Distribution and micro-grid cooperative operation method and system based on micro-grid operation domain, terminal and medium

Abstract

The invention relates to a micro-grid operation domain-based distribution and micro-grid cooperative operation method and system, a terminal and a medium, and the method comprises the steps: carrying out the aggregation of a photovoltaic unit, an energy storage device and a non-black-start unit in a transformer area according to the incidence relation among the active power, reactive power and equipment capacity of various types of equipment in the transformer area, so as to build an aggregation model of the same type of equipment; the parameters of the established aggregation model of the same equipment are constrained through a graphical method, so that a microgrid operation domain model is obtained; taking the maximum joint active power and the minimum microgrid topology change as targets, constructing joint constraints by taking the connection topology, the equipment access and the switch state of the microgrid, and establishing a micro-power distribution cooperative operation model by taking each microgrid operation domain model as a unit; solving the distribution-micro collaborative elastic operation model, and obtaining a load recovery initial scheme of the power distribution network within the fault time; and establishing a power generation planning model, and solving the power generation planning model according to the load recovery state generated by the initial scheme to obtain a power generation plan of each distributed resource.

Description

Technical Field

[0001] The present invention relates to a field, and more specifically, to a method, system, terminal and medium for coordinated operation of distribution and microgrid based on a microgrid operation domain. Background Art

[0002] The increasing depletion of traditional energy sources and the deteriorating ecological environment urgently require the vigorous development of renewable clean energy sources such as wind and solar power in modern power systems. Renewable clean energy is typically integrated into the power grid in two ways: large-scale integration for centralized transmission, and decentralized integration for local consumption. Renewable energy, through small-capacity, high-density, distributed integration into the distribution network, is poised for rapid growth in the short term and will gradually form a new energy distribution network with high penetration.

[0003] Microgrids are the main carriers for high-density distributed power access in the future. Their large-scale development trend will inevitably make the main operation and control objects of future intelligent distribution systems include a large number of microgrid systems of different types. It is urgent to explore new operation and control mechanisms to adapt to the needs of the rapid development of new energy microgrid technologies.

[0004] In terms of quantifying the grid's regulation capacity with the access of massive flexible resources, most existing studies focus on analyzing the flexibility of distribution networks, and the quantification of the adjustable potential of microgrids needs further research; in terms of coordinated grid regulation, the coordinated operation between distribution and microgrids is mostly based on distributed algorithms, which require repeated iterations to ensure the consistency of the optimal strategy, which is not conducive to simplifying the distribution-microgrid coordination process and improving scheduling efficiency.

[0005] In recent years, global warming has led to frequent extreme weather events and significant meteorological extremes. The frequent occurrence of various extreme weather events has highlighted the importance of natural disaster prevention and has prompted research into how to quickly restore power after major power outages. Using operational domain analysis technology, distributed computing of microgrid operational domains can reduce the computational burden of developing fault recovery strategies. Existing distributed microgrid collaborative operation technologies typically centralize fault recovery strategies, with the distribution master station bearing the majority of the computational burden. As the installed capacity of distributed resources in the distribution network increases, the amount of data that the distribution master station must process and analyze in real time has increased dramatically, posing a significant challenge to the system's real-time performance and accuracy.

[0006] In response to the above problems, there is an urgent need for a distribution and micro-cooperative operation method, system, terminal and medium based on the microgrid operation domain. Summary of the Invention

[0007] In order to address the deficiencies in the prior art, the present invention provides a method, system, terminal and medium for coordinated operation of distribution and microgrid based on the microgrid operation domain, which can reduce the amount of data that the distribution master station needs to process and analyze in real time, and reduce the computational burden of the flexible operation of distribution and microgrid coordination.

[0008] The present invention adopts the following technical solutions.

[0009] The first aspect of the present invention relates to a distribution and micro-cooperative operation method based on a microgrid operation domain, and the method includes the following steps: S1: According to the correlation between the active power, reactive power and equipment capacity of various types of equipment in the substation, the photovoltaic units, energy storage devices and non-black start units in the substation are aggregated to establish an aggregation model of the same equipment; S2: The parameters of the aggregation model of the same equipment established by S1 are constrained by a graphical method to obtain a microgrid operation domain model; S3: With the goal of maximizing the joint active power and minimizing the microgrid topology change, a joint constraint is constructed based on the connection topology, equipment access and switch status of the microgrid, and a distribution and micro-cooperative operation model is established with each microgrid operation domain model as a unit; S4: Solving the distribution and micro-cooperative elastic operation model to obtain the initial load recovery plan of the distribution network within the fault time; S5: Establishing a power generation planning model, and solving the power generation planning model according to the load recovery state generated by the initial plan to obtain the power generation plan of each distributed resource.

[0010] Based on the correlation between the active power, reactive power, and capacity of various types of equipment in the substation, the photovoltaic units, energy storage devices, and non-black start units in the substation are aggregated to establish an aggregation model for the same type of equipment, including:

[0011] The output power expression of the photovoltaic group after aggregation is:

[0012]

[0013] Where, is the total installed capacity of photovoltaic units pv in area i;

[0014] is the reactive power output of the PV units in the grid area i at time t;

[0015] is the active power output of the PV units in the grid area i at time t;

[0016] is the power prediction of the photovoltaic unit in the station area i at time t;

[0017] Based on the correlation between the active power, reactive power, and capacity of various types of equipment in the substation, the photovoltaic units, energy storage devices, and non-black start units in the substation are aggregated to establish an aggregation model for the same type of equipment, including:

[0018] The output power expression of the energy storage device group after aggregation is:

