carrying capacity based on the coordinated operation of the main distribution and micro-circuit, which includes:

[0007] Input the basic data of each level of power grid; obtain the total open capacity of the first level power grid;

[0008] Allocate the total amount of openable capacity level by level according to the basic data to obtain the openable capacity components allocated to each level of power grid under the first level of power grid;

[0009] Through the aggregation model, the lower-level power grid is aggregated to the upper-level power grid step by step to obtain the total installed capacity of the upper-level power grid;

[0010] Verifying the total installed capacity according to the openable capacity component of the target-level power grid, and correcting and obtaining the first carrying capacity data of the target-level power grid according to the verification result;

[0011] Determine whether there is a microgrid participating in the coordinated operation of the target-level power grid according to the judgment index, wherein the judgment index includes the source-load matching degree and the proportion of the annual power generation of the power source in the annual load power;

[0012] When it is determined that there is a microgrid participating in the collaborative operation of the target-level power grid, the carrying capacity improvement value of the microgrid on the distribution network is obtained, and the first carrying capacity data is corrected based on the carrying capacity improvement value to obtain the new energy carrying capacity based on the collaborative operation of the main distribution network and the microgrid.

[0013] In one embodiment of the present invention, obtaining the total amount of openable capacity of the first-level power grid includes:

[0014] Creating a first objective function according to the unit startup cost and the unit operation cost, wherein the first objective function is used to calculate the total amount of openable capacity;

[0015] Establishing a first constraint condition for the first objective function according to the instruction, wherein the first constraint condition includes at least one of the following: a minimum start-stop constraint of a unit, a system active power balance constraint, a unit output constraint, a unit ramp constraint, a line capacity constraint, and a system spinning reserve constraint;

[0016] The total amount of openable capacity is calculated according to the first objective function and the first constraint condition.

[0017] In one embodiment of the present invention, allocating the total amount of openable capacity step by step according to the basic data includes:

[0018] The allocation coefficient is calculated / determined by weighted summation of the basic data corresponding to the lower-level power grid;

[0019] Obtaining the proportion of the open capacity of the lower-level power grid compared to the upper-level power grid through the allocation coefficient;

[0020] The openable capacity of the upper-level power grid is allocated to adjacent lower-level power grids according to the proportions.

[0021] In one embodiment of the present invention, the allocation coefficient is calculated / determined by weighted summation of basic data corresponding to the lower-level power grid, wherein the basic data corresponding to the lower-level power grid includes installed capacity status, resource endowment, developable capacity, regional load level and flexible adjustable resource level.

[0022] In one embodiment of the present invention, the total installed capacity of the upper-level power grid is obtained by aggregating the lower-level power grid to the upper-level power grid step by step through the aggregation model, including:

[0023] The second objective function is created based on the installed capacity of the equipment at the grid access node as follows:

[0024] ;

[0025] in, is a collection of computational scenarios; is the set of node locations connected to photovoltaics; Represents the installed capacity of the photovoltaic equipment connected to node i in scenario m.

[0026] In one embodiment of the present invention, a second constraint condition is established for the second objective function according to an instruction, wherein the second constraint condition includes a power flow constraint, a voltage deviation constraint, a thermal stability constraint, a forward load rate constraint, a reverse load rate constraint, a short-circuit current constraint, a harmonic constraint and a power abandonment rate constraint.

[0027] In one embodiment of the present invention, obtaining the first carrying capacity data of the target-level power grid according to the correction result includes:

[0028] adjusting the step-by-step allocation process according to the verification results;

[0029] Iterate the optimization until the first bearing capacity data is obtained.

[0030] In one embodiment of the present invention, determining whether there is a microgrid participating in the coordinated operation in the target level power grid according to the judgment index includes:

[0031] Obtaining the source-load matching degree, wherein the source-load matching degree is set to the average consistency of the new energy output change rate and the new energy load change rate within the time period;

[0032] If the source-load matching degree and the proportion of the annual power generation of the power source in the annual load power both exceed preset thresholds, it is determined that there is a microgrid participating in the coordinated operation.

