Micro-grid optimal scheduling algorithm

Abstract

The invention relates to a micro-grid optimal scheduling algorithm which comprises the following steps: determining power balance and load reduction constraints of micro-grid operation, and constructing a scheduling objective function; introducing an auxiliary variable to simplify the objective function, and constructing an augmented Lagrange function; decomposing the optimization problem by using an ADMM technology, and solving to obtain optimal solutions in different operation modes; and deploying the optimal solution on a computer node to realize the optimal scheduling of the micro-grid. According to the method, the objective function of the micro-grid scheduling problem is constructed, the auxiliary variable is introduced for simplification, then the augmented Lagrange function is constructed, and finally the ADMM technology is utilized to decompose and optimize the problem and solve the problem, so that the optimal solution of the micro-grid in different operation modes can be efficiently obtained, the efficiency and accuracy of micro-grid scheduling can be remarkably improved, and the method is suitable for large-scale popularization and application. Therefore, the micro-grid can better meet the load requirement, and the energy utilization is optimized at the same time.

Description

Technical Field

[0001] The invention relates to a microgrid optimal dispatching algorithm, and belongs to the technical field of smart grids. Background Art

[0002] Microgrids have been proposed as one of the key components of grid modernization, capable of supplying power to a group of interconnected loads as a single controllable entity. By integrating renewable energy resources and energy storage devices, microgrids are expected to reduce large capital investments by utilizing locally generated electricity to meet growing energy demands. In addition, by deploying power generation close to end users, microgrids have become a promising solution to help improve the reliability and quality of electricity. A notable feature of microgrids is the islanding capability, which is the ability to disconnect from the main distribution network and supply power locally. However, due to the limited ability of local generators to increase power output during normal operation before switching to islanding mode, microgrids may not be able to meet the load needs of all local users.

[0003] The patent document with the patent number "CN112117782A" discloses a microgrid operation optimization method based on the radial basis function model. The problem with this method is that although the radial basis function model can estimate and solve the optimal solution of the microgrid optimization problem by constructing a model, its effect depends largely on the selection of the initial sampling point set and the parameter setting of the radial basis function. If the initial sampling point set is not representative or the parameters are improperly set, the model may not accurately reflect the actual operating conditions of the microgrid, thereby affecting the accuracy of the optimization results. As the operating environment and control requirements of the microgrid continue to change, the radial basis function model may need to be frequently updated and maintained to ensure its accuracy and effectiveness. This includes steps such as reselecting the sampling point set and adjusting the model parameters, which may be cumbersome and time-consuming. Summary of the invention

[0004] In order to solve the above problems existing in the prior art, the present invention proposes a microgrid optimal scheduling algorithm.

[0005] The technical solution of the present invention is as follows:

[0006] A microgrid optimal scheduling algorithm includes the following steps:

[0007] Determine the normal power balance constraints of the microgrid when the microgrid is operating normally;

[0008] Determine the microgrid island load reduction constraints and the microgrid island load demand constraints when the microgrid is operating in an islanded mode;

[0009] Determine the off-grid power balance constraint of the microgrid, the off-grid power generation output constraint of the microgrid, and the off-grid power generation ramp constraint of the microgrid when the microgrid is operating off-grid;

[0010] The objective function of the microgrid scheduling problem is constructed according to the microgrid normal power balance constraint, the microgrid island load reduction constraint, the microgrid island load demand constraint, the microgrid off-grid power balance constraint, the microgrid off-grid power generation output constraint and the microgrid off-grid power generation ramp constraint;

[0011] Setting a first auxiliary variable and a second auxiliary variable, and simplifying the objective function by using the first auxiliary variable and the second auxiliary variable;

[0012] Construct the augmented Lagrangian function of the simplified objective function;

[0013] Iteratively decompose the simplified objective function using the ADMM decomposition technique, and decompose the simplified objective function into N+1 optimization problems according to the augmented Lagrangian function;

[0014] By solving N+1 optimization problems, the optimal solutions are obtained when the microgrid is operating normally, when the microgrid is operating in an isolated island, and when the microgrid is operating off-grid.

[0015] The optimal solution for the normal operation of the microgrid is deployed on the computer main node, and the optimal solution for the microgrid island operation and the microgrid off-grid operation is deployed on the computer distributed nodes, and the optimal scheduling of the microgrid is achieved through the computer.

[0016] As a preferred implementation, the normal power balance constraint of the microgrid is expressed as:

[0017] Let the set of the i-th normally operating microgrid and the microgrids connected to it through transmission lines be N i ;

[0018] Let the i-th microgrid in normal operation transmit to N i The electric power vector is

[0019] in, represents the power transmitted from the i-th microgrid to the j-th microgrid connected to it during normal operation, and o represents the preset variable when the microgrid is operating normally;

[0020] Let the total power generated locally by the i-th microgrid during normal operation be

[0021] Where l = [1,1,…,1] T is a column vector whose elements are all 1. The length of vector l is preset according to the operator's experience. T represents the transpose of l;

[0022] Let the power obtained by the i-th microgrid from the main grid during normal operation be

[0023] The power loss of the microgrid exchanging power with the main grid during normal operation of the i-th microgrid express:

[0024]

[0025] Among them, R oi represents the transmission line resistance between the i-th microgrid and the main grid during normal operation, α represents the power loss factor of the preset transformer, Indicates the preset operating voltage V o The square of