[0019]

[0020]

[0021] Where, is the active power output of the energy storage device in substation i at time t;

[0022] and are the installed capacity of the energy storage device in the substation i;

[0023] and are the maximum electric energy that can be absorbed and released by the energy storage unit in substation i when a fault occurs;

[0024] Δt is the length of the time period between adjacent decision points,

[0025] d is the decision point number,

[0026] T is the length of the expected failure time;

[0027] Based on the correlation between the active power, reactive power, and capacity of various types of equipment in the substation, the photovoltaic units, energy storage devices, and non-black start units in the substation are aggregated to establish an aggregation model for the same type of equipment, including:

[0028] The output power expression of the non-black start generator group after aggregation is:

[0029]

[0030] Where, and is the active and reactive power output of the non-black start units in the substation i at time t;

[0031] is the installed capacity of non-black start units in substation i;

[0032] is the start-up time of non-black start units in substation i;

[0033] t is the current time, The time it takes for non-black start units in station i to absorb the starting power;

[0034] M is the preset maximum value,

[0035] and is the 0-1 state variable of the non-black start unit in the station i, Indicates that all non-black start units in substation i are started at time t. Indicates that none of the non-black start units in the station area i were started at time t. It means that all non-black start units in the area i can output power at time t. Indicates that the non-black start units in the station area i cannot output power at time t; X i,t Is a 0-1 state variable indicating whether the station i is restored at time t, X i,t =1 means that the station area i is restored at time t, X i,t =0 means that station i has not recovered at time t.

[0036] By using a graphical method to constrain the parameters of the aggregation model of the same type of equipment established by S1, the microgrid operation domain model is obtained, including:

[0037] Construct a multidimensional independent variable based on the number of similar devices in the aggregation model of similar devices established in S1;

[0038] Using the inequality constraints in the aggregation model of the same equipment established by S1, a linear programming problem with multi-dimensional independent variables is constructed;

[0039] The linear programming problem is solved according to a graphical method to obtain the feasible domain of the aggregation model of the same type of equipment established in S1.

[0040] The goal is to maximize the joint active power and minimize the change in microgrid topology. Joint constraints are constructed based on the microgrid's connection topology, device access, and switch status. A distribution-microgrid collaborative operation model is established with each microgrid operation domain model as a unit, including:

[0041] The objective function of the micro-cooperative operation model is:

[0042]

[0043] X i,t Represents the state of area i at time t, N is the number of areas

[0044] C i is the load weight coefficient,

[0045] It is the dispatching power under the cooperative operation model of distribution micro;

[0046] b ij,t Represents the topological connection relationship between stations ij at time t.

[0047] The goal is to maximize joint active power and minimize microgrid topology changes, construct joint constraints based on the microgrid's connection topology, device access, and switch status, and establish a distribution-microgrid collaborative elastic operation model with each microgrid operation domain model as a unit, including:

[0048] The constraints of the micro-cooperative elastic operation model are:

[0049] (p i,t ,q i,t )∈ΩDC,net

[0050] b ij,t ≤a ij

[0051] h ij1,t =b ij,t

[0052]

[0053] k[2+log2(N-1)] max

[0054] 1<k≤k max

[0055]

[0056] h ijk,t =h jik,t

[0057] (c ij(k-1)q,t -1)M≤h iq(k-1),t +h qj(k-1),t -1≤c ij(k-1)q,t M

[0058]

[0059] (g ij,t -1)M≤y ij,t -x j,t ≤(1-g ij,t )M

[0060] -g ij,t M≤y ij,t ≤g ij,t M

[0061] (g ij,t -1)M≤G ij,t -p j,t ≤(1-g ij,t )M

[0062] -g ij,t M≤G ij,t ≤g ij,t M

[0063]

[0064] (A ij,t -1)M≤G ii,t -G ij,t ≤A ij,t M

[0065]

[0066] Where, (p i,t ,q i,t ) is the active and reactive interaction power between substation i and the upper grid;

[0067] Ω DC,net is the area interaction power set,

[0068] a ij It is a tie line indicating whether there is a section switch or circuit breaker between the substations i and j;

[0069] h ij1,t h iqk,t Initialization of h ijkmax,t for At the maximum number of iterations k max The value of

[0070] k is the number of iterations, h iqk,t To describe c ijqk,t The intermediate variable, q is another area different from ij;

[0071] g ij,t Indicates whether the substation j is located in the microgrid i at time t;

[0072] c ijqk,t To calculate h at time t ijk,t → The intermediate amount;

[0073] x i,t represents the total number of tie lines connected to the station area i at time t;

[0074] y ij,t is the total number of tie lines from substation j to microgrid i;

[0075] G ij,t represents the active power contributed by substation j to microgrid i at time t;

[0076] P ij,t and Q ij,t represents the active and reactive power flowing from substation i to substation j at time t;

[0077] A ij,t Indicates whether the active power provided by substation j to microgrid i is the largest at time t;

[0078] It represents the square of the bus voltage amplitude of the station i at time t;

[0079] is the square of the rated value of the bus voltage in station i;

[0080] R ij represents the resistance of the tie line between area i and area j; Xij represents the reactance of the tie line between substations i and j;

[0081] and are the squares of the lower and upper voltage limits of substation i, respectively.

[0082] A power generation planning model is established and solved based on the load recovery state generated by the initial plan to obtain the power generation plan for each distributed resource, including:

[0083] The objective function of the power generation planning model is:

[0084]

[0085] Where, is the active power output of the b-th PV unit in the grid area i at time t;

[0086] is the active power output of the cth energy storage device in the grid area i at time t;

[0087] is the active power output of the e-th non-black start unit in the station i at time t;

[0088] The constraints of the power generation planning model are:

[0089]

[0090] Solve the power generation planning model to obtain the active power of each device.