[0033] In one embodiment of the present invention, obtaining the carrying capacity improvement value of the microgrid to the distribution network includes:

[0034] Determine power constraints, wherein the power constraints include that the interactive power of the interconnection line between the microgrid and the distribution network is between upper and lower limits, and that the interactive power of the interconnection lines between different microgrids is between upper and lower limits, and that the real-time power of the load, the photovoltaic output power of the microgrid, and the wind power output power of the microgrid are balanced;

[0035] Under the power constraint, the carrying capacity improvement value is calculated / determined according to the difference between the sum of the photovoltaic output power of the microgrid and the wind power output power of the microgrid and the real-time power of the load.

[0036] In a second aspect, the present invention also provides a new energy carrying capacity calculation system based on the coordinated operation of the main distribution micro, which includes: a data processing module, a verification module and an evaluation output module;

[0037] The data processing module is used to obtain basic data of power grids at each level, and obtain the open capacity component and total installed capacity of the target level power grid;

[0038] The verification module is used to obtain the first carrying capacity data of the target level power grid;

[0039] The evaluation output module is used to obtain the carrying capacity improvement value of the microgrid to the distribution network and output the new energy carrying capacity result.

[0040] The above technical solution of the present invention has the following beneficial effects compared with the prior art:

[0041] Based on the analysis of the interactive operation characteristics of the microgrid composed of source, grid, load and storage and the main grid and distribution grid, the present invention establishes a calculation method for the new energy access carrying capacity in the dimensions of substation, main transformer, feeder and distribution transformer, and a calculation method for the new energy access carrying capacity in the dimensions of regional level. It provides qualitative and quantitative analysis of access points and capacity of new energy in transit, and provides decision support and data reference for project planning and construction.

[0042] The new energy carrying capacity data obtained by the present invention is more accurate, and can achieve orderly access management for the power grid with coordinated operation of the main distribution and micro-grid; reduce overvoltage, heavy overload and other phenomena caused by concentrated access of new energy, and optimize resource allocation. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to make the content of the present invention more clearly understood, the present invention is further described in detail below according to specific embodiments of the present invention in conjunction with the accompanying drawings, wherein:

[0044] Figure 1 It is a flow chart of a method for calculating the new energy carrying capacity based on the coordinated operation of the main, distribution and micro-circuits in the first embodiment of the present invention. DETAILED DESCRIPTION

[0045] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments so that those skilled in the art can better understand the present invention and implement it, but the embodiments are not intended to limit the present invention. Embodiment 1

[0046] Reference Figure 1As shown, Embodiment 1 of the present invention provides a method for calculating the new energy carrying capacity based on the coordinated operation of the main grid, distribution network and microgrid. Distributed energy refers to the use of renewable energy and energy storage equipment to produce and consume energy at the edge of the power system, and the microgrid combines distributed energy with the traditional power system to form a relatively independent system. With more and more distributed energy sources connected to the distribution network, the structure of the traditional distribution network has undergone major changes. In the prior art, there is a lack of new energy carrying capacity calculation based on the coordinated operation of the main grid, distribution network and microgrid.

[0047] Renewable energy carrying capacity refers to the comprehensive analysis and evaluation of the power grid system in a region or a specific area to determine the ability of the region or area to accommodate the installed capacity of renewable energy power generation. As an important indicator for measuring the stable operation of the power grid system, the renewable energy carrying capacity is of great significance to ensuring the stability and safety of the power grid operation.

[0048] The method provided in the first embodiment of the present invention comprises the following steps:

[0049] Step S100: input basic data of power grids at each level.

[0050] In a preferred embodiment of the present invention, the grid level is divided according to the administrative level. The first-level grid is set as a provincial grid, and the lower-level areas of the provincial grid are set as prefecture-level grids, district-level grids, and township-level grids in turn. When the upper-level grid is set as a provincial grid, the lower-level grid includes multiple prefecture-level cities; when the upper-level grid is set as a prefecture-level grid, the lower-level grid also includes multiple districts and counties; and so on. In other embodiments, the regional level division can also be based on other standards, not limited to this.

[0051] Preferably, basic data is collected for each lower-level power grid of the first-level power grid. The basic data includes the distribution and transformation relationship between each level and the evaluation data; wherein the distribution and transformation relationship includes the inclusion relationship and the subordinate relationship division of the distribution and transformation equipment between each level. The evaluation data includes the load level, flexibility resource level, installed capacity, resource endowment and development capacity of each level of power grid.

[0052] Table 1 below shows the requirements and calculation purposes of some basic data in some embodiments.

[0053] Table 1

[0054]

[0055] Step S200: Obtain the total amount of openable capacity of the first-level power grid.

