Distribution coordination optimization control method for micro-grid group

Abstract

The invention provides a micro-grid group distribution coordination optimization control method. The method comprises the following steps: constructing an optimization model of a micro-grid group system according to an optimization target and constraint conditions; solving the optimization model according to a KKT condition to obtain a GIC of each DG; calculating a voltage reference value of an AC microgrid interface flexible DC VSC and an active power reference value of a DC microgrid interface DCT under distributed coordination optimization control based on the difference of the GICs among the sub-microgrids; the voltage reference value of the flexible DC converter is substituted into a constant voltage controlled voltage outer ring to obtain a current reference value, and control of each flexible DC VSC is realized; and substituting the active power reference value of the direct current transformer into a constant power controller to calculate a phase shift angle, thereby realizing control of the direct current micro-grid interface DCT. According to the method, the active power economic dispatching of each distributed power supply in the microgrid can be realized, and the coordinated optimization control of the microgrid group system can be realized through the coordination between each flexible direct current converter and the direct current transformer.

Description

Technical Field

[0001] The present invention relates to the field of microgrid group operation and control technology, and in particular to a distributed coordinated optimization control method for a microgrid group. Background Art

[0002] A microgrid (MG) is an independent power supply system that integrates multiple distributed generation (DG) systems, energy storage devices, and loads. It can effectively absorb renewable energy and reduce carbon emissions. A microgrid cluster (MGC) combines the advantages of AC and DC microgrids. MGCs can be connected via interlinking converters (ICs), enabling high-speed energy conversion, coordinated power balance, and flexible microgrid operation.

[0003] There are two types of microgrid cluster systems: 1) Microgrid clusters based on interconnected power electronic devices; 2) Flexible DC interconnected microgrid cluster systems. In the first form, since the microgrids are connected only by a power electronic device (PED), there is a lack of a DC distribution network, and only connections between adjacent feeders can be achieved. In contrast, the second form of microgrid cluster system can connect AC microgrids and DC microgrids to the DC distribution bus through flexible DC converters and DC transformers, facilitating cross-feeder connections between AC and DC microgrids, and achieving collaborative sharing of grid resources on a larger scale.

[0004] Microgrids primarily use hierarchical control to achieve system electrical quantity recovery and optimized operation. This hierarchical control includes primary, secondary, and tertiary control. Primary control primarily implements local coordinated control of the microgrid to maintain electrical quantity stability. In current research, secondary control of microgrids is primarily used to achieve control objectives such as frequency and voltage recovery, and active power ratio distribution. Tertiary control optimizes the microgrid's power generation cost to the lowest possible level, focusing primarily on the economic dispatch of the microgrid. Due to the varying power generation costs of different DGs within a microgrid cluster, a reasonable distributed coordinated optimization dispatching scheme should be designed for the microgrid to minimize operating costs. Therefore, in addition to coordinated operation of converters between microgrid clusters, achieving optimized operation of the entire system is also a key issue.

[0005] Currently, existing solutions for coordinated optimization and control of microgrids primarily focus on the single microgrid level. These solutions have drawbacks: while flexible interconnected microgrid clusters offer significant advantages, they face the diverse interests of different stakeholders, the complexity of multi-terminal AC / DC networks, the multidirectional nature of power flow dynamics, and potential conflicts between control objectives. The lack of distributed, coordinated optimization control methods within and between microgrids hinders the full realization of microgrid clusters' advantages in absorbing high proportions of renewable energy. In adverse scenarios, they can even lead to system instability, impacting the economic operation of the system. Summary of the Invention

[0006] An embodiment of the present invention provides a distributed coordinated optimization control method for a microgrid group, so as to effectively perform distributed coordinated optimization control on the microgrid group.

[0007] In order to achieve the above-mentioned purpose, the present invention adopts the following technical solutions.

[0008] A distributed coordinated optimization control method for a microgrid group, comprising:

[0009] Formulate optimization objectives and constraints for the microgrid cluster system and build an optimization model for the microgrid cluster system;

[0010] Solving the optimization model according to the KKT condition to obtain a generalized incremental cost representing each distributed power source in the microgrid group system;

[0011] Based on the differences in generalized incremental costs between sub-microgrids, the voltage reference value of the flexible DC converter (VSC) at the AC microgrid interface and the active power reference value of the DC transformer (DCT) at the DC microgrid interface are calculated using a finite-time consensus algorithm under distributed coordinated optimization control.

[0012] The voltage reference value of the AC microgrid interface flexible direct current (VSC) is brought into the voltage outer loop of the constant voltage control to obtain a current reference value, which is used as the input of the current inner loop. After the current inner loop is tracked, the control signal of each flexible direct current (VSC) is obtained in combination with coordinate transformation to achieve control of each flexible direct current (VSC);

[0013] The active power reference value of the DC microgrid interface DCT is brought into the constant power controller to calculate the phase shift angle, and the control signal of each DCT is generated through pulse width modulation to realize the control of the DC microgrid interface DCT.