[0091] The second aspect of the present invention relates to a distribution-micro-cooperative operation system based on a microgrid operation domain using the method described in the first aspect of the present invention, the system including an aggregation module, a constraint module, a collaboration module, a recovery module and a planning module; the aggregation module is used to aggregate photovoltaic units, energy storage devices and non-black start units in the substation area according to the correlation between the active power, reactive power and equipment capacity of various types of equipment in the substation area to establish an aggregation model of the same type of equipment; the constraint module is used to constrain the parameters of the aggregation model of the same type of equipment established by S1 through a graphical method, thereby obtaining a microgrid operation domain model; the collaboration module is used to construct joint constraints based on the connection topology, equipment access and switch status of the microgrid with the goal of maximizing the joint active power and minimizing the microgrid topology change, and establish a distribution-micro-cooperative operation model with each microgrid operation domain model as a unit; the recovery module is used to solve the distribution-micro-cooperative elastic operation model to obtain an initial load recovery plan for the distribution network within the fault time; the planning module is used to establish a power generation planning model, and solve the power generation planning model based on the load recovery state generated by the initial plan to obtain the power generation plan of each distributed resource. A third aspect of the present invention relates to a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; and the processor is used to operate according to the instructions to execute the steps of the method described in the first aspect of the present invention.

[0092] A fourth aspect of the present invention relates to a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in the first aspect of the present invention.

[0093] The beneficial effect of the present invention is that, compared with the prior art, the method, system, terminal and medium for coordinated operation of distribution and microgrid based on the microgrid operation domain in the present invention can reduce the amount of data that the distribution master station needs to process and analyze in real time, and reduce the computational burden of the flexible operation of distribution and microgrid coordination.

[0094] The beneficial effects of the present invention also include:

[0095] The invention utilizes the operation domain analysis technology to reduce the amount of data that the distribution master station needs to process and analyze in real time through distributed computing of the microgrid operation domain, thereby improving computing efficiency and reducing the difficulty of solving the distribution network fault recovery problem, thereby reducing the computational burden of formulating fault recovery strategies, improving the applicability and flexibility of the model in dealing with distribution network fault recovery problems considering large-scale renewable energy grid connection, enhancing the resilience of the distribution network, and providing theoretical support for the operation control of building a strong power grid.

[0096] The present invention realizes distributed computing of the microgrid operating domain by analyzing the microgrid operating domain and aggregating distributed resources. By establishing a microgrid operating domain model, the computational burden of formulating fault recovery strategies is reduced, and the amount of data that needs to be processed and analyzed in real time by the distribution master station is reduced. The balance between the real-time performance and accuracy of the distribution system during the fault recovery process is maintained, thereby improving the flexibility of the distribution system operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0097] Figure 1 It is a flow chart of the distribution network fault recovery method in the present invention;

[0098] Figure 2 is a diagram of a power grid structure used in an embodiment of the present invention;

[0099] Figure 3 is a simplified diagram of the power grid structure according to an embodiment of the present invention;

[0100] Figure 4 is a schematic diagram of a load recovery solution obtained in an embodiment of the present invention;

[0101] Figure 5 This is a schematic diagram of the recovery of a photovoltaic unit after a fault over time according to an embodiment of the present invention;

[0102] Figure 6 is a schematic diagram of the recovery of the energy storage device after a fault over time according to an embodiment of the present invention;

[0103] Figure 7 This is a schematic diagram of the recovery of a non-black start unit after a fault according to an embodiment of the present invention over time. DETAILED DESCRIPTION

[0104] In order to make the purpose, technical solutions and advantages of the present invention clearer and more accurate, the technical solutions of the present invention are described in detail below through multiple specific embodiments. The embodiments used in the present invention are only used to explain the present invention and are not intended to limit the content of the present invention.

[0105] A first aspect of the present invention relates to a method for coordinated operation of a distribution network and a microgrid based on a microgrid operation domain, comprising the following steps:

[0106] S1: Aggregate the photovoltaic units, energy storage devices and non-black start units in the substation area respectively;

[0107] S2: Based on the aggregation model established in S1, a microgrid operation domain model is established;

[0108] S3: Based on the microgrid operation domain model established in S2, a distribution-microgrid collaborative elastic operation model is established;

[0109] S4: Call the solver to solve the model established in steps S2 and S3 to obtain the load recovery plan of the distribution network within the fault time;

[0110] S5: Establish a power generation planning model and solve it according to the load recovery plan to obtain the power generation plan of each distributed resource. Combined with the load recovery plan, perform coordinated elastic operation of distribution and micro-resources.

[0111] Preferably, the S1 further includes:

[0112] A1: Establish a photovoltaic unit aggregation model within the substation:

[0113] Assuming that there are B photovoltaic units in the grid area i, the actual power supply capacity of the photovoltaic unit group in the grid area is expressed as:

[0114]

[0115] Where: is the installed capacity of the b-th photovoltaic unit pv in the station area i; is the active power output of the b-th PV unit in the grid area i at time t; is the reactive power output of the b-th PV unit in the grid area i at time t; is the upper limit of the power factor angle of distributed resources; is the power forecast of the b-th PV unit in the station area i at time t, in pu; X i,t-1 represents the state of station i at time t-1, X i,t-1 =1 means that the station i is restored at time t-1, X i,t-1 =0 means that the station area i has not recovered at time t-1. When t-1=0, X i,0 =0.