[0056] According to parameters such as unit startup cost and unit operation cost, a first objective function is created. The first objective function is used to calculate the total amount of open capacity of the first-level power grid. The first objective function is as follows:

[0057] ;

[0058] in, The unit is in the start-stop state. is the unit startup cost, is the transmission cost per unit power, is the transmission power of the unit, g is the number of units put into operation, and t is the sequence of units put into operation.

[0059] The time series operation simulation is carried out with the expected sum of the unit startup cost and the unit operating cost as the target, and the simulation result of the first objective function is used as the total amount of open capacity of the first-level power grid.

[0060] A first constraint condition is established for the first objective function according to the instruction, and the first constraint condition includes at least one of the following: minimum start-stop constraint of the unit, system active power balance constraint, unit output constraint, unit climbing constraint, line capacity constraint and system rotating standby constraint.

[0061] The minimum start and stop constraints of the unit are:

[0062] ;

[0063] in, =1 means the unit is turned on, =0 means the unit is in shutdown state, is the total number of starts, is the total number of downtimes, is the number of starts at that moment, is the number of shutdowns at that moment, For other situations.

[0064] The system active power balance constraint is:

[0065] ;

[0066] in, For the power generation of conventional units, The power generated by the wind turbine is is the power generated by the photovoltaic unit, is the system active power.

[0067] The unit output constraint is:

[0068] ;

[0069] in, is the minimum output of the unit, The maximum output of the unit is constrained between the maximum and minimum values.

[0070] The unit climbing constraint is:

[0071] ;

[0072] in, is the negative climbing rate of the unit, It is the positive rate of the unit climbing.

[0073] The line capacity constraint is:

[0074] ;

[0075] in, is the unit capacity per unit number of feeder lines, The power limit of the transmission line.

[0076] The system spinning reserve constraints are:

[0077] ;

[0078] in, is the maximum system power, sup is the system spinning reserve coefficient.

[0079] According to the first objective function and the first constraint condition, the total amount of openable capacity of the first-level power grid is calculated.

[0080] Step S300: allocating the total amount of openable capacity level by level according to the basic data to obtain the openable capacity components allocated to each level of power grid under the first level of power grid.

[0081] As an implementable method, step S300 includes the following steps:

[0082] Determine the basic data corresponding to the lower-level power grid to participate in the calculation of the allocation coefficient.

[0083] The basic data involved in the calculation of the allocation coefficient include regional load level, flexible and adjustable resource level, installed capacity, resource endowment and developable capacity.

[0084] When calculating the allocation coefficient for the jth area to be allocated in the lower-level power grid,

[0085] The regional load levels are:

[0086] ;

[0087] in, Indicates that the regional load level is used as the first calculation dimension to participate in the calculation of the allocation coefficient of the jth area to be allocated; The power load of the area to be allocated in the lower-level power grid; It is the total social electricity load of the upper-level power grid.

[0088] Taking the allocation of provincial power grid to prefecture-level power grid as an example, there are multiple prefecture-level regions under the provincial level. Take the jth prefecture-level city as the area to be allocated. is the social electricity load of the area to be allocated, It is the sum of the social electricity loads of all prefecture-level cities, that is, the total social electricity load of the province.

[0089] Flexibility to adjust resource levels:

[0090] ;

[0091] in, It indicates that the flexible and adjustable resource level is used as the second calculation dimension to participate in the calculation of the allocation coefficient of the j-th area to be allocated. The flexible and adjustable resource level represents the regional energy storage level. The available flexibility resources in the lower-level grid to be allocated to the area; is the total amount of available flexibility resources in the upper-level power grid.

[0092] The current status of installation is:

[0093] ;

[0094] in, It indicates that the current status of installed capacity is used as the third calculation dimension to participate in the calculation of the allocation coefficient of the j-th area to be allocated. The installed capacity scale represents the potential for future new development in the region. The larger the installed capacity scale, the smaller the development potential. The capacity scale of the installed capacity connected to the grid in the area to be allocated in the lower-level power grid; The scale of distributed photovoltaic installed capacity that has been approved, approved and under construction in the areas to be allocated in the lower-level power grid; It is the total installed capacity of the upper-level power grid.