[0014] Preferably, the formulation of the optimization objectives and constraints of the microgrid cluster system and the construction of the optimization model of the microgrid cluster system include:

[0015] While maintaining the active power balance constraint of the microgrid group system, the active power limit constraint of the AC / DC microgrid distributed power source DG, and the active power limit constraint of the flexible direct current (VSC) and direct current (DCT), the goal is to minimize the power generation cost of all units in the microgrid group system. The optimization objectives and constraints of the microgrid group system are formulated, and the optimization model of the microgrid group system is constructed, namely:

[0016]

[0017] represents the cost function of the i-th DG in the k-th AC microgrid ACMG, represents the cost function of the jth DG in the pth DC microgrid DCMG, as well as ACMG k The active power, minimum active power and maximum active power emitted by the i-th DG in as well as DCMG p The active power, minimum active power and maximum active power emitted by the jth DG in is the active power transmitted by the kth VSC, and are the minimum active power and maximum active power transmitted by the kth VSC, is the active power transmitted by the pth DCT, and are the minimum active power and maximum active power transmitted by DCTp, N k is the number of AC microgrids, N ac is the number of DGs in the AC microgrid, N p is the number of DC microgrids, N dc is the number of DGs inside the DC microgrid, and are the total active power generated by the AC microgrid and the DC microgrid respectively. and are the total load sizes of the AC microgrid and the DC microgrid respectively.

[0018] Preferably, solving the optimization model according to the KKT condition to obtain the generalized incremental cost characterizing each distributed power source in the microgrid group system includes:

[0019] Formulate the Lagrange function that characterizes the optimization model, namely:

[0020]

[0021] L(x) represents the Lagrange function, where x represents the input variable, λ G represents the Lagrange multiplier of the active power balance constraint, which corresponds to the dual variable related to the demand-supply balance equation of the microgrid optimal scheduling problem, and the dual variable is the incremental cost; where, The limit factor representing the active power limit constraint of each DG in the AC and DC microgrids; The limits representing the VSC and DCT transmission power limit constraints;

[0022] In steady state, the relationship between the power generated by each microgrid in the system, the power transmitted by the VSC and DCT, and the load is expressed as:

[0023]

[0024] The KKT conditions representing the optimization model are as follows:

[0025]

[0026] in, Denotes the Lagrange function for the internal DG of the AC microgrid i The output power is derived, Denotes the Lagrange function for the DC microgrid internal DG j The power is emitted to obtain the derivative; as well as is the differential term of the cost function with respect to the active power generated by the DG. It is the Lagrange multiplier corresponding to the case of considering only the active power balance constraint;

[0027] According to the KKT condition, the generalized incremental cost GIC of each DG is calculated as follows:

[0028]

[0029]

[0030] It's ACMG k The GIC of the i-th DG in , It is DCMG p According to the equal incremental cost criterion, all DGs in the entire microgrid group must have the same generalized incremental cost, that is:

[0031]

[0032] Among them, this formula is the optimality condition of the microgrid group system optimization model. When this formula is met, the total power generation cost of the microgrid group system is minimized.

[0033] Preferably, the voltage reference value of the AC microgrid interface flexible direct current (VSC) and the active power reference value of the DC microgrid interface DCT under distributed coordinated optimization control are calculated based on the difference in generalized incremental costs between the sub-microgrids according to a finite-time consensus algorithm, including:

[0034] To achieve convergence of active power transmission of each converter, a finite time consensus algorithm is used to calculate according to the following formula:

[0035]

[0036] Where c>0 is the control parameter, β∈(0,1) is the parameter representing the convergence speed of the microgrid group system, and sign(x) is the sign function. Through this algorithm, the microgrid group system is kept consistent with the state of the adjacent intelligent agents within a limited time, and the convergence time is defined as:

[0037]

[0038] Where V(x0) is the Lyapunov-Krasovskii candidate function, x0 is the initial state of the system;

[0039] Based on the finite-time consensus algorithm, all converters are connected to the distributed communication network. According to the difference in GICs between the leading DGs in the AC microgrid and the DC microgrid, the change in the DC voltage of the flexible DC VSC is calculated. The DC voltage change of each flexible DC VSC is added to the rated voltage of the flexible DC VSC to obtain the voltage reference value of the mutual flexible DC VSC, which is:

[0040]

[0041] Where, For VSC k The voltage reference value, For VSC k Rated voltage; is the DC voltage variation of the flexible VSC, c vsc,p and c vsc,k is the control parameter, β is the adjustment parameter related to the controller convergence speed, where VSC k From the adjacent proxy node VSC through the upper communication network m With DCT p Get GIC information, sig is defined as: sig(x) β =sign(x)·|x| β , |·| is the absolute value function; and and VSC respectively kThe rest of the VSCs and DCTs that communicate with the upper layer, and is the communication weight between VSCs and DCT in the upper communication network. Its value is 1 if there is communication, otherwise it is 0; and DCMG p DG j GIC, ACMG k DG i GIC, ACMG m DG j GIC, and Microgrid ACMG k ,DCMG p and ACMG m The set of dominant DGs;

[0042] The active power reference value of the DC microgrid interface DCT under distributed coordinated optimization control is calculated according to the finite time consensus algorithm, namely:

[0043]

[0044] Among them, P DCTp,ref DCT p Transmitted active power reference value, c dct,p and c dct,k is the control parameter; β is the adjustment parameter related to the controller convergence speed, DCT p From the adjacent proxy node VSC through the upper communication network k With DCT n Get GIC information; sig is defined as: sig(x) β =sign(x)·|x| β , |·| is the absolute value function; and and DCT respectively p The rest of the VSCs and DCTs that communicate with the upper layer, and is the communication weight between VSCs and DCT in the upper communication network. Its value is 1 if there is communication, otherwise it is 0; and ACMG k DG i Generalized incremental cost, DCMG p DG j Generalized incremental cost, DCMG n DG i generalized incremental costs. and Microgrid ACMG k ,DCMG p and DCMG n The set of dominant DGs in .