[0116] Define the relevant parameters during the photovoltaic unit aggregation process:

[0117]

[0118] Pick The output power expression of the photovoltaic group after aggregation is:

[0119]

[0120] A2: Establish an aggregation model of energy storage devices within the substation area:

[0121] Assuming that there are C energy storage devices in substation i, the actual power supply capacity of the energy storage device group in the substation is expressed as:

[0122]

[0123] Where: is the installed capacity of the cth energy storage device in substation i; is the active power output of the cth energy storage device in the grid area i at time t; is the reactive power output of the cth energy storage device in substation i at time t; is the maximum energy that can be absorbed by the cth energy storage unit in the station i when a fault occurs; is the maximum amount of energy that can be released by the cth energy storage unit in substation i when a fault occurs; Δt represents the length of the time interval between adjacent decision points, i.e., the decision step size; and T is the expected length of the fault time.

[0124] Define the relevant parameters during the energy storage device aggregation process:

[0125]

[0126] Pick The output power expression of the energy storage device group after aggregation is:

[0127]

[0128] A3: Establish an aggregation model of non-black start units in the substation area:

[0129] Assuming that there are E non-black start units in the substation i, the actual power supply capacity of the non-black start unit group in the substation is expressed as:

[0130]

[0131] Where: is the installed capacity of the e-th non-black start unit in substation i; is the active power output of the e-th non-black start unit in the station i at time t; is the reactive power output of the e-th non-black start unit in the grid i at time t; and are all 0-1 variables representing the status of the e-th non-black start unit in the station i at time t. It means that the e-th non-black start unit in the station i is started at time t. Indicates that the e-th non-black start unit in the station i did not start at time t. It indicates that the e-th non-black start unit in the station area i can output electric energy at time t. Indicates that the e-th non-black start unit in the substation i cannot output power at time t; M is the preset maximum value; is the start-up time of the e-th non-black start unit in substation i; The time it takes for the e-th non-black start unit in the station i to absorb the starting power; is the starting power of the e-th non-black start unit in the station i; is the maximum ramp-down rate of the e-th non-black start unit in the station i; It is the maximum ramp rate of the e-th non-black start unit in substation i.

[0132] Define the relevant parameters during the aggregation process of non-black start units:

[0133]

[0134] Pick The output power expression of the non-black start generator group after aggregation is:

[0135]

[0136] Preferably, in step A1, the process of aggregating photovoltaic units in the area is as follows:

[0137] When B=2, the aggregated output power of the photovoltaic unit is expressed as:

[0138]

[0139] consider Based on (2) and (3) The feasible region of The feasible domain of:

[0140]

[0141] consider Based on (2) and (4) The feasible region of The feasible domain of:

[0142]

[0143] From (5), we can see that (7) is equivalent to (44), which is The feasible domain of ; From (5, 6), we can see that (8) is equivalent to (45), which is feasible domain.

[0144] When B>2, the aggregated output power of the photovoltaic unit is expressed as:

[0145]

[0146] and Satisfy (7) and (8) respectively, Satisfy (2) to (4). By graphical method, we can give and The value range of is:

[0147]

[0148] Where:

[0149]

[0150] based on and The necessary conditions for (47) and (48) are obtained respectively:

[0151]

[0152] From (5), we can see that (7) is equivalent to (49), and Within the range of values; From (5, 6), we can see that (8) is equivalent to (45), and is located is within the value range of .

[0153] Preferably, in step A2, the process of aggregating the energy storage devices in the platform area is as follows:

[0154] When C=2, the output power of the energy storage device after aggregation is expressed as:

[0155]

[0156] consider Based on (10) to (12) The feasible region is given by graphical method The value range of is:

[0157]

[0158] Based on (10) to (13) The feasible region is given by graphical method The value range of is:

[0159]

[0160] Where:

[0161] Based on (17), we get A set of necessary linearization conditions for is:

[0162]

[0163] Based on (17), we get A set of necessary linearization conditions for is:

[0164]

[0165] From (16), we can see that (52) is equivalent to (18); (54, 56) is equivalent to (19); based on (14, 15), (55, 57) can be equivalently transformed into (20).

[0166] When C>2, the output power of the energy storage device after aggregation is expressed as:

[0167]

[0168] and Satisfy (18) to (20), Satisfies (10)~(13). The graphical method gives and The value range of is:

[0169]

[0170] Where:

[0171]

[0172]

[0173] based on The necessary conditions for (59) can be obtained:

[0174]

[0175] From (16), we can see that (61) is equivalent to (18).

[0176] Based on (17), a set of necessary conditions for (60) are given:

[0177]

[0178] (62) is equivalent to (19); based on (14, 15), (63) can be equivalently transformed into (20).

[0179] Preferably, in step A3, the process of aggregating non-black start units in the substation area is as follows:

[0180] When E=2, the aggregated output power of the non-black start units is expressed as:

[0181]

[0182] Based on (22) and (23) The feasible region is given by graphical method The value range of is:

[0183]

[0184] Where:

[0185]

[0186] consider A necessary condition for (65) is:

[0187]

[0188] From (29), we can see that (37) and (66) are equivalent.

[0189] The startup strategy of NBSU is formulated based on (34) to (36): the NBSU units absorb power and start at the same time, and output power at the same time, so that (34) to (36) are established, and thus (26) can be transformed into (40).

[0190] Table 1 Upper limit change table (E=2)

[0191]

[0192] Table 2 Lower limit change table (E=2)

[0193]

[0194] Based on (30), (31), Table 1 and Table 2, linearization The value range of is:

[0195]

[0196] Where:

[0197] (41) is equivalent to (67), and (42) is equivalent to (68).