[0095] The resource endowment is:

[0096] ;

[0097] in, It means that resource endowment, as the fourth calculation dimension, participates in the calculation of the allocation coefficient of the j-th area to be allocated. Resource endowment represents the natural conditions for regional resource development. The area of ​​land available for photovoltaic development in the area to be allocated for the lower-level power grid; is the unit light intensity.

[0098] The capabilities that can be developed are:

[0099] ;

[0100] in, Indicates that the developable capacity is used as the fifth calculation dimension to participate in the calculation of the allocation coefficient of the jth area to be allocated; The potential for photovoltaic development per square kilometer, The area of ​​developable photovoltaic land in the area to be allocated in the lower-level power grid.

[0101] When the administrative division area of ​​the lower-level power grid is at the level of prefecture-level cities, districts, counties, towns, communities, etc. or above, the allocation coefficient is calculated / determined by weighted summation of the basic data corresponding to the lower-level power grid;

[0102] Specifically, weight and distribute according to the following formula:

[0103] ;

[0104] in, is the weighted distribution coefficient; is the weight coefficient of the calculation dimension; It indicates the result of the calculation of the allocation coefficient of the i-th calculation dimension of the j-th region to be allocated.

[0105] In some embodiments, the weight coefficients are shown in Table 2 below.

[0106] Table 2

[0107]

[0108] Continued, The total amount of photovoltaic capacity available in the upper-level power grid of the area to be allocated; It is the available photovoltaic capacity allocated to the jth area to be allocated in the lower-level power grid.

[0109] The proportion of the open capacity of the lower-level power grid compared to the upper-level power grid is obtained through the allocation coefficient; and the open capacity of the upper-level power grid is allocated to the to-be-allocated area of ​​the adjacent lower-level power grid according to the proportion.

[0110] It should be noted that when the administrative division of the lower-level power grid is at the prefecture-level city, district, county, township or community level or above, the basic data involved in the calculation of the allocation coefficient include regional load level, flexible and adjustable resource level, installed capacity, resource endowment and developable capacity; the allocation coefficient is calculated by weighting using the above formula.

[0111] When the administrative divisions of the lower-level power grid are towns, communities and below, some basic data are difficult to obtain. Preferably, the basic data involved in the calculation of the distribution system include regional load levels and flexible adjustable resource levels.

[0112] Specifically, weight and distribute according to the following formula:

[0113] ;

[0114] in, is the weighted distribution coefficient; is the weight coefficient of regional load level; Weight coefficients for adjustable resource levels for flexibility.

[0115] In the allocation process of step S300 , the target-level power grid participates in the allocation as the jth area to be allocated in the lower-level power grid.

[0116] If the upper grid of the target grid is the first grid, the total available capacity of the first grid is calculated directly in step S200, and then the available capacity of the target grid is obtained by allocating it once in step S300. .

[0117] If the upper level grid of the target grid is below the first level grid, the total amount of the available capacity of the first level grid is calculated in step S200, and then allocated step by step in step S300 until the available capacity of the target grid is obtained. .

[0118] Step S400: by using the aggregation model, with the distribution transformer as the smallest associated unit, the lower-level power grid is summed up step by step to the upper-level power grid to obtain the total installed capacity of the upper-level power grid.

[0119] As an implementable method, step S400 includes the following steps:

[0120] Step S410: Create a second objective function based on the installed capacity of the equipment at the grid access node as follows:

[0121] ;

[0122] in, is a collection of computational scenarios; It is the set of node locations connected to the photovoltaic equipment. Represents the installed capacity of the photovoltaic equipment connected to a single node i in scenario m.

[0123] A second constraint condition is established for the second objective function according to the instruction, wherein the second constraint condition includes power flow constraint, voltage deviation constraint, thermal stability constraint, forward load rate constraint, reverse load rate constraint, short-circuit current constraint, harmonic constraint and abandonment rate constraint.

[0124] The power flow constraint is:

[0125] ;

[0126] in, is the active power injected by node i connected to the photovoltaic device at time t in scenario m; It is the reactive power injected by node i connected to the photovoltaic device at time t in scenario m. is the voltage amplitude of node i connected to the photovoltaic device at time t in scenario m. is the real part of the branch admittance matrix; is the imaginary part of the branch admittance matrix; is the voltage phase angle difference between nodes i and j.