[0045] Preferably, the voltage reference value of the AC microgrid interface flexible direct current VSC is brought into the voltage outer loop of constant voltage control to obtain a current reference value, the current reference value is used as the input of the current inner loop, and after the current inner loop tracking, the control signal of each flexible direct current VSC is obtained in combination with coordinate transformation to realize the control of each flexible direct current VSC, including:

[0046] The voltage reference value of the flexible DC VSC is brought into the voltage outer loop of the constant voltage control to obtain the current reference value, which is used as the input of the current inner loop. After the current inner loop tracking, combined with the abc / dq0 coordinate transformation, the control signal of each flexible DC VSC is obtained to realize the control of each flexible DC VSC. The control method is as follows:

[0047]

[0048] Where, VSC k D-axis reference value of the current loop; For VSC k The DC voltage reference value; VSC k The actual DC voltage; VSC k The q-axis reference value of the current loop; VSC k Reactive power reference value; VSC k The actual reactive power of k p1 and k i1 are the proportional and integral parameters of the d-axis controller; k p2 and k i2 are the proportional and integral parameters of the q-axis controller; 1 / s represents the integral link.

[0049] Preferably, the active power reference value of the DC microgrid interface DCT is brought into the constant power controller to calculate the phase shift angle, and the control signal of each DCT is generated by pulse width modulation to realize the control of the DC microgrid interface DCT, including:

[0050] The active power reference value of DCT is brought into the constant power controller to calculate the phase shift angle, and the control signal of each DCT is generated through pulse width modulation to realize the control of the DC microgrid interface DCT, that is:

[0051]

[0052] Where, DCT p Actual active power transmitted, k p3 and k i3 are the proportional and integral parameters of the controller, and the shift ratio is obtained by constant power control. Calculate the shift angle α between the switch tube conduction pulses; T h is the switching period; 1 / s represents the integral.

[0053] It can be seen from the technical solutions provided by the above-mentioned embodiments of the present invention that the method can realize the economic dispatch of active power of each distributed power source within the sub-microgrid, and can also realize coordinated optimization control of the microgrid group system through coordination between each flexible DC converter and DC transformer.

[0054] Additional aspects and advantages of the present invention will be set forth in part in the following description, will become apparent from the following description, or may be learned by practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0056] Figure 1 A flow chart of a distributed coordinated optimization control method for a microgrid group provided by an embodiment of the present invention;

[0057] Figure 2 A system topology diagram of a distributed coordinated optimization control method for a microgrid group provided by an embodiment of the present invention;

[0058] Figure 3 A network communication diagram of a distributed coordinated optimization control method for a microgrid group provided by an embodiment of the present invention;

[0059] Figure 4 A control block diagram of a flexible direct current converter (VSC) in a distributed coordinated optimization control method for a microgrid group provided by an embodiment of the present invention;

[0060] Figure 5 A control block diagram of a DC transformer DCT of a distributed coordinated optimization control method for a microgrid group provided by an embodiment of the present invention;

[0061] Figure 6 and Figure 7A diagram showing simulation results of a distributed coordinated optimization control method for a microgrid cluster provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0062] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limiting the present invention.

[0063] It will be understood by those skilled in the art that, unless expressly stated otherwise, the singular forms "a", "an", "said" and "the" used herein may also include the plural forms. It should be further understood that the term "comprising" used in the description of the present invention refers to the presence of the features, integers, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof. It should be understood that when we refer to an element as being "connected" or "coupled" to another element, it may be directly connected or coupled to the other element, or there may be intermediate elements. In addition, "connected" or "coupled" as used herein may include wireless connections or couplings. The term "and / or" used herein includes any unit and all combinations of one or more associated listed items.

[0064] It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by those skilled in the art in the art to which the present invention pertains. It should also be understood that terms such as those defined in common dictionaries should be understood to have meanings consistent with their meanings in the context of the prior art and, unless defined as such herein, will not be interpreted in an idealized or overly formal sense.

[0065] To facilitate understanding of the embodiments of the present invention, several specific embodiments will be further explained below with reference to the accompanying drawings, and each embodiment does not constitute a limitation on the embodiments of the present invention.

[0066] Because the topology of a flexible interconnected microgrid cluster includes a DC distribution bus, the voltage of the DC distribution bus must be reasonably controlled within a certain range. Therefore, designing an appropriate and effective distributed coordination optimization control strategy for the microgrid cluster is of great significance for achieving system frequency and voltage stability, as well as optimal active power distribution, to rapidly improve system stability, economy, and safety.