[0198] When E>2, the aggregated output power of the non-black start units is expressed as:

[0199]

[0200] and Satisfy (37) to (42), and Satisfies (22) to (28). Given by the graphical method The value range of is:

[0201]

[0202] Where:

[0203] consider and Find a necessary condition for (70):

[0204]

[0205] Based on (29), (37) and (71) are equivalent.

[0206] Given different states The value range of is shown in Table 3 and Table 4

[0207] Table 3 Upper limit change table (E>2)

[0208]

[0209] Table 4 Lower limit change table (E>2)

[0210]

[0211]

[0212] In the table:

[0213] Based on (30), (31), Table 3 and Table 4, linearization The value range of , we can get (41) and (42).

[0214] Preferably, in step S2, the process of establishing the microgrid operation domain model is as follows:

[0215] Based on (7) and (18), the range of reactive power values ​​after the photovoltaic system and energy storage device are aggregated is given by graphical method:

[0216]

[0217] Based on (37) and (72), the reactive power range of the photovoltaic unit, energy storage device and non-black start unit after aggregation is given by graphical method:

[0218]

[0219] The power balance constraints that each substation must meet are as follows:

[0220]

[0221] Where: p i,t is the active interaction power between substation i and the upper grid, is the active power demand of station i at time t, q i,t is the reactive interaction power between the station area i and the upper grid, is the reactive power demand of station i at time t.

[0222] Substituting (75) into (73), (73) can be equivalently transformed into:

[0223]

[0224] The expression of the established microgrid operation domain model is as follows:

[0225] Ω DC,net ={(p i,t ,q i,t )|stEq.7,Eq.8,Eq.18~Eq.20,Eq.37~Eq.42,Eq.74,Eq.76}

[0226] Preferably, the flexible operation model of the micro-distribution collaboration in step S3 is as follows:

[0227]

[0228] (p i,t ,q i,t )∈Ω DC,net (78)

[0229] b ij,t ≤a ij (79)

[0230] h ij1,t =b ij,t (80)

[0231]

[0232] k max =[2+log2(N-1)] (82)

[0233] 1 <k≤k max (83)

[0234]

[0235] h ijk,t =h jik,t (85)

[0236] (c ij(k-1)q,t -1)M≤h iq(k-1),t +h qj(k-1),t -1≤c ij(k-1)q,t M (86)

[0237]

[0238] (g ij,t -1)M≤y ij,t -x j,t ≤(1-g ij,t )M (89)

[0239] -g ij,t M≤y ij,t ≤g ij,t M (90)

[0240] (g ij,t -1)M≤G ij,t -p j,t ≤(1-g ij,t )M (91)

[0241] -g ij,t M≤G ij,t ≤g ij,t M (92)

[0242]

[0243] (A ij,t -1)M≤G ii,t -G ij,t ≤A ij,t M (95)

[0244]

[0245] Where: (77) describes the objective function F1, (78) describes the power supply capacity of the station i. N is the total number of nodes in the distribution network topology; X i,t is a 0-1 variable representing the state of station i at time t, X i,t =1 means that the station area i is restored at time t; X i,t =0 means that the station area i has not been restored at time t; C i is the load weight coefficient; b ij,t is a 0-1 variable representing the relationship between area i and area j at time t, b ij,t =1 means that at time t, area i and area j are connected, b ij,t =0 means that at time t, area i and area j are not connected.

[0246] (79)~(90) describe the topological constraints of the distribution network. ij Is a 0-1 constant indicating whether a section switch or circuit breaker is installed between the area i and the area j. ij =1 indicates that there is a connecting line with a section switch or circuit breaker between the stations i and j, a ij =0 means there is no tie line between area i and area j. When the tie line between area i and area j fails and cannot be connected, it is considered that there is no tie line between area i and area j. When there is no tie line between area i and area j or the tie line fails and cannot be connected, a ij =0,b ij,tIt can only be 0, which means that the area i and the area j are not connected; when the area i and the area j are connected by a section switch or circuit breaker, a ij =1,b ij,t Can be 0 or 1, when the section switch or circuit breaker is open b ij,t =0, when the section switch or circuit breaker is closed b ij,t = 1. [2+log2(N-1)] represents the largest integer not exceeding 2+log2(N-1); g ij,t is a 0-1 variable indicating whether substation j is located in microgrid i at time t. Indicates that the substation j is located in the microgrid i at time t, k indicates that the substation j is not located in the microgrid i at time t; max is the maximum number of iterations; h ijk,t It is a 0-1 integer variable; To calculate h ijk,t The intermediate value is a 0-1 integer variable, indicating h iqk,t and h jqk,t Is it 1 at the same time? Time iqk,t =h jqk,t =1, Time iqk,t and h jqk,t At least one is 0; M is the preset maximum value; x i,t represents the total number of tie lines connected to the station area i at time t; y ij,t is the total number of interconnection lines connecting substation j to microgrid i.

[0247] (91) to (93) describe the state of microgrid i. ij,t It represents the active power contributed by substation j to microgrid i at time t.

[0248] (94)~(99) describe the power flow of the distribution network. ij,t represents the active power flowing from area i to area j at time t; Q ij,t A represents the reactive power flowing from area i to area j at time t; ij,t is a 0-1 variable representing the relationship between microgrid i and substation j at time t, A ij,t =1 means that at time t, the active power provided by the substation j to the microgrid i is the largest, A ij,t =0 means that the active power provided by substation j to microgrid i at time t is not the maximum; It represents the square of the bus voltage amplitude of the station i at time t; Indicates the square of the bus voltage rating; R ij represents the resistance of the tie line between area i and area j; X ij It represents the reactance of the interconnection line between substations i and j.