[0026] The power loss of the i-th microgrid in normal operation when exchanging power with the j-th microgrid connected to it express:

[0027]

[0028] Among them, R ij represents the transmission line resistance between the i-th microgrid in normal operation and the j-th microgrid connected to it, represents the square of the operating voltage V1 between the i-th microgrid in normal operation and the j-th microgrid connected to it;

[0029] according to and The normal power balance constraint of the microgrid during normal operation of the i-th microgrid is obtained:

[0030]

[0031] in, represents the power generated locally by the i-th microgrid during normal operation, represents the power exchange between the jth microgrid and the ith microgrid in normal operation, D i It represents the total power provided to customers by the i-th microgrid during normal operation;

[0032] D i =P i +E i ;

[0033] Among them, P i represents the power generated by distributed generation in the i-th microgrid during normal operation, E i It represents the power provided by the energy storage device during the normal operation of the i-th microgrid.

[0034] As a preferred implementation, the microgrid island load reduction constraint is expressed as:

[0035] Let the load demand ratio that needs to be reduced when the microgrid is disconnected from the main grid be ∈ k ; Wherein, k represents the preset variable when the microgrid is operating in an isolated island;

[0036] According to ∈ k Get the microgrid island load reduction constraint:

[0037]

[0038] in, Indicates the preset maximum allowable load reduction ratio.

[0039] As a preferred implementation, the microgrid island load demand constraint is expressed as:

[0040] Let the load demand of the microgrid when the hth island is running be (1-∈ k )D h ;

[0041] Let the set of the hth islanded microgrid and the microgrids connected to it through transmission lines be N h ;

[0042] According to (1-∈ k )D h The microgrid island load demand constraint of the microgrid when the hth island is operating is obtained:

[0043]

[0044] in, represents the power generated locally by the microgrid when the hth island is operating, represents the power exchange between the hth microgrid and the jth microgrid when the hth island is operating, represents the power loss of the hth microgrid when operating in an isolated island and the jth microgrid when exchanging power, D h It represents the power that the hth microgrid needs to provide when operating in an isolated island;

[0045] D h =L h +ΔE h ;

[0046] Among them, L h represents the load demand of the microgrid when the hth island is operating, ΔE h It represents the power supplement amount of the energy storage system of the microgrid when the hth island is operating.

[0047] As a preferred implementation, the off-grid power balance constraint of the microgrid is expressed as:

[0048]

[0049] in, represents the power generated locally by the microgrid when the i-th microgrid is operating off-grid, represents the power exchange between the microgrid and the main grid during the i-th off-grid operation, represents the power loss of the microgrid exchanging electricity with the main grid when the i-th microgrid is operating off-grid, represents the power loss of the i-th off-grid microgrid when exchanging power with the j-th connected microgrid, represents the power exchange between the jth microgrid and the i-th microgrid when operating off-grid;

[0050] The off-grid power generation output constraint of the microgrid is expressed as:

[0051]

[0052] in, represents the total power generated by the local power generation of the microgrid when the i-th microgrid is operating off-grid, represents the maximum ramp rate of the generator of the microgrid when the i-th microgrid is operating off-grid, N represents a non-negative integer set;

[0053] The off-grid power generation ramp constraint of the microgrid is expressed as:

[0054]

[0055] in, Indicates the maximum ramp rate of the main grid generator, represents the total power obtained by the i-th microgrid from the main grid during off-grid operation, represents the total power obtained by the i-th microgrid from the main grid during normal operation, represents the power flow vector from the main grid to the microgrid when the hth island operates.

[0056] As a preferred implementation, let the load reduction vector ∈ D It is expressed as:

[0057] ∈ D =[∈ 1 D1,∈ 2 D2,...,∈ i D i ,...,∈ N D N ] T ;

[0058] Among them, ∈ i D i represents the load reduction of the i-th microgrid;

[0059] The objective function is expressed as:

[0060]

[0061] Among them, min represents the minimum function, minC o (y o ) represents the minimum generation cost, y o It means that the microgrid can obtain electricity from the main grid when it is operating normally. represents the transmission cost, τ represents the preset weighting parameter, ||∈ D ||1 means ∈ D of -norm norm, calculated as:

[0062]

[0063] The constraints of the objective function include:

[0064] Normal power balance constraints of microgrid:

[0065]

[0066] Among them, st represents the format symbol of the optimization problem under the condition of...;

[0067] Microgrid normal secondary power flow constraints:

[0068]

[0069] in, represents the maximum allowable power flow between the i-th microgrid and the j-th microgrid;

[0070] Normal main power flow constraints of microgrid:

[0071]

[0072] in, represents the maximum power flow allowed by the i-th microgrid;

[0073] Microgrid island load demand constraints:

[0074]

[0075] Microgrid off-grid power balance constraints:

[0076]

[0077] Microgrid off-grid secondary power flow constraints:

[0078]

[0079] Main power flow constraints of off-grid microgrid:

[0080]

[0081] Microgrid island load reduction constraints:

[0082]

[0083] Microgrid off-grid power generation output constraints:

[0084]

[0085] Microgrid off-grid power generation ramp-up constraints:

[0086]

[0087] in, represents the power obtained by the i-th microgrid from the main grid when it is operating off-grid, It represents the power exchange between the i-th microgrid in off-grid operation and the j-th microgrid.