[0067] The embodiment of the present invention provides a distributed coordinated optimization control method for a microgrid group, which realizes the coordinated optimization operation of the microgrid group system by coordinating the control of converters between microgrids. First, the optimization objectives and constraints of the microgrid group system are formulated, and an optimization model of the microgrid group system is constructed. The optimization model is solved according to the KKT condition to obtain the generalized incremental cost (GIC) that can characterize each distributed generation (DG); then, based on the difference in the generalized incremental cost between each sub-microgrid, the voltage reference value of the AC microgrid interface flexible DC converter (VSC) and the DC microgrid interface DC transformer (DC) under distributed coordinated optimization control are calculated according to the finite time consistency algorithm. The active power reference value of the DC transformer (DC transformer, DCT) is obtained; secondly, the voltage reference value of the flexible DC converter is brought into the voltage outer loop (VdcQ) of the constant voltage control to obtain the current reference value, which is used as the input of the current inner loop. After the current inner loop is tracked, the control signal of each flexible DC converter is obtained in combination with the coordinate transformation to realize the control of each flexible DC converter; constant power control is adopted for the DC transformers, and the phase shift angle is calculated based on the obtained active power reference value. The control signal of each DC transformer is generated by pulse width modulation to realize the control of the DC transformer at the DC microgrid interface. Through the above steps, the goal of global economic dispatch of the entire microgrid group can be achieved.

[0068] The processing flow of a distributed coordinated optimization control method for a microgrid group provided by an embodiment of the present invention is as follows: Figure 1 As shown, the system topology diagram of a distributed coordinated optimization control method for a microgrid group provided by an embodiment of the present invention is as follows Figure 2 As shown, a network communication diagram of a distributed coordinated optimization control method for a microgrid group provided by an embodiment of the present invention is shown in FIG. Figure 3 The method includes the following processing steps:

[0069] Step S10: Formulate optimization objectives and constraints for the microgrid cluster system and construct an optimization model for the microgrid cluster system.

[0070] Step S20: solving the optimization model according to KKT (Karush-Kuhn-Tucker Conditions) to obtain a generalized incremental cost that can characterize each distributed power source;

[0071] Step S30: Based on the differences in generalized incremental costs between the sub-microgrids, a finite-time consensus algorithm is used to calculate a voltage reference value of the flexible direct current (VSC) at the AC microgrid interface and an active power reference value of the direct current (DCT) at the DC microgrid interface under distributed coordinated optimization control.

[0072] The voltage reference value of the flexible DC converter is brought into the voltage outer loop of the constant voltage control to obtain the current reference value, which is used as the input of the current inner loop. After the current inner loop is tracked, the control signal of each flexible DC converter is obtained in combination with the coordinate transformation to realize the control of each flexible DC converter;

[0073] The active power reference value of the DC transformer is brought into the constant power controller to calculate the phase shift angle, and the control signals of each DC transformer are generated through pulse width modulation to realize the control of the DC transformer at the DC microgrid interface.

[0074] Specifically, the above step S10 includes: formulating optimization objectives and constraints for the microgrid group system, and constructing an optimization model for the microgrid group system, namely:

[0075]

[0076] represents the cost function of the i-th DG in the k-th AC microgrid ACMG, represents the cost function of the jth DG in the pth DC microgrid DCMG, as well as ACMG k The active power, minimum active power and maximum active power emitted by the i-th DG in as well as DCMG p The active power, minimum active power and maximum active power emitted by the jth DG in . is the active power transmitted by the kth VSC, and are the minimum active power and maximum active power transmitted by the kth VSC, respectively. is the active power transmitted by the pth DCT, and are the minimum active power and maximum active power transmitted by DCTp respectively; N k is the number of AC microgrids, N ac is the number of DGs in the AC microgrid; N p is the number of DC microgrids, N dc is the number of DGs inside the DC microgrid; and are the total active power generated by the AC microgrid and the DC microgrid respectively, and are the total loads of the AC microgrid and the DC microgrid, respectively. For this microgrid cluster system, the optimization model considered is to minimize the power generation cost of all units in the microgrid cluster system while maintaining the system active power balance constraint, the active power limit constraint of the AC / DC microgrid DG, and the active power limit constraint of the flexible direct current (VSC) and direct current (DCT).

[0077] Specifically, the above step S20 includes: solving the optimization model according to the KKT condition to obtain the generalized incremental cost that can characterize each DG, that is, calculating according to the following steps:

[0078] First, a Lagrange function that can characterize the optimization model of the microgrid group system is formulated, namely:

[0079]

[0080] L(x) represents the Lagrange function, where x represents the input variable. G represents the Lagrange multiplier of the active power balance constraint, which corresponds to the dual variable related to the demand-supply balance equation of the microgrid optimal scheduling problem and can be interpreted as the incremental cost; where, The limit factor representing the active power limit constraint of each DG in the AC and DC microgrids; Represents the limits of VSC and DCT transmit power limit constraints.

[0081] In steady state, the relationship between the power generated by each microgrid in the system, the power transmitted by the VSC and DCT, and the load can be expressed as:

[0082]

[0083] Then, considering the above optimization model, the KKT conditions representing the optimization model are obtained as follows:

[0084]

[0085] in, Denotes the Lagrange function for the internal DG of the AC microgrid i The output power is derived, Denotes the Lagrange function for the DC microgrid internal DG j The power is emitted to obtain the derivative; as well as It is the differential term of the cost function with respect to the active power generated by the DG. It is the Lagrange multiplier corresponding to the case where only the active power balance constraint is considered.

[0086] Finally, according to the KKT condition, the GIC of each DG can be calculated as follows:

[0087]

[0088] When the active power inequality constraint is considered, the obtained incremental cost is called the generalized incremental cost, that is: It's ACMG k The generalized incremental cost of the i-th DG in ; It is DCMG p According to the equal incremental cost principle, all DGs in the entire microgrid group must have the same generalized incremental cost in order to achieve global economic dispatch, that is:

[0089]

[0090] Among them, this formula is the optimality condition of the microgrid group system optimization model. When this formula is met, the total power generation cost of the microgrid group system is minimized.