[0249] (100)Describe the voltage security constraints of the distribution network. Represents the square of the lower limit of voltage in station i; Represents the square of the upper voltage limit amplitude of substation i.

[0250] Preferably, in step S4, obtaining a distribution network load recovery plan within the fault time further includes:

[0251] Solve the model and get the on / off status of each section switch and circuit breaker at different times and the interactive power plan between each substation and the upper grid (p i,t ,q i,t ).

[0252] Preferably, the specific process of step S5 is as follows:

[0253] Establish a power generation planning model, input the interactive power plan of the substation obtained in step S4 into the power generation planning model, apply mathematical methods to solve, and obtain the power generation plan of each distributed resource, including the active output of the b-th photovoltaic unit in substation i at time t and reactive power output Active power output of the cth energy storage device in the grid area i at time t and reactive power output Active power output of the e-th non-black start unit in the station i at time t and reactive power output Combined with the distribution network load recovery plan, the distribution and micro-network coordinated flexible operation is carried out.

[0254] Among them, the power generation planning of each distributed resource is combined with the distribution network load recovery plan to achieve coordinated elastic operation of distribution and micro-distribution as follows:

[0255] According to the distribution network load recovery plan, the on and off states of each section switch and circuit breaker at different times during the fault time are controlled. At the same time, according to the power generation plan of each distributed resource, the output of each distributed resource in each substation of the distribution network during the fault time is controlled to achieve flexible coordinated operation of distribution and micro-network.

[0256] Preferably, in step S5, the power generation planning model established is as follows:

[0257]

[0258] Based on the above scheme, the above method is applied and analyzed through specific examples, as follows:

[0259] In this embodiment, a regional distribution network is selected as a distribution network calculation example. PV units are connected to busbars 21, 22, 27, and 35, diesel engines are connected to busbars 34 and 35, and energy storage devices are connected to busbars 25, 27, and 35. The fault point is located on the line between busbar 17 and the substation busbar. Figure 2 The parameters of the system are shown in Table 5.

[0260] After an extreme event occurs, the substation is disconnected from the upstream power grid, and the distribution network changes its structure through section switches / circuit breakers. Therefore, if there is no section switch / circuit breaker installed between two nodes, then during the fault recovery process, the two nodes can be regarded as the same node. Figure 2 The installation location of the section switch / circuit breaker in the middle, merging the nodes, the regional distribution network can be simplified into a 13-node network, such as Figure 3 shown.

[0261] After an extreme event occurs, the distribution network changes its structure through section switches / circuit breakers. Therefore, if there is no section switch / circuit breaker installed between two nodes, then the two nodes can be regarded as the same node during the islanding process. Figure 2 The installation location of the section switch / circuit breaker in the middle, merging the nodes, the regional distribution network can be simplified into a 13-node network, such as Figure 3 The distribution network is simplified to Figure 3 After that, the power supply connection status is shown in Table 6.

[0262] In this embodiment, the load weight coefficients are shown in Table 7, the energy storage device parameters are shown in Table 8, and the non-black unit parameters are shown in Table 9. The fault time is set to T = 8 hours, and the fault time section is selected from 4:00 am to 12:00 am, with a total of 16 time sections, and Δt = 0.5 hours.

[0263] Table 5 Distribution network example parameters

[0264]

[0265]

[0266] Table 6 Power supply connection status

[0267]

[0268] Table 7 Weight coefficients of various electrical loads

[0269]

[0270]

[0271] Table 8 Energy storage device parameters

[0272]

[0273] Table 9 Non-black unit parameters

[0274]

[0275] According to the parameters in Tables 6 to 9, the microgrid operation domain model of each substation is established.

[0276] According to the distribution network-micro collaborative elastic operation model provided by the present invention, the CPLEX solver is called on the MATLAB platform using YALMIP to obtain a feasible solution that meets the constraints. The load recovery plan results of the distribution network within the fault time are as follows: Figure 4 shown.

[0277] Further, based on Figure 4 The load recovery plan can solve the power generation planning of each distributed resource. The power generation costs of various distributed resources are shown in Table 10. The power generation planning results are as follows: Figure 5-7 shown.

[0278] Table 10 Power generation costs of various power sources

[0279]

[0280] Figure 5-7 The power generation planning proves Figure 4 Feasibility of the load restoration plan. After the fault occurred, the distribution network was able to fully restore the downstream area of ​​the fault by relying on distributed resources from 4:00am to 8:00am. Starting at 8:00am, the system's power supply capacity was unable to meet the load demand. From 8:00am to 8:30am, the load downstream of busbars 1-8 and 16-22 was removed due to continued growth in load demand and insufficient system power supply capacity. From 8:30am to 9:30am, the load downstream of busbar 13-15 was further removed. From 9:30am to 11:30am, the load downstream of busbar 13-15 was restored due to a decrease in load demand. From 11:30am to 12:00am, as load demand increased again, the load downstream of busbar 13-15 was removed.

[0281] analyze Figure 5-7 Before 5:30 a.m., the energy storage device played a key role. The system relied primarily on the energy storage device to restore power, and the non-blackstart units also relied on the energy storage device to start. At 5:00 a.m., the non-blackstart units completed startup and began outputting power, supporting system recovery while also providing energy reserve for energy storage devices ESS1 and ESS3. After 5:30 a.m., the photovoltaic system began outputting a large amount of power, and the system power supply was primarily provided by the photovoltaic system and the non-blackstart units. The energy storage device was responsible for smoothing load fluctuations.