[0088] As a preferred embodiment, the simplified method of the objective function is:

[0089] Let the microgrid normal operation variable constraint set F o ={(X o ,y o )}, the F o It is subject to the constraints of normal power balance of microgrid, normal secondary power flow of microgrid and normal main power flow of microgrid;

[0090] Among them, X o It indicates that the microgrid is operating normally and generating local power;

[0091] Set of constraints on the microgrid off-grid operation variables The F k It is subject to the constraints of microgrid island load demand, microgrid off-grid power balance, microgrid off-grid secondary power flow, microgrid off-grid main power flow, and microgrid island load reduction;

[0092] Among them, X k represents the local power generation of the microgrid when it is off-grid, y k It means that the microgrid can obtain electricity from the main grid when it is off-grid.

[0093] Let the first auxiliary variable Let the second auxiliary variable

[0094] According to y o,k , The simplified objective function is expressed as:

[0095]

[0096] The constraints are expressed as:

[0097]

[0098] Among them, l T y k represents the total power obtained by the i-th microgrid from the main grid during off-grid operation, l T y o,k It indicates that the i-th microgrid obtains total power from the main grid during normal operation.

[0099] As a preferred implementation, the simplified augmented Lagrangian function L of the objective function is expressed as:

[0100]

[0101] The augmented Lagrangian function L is simplified and expressed as:

[0102]

[0103] Among them, λ and μ represent Lagrange multipliers, γ represents penalty parameters, (λ k ) T The transpose of the matrix representing the value of λ corresponding to the microgrid when it is off-grid, Represents the transpose of the matrix of μ values ​​corresponding to the microgrid when operating off-grid.

[0104] As a preferred implementation, let the first original variable Second original variable

[0105] The simplified objective function is iteratively decomposed using the ADMM decomposition technique. At the fourth iteration, the steps are expressed as:

[0106] z[t+1]=argminL(z,w[t],λ[t],μ[t]);

[0107] Among them, z[t+1] represents the updated z, argmin L represents the minimum value of L, and w[t] represents w k or ∈ k , λ[t], μ[t] represent Lagrange multiplier variables;

[0108] w[t+1]=argminL(z[t+1],w,λ[t],μ[t]);

[0109] Among them, w[t+1] represents the updated w k or ∈ k , w represents w before update k or ∈ k ;

[0110]

[0111] Among them, λ k [t+1] represents the k [t] Update once, y o,k [t+1] represents the o,k [t] Update once, y o [t+1] represents the o [t] Update once, λ k [t] represents the Lagrangian multiplier λ variable of each microgrid in off-grid operation, y o,k [t] represents y o Auxiliary variable of [t], y o [t] represents the variable of the normal operation of the microgrid to obtain power from the main grid;

[0112]

[0113] in, Express Update once, Express Update once, express Update once, represents the Lagrange multiplier μ variable of the off-grid microgrid, express Auxiliary variables, A variable representing the power obtained from local generation in a normally operating microgrid.

[0114] As a preferred implementation, the simplified objective function is decomposed into N+1 optimization problems according to the augmented Lagrangian function, wherein the first problem is related to the normal operation of the microgrid, and is expressed as:

[0115]

[0116] in, Represents the transpose of the matrix of values ​​of μ corresponding to the microgrid when operating off-grid;

[0117] The constraints are expressed as:

[0118]

[0119] By fixing λ, μ are used to solve the first problem to obtain the optimal solution of the first problem

[0120] The remaining N problems are related to the microgrid when it is off-grid or islanded, and are expressed as:

[0121]

[0122] The constraints are expressed as:

[0123] st(x k ,y k ,∈ k )∈F k ;

[0124]

[0125] By fixing y o,k , λ, μ to solve the remaining N problems and obtain the optimal solution of the N problems

[0126] The present invention has the following beneficial effects:

[0127] The present invention constructs the objective function of the microgrid scheduling problem, introduces auxiliary variables to simplify it, then constructs the augmented Lagrangian function, and finally uses the ADMM technology to decompose the optimization problem and solve it, so that the optimal solution of the microgrid under different operating modes can be efficiently obtained, which can significantly improve the efficiency and accuracy of the microgrid scheduling, so that the microgrid can better meet the load demand and optimize energy utilization. It also considers a variety of operating modes of the microgrid, including normal operation, island operation and off-grid operation, and constructs corresponding constraints and objective functions for each mode, so that the present invention can be applied to various complex power grid environments and operating conditions, and improves the flexibility and reliability of the microgrid. The optimal solution obtained by solving is deployed on the computer node, wherein the optimal solution of the microgrid during normal operation is deployed on the computer main node, and the optimal solution of island operation and off-grid operation is deployed on the computer distributed node. This distributed computing method can make full use of computer resources, improve computing efficiency, and make the scheduling of the microgrid more intelligent and automated. BRIEF DESCRIPTION OF THE DRAWINGS

[0128] Figure 1 The present invention is implemented in the form of a flow chart.

[0129] Figure 2 It is a schematic diagram of computer scheduling of the present invention.