[0091] Specifically, the above step S30 includes: a control block diagram of a flexible direct current converter VSC of a distributed coordinated optimization control method of a microgrid group provided by an embodiment of the present invention is as follows: Figure 4 As shown, the control block diagram of the DCT of a distributed coordinated optimization control method of a microgrid group provided by an embodiment of the present invention is as follows Figure 5 shown.

[0092] Based on the differences in generalized incremental costs among the sub-microgrids, the voltage reference value of the AC microgrid interface VSC and the active power reference value of the DC microgrid interface DCT under distributed coordinated optimal control are calculated using the finite-time consensus algorithm.

[0093] The finite time consensus algorithm can achieve the purpose of rapid convergence of the active power transmitted by each converter, that is, it is calculated according to the following formula:

[0094]

[0095] Where c>0 is the control parameter, β∈(0,1) is the parameter representing the convergence speed of the system, and sign(x) is the sign function. This algorithm can make the system consistent with the state of the adjacent intelligent agents within a finite time, and the convergence time can be defined as:

[0096]

[0097] Where V(x0) is the Lyapunov-Krasovskii candidate function and x0 is the initial state of the system. Compared with the asymptotic protocol, the finite-time protocol accelerates the convergence speed and adds a certain level of disturbance rejection.

[0098] Therefore, based on the finite-time consensus algorithm, all converters are connected to the distributed communication network. According to the difference in GICs between the leading DGs in the AC microgrid and the DC microgrid, the change in the DC voltage of the flexible DC VSC can be calculated. Then, the DC voltage change of each flexible DC VSC is added to the rated voltage of each flexible DC VSC to obtain the voltage reference value of the mutual flexible DC VSC, that is:

[0099]

[0100] Where, For VSC k The voltage reference value, For VSC k Rated voltage; is the DC voltage variation of the flexible VSC, c vsc,p and c vsc,k is the control parameter, and β is the adjustment parameter related to the controller convergence speed. k From the adjacent proxy node VSC through the upper communication network m With DCT p Get GIC information. sig is defined as: sig(x) β =sign(x)·|x| β , |·| is the absolute value function; and and VSC respectively k A collection of the remaining VSCs and DCTs that perform upper layer communication. and is the communication weight between VSCs and DCT in the upper communication network. Its value is 1 if there is communication, otherwise it is 0; and DCMG p DG j Generalized incremental cost, ACMG k DG i Generalized incremental cost, ACMG m DG j The generalized incremental cost. and Microgrid ACMG k ,DCMG p and ACMG m The set of dominant DGs in .

[0101] The active power reference value of the DC microgrid interface DCT under distributed coordinated optimization control is calculated according to the finite time consensus algorithm, namely:

[0102]

[0103] in, DCT p Transmitted active power reference value, c dct,p and c dct,k is the control parameter; β is the adjustment parameter related to the controller convergence speed. p From the adjacent proxy node VSC through the upper communication network k With DCT n Get GIC information; sig is defined as: sig(x) β =sign(x)·|x| β , |·| is the absolute value function; and and DCT respectively p A collection of the remaining VSCs and DCTs that perform upper layer communication. and is the communication weight between VSCs and DCT in the upper communication network. Its value is 1 if there is communication, otherwise it is 0; and ACMG k DG i Generalized incremental cost, DCMG p DG j Generalized incremental cost, DCMG n DG i The generalized incremental cost. and Microgrid ACMG k ,DCMG p and DCMG n The set of dominant DGs in .

[0104] Specifically, step S40 includes: bringing the voltage reference value of the flexible DC converter into the voltage outer loop of the constant voltage control to obtain a current reference value as the input of the current inner loop; after the current inner loop is tracked, combining abc / dq0 coordinate transformation to obtain the control signal of each flexible DC converter, thereby achieving control of each flexible DC converter. The control method is as follows:

[0105]

[0106] Where, VSC k D-axis reference value of the current loop; For VSC k DC voltage reference value; VSC k The actual DC voltage. VSC k The q-axis reference value of the current loop; VSC k Reactive power reference value; VSC k The actual reactive power of p1 and k i1 are the proportional and integral parameters of the d-axis controller; k p2 and k i2 are the proportional and integral parameters of the q-axis controller; 1 / s represents the integral component. Based on the controller design above, all flexible DC VSCs jointly control the stability of the DC bus voltage, resulting in high DC bus voltage reliability.

[0107] The active power reference value of the DC transformer is brought into the constant power controller to calculate the phase shift angle. The control signal of each DC transformer is generated through pulse width modulation to realize the control of the DC transformer at the DC microgrid interface and achieve rapid tracking of the transmitted active power, that is:

[0108]

[0109] Where, DCT p Actual active power transmitted, k p3 and k i3 The proportional and integral parameters of the controller are then used to obtain the shift ratio by constant power control. Then calculate the shift angle α between the switch tube conduction pulses; T h is the switching period; 1 / s represents the integral. According to the controller designed above, DCT p The transmitted active power can accurately track the reference value Realize power interaction between AC microgrid groups and DC microgrid groups.