[0127] The voltage deviation constraint is:

[0128] ;

[0129] in, is the voltage rating; is the allowable voltage deviation operating range under the voltage deviation constraint condition, It is the voltage amplitude of node i connected to the photovoltaic device at time t in scenario m. According to the "Power Quality-Supply Voltage Deviation" (GB / T 12325): the sum of the absolute values ​​of the positive and negative deviations of the 110-35 kV supply voltage shall not exceed 10% of the nominal voltage; the allowable deviation of the three-phase supply voltage of 10 kV and below is ±7% of the nominal voltage; the allowable deviation of the 220 V single-phase supply voltage is +7% and -10% of the nominal voltage.

[0130] The thermal stability constraint is:

[0131] ;

[0132] in, is the current flowing through the line at time t in scenario m; Indicates the maximum current carrying capacity of the line.

[0133] The forward load factor constraint is:

[0134] According to the Technical Guidelines for Planning and Design of Distribution Networks (Q / GDW 10738-2020), 10kV lines in A+, A, B, and C power supply areas should meet the "N-1" principle‌, that is, under normal operating conditions, if any component in the power system (such as lines, generators, transformers, etc.) is fault-free or disconnected due to a fault, the power system should be able to maintain stable operation and normal power supply, other components should not be overloaded, and the voltage and frequency should be within the allowable range.

[0135] Therefore, the maximum forward load rate of the 10kV line in the wiring mode of this embodiment is 50%.

[0136] The reverse load rate constraint is:

[0137] ;

[0138] in, represents the reverse load rate at time t in scenario m; represents the photovoltaic output at time t in scenario m; It represents the equivalent power load at time t in scenario m, that is, the load minus the output of other power sources except distributed power sources; Indicates the actual operating limit of the transformer or line; Indicates the maximum allowable reverse load rate.

[0139] In order to meet the "N-1" principle, the reverse load rate constraint of the device is essentially the reverse load constraint of N-1. Therefore, considering that the wiring mode in the embodiment is single contact, the maximum reverse load rate is 50%.

[0140] The short-circuit current constraint is:

[0141] ;

[0142] in, represents the system bus short-circuit current at time t in scenario m; Indicates the maximum allowable short-circuit current limit. The minimum value of the breaking current limit of all devices connected to the busbar and the corresponding circuit breakers on the feeder should be selected.

[0143] The short-circuit current of the photovoltaic power station after it is connected to the system includes the short-circuit current of the public connection point and the short-circuit current of the grid connection point. Please refer to the following formula for specific calculation:

[0144] Short-circuit current at common connection point:

[0145] ;

[0146] in, It is the short-circuit current of the public connection point before the photovoltaic power station is connected, provided by the power supply company; Short-circuit current at the common connection point after the photovoltaic power station is connected. It is the rated working current of the photovoltaic power station.

[0147] Short-circuit current at the grid connection point:

[0148] ;

[0149] in, It is the short-circuit current of the grid connection point before the photovoltaic power station is connected. Short-circuit current at the grid connection point after the photovoltaic power station is connected. is the common connection point reference voltage; is the grid connection point reference voltage; is the impedance of the line from the grid connection point to the public connection point.

[0150] The harmonic constraints are:

[0151] ;

[0152] in, represents the system harmonic voltage distortion rate at time t in scenario m; Indicates the maximum allowable value of harmonic voltage distortion rate.

[0153] The light abandonment rate constraint is:

[0154] ;

[0155] in, Indicates the maximum allowable abandoned light rate; It represents the actual maximum output of photovoltaic power at time t in scenario m.

[0156] According to the power flow constraints and operation constraints of the distribution network, a calculation model is established to solve the maximum photovoltaic acceptance capacity, where the calculation model is a mixed integer non-convex nonlinear model.

[0157] Step S420: transform the power flow constraints and operation constraints of the distribution network into , , converting the nonlinear constraint into a second-order cone constraint. Optimizing the solution process of step S410.

[0158] The mixed integer non-convex nonlinear model is transformed into a mixed integer second-order cone programming model through the second-order cone relaxation technique and linearization technique. The transformation process is shown in the following formula:

[0159] .

[0160] Quantitative index of second-order cone relaxation deviation in distribution network and distribution network cut plane constraints Refer to the following formula,

[0161] ;

[0162] ;

[0163] in, is the active power flow of branch ij at time t in the kth iteration; is the reactive power flow of branch ij at time t in the kth iteration; is the square of the current amplitude of branch ij at time t in the kth iteration; is the square of the voltage amplitude at node i at time t in the kth iteration.