[0130] Figure 3 This is a model diagram of the microgrid operating in an isolated island according to the present invention. DETAILED DESCRIPTION

[0131] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0132] It should be understood that the step numbers used in this document are only for convenience of description and are not intended to limit the order in which the steps are executed.

[0133] It should be understood that the terms used in the present specification are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0134] The terms “include” and “comprising” indicate the presence of described features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or combinations thereof.

[0135] The term "and / or" means and includes any and all possible combinations of one or more of the associated listed items.

[0136] Embodiment 1:

[0137] See also Figure 1 , an optimal scheduling algorithm for a microgrid, comprising the following steps:

[0138] Determine the normal power balance constraints of the microgrid when the microgrid is operating normally;

[0139] Determine the microgrid island load reduction constraints and the microgrid island load demand constraints when the microgrid is operating in an islanded mode;

[0140] Determine the off-grid power balance constraint of the microgrid, the off-grid power generation output constraint of the microgrid, and the off-grid power generation ramp constraint of the microgrid when the microgrid is operating off-grid;

[0141] The objective function of the microgrid scheduling problem is constructed according to the microgrid normal power balance constraint, the microgrid island load reduction constraint, the microgrid island load demand constraint, the microgrid off-grid power balance constraint, the microgrid off-grid power generation output constraint and the microgrid off-grid power generation ramp constraint;

[0142] Setting a first auxiliary variable and a second auxiliary variable, and simplifying the objective function by using the first auxiliary variable and the second auxiliary variable;

[0143] Construct the augmented Lagrangian function of the simplified objective function;

[0144] Iteratively decompose the simplified objective function using the ADMM decomposition technique, and decompose the simplified objective function into N+1 optimization problems according to the augmented Lagrangian function;

[0145] By solving N+1 optimization problems, the optimal solutions are obtained when the microgrid is operating normally, when the microgrid is operating in an isolated island, and when the microgrid is operating off-grid.

[0146] See also Figure 2-3 , the optimal solution for the normal operation of the microgrid is deployed on the computer main node, and the optimal solution for the microgrid island operation and the microgrid off-grid operation is deployed on the computer distributed nodes, and the optimal scheduling of the microgrid is achieved through the computer;

[0147] Figure 2 The host computer in the embodiment corresponds to the computer main node in this embodiment, and the computers 1-N correspond to the computer distributed nodes in this embodiment; in this embodiment, it is only necessary to transmit the optimal solution to the host computer and the computers 1-N, and how to achieve the most efficient scheduling can be automatically achieved by the computer, which is not limited in this embodiment;

[0148] Figure 3 Here, Main grid represents the main power grid, and Microgrid 1-N represents N microgrids.

[0149] As a preferred implementation, the normal power balance constraint of the microgrid is expressed as:

[0150] Let the set of the i-th normally operating microgrid and the microgrids connected to it through transmission lines be N i ;

[0151] Let the i-th microgrid in normal operation transmit to N i The electric power vector is

[0152]

[0153] in, represents the power transmitted from the i-th microgrid to the j-th microgrid connected to it during normal operation, and o represents the preset variable when the microgrid is operating normally;

[0154] Let the total power generated locally by the i-th microgrid during normal operation be

[0155] Where l = [1,1,…,1] T is a column vector whose elements are all 1. The length of vector l is preset according to the operator's experience. T represents the transpose of l;

[0156] Let the power obtained by the i-th microgrid from the main grid during normal operation be

[0157] The power loss of the microgrid exchanging power with the main grid during normal operation of the i-th microgrid express:

[0158]

[0159] Among them, R oi represents the transmission line resistance between the i-th microgrid and the main grid during normal operation, α represents the power loss factor of the preset transformer, Indicates the preset operating voltage V o The square of

[0160] The power loss of the i-th microgrid in normal operation when exchanging power with the j-th microgrid connected to it express:

[0161]

[0162] Among them, R ij represents the transmission line resistance between the i-th microgrid in normal operation and the j-th microgrid connected to it, represents the square of the operating voltage V1 between the i-th microgrid in normal operation and the j-th microgrid connected to it;

[0163] according to and The normal power balance constraint of the microgrid during normal operation of the i-th microgrid is obtained:

[0164]

[0165] in, represents the power generated locally by the i-th microgrid during normal operation, represents the power exchange between the jth microgrid and the ith microgrid in normal operation, D i It represents the total power provided to customers by the i-th microgrid during normal operation;

[0166] D i =P i +E i ;

[0167] Among them, P i represents the power generated by distributed generation in the i-th microgrid during normal operation, E i It represents the power provided by the energy storage device during the normal operation of the i-th microgrid.

[0168] As a preferred implementation, the microgrid island load reduction constraint is expressed as:

[0169] Let the load demand ratio that needs to be reduced when the microgrid is disconnected from the main grid be ∈ k ; Wherein, k represents the preset variable when the microgrid is operating in an isolated island;

[0170] According to ∈ k Get the microgrid island load reduction constraint:

[0171]

[0172] in, Indicates the preset maximum allowable load reduction ratio.