[0110] Example 1

[0111] In this implementation, a distributed coordination optimization control method for a microgrid group is applied to Figure 2 In the example system shown. This embodiment 2 is a microgrid group system including 2 AC microgrids (4 AC DGs), 2 DC microgrids (4 DC DGs), 2 flexible direct current VSCs and 2 DC DCTs. This topology is used as an example to verify the effectiveness of the distributed coordinated optimization control method of a microgrid group proposed in the present invention. The simulation results of the distributed coordinated optimization control method of a microgrid group provided in embodiment 2 are shown as follows. Figure 6 and Figure 7 As shown, the results of verifying the effectiveness of the present invention are obtained from Simulink simulation software.

[0112] The rated voltages of the AC microgrid and DC distribution network are 380 V and 375 V, respectively. Tables 1 and 2 provide the system electrical and control parameters. In this invention, the positive direction of active power transmission by the VSC is specified as DC instead of AC. The active power transmission constraints for VSC2, DCT1, and DCT2 are -10 kW to 10 kW and -20 kW to 20 kW, respectively.

[0113] The relevant control parameters and circuit parameters are shown in the following table:

[0114] Table 1 Microgrid system circuit parameters

[0115]

[0116] Table 2 Microgrid system control parameters

[0117]

[0118] The total simulation time of the system is 4s, and the step size is 1×10 -5 s. First, the local control layer is activated, allowing the system to quickly reach steady state. Then, at t = 2s, the microgrid layer (MG-layer) and microgrid cluster layer (MGC-layer) controllers are activated. At t = 4s, the load of ACMG1 increases from 45kW to 65kW. The load of DCMG1 increases from 60kW to 80kW at t = 6s, and then decreases from 80kW to 60kW at t = 8s. Figure 6 and Figure 7 The simulation results of this example are shown.

[0119] Figure 6 Simulation results for the GICs of all DGs in ACMGs and DCMGs are presented. Before t = 2 seconds, the GICs of all DGs were inconsistent. After t = 2 seconds, the MG-layer and MGC-layer controllers brought all GICs into agreement. Even with load fluctuations, the GICs remained consistent. Consequently, global economic dispatch of the microgrid system was achieved. Figure 7 (a) represents the total cost of the system. It can be seen that the total cost decreases at t = 2s, which reflects the effect of global economic dispatch under our proposed controller. Figure 7 (b) shows that as the operating conditions change, the voltage of the DC distribution network is always around the rated value of 750V and has high reliability. Figure 7(c) shows the output active power of all DGs in ACMG1. After ACMG1's load increases at t = 4 s, DG1, due to its lower cost factor, shares more active power. Therefore, it reaches a maximum of 20 kW between t = 4 s and t = 10 s and is then capped at this value.

[0120] Figure 7 (d) shows the corresponding limit factor of each DG in ACMG1. It can be seen that the limit factor of DG1 After t = 4s, it begins to exceed 0, but remains at 0 at other times. This is because only DG1 reaches its maximum power, while the other DGs do not. At t = 8s, when the load of DCMG1 decreases from 65kW to 45kW, it returns to its original state level.

[0121] Figure 7 (e) and (f) are the active power transmitted by VSC and DCT and their limit factors, respectively. At t = 6s, when the load of DCMG1 increases from 45kW to 65kW, the active power transmitted by VSC2 and DCT1 both reaches a maximum value of 20kW and is then limited to this value and does not change. This constraint effect can also be reflected in Figure 7 In (f), it shows that VSC2 and DCT1 begin to be greater than 0 at t=6s. At t=8s, when the load of DCMG1 decreases from 65kW to 45kW, Figure 7 (e) and (f) show that the active power transmitted by VSC2 and DCT1 and their respective limit factors have returned to their previous levels. Therefore, it can be seen from the above results that the proposed control method achieves the limit of the converter transmission power.

[0122] Figure 7 Figures (g) and (h) show that after the MG-layer and MGC-layer controllers are activated at time t = 2s, the frequency of ACMG1 and the average voltage of all DGs in DCMG1 are controlled to the desired values of 50 Hz and 375 V. Therefore, the proposed control strategy also achieves the control objectives of restoring the frequency and average voltage within the microgrid.

[0123] In summary, the simulation results demonstrate that the proposed distributed coordinated optimization control method for a microgrid cluster system can simultaneously achieve control objectives within and across microgrids. It also considers the power constraints of DGs within a microgrid and the transmission power capacity constraints of VSCs and DCTs between microgrids, effectively mitigating the risk of microgrid overload.

[0124] In summary, the present invention achieves coordinated and optimized operation of a microgrid group system by coordinated control of converters between microgrids. In order to formulate optimization objectives and constraints for the microgrid group system, an optimization model of the microgrid group system is constructed, and the optimization model is solved according to the KKT condition to obtain the generalized incremental cost (GIC) that can characterize each distributed power source (DG); then, based on the difference in generalized incremental cost between each sub-microgrid, the voltage reference value of the flexible DC converter (VSC) at the AC microgrid interface and the active power reference value of the DC transformer (DCT) at the DC microgrid interface under distributed coordinated optimization control are calculated according to the finite time consistency algorithm; thirdly, the voltage reference value of the flexible DC converter is substituted into the voltage outer loop of the constant voltage control to obtain the current reference value, which is used as the input of the current inner loop. After the current inner loop is tracked, the control signal of each flexible DC converter is obtained in combination with the coordinate transformation to realize the control of each flexible DC converter; finally, the active power reference value of the DC transformer is substituted into the constant power controller to calculate the phase shift angle, and the control signal of each DC transformer is generated through pulse width modulation to realize the control of the DC transformer at the DC microgrid interface. Through the above steps, the goal of global economic dispatch of the entire microgrid group can be achieved. Finally, based on the MATLAB / Simulink platform, a simulation was carried out on a microgrid cluster simulation system consisting of 2 ACMGs, 2 DCMGs, 2 flexible direct current (VSCs) and 2 direct current (DCTs), verifying the effectiveness of the control method proposed in this invention.