[0282] The present invention also proposes a method for flexible operation of distribution network and microgrid based on the microgrid operation domain. The method can be implemented based on the system. The system specifically includes: an acquisition module, a model and constraint construction module, and a calculation and solution module.

[0283] The acquisition module can collect relevant parameters of the distribution network and distributed resources to be processed and send them to the model and constraint construction module;

[0284] The model and constraint construction module constructs the microgrid operation domain model of the substation, the distribution network's microgrid collaborative elastic operation model, and the distributed power generation planning model based on the collected parameters;

[0285] The calculation and solution module obtains the load recovery plan of the distribution network to be processed within the fault time by solving the model and the model constructed by the constraint construction module, and solves the power generation plan of each generator based on the load recovery plan.

[0286] The present invention also provides a distribution-micro collaborative elastic operation system based on a microgrid operation domain, the system including an aggregation module, a constraint module, a collaboration module, a recovery module and a planning module; the aggregation module is used to aggregate photovoltaic units, energy storage devices and non-black start units in the substation according to the correlation between the active power, reactive power and equipment capacity of various types of equipment in the substation to establish an aggregation model of the same type of equipment; the constraint module is used to constrain the parameters of the aggregation model of the same type of equipment established by S1 through a graphical method, so as to obtain a microgrid operation domain model; the collaboration module is used to take the maximum joint active power and the minimum microgrid topology change as the goal, construct joint constraints based on the connection topology, equipment access and switch status of the microgrid, and establish a distribution-micro collaborative operation model with each microgrid operation domain model as a unit; the recovery module is used to solve the distribution-micro collaborative elastic operation model and obtain the initial load recovery plan of the distribution network within the fault time; the planning module is used to establish a power generation planning model, and solve the power generation planning model according to the load recovery state generated by the initial plan to obtain the power generation plan of each distributed resource.

[0287] The present invention also provides a terminal, comprising a processor and a storage medium; the storage medium is used to store instructions; the processor is used to operate according to the instructions to execute the steps of the distribution network fault recovery method.

[0288] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which implements the steps of the distribution network elastic operation method when executed by a processor.

[0289] Finally, it should be noted that the above embodiments are intended only to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art will appreciate that the technical solutions of the present invention still include modifications or equivalent substitutions that may be made to the specific embodiments of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention are intended to be covered by the claims of the present invention.

Claims

1. A method for coordinated operation of distribution and microgrid based on microgrid operation domain, characterized in that: The method comprises the following steps: S1: Based on the correlation between the active power, reactive power, and capacity of various types of equipment in the substation, the photovoltaic units, energy storage devices, and non-black start units in the substation are aggregated to establish an aggregation model for the same type of equipment; S2: Constrain the parameters of the aggregation model of the same type of equipment established in S1 through a graphical method to obtain the microgrid operation domain model; S3: With the goal of maximizing joint active power and minimizing microgrid topology changes, joint constraints are constructed based on the microgrid connection topology, device access, and switch status, and a distribution-microgrid collaborative operation model is established with each microgrid operation domain model as a unit; S4: Solve the distribution network-microgrid coordinated elastic operation model to obtain an initial load recovery plan for the distribution network within the fault time; S5: Establish a power generation planning model, and solve the power generation planning model according to the load recovery state generated by the initial plan to obtain the power generation plan of each distributed resource.

2. A method for coordinated operation of a distribution network and a microgrid based on a microgrid operation domain according to claim 1, characterized in that: Based on the correlation between the active power, reactive power, and device capacity of various types of equipment in the substation, the photovoltaic units, energy storage devices, and non-black start units in the substation are aggregated to establish an aggregation model for the same type of equipment, including: The output power expression of the photovoltaic group after aggregation is: Where, is the total installed capacity of photovoltaic units pv in area i; is the reactive power output of the PV units in the grid area i at time t; is the active power output of the PV units in the grid area i at time t; is the power prediction of the PV units in the grid area i at time t.

3. The method for coordinated operation of a distribution network and a microgrid based on a microgrid operation domain according to claim 1, characterized in that: Based on the correlation between the active power, reactive power, and device capacity of various types of equipment in the substation, the photovoltaic units, energy storage devices, and non-black start units in the substation are aggregated to establish an aggregation model for the same type of equipment, including: The output power expression of the energy storage device group after aggregation is: Where, is the active power output of the energy storage device in substation i at time t; and are the installed capacity of the energy storage device in the substation i; and are the maximum electric energy that can be absorbed and released by the energy storage unit in substation i when a fault occurs; Δt is the length of the time period between adjacent decision points, d is the decision point number, T is the expected length of failure time.

4. The method for coordinated operation of a distribution network and a microgrid based on a microgrid operation domain according to claim 1, characterized in that: Based on the correlation between the active power, reactive power, and device capacity of various types of equipment in the substation, the photovoltaic units, energy storage devices, and non-black start units in the substation are aggregated to establish an aggregation model for the same type of equipment, including: The output power expression of the non-black start generator group after aggregation is: Where, and is the active and reactive power output of the non-black start units in the substation i at time t; is the installed capacity of non-black start units in substation i; is the start-up time of non-black start units in substation i; t is the current time, The time it takes for non-black start units in zone i to absorb the starting power; M is the preset maximum value, and is the 0-1 state variable of the non-black start unit in the station i, Indicates that all non-black start units in substation i are started at time t. Indicates that none of the non-black start units in the station area i were started at time t. It means that all non-black start units in the area i can output power at time t. Indicates that the non-black start units in the station area i cannot output power at time t; X i,t Is a 0-1 state variable indicating whether the station i is restored at time t, X i,t =1 means that the station area i is restored at time t, X i,t =0 means that station i has not recovered at time t.