[0173] As a preferred implementation, the microgrid island load demand constraint is expressed as:

[0174] Let the load demand of the microgrid when the hth island is running be (1-∈ k )D h ;

[0175] Let the set of the hth islanded microgrid and the microgrids connected to it through transmission lines be N h ;

[0176] According to (1-∈ k )D h The microgrid island load demand constraint of the microgrid when the hth island is operating is obtained:

[0177]

[0178] in, represents the power generated locally by the microgrid when the hth island is operating, represents the power exchange between the hth microgrid and the jth microgrid when the hth island is operating, represents the power loss of the hth microgrid when operating in an isolated island and the jth microgrid when exchanging power, D h It represents the power that the hth microgrid needs to provide when operating in an isolated island;

[0179] D h =L h +ΔE h ;

[0180] Among them, Lh represents the load demand of the microgrid when the hth island is operating, ΔE h It represents the power supplement amount of the energy storage system of the microgrid when the hth island is operating.

[0181] As a preferred implementation, the off-grid power balance constraint of the microgrid is expressed as:

[0182]

[0183] in, represents the power generated locally by the microgrid when the i-th microgrid is operating off-grid, represents the power exchange between the microgrid and the main grid during the i-th off-grid operation, represents the power loss of the microgrid exchanging electricity with the main grid when the i-th microgrid is operating off-grid, represents the power loss of the i-th off-grid microgrid when exchanging power with the j-th connected microgrid, represents the power exchange between the jth microgrid and the i-th microgrid when operating off-grid;

[0184] The off-grid power generation output constraint of the microgrid is expressed as:

[0185]

[0186] in, represents the total power generated by the local power generation of the microgrid when the i-th microgrid is operating off-grid, represents the maximum ramp rate of the generator of the microgrid when the i-th microgrid is operating off-grid, N represents a non-negative integer set;

[0187] The off-grid power generation ramp constraint of the microgrid is expressed as:

[0188]

[0189] in, Indicates the maximum ramp rate of the main grid generator, represents the total power obtained by the i-th microgrid from the main grid during off-grid operation, represents the total power obtained by the i-th microgrid from the main grid during normal operation, represents the power flow vector from the main grid to the microgrid when the hth island operates.

[0190] As a preferred implementation, let the load reduction vector ∈ D It is expressed as:

[0191] ∈ D =[∈ 1 D1,∈ 2 D2,...,∈i D i ,...,∈ N D N ] T ;

[0192] Among them, ∈ i D i represents the load reduction of the i-th microgrid;

[0193] The objective function is expressed as:

[0194]

[0195] Among them, min represents the minimum function, minC o (y o ) represents the minimum generation cost, y o It means that the microgrid can obtain electricity from the main grid when it is operating normally. represents the transmission cost, τ represents the preset weighting parameter, ||∈ D ||1 means ∈ D of -norm norm, calculated as:

[0196]

[0197] The constraints of the objective function include:

[0198] Normal power balance constraints of microgrid:

[0199]

[0200] Among them, st represents the format symbol of the optimization problem under the condition of...;

[0201] Microgrid normal secondary power flow constraints:

[0202]

[0203] in, represents the maximum allowable power flow between the i-th microgrid and the j-th microgrid;

[0204] Normal main power flow constraints of microgrid:

[0205]

[0206] in, represents the maximum power flow allowed by the i-th microgrid;

[0207] Microgrid island load demand constraints:

[0208]

[0209] Microgrid off-grid power balance constraints:

[0210]

[0211] Microgrid off-grid secondary power flow constraints:

[0212]

[0213] Main power flow constraints of off-grid microgrid:

[0214]

[0215] Microgrid island load reduction constraints:

[0216]

[0217] Microgrid off-grid power generation output constraints:

[0218]

[0219] Microgrid off-grid power generation ramp-up constraints:

[0220]

[0221] in, represents the power obtained by the i-th microgrid from the main grid when it is operating off-grid, It represents the power exchange between the i-th microgrid in off-grid operation and the j-th microgrid.

[0222] As a preferred embodiment, the simplified method of the objective function is:

[0223] Let the microgrid normal operation variable constraint set F o ={(X o ,y o )}, the F o It is subject to the constraints of normal power balance of microgrid, normal secondary power flow of microgrid and normal main power flow of microgrid;

[0224] Among them, X o It indicates that the microgrid is operating normally and generating local power;

[0225] Set of constraints on the microgrid off-grid operation variables The F k It is subject to the constraints of microgrid island load demand, microgrid off-grid power balance, microgrid off-grid secondary power flow, microgrid off-grid main power flow, and microgrid island load reduction;

[0226] Among them, X krepresents the local power generation of the microgrid when it is off-grid, y k It means that the microgrid can obtain electricity from the main grid when it is off-grid.

[0227] Let the first auxiliary variable Let the second auxiliary variable

[0228] According to y o,k , The simplified objective function is expressed as:

[0229]

[0230] The constraints are expressed as:

[0231]

[0232]

[0233] Among them, l T y k represents the total power obtained by the i-th microgrid from the main grid during off-grid operation, l T y o,k It indicates that the i-th microgrid obtains total power from the main grid during normal operation.

[0234] As a preferred implementation, the simplified augmented Lagrangian function L of the objective function is expressed as:

[0235]

[0236] The augmented Lagrangian function L is simplified and expressed as:

[0237]

[0238] Among them, λ and μ represent Lagrange multipliers, γ represents penalty parameters, (λ k ) T The transpose of the matrix representing the value of λ corresponding to the microgrid when it is off-grid, Represents the transpose of the matrix of μ values ​​corresponding to the microgrid when operating off-grid.