[0164] The converted mixed integer second-order cone programming model can be efficiently solved by using mature mathematical optimization tools such as CPLEX and GUROBI, and the results are more accurate and precise.

[0165] The mixed integer second-order cone programming model is solved by a mathematical optimization tool, and the solution result is output , Installed capacity for a single node device After regional aggregation, the total installed capacity of the upper-level power grid is obtained.

[0166] In the aggregation model of step S400 , the target-level power grid participates in aggregation as an upper-level power grid.

[0167] If the target level grid has no next level in the hierarchical division, the total installed capacity of the target level grid is directly calculated according to the data of each node device in the target level grid in step S400. .

[0168] If the target level grid includes the next level, then step S400 summarizes the data of each node device level by level, and obtains the data of the upper level grid from the lower level grid until the total installed capacity of the target level grid is obtained. .

[0169] Step S500: according to the available capacity of the target level power grid in step S300 , the total installed capacity of the target level power grid in step S400 Carry out verification.

[0170] When the target grid's available capacity Greater than or equal to the total installed capacity of the target level power grid When the target grid has an open capacity of Smaller than the total installed capacity of the target grid When the total installed capacity is Carry out proportional allocation, adjust the allocation process, and repeat the verification and correction until the available capacity of the target-level power grid is greater than or equal to the total installed capacity.

[0171] The total installed capacity of the target-level power grid is obtained as the first carrying capacity data.

[0172] Step S600: determine whether there is a microgrid participating in the coordinated operation of the target-level power grid according to the judgment index; if it is determined that there is a microgrid participating in the coordinated operation of the target-level power grid, obtain the carrying capacity improvement value of the microgrid on the distribution network.

[0173] As an implementable method, step S600 includes the following steps:

[0174] Step S610: Obtain judgment indicators, where the judgment indicators include source-load matching degree and power proportion.

[0175] The source-charge matching degree is:

[0176] In the first embodiment of the present invention, the source-load matching characteristic is calculated by the consistency index, and the source-load matching degree is set as the average consistency of the new energy output change rate and the new energy load change rate within the time period. Refer to the following formula for calculation:

[0177] ;

[0178] in, Contribute to the new energy at t+T moment, Contribute to the new energy at time t; The rate of change of renewable energy output.

[0179] is the load at time t+T; is the load at time t; is the change rate of renewable energy load.

[0180] The consistency of the change in the output of new energy and the change in load at time t; The closer it is to 0, the better the consistency between the new energy output and the load.

[0181] when =0, it means that the change rate of new energy output and load is in the same direction and equal in magnitude, and is completely consistent.

[0182] Furthermore, the average consistency of the new energy output change rate and the new energy load change rate is calculated as follows:

[0183] ;

[0184] in, is the source-load matching degree; n is the total number of statistical moments.

[0185] The proportion of electricity is the proportion of annual power generation to annual load electricity; refer to the following formula for calculation:

[0186] ;

[0187] in, It is the ratio of power generation to annual load. The annual power generation The annual load electricity.

[0188] Step S620: Determine whether there is a microgrid participating in the coordinated operation in the target-level power grid according to the judgment index.

[0189] Specifically, if the source-load matching degree and the proportion of annual power generation in the annual load electricity both exceed the preset thresholds, it is determined that there is a microgrid participating in the coordinated operation.

[0190] The ranking is based on the source-load matching degree and the power proportion, among which the component set with a power proportion weight of 0.7 and a source-load matching degree weight of 0.3 is judged to have the potential to form a microgrid.

[0191] Step S630: When the microgrid participates in the coordinated operation, the power constraint is determined and the value of the microgrid's carrying capacity improvement for the distribution network is obtained.

[0192] The power constraints include: the interactive power of the interconnection line between the microgrid and the distribution network is between the upper and lower limits, the interactive power of the interconnection line between different microgrids is between the upper and lower limits, and the power balance among the real-time power of the load, the photovoltaic output power of the microgrid, and the wind power output power of the microgrid.

[0193] The interactive power constraint of the tie line between the microgrid and the distribution network is as follows:

[0194] ;

[0195] in, is the interaction power between the microgrid and the distribution network; is the lower limit of the interactive power of the tie line between the microgrid and the distribution network; It is the upper limit of the interaction power of the tie line between the microgrid and the distribution network.