[0125] Those skilled in the art should understand that the above-mentioned application types are only examples, and other existing or future application types that are applicable to the embodiments of the present invention should also be included in the scope of protection of the present invention and are included here by reference.

[0126] Those skilled in the art should understand that Figure 2 The number of various network elements shown for the sake of simplicity may be smaller than the number in an actual network, but such omission is undoubtedly based on the premise that it will not affect the clear and sufficient disclosure of the embodiments of the invention.

[0127] Those skilled in the art will appreciate that the accompanying drawings are merely schematic diagrams of an embodiment, and the modules or processes in the accompanying drawings are not necessarily required to implement the present invention.

[0128] From the above description of the embodiments, it can be seen that those skilled in the art can clearly understand that the present invention can be implemented by means of software plus the necessary general-purpose hardware platform. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, can be embodied in the form of a software product. This computer software product can be stored in a storage medium such as ROM / RAM, a magnetic disk, or an optical disk, and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in various embodiments of the present invention or certain parts of the embodiments.

[0129] Each embodiment in this specification is described in a progressive manner. The same or similar parts between the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device or system embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, refer to the partial description of the method embodiments. The device and system embodiments described above are merely schematic, wherein the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of this embodiment. A person of ordinary skill in the art can understand and implement it without making any creative efforts.

[0130] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by a person skilled in the art within the technical scope disclosed in the present invention should be included in the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be based on the scope of protection of the claims.

Claims

1. A distributed coordination optimization control method for a microgrid group, characterized in that: include: Formulate optimization objectives and constraints for the microgrid cluster system and build an optimization model for the microgrid cluster system; Solving the optimization model according to the KKT condition to obtain a generalized incremental cost representing each distributed power source in the microgrid group system; Based on the differences in generalized incremental costs between sub-microgrids, the voltage reference value of the flexible DC converter (VSC) at the AC microgrid interface and the active power reference value of the DC transformer (DCT) at the DC microgrid interface are calculated using a finite-time consensus algorithm under distributed coordinated optimization control. The voltage reference value of the AC microgrid interface flexible direct current (VSC) is brought into the voltage outer loop of the constant voltage control to obtain a current reference value, which is used as the input of the current inner loop. After the current inner loop is tracked, the control signal of each flexible direct current (VSC) is obtained in combination with coordinate transformation to achieve control of each flexible direct current (VSC); The active power reference value of the DC microgrid interface DCT is brought into the constant power controller to calculate the phase shift angle, and the control signal of each DCT is generated through pulse width modulation to realize the control of the DC microgrid interface DCT.

2. The method according to claim 1, characterized in that The formulation of optimization objectives and constraints for the microgrid cluster system and the construction of an optimization model for the microgrid cluster system include: While maintaining the active power balance constraint of the microgrid group system, the active power limit constraint of the AC / DC microgrid distributed power source DG, and the active power limit constraint of the flexible direct current (VSC) and direct current (DCT), the goal is to minimize the power generation cost of all units in the microgrid group system. The optimization objectives and constraints of the microgrid group system are formulated, and the optimization model of the microgrid group system is constructed, namely: represents the cost function of the i-th DG in the k-th AC microgrid ACMG, represents the cost function of the jth DG in the pth DC microgrid DCMG, as well as ACMG k The active power, minimum active power and maximum active power emitted by the i-th DG in as well as DCMG p The active power, minimum active power and maximum active power emitted by the jth DG in is the active power transmitted by the kth VSC, and are the minimum active power and maximum active power transmitted by the kth VSC, is the active power transmitted by the pth DCT, and are the minimum active power and maximum active power transmitted by DCTp, N k is the number of AC microgrids, N ac is the number of DGs in the AC microgrid, N p is the number of DC microgrids, N dc is the number of DGs inside the DC microgrid, and are the total active power generated by the AC microgrid and the DC microgrid respectively. and are the total load sizes of the AC microgrid and the DC microgrid respectively.

3. The method according to claim 2, characterized in that Solving the optimization model according to the KKT condition to obtain the generalized incremental cost representing each distributed power source in the microgrid group system includes: Formulate the Lagrange function that characterizes the optimization model, namely: L(x) represents the Lagrange function, where x represents the input variable, λ G represents the Lagrange multiplier of the active power balance constraint, which corresponds to the dual variable related to the demand-supply balance equation of the microgrid optimal scheduling problem, and the dual variable is the incremental cost; where, The limit factor representing the active power limit constraint of each DG in the AC and DC microgrids; The limits representing the VSC and DCT transmission power limit constraints; In steady state, the relationship between the power generated by each microgrid in the system, the power transmitted by the VSC and DCT, and the load is expressed as: The KKT conditions representing the optimization model are as follows: in, Denotes the Lagrange function for the internal DG of the AC microgrid i The output power is derived, Denotes the Lagrange function for the DC microgrid internal DG j The power is emitted to obtain the derivative; as well as is the differential term of the cost function with respect to the active power generated by the DG. It is the Lagrange multiplier corresponding to the case of considering only the active power balance constraint; According to the KKT condition, the generalized incremental cost GIC of each DG is calculated as follows: It's ACMG k The GIC of the i-th DG in , It is DCMG p According to the equal incremental cost criterion, all DGs in the entire microgrid group must have the same generalized incremental cost, that is: Among them, this formula is the optimality condition of the microgrid group system optimization model. When this formula is met, the total power generation cost of the microgrid group system is minimized.