[0239] As a preferred implementation, let the first original variable Second original variable

[0240] The simplified objective function is iteratively decomposed using the ADMM decomposition technique. At the fourth iteration, the steps are expressed as:

[0241] Z[t+1]=argminL(Z,w[t],λ[t],μ[t]);

[0242] Among them, z[t+1] represents the updated z, argmin L represents the minimum value of L, and w[t] represents w k or ∈ k , λ[t], μ[t] represent Lagrange multiplier variables;

[0243] w[t+1]=argminL(z[t+1],w,λ[t],μ[t]);

[0244] Among them, w[t+1] represents the updated w k or ∈ k , w represents w before update k or ∈ k ;

[0245]

[0246] Among them, λ k [t+1] represents the k [t] Update once, y o,k [t+1] represents the o,k [t] Update once, y o [t+1] represents the o [t] Update once, λ k [t] represents the Lagrangian multiplier λ variable of each microgrid in off-grid operation, y o,k [t] represents y o Auxiliary variable of [t], y o [t] represents the variable of the normal operation of the microgrid to obtain power from the main grid;

[0247]

[0248] in, Express Update once, Express Update once, express Update once, represents the Lagrange multiplier μ variable of the off-grid microgrid, express Auxiliary variables, A variable representing the power obtained from local generation in a normally operating microgrid.

[0249] As a preferred implementation, the simplified objective function is decomposed into N+1 optimization problems according to the augmented Lagrangian function, wherein the first problem is related to the normal operation of the microgrid, and is expressed as:

[0250]

[0251] in, Represents the transpose of the matrix of values ​​of μ corresponding to the microgrid when operating off-grid;

[0252] The constraints are expressed as:

[0253]

[0254] By fixing y o,k , λ, μ to solve the first problem and obtain the optimal solution of the first problem

[0255] The remaining N problems are related to the microgrid when it is off-grid or islanded, and are expressed as:

[0256]

[0257] The constraints are expressed as:

[0258] st(x k ,y k ,∈ k )∈F k ;

[0259]

[0260] By fixing y o,k , λ, μ to solve the remaining N problems and obtain the optimal solution of the N problems

[0261] The optimal solution of the calculation steps in this embodiment can be obtained by using a computer, which is not limited in this embodiment.

[0262] Embodiment 2:

[0263] A microgrid optimal dispatching system, comprising:

[0264] Microgrid constraint module: determine the normal power balance constraint of the microgrid when the microgrid is operating normally; determine the microgrid island load reduction constraint and the microgrid island load demand constraint when the microgrid is operating in an isolated island; determine the microgrid off-grid power balance constraint, microgrid off-grid power generation output constraint and microgrid off-grid power generation climbing constraint when the microgrid is operating off-grid;

[0265] Objective function module: construct an objective function of the microgrid scheduling problem according to the microgrid normal power balance constraint, microgrid island load reduction constraint, microgrid island load demand constraint, microgrid off-grid power balance constraint, microgrid off-grid power generation output constraint and microgrid off-grid power generation ramp constraint;

[0266] Objective function simplification module: setting a first auxiliary variable and a second auxiliary variable, and simplifying the objective function by using the first auxiliary variable and the second auxiliary variable;

[0267] Microgrid objective function solving module: construct an augmented Lagrangian function of the simplified objective function; use ADMM decomposition technology to iteratively decompose the simplified objective function, and decompose the simplified objective function into N+1 optimization problems according to the augmented Lagrangian function; by solving the N+1 optimization problems, the optimal solution is obtained when the microgrid is operating normally, when the microgrid is operating in an island, and when the microgrid is operating off the grid;

[0268] Microgrid dispatching module: The optimal solution for the normal operation of the microgrid is deployed on the computer main node, and the optimal solution for the microgrid island operation and the microgrid off-grid operation is deployed on the computer distributed nodes, and the optimal dispatch of the microgrid is achieved through the computer.

[0269] The system is used to implement the method in Example 1, which will not be described in detail here.

[0270] In the embodiments of the present application, "at least one" refers to one or more, and "more than one" refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent the existence of A alone, the existence of A and B at the same time, and the existence of B alone. Among them, A and B can be singular or plural. The character " / " generally indicates that the previous and next associated objects are in an "or" relationship. "At least one of the following" and similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one of a, b and c can be represented by: a, b, c, a and b, a and c, b and c, or a and b and c, where a, b, c can be single or multiple.

[0271] Those of ordinary skill in the art will appreciate that the various units and algorithm steps described in the embodiments disclosed herein can be implemented in a combination of electronic hardware, computer software, and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0272] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0273] In several embodiments provided in the present application, if any function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory; hereinafter referred to as: ROM), random access memory (Random Access Memory; hereinafter referred to as: RAM), disk or optical disk, and other media that can store program codes.

[0274] The above descriptions are merely embodiments of the present invention and are not intended to limit the patent scope of the present invention. Any equivalent structure or equivalent process transformation made using the contents of the present invention specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present invention.