[0196] The interactive power constraints of the tie lines between different microgrids refer to the following formula:

[0197] ;

[0198] in, is the interaction power of the interconnection line between microgrids; is the lower limit of the interactive power of the interconnection lines between microgrids; are the upper limits of the interaction power of the interconnection lines between microgrids.

[0199] The power balance constraint of the microgrid is referred to the following formula:

[0200] ;

[0201] in, The photovoltaic output power of the microgrid's new energy, They are the new energy wind power output power of the microgrid; is the real-time power of the load.

[0202] when or When the interval requirements are met, the carrying capacity improvement value is calculated / determined according to the difference between the sum of the photovoltaic output power of the microgrid and the wind power output power of the microgrid and the real-time power of the load.

[0203] Microgrids can improve the carrying capacity of distribution networks Refer to the following formula for calculation:

[0204] .

[0205] Step S700: Based on the carrying capacity improvement value The first carrying capacity data obtained in step S500 is corrected by increasing or decreasing the first carrying capacity to obtain a correction result, and the correction result is used as the optimal new energy carrying capacity and the new energy carrying capacity based on the coordinated operation of the main distribution and micro-power.

[0206] Both the large power grid and the microgrid are organic components of the new power system with new energy as the main body. The new energy carrying capacity result calculated by the first embodiment of the present invention can optimize the supporting role of the large power grid to the microgrid, as well as the reasonable supplement of the microgrid to the large power grid, and play a role in optimizing the allocation of energy resources in different geographical scopes and different time scales. Embodiment 2

[0207] Embodiment 2 of the present invention provides a new energy carrying capacity calculation system based on the coordinated operation of the main distribution microcomputer, which includes: a data processing module, a verification module and an evaluation output module;

[0208] The data processing module is used to obtain the basic data of each level of power grid and obtain the open capacity component and total installed capacity of the target level power grid;

[0209] A verification module, used to obtain the first carrying capacity data of the target level power grid;

[0210] The evaluation output module is used to obtain the carrying capacity improvement value of the microgrid to the distribution network and output the optimal new energy carrying capacity result.

[0211] It should be noted that, in the absence of conflict, the embodiments and features in the embodiments of the present application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0212] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprise" and / or "include" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0213] Unless otherwise specifically stated, the relative arrangement, numerical expressions and numerical values ​​of the parts and steps set forth in these embodiments do not limit the scope of the present application. At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to the actual proportional relationship. The technology, methods and equipment known to those of ordinary skill in the relevant art may not be discussed in detail, but in appropriate cases, the technology, methods and equipment should be considered as a part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, and therefore, once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

[0214] In addition, it should be noted that the use of terms such as "first" and "second" to limit components is only for the convenience of distinguishing the corresponding components. Unless otherwise stated, the above terms have no special meaning and therefore cannot be understood as limiting the scope of protection of this application.

[0215] The above are only preferred embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and changes. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application. The above embodiments are merely examples for clear explanation and are not limitations on the implementation methods. For those of ordinary skill in the art, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to list all the implementation methods here. The obvious changes or modifications derived from this are still within the protection scope of the present invention.

Claims

1. A method for calculating the new energy carrying capacity based on the coordinated operation of main distribution and micro-power, characterized in that: include: Input basic data of power grids at all levels; The total amount of openable capacity of the first-level power grid is obtained, specifically including: creating a first objective function according to the unit startup cost and the unit operation cost, wherein the first objective function is used to calculate the total amount of openable capacity, and the first objective function is as follows: ； in, The unit is in the start-stop state. is the unit startup cost, is the transmission cost per unit power, is the transmission power of the unit, g is the number of units put into operation, and t is the sequence of units put into operation; Establishing a first constraint condition for the first objective function according to the instruction, and calculating the total amount of openable capacity according to the first objective function and the first constraint condition; Allocate the total amount of openable capacity level by level according to the basic data to obtain the openable capacity components allocated to each level of power grid below the first level of power grid; Through the aggregation model, the lower-level power grid is aggregated to the upper-level power grid step by step to obtain the total installed capacity of the upper-level power grid, which includes: The second objective function is created based on the installed capacity of the equipment at the grid access node as follows: ； in, is a collection of computational scenarios; is the set of node locations connected to photovoltaics; represents the installed capacity of the photovoltaic equipment connected to node i in scenario m; Verifying the total installed capacity according to the openable capacity component of the target-level power grid, and correcting and obtaining the first carrying capacity data of the target-level power grid according to the verification result; Determine whether there is a microgrid participating in the coordinated operation of the target level power grid according to the judgment index, wherein the judgment index includes the source-load matching degree and the proportion of the annual power generation in the annual load power, specifically including: Obtaining the source-load matching degree, wherein the source-load matching degree is set to the average consistency of the new energy output change rate and the new energy load change rate within the time period; The source-load matching degree and the proportion of the annual power generation in the annual load power both exceed the preset threshold value, and it is determined that there is a microgrid participating in the coordinated operation; When it is determined that there is a microgrid participating in the collaborative operation of the target-level power grid, the carrying capacity improvement value of the microgrid on the distribution network is obtained, and the first carrying capacity data is corrected based on the carrying capacity improvement value to obtain the new energy carrying capacity based on the collaborative operation of the main distribution network and the microgrid.