5. A method for coordinated operation of a distribution network and a microgrid based on a microgrid operation domain according to any one of claims 2 to 4, characterized in that: By using a graphical method to constrain the parameters of the aggregation model of the same type of equipment established by S1, the microgrid operation domain model is obtained, including: Construct a multidimensional independent variable based on the number of similar devices in the aggregation model of similar devices established in S1; Using the inequality constraints in the aggregation model of the same equipment established by S1, a linear programming problem with multi-dimensional independent variables is constructed; The linear programming problem is solved according to a graphical method to obtain the feasible domain of the aggregation model of the same type of equipment established in S1.

6. The method for coordinated operation of a distribution network and a microgrid based on a microgrid operation domain according to claim 5, characterized in that: The goal is to maximize the joint active power and minimize the change in microgrid topology. Joint constraints are constructed based on the microgrid's connection topology, device access, and switch status. A distribution-microgrid collaborative operation model is established with each microgrid operation domain model as a unit, including: The objective function of the micro-cooperative operation model is: X i,t Represents the state of area i at time t, N is the number of areas C i is the load weight coefficient, It is the dispatching power under the micro-cooperative operation model; b ij,t Represents the topological connection relationship between stations ij at time t.

7. The method for coordinated operation of a distribution network and a microgrid based on a microgrid operation domain according to claim 6, characterized in that: The goal is to maximize joint active power and minimize microgrid topology changes, construct joint constraints based on the microgrid's connection topology, device access, and switch status, and establish a distribution-microgrid collaborative elastic operation model with each microgrid operation domain model as a unit, including: The constraints of the micro-cooperative elastic operation model are: (p i,t ,q i,t )∈Ω DC,net b ij,t ≤a ij h ij1,t =b ij,t k[2+log2(N-1)] max 1<k≤k max h ijk,t =h jik,t (c ij(k-1)q,t -1)m≤h iq(k-1),t +h qj(k-1),t -1≤c ij(k-1)q,t m (g ij,t -1)M≤y ij,t -x j,t ≤(1-g ij,t )M -g ij,t M≤y ij,t ≤g ij,t M (g ij,t -1)M≤G ij,t -p j,t ≤(1-g ij,t )M -g ij,t M≤G ij,t ≤g ij,t M Where, (p i,t ,q i,t ) is the active and reactive interaction power between substation i and the upper grid; Ω DC,net is the area interaction power set, a ij It is a tie line indicating whether there is a section switch or circuit breaker between the substations i and j; h ij1,t h iqk,t Initialization, for At the maximum number of iterations k max The value of k is the number of iterations, h iqk,t To describe c ijqk,t The intermediate variable, q is another area different from ij; g ij,t Indicates whether the substation j is located in the microgrid i at time t; c ijqk,t To calculate h at time t ijk,t → The intermediate amount; x i,t represents the total number of tie lines connected to the station area i at time t; y ij,t is the total number of tie lines from substation j to microgrid i; G ij,t represents the active power contributed by substation j to microgrid i at time t; P ij,t and Q ij,t represents the active and reactive power flowing from substation i to substation j at time t; A ij,t Indicates whether the active power provided by substation j to microgrid i is the largest at time t; It represents the square of the bus voltage amplitude of the station i at time t; is the square of the rated value of the bus voltage in station i; R ij represents the resistance of the tie line between area i and area j; X ij represents the reactance of the tie line between substations i and j; and are the squares of the lower and upper voltage limits of substation i, respectively.

8. The method for coordinated operation of a distribution network and a microgrid based on a microgrid operation domain according to claim 7, characterized in that: The power generation planning model is established, and according to the load recovery state generated by the initial solution, the power generation planning model is solved to obtain the power generation plan of each distributed resource, including: The objective function of the power generation planning model is: Where, is the active power output of the b-th PV unit in the grid area i at time t; is the active power output of the cth energy storage device in the grid area i at time t; is the active power output of the e-th non-black start unit in the station i at time t; The constraints of the power generation planning model are: Solve the power generation planning model to obtain the active power of each device.

9. A distribution and micro-cooperative operation system based on a microgrid operation domain using the method according to any one of claims 1 to 8, characterized in that: The system includes an aggregation module, a constraint module, a collaboration module, a recovery module and a planning module; The aggregation module is used to aggregate photovoltaic units, energy storage devices, and non-black start units in the substation area based on the correlation between the active power, reactive power, and equipment capacity of various types of equipment in the substation area to establish an aggregation model for the same type of equipment; The constraint module is used to constrain the parameters of the aggregation model of the same type of equipment established by S1 through a graphical method, so as to obtain a microgrid operation domain model; The collaborative module is used to maximize the joint active power and minimize the change of microgrid topology, construct joint constraints based on the connection topology, device access, and switch status of the microgrid, and establish a distribution-micro collaborative operation model with each microgrid operation domain model as a unit; The recovery module is used to solve the distribution network-micro network collaborative elastic operation model and obtain an initial load recovery plan for the distribution network within the fault time; The planning module is used to establish a power generation planning model and solve the power generation planning model according to the load recovery state generated by the initial plan to obtain the power generation plan of each distributed resource.

10. A terminal comprising a processor and a storage medium; characterized in that: The storage medium is used to store instructions; The processor is configured to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 8.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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