Claims

1. A microgrid optimal scheduling algorithm, characterized in that: The following steps are involved: Determine the normal power balance constraints of the microgrid when the microgrid is operating normally; Determine the microgrid island load reduction constraints and the microgrid island load demand constraints when the microgrid is operating in an islanded mode; Determine the off-grid power balance constraint of the microgrid, the off-grid power generation output constraint of the microgrid, and the off-grid power generation ramp constraint of the microgrid when the microgrid is operating off-grid; The objective function of the microgrid scheduling problem is constructed according to the microgrid normal power balance constraint, the microgrid island load reduction constraint, the microgrid island load demand constraint, the microgrid off-grid power balance constraint, the microgrid off-grid power generation output constraint and the microgrid off-grid power generation ramp constraint; Setting a first auxiliary variable and a second auxiliary variable, and simplifying the objective function by using the first auxiliary variable and the second auxiliary variable; Construct the augmented Lagrangian function of the simplified objective function; Iteratively decompose the simplified objective function using the ADMM decomposition technique, and decompose the simplified objective function into N+1 optimization problems according to the augmented Lagrangian function; By solving N+1 optimization problems, the optimal solutions are obtained when the microgrid is operating normally, when the microgrid is operating in an isolated island, and when the microgrid is operating off-grid. The optimal solution for the normal operation of the microgrid is deployed on the computer main node, and the optimal solution for the microgrid island operation and the microgrid off-grid operation is deployed on the computer distributed nodes, and the optimal scheduling of the microgrid is achieved through the computer.

2. The microgrid optimal scheduling algorithm according to claim 1, characterized in that: The normal power balance constraint of the microgrid is expressed as: Let the set of the i-th normally operating microgrid and the microgrids connected to it through transmission lines be N i ; Let the i-th microgrid in normal operation transmit to N i The electric power vector is in, represents the power transmitted from the i-th microgrid to the j-th microgrid connected to it during normal operation, and o represents the preset variable when the microgrid is operating normally; Let the total power generated locally by the i-th microgrid during normal operation be Where l = [1, 1, …, 1] T is a column vector whose elements are all 1. The length of vector l is preset according to the operator's experience. T represents the transpose of l; Let the power obtained by the i-th microgrid from the main grid during normal operation be The power loss of the microgrid exchanging power with the main grid during normal operation of the i-th microgrid express: Among them, R oi represents the transmission line resistance between the i-th microgrid and the main grid during normal operation, α represents the power loss factor of the preset transformer, Indicates the preset operating voltage V o The square of The power loss of the i-th microgrid in normal operation when exchanging power with the j-th microgrid connected to it express: Among them, R ij represents the transmission line resistance between the i-th microgrid in normal operation and the j-th microgrid connected to it, represents the square of the operating voltage V1 between the i-th microgrid in normal operation and the j-th microgrid connected to it; according to and The normal power balance constraint of the microgrid during normal operation of the i-th microgrid is obtained: in, represents the power generated locally by the i-th microgrid during normal operation, represents the power exchange between the jth microgrid and the ith microgrid in normal operation, D i It represents the total power provided to customers by the i-th microgrid during normal operation; D i =P i +E i ; Among them, P i represents the power generated by distributed generation in the i-th microgrid during normal operation, E i It represents the power provided by the energy storage device during the normal operation of the i-th microgrid.

3. The microgrid optimal scheduling algorithm according to claim 1, characterized in that: The microgrid island load reduction constraint is expressed as: Let the load demand ratio that needs to be reduced when the microgrid is disconnected from the main grid be ∈ k ; Wherein, k represents the preset variable when the microgrid is operating in an isolated island; According to ∈ k Get the microgrid island load reduction constraint: in, Indicates the preset maximum allowable load reduction ratio.

4. The microgrid optimal scheduling algorithm according to claim 2 or 3, characterized in that: The microgrid island load demand constraint is expressed as: Let the load demand of the microgrid when the hth island is running be (1-∈ k )D h ; Let the set of the hth islanded microgrid and the microgrids connected to it through transmission lines be N h ; According to (1-∈ k )D h The microgrid island load demand constraint of the microgrid when the hth island is operating is obtained: in, represents the power generated locally by the microgrid when the hth island is operating, represents the power exchange between the hth microgrid and the jth microgrid when the hth island is operating, represents the power loss of the hth microgrid when operating in an isolated island and the jth microgrid when exchanging power, D h It represents the power that the hth microgrid needs to provide when operating in an isolated island; D h =L h +ΔE h ; Among them, L h represents the load demand of the microgrid when the hth island is operating, ΔE h It represents the power supplement amount of the energy storage system of the microgrid when the hth island is operating.

5. The microgrid optimal scheduling algorithm according to claim 4 is characterized in that: The off-grid power balance constraint of the microgrid is expressed as: in, represents the power generated locally by the microgrid when the i-th microgrid is operating off-grid, represents the power exchange between the microgrid and the main grid during the i-th off-grid operation, represents the power loss of the microgrid exchanging electricity with the main grid when the i-th microgrid is operating off-grid, represents the power loss of the i-th off-grid microgrid when exchanging power with the j-th connected microgrid, represents the power exchange between the jth microgrid and the i-th microgrid when operating off-grid; The off-grid power generation output constraint of the microgrid is expressed as: in, represents the total power generated by the local power generation of the microgrid when the i-th microgrid is operating off-grid, represents the maximum ramp rate of the generator of the microgrid when the i-th microgrid is operating off-grid, N represents a non-negative integer set; The off-grid power generation ramp constraint of the microgrid is expressed as: in, Indicates the maximum ramp rate of the main grid generator, represents the total power obtained by the i-th microgrid from the main grid during off-grid operation, represents the total power obtained by the i-th microgrid from the main grid during normal operation, represents the power flow vector from the main grid to the microgrid when the hth island operates.