4. The method according to claim 3, characterized in that The voltage reference value of the AC microgrid interface flexible direct current (VSC) and the active power reference value of the DC microgrid interface DCT under distributed coordinated optimization control are calculated based on the difference in generalized incremental costs between the sub-microgrids according to the finite time consensus algorithm, including: To achieve convergence of active power transmission of each converter, a finite time consensus algorithm is used to calculate according to the following formula: Where c>0 is the control parameter, β∈(0,1) is the parameter representing the convergence speed of the microgrid group system, and sign(x) is the sign function. Through this algorithm, the microgrid group system is kept consistent with the state of the adjacent intelligent agents within a limited time, and the convergence time is defined as: Where V(x0) is the Lyapunov-Krasovskii candidate function, x0 is the initial state of the system; Based on the finite-time consensus algorithm, all converters are connected to the distributed communication network. According to the difference in GICs between the leading DGs in the AC microgrid and the DC microgrid, the change in the DC voltage of the flexible DC VSC is calculated. The DC voltage change of each flexible DC VSC is added to the rated voltage of the flexible DC VSC to obtain the voltage reference value of the mutual flexible DC VSC, which is: Where, For VSC k The voltage reference value, For VSC k Rated voltage; is the DC voltage variation of the flexible VSC, c vsc,p and c vsc,k is the control parameter, β is the adjustment parameter related to the controller convergence speed, where VSC k From the adjacent proxy node VSC through the upper communication network m With DCT p Get GIC information, sig is defined as: sig(x) β =sign(x)·|x| β , |·| is the absolute value function; and and VSC respectively k The rest of the VSCs and DCTs that communicate with the upper layer, and is the communication weight between VSCs and DCT in the upper communication network. Its value is 1 if there is communication, otherwise it is 0; and DCMG p DG j GIC, ACMG k DG i GIC, ACMG m DG j GIC, and Microgrid ACMG k ,DCMG p and ACMG m The set of dominant DGs; The active power reference value of the DC microgrid interface DCT under distributed coordinated optimization control is calculated according to the finite time consensus algorithm, namely: in, DCT p Transmitted active power reference value, c dct,p and c dct,k is the control parameter; β is the adjustment parameter related to the controller convergence speed, DCT p From the adjacent proxy node VSC through the upper communication network k With DCT n Get GIC information; sig is defined as: sig(x) β =sign(x)·|x| β , |·| is the absolute value function; and and DCT respectively p The rest of the VSCs and DCTs that communicate with the upper layer, and is the communication weight between VSCs and DCT in the upper communication network. Its value is 1 if there is communication, otherwise it is 0; and ACMG k DG i Generalized incremental cost, DCMG p DG j Generalized incremental cost, DCMG n DG i The generalized incremental cost. and Microgrid ACMG k ,DCMG p and DCMG n The set of dominant DGs in .

5. The method according to claim 4, characterized in that The voltage reference value of the AC microgrid interface flexible direct current VSC is brought into the voltage outer loop of the constant voltage control to obtain a current reference value, the current reference value is used as the input of the current inner loop, and after the current inner loop tracking, the control signal of each flexible direct current VSC is obtained in combination with the coordinate transformation to realize the control of each flexible direct current VSC, including: The voltage reference value of the flexible DC VSC is brought into the voltage outer loop of the constant voltage control to obtain the current reference value, which is used as the input of the current inner loop. After the current inner loop tracking, combined with the abc / dq0 coordinate transformation, the control signal of each flexible DC VSC is obtained to realize the control of each flexible DC VSC. The control method is as follows: Where, VSC k D-axis reference value of the current loop; For VSC k DC voltage reference value; VSC k The actual DC voltage; VSC k The q-axis reference value of the current loop; VSC k Reactive power reference value; VSC k The actual reactive power of p1 and k i1 are the proportional and integral parameters of the d-axis controller; k p2 and k i2 are the proportional and integral parameters of the q-axis controller; 1 / s represents the integral link.

6. The method according to claim 4, characterized in that The active power reference value of the DC microgrid interface DCT is brought into the constant power controller to calculate the phase shift angle, and the control signal of each DCT is generated by pulse width modulation to realize the control of the DC microgrid interface DCT, including: The active power reference value of DCT is brought into the constant power controller to calculate the phase shift angle, and the control signal of each DCT is generated through pulse width modulation to realize the control of the DC microgrid interface DCT, that is: Where, is the actual active power transmitted by DCTp, k p3 and k i3 are the proportional and integral parameters of the controller, and the shift ratio is obtained by constant power control. Calculate the shift angle α between the switch tube conduction pulses; T h is the switching period; 1 / s represents the integral.

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