2. According to claim 1, a new energy carrying capacity calculation method based on the coordinated operation of main distribution and micro-circuit is characterized in that: The first constraint condition includes at least one of the following: minimum start-stop constraint of the unit, system active power balance constraint, unit output constraint, unit climbing constraint, line capacity constraint and system spinning reserve constraint.

3. According to claim 1, a new energy carrying capacity calculation method based on the coordinated operation of main distribution and micro-circuit is characterized in that: The total amount of openable capacity is allocated step by step according to the basic data, including: The allocation coefficient is calculated / determined by weighted summation of the basic data corresponding to the lower-level power grid; Obtaining the proportion of the open capacity of the lower-level power grid compared to the upper-level power grid through the allocation coefficient; The openable capacity of the upper-level power grid is allocated to adjacent lower-level power grids according to the proportions.

4. According to claim 2, a new energy carrying capacity calculation method based on the coordinated operation of main distribution and micro-circuit is characterized in that: The allocation coefficient is calculated / determined by weighted summation of basic data corresponding to the lower-level power grid, wherein the basic data corresponding to the lower-level power grid includes installed capacity status, resource endowment, developable capacity, regional load level and flexible adjustable resource level; wherein the resource endowment represents the natural conditions for regional resource development.

5. According to claim 1, a new energy carrying capacity calculation method based on the coordinated operation of main distribution and micro-circuit is characterized in that: A second constraint condition is established for the second objective function according to the instruction, wherein the second constraint condition includes power flow constraint, voltage deviation constraint, thermal stability constraint, forward load rate constraint, reverse load rate constraint, short-circuit current constraint, harmonic constraint and abandonment rate constraint.

6. The method for calculating the new energy carrying capacity based on the coordinated operation of main distribution and micro-circuit according to claim 1 is characterized in that: Correcting and obtaining the first carrying capacity data of the target-level power grid according to the verification result includes: adjusting the step-by-step allocation process according to the verification results; Iterate the optimization until the first bearing capacity data is obtained.

7. The method for calculating the new energy carrying capacity based on the coordinated operation of main distribution and micro-circuit according to claim 1 is characterized in that: The value of the microgrid's carrying capacity improvement on the distribution network includes: Determine power constraints, wherein the power constraints include that the interactive power of the interconnection line between the microgrid and the distribution network is between upper and lower limits, and that the interactive power of the interconnection lines between different microgrids is between upper and lower limits, and that the real-time power of the load, the photovoltaic output power of the microgrid, and the wind power output power of the microgrid are balanced; Under the power constraint, the carrying capacity improvement value is calculated / determined according to the difference between the sum of the photovoltaic output power of the microgrid and the wind power output power of the microgrid and the real-time power of the load.

8. A new energy carrying capacity calculation system based on the coordinated operation of main distribution and micro-circuit, characterized in that: The system is implemented based on the new energy carrying capacity calculation method based on the coordinated operation of the main distribution and micro-circuit as described in any one of claims 1 to 7; the system includes: a data processing module, a verification module and an evaluation output module; The data processing module is used to obtain basic data of power grids at each level, and obtain the open capacity component and total installed capacity of the target level power grid; The verification module is used to obtain the first carrying capacity data of the target level power grid; The evaluation output module is used to obtain the carrying capacity improvement value of the microgrid to the distribution network and output the new energy carrying capacity result.

Images