6. The microgrid optimal scheduling algorithm according to claim 5, characterized in that: Let the load reduction vector of the microgrid ∈ D It is expressed as: ∈ D =[∈ 1 D1,∈ 2 D2,...,∈ i D i ,...,∈ N D N ] T ; Among them, ∈ i D i represents the load reduction of the i-th microgrid; The objective function is expressed as: Among them, min represents the minimum function, minC o (y o ) represents the minimum generation cost, y o It means that the microgrid can obtain electricity from the main grid when it is operating normally. represents the transmission cost, τ represents the preset weighting parameter, ||∈ D ||1 means ∈ D of -norm norm, calculated as: The constraints of the objective function include: Normal power balance constraints of microgrid: Among them, st represents the format symbol of the optimization problem under the condition of...; Microgrid normal secondary power flow constraints: in, represents the maximum allowable power flow between the i-th microgrid and the j-th microgrid; Normal main power flow constraints of microgrid: in, represents the maximum power flow allowed by the i-th microgrid; Microgrid island load demand constraints: Microgrid off-grid power balance constraints: Microgrid off-grid secondary power flow constraints: Main power flow constraints of off-grid microgrid: Microgrid island load reduction constraints: Microgrid off-grid power generation output constraints: Microgrid off-grid power generation ramp-up constraints: in, represents the power obtained by the i-th microgrid from the main grid when it is operating off-grid, It represents the power exchange between the i-th microgrid in off-grid operation and the j-th microgrid.

7. The microgrid optimal scheduling algorithm according to claim 6, characterized in that: The simplified method of the objective function is: Let the microgrid normal operation variable constraint set F o ={(X o ,y o )}, the F o It is subject to the constraints of normal power balance of microgrid, normal secondary power flow of microgrid and normal main power flow of microgrid; Among them, X o It indicates that the microgrid is operating normally and generating local power; Set of constraints on the microgrid off-grid operation variables The F k It is subject to the constraints of microgrid island load demand, microgrid off-grid power balance, microgrid off-grid secondary power flow, microgrid off-grid main power flow, and microgrid island load reduction; Among them, X k represents the local power generation of the microgrid when it is off-grid, y k It means that the microgrid can obtain electricity from the main grid when it is off-grid. Let the first auxiliary variable Let the second auxiliary variable According to y o,k , The simplified objective function is expressed as: The constraints are expressed as: Among them, l T y k represents the total power obtained by the i-th microgrid from the main grid during off-grid operation, l T y o,k It indicates that the i-th microgrid obtains total power from the main grid during normal operation.

8. The microgrid optimal scheduling algorithm according to claim 7, characterized in that: The simplified augmented Lagrangian function L of the objective function is expressed as: The augmented Lagrangian function L is simplified and expressed as: Among them, λ and μ represent Lagrange multipliers, γ represents penalty parameters, (λ k ) T The transpose of the matrix representing the value of λ corresponding to the microgrid when it is off-grid, Represents the transpose of the matrix of μ values ​​corresponding to the microgrid when operating off-grid.

9. The microgrid optimal scheduling algorithm according to claim 8, characterized in that: Let the first original variable Second original variable The simplified objective function is iteratively decomposed using the ADMM decomposition technique. At the fourth iteration, the steps are expressed as: Z[t+1]=argminL(Z,w[t],λ[t],μ[t]); Among them, z[t+1] represents the updated z, argmin L represents the minimum value of L, and w[t] represents w k or ∈ k , λ[t], μ[t] represent Lagrange multiplier variables; w[t+1]=argminL(z[t+1],w,λ[t],μ[t]); Among them, w[t+1] represents the updated w k or ∈ k , w represents w before update k or ∈ k ; Among them, λ k [t+1] represents the k [t] Update once, y o,k [t+1] represents the o,k [t] Update once, y o [t+1] represents the o [t] Update once, λ k [t] represents the Lagrangian multiplier λ variable of each microgrid in off-grid operation, y o,k [t] represents y o Auxiliary variable of [t], y o [t] represents the variable of the normal operation of the microgrid to obtain power from the main grid; in, Express Update once, Express Update once, express Update once, represents the Lagrange multiplier μ variable of the off-grid microgrid, express Auxiliary variables, A variable representing the power obtained from local generation in a normally operating microgrid.

10. The microgrid optimal dispatching algorithm according to claim 9, characterized in that: According to the augmented Lagrangian function, the simplified objective function is decomposed into N+1 optimization problems, wherein the first problem is related to the normal operation of the microgrid and is expressed as: in, Represents the transpose of the matrix of values ​​of μ corresponding to the microgrid when operating off-grid; The constraints are expressed as: By fixing y o,k , λ, μ to solve the first problem and obtain the optimal solution of the first problem The remaining N problems are related to the microgrid when it is off-grid or islanded, and are expressed as: The constraints are expressed as: s.t.(x k ,y k ,∈ k )∈F k ; By fixing y o,k , λ, μ to solve the remaining N problems and obtain the optimal solution of the N problems

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