A distributed coordination and optimization control method for micro-grid groups

Abstract

The application 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 KKT conditions to obtain GIC of each DG; calculating voltage reference values of AC micro-grid interface flexible VSC and active power reference values of DC micro-grid interface DCT under distribution coordination optimization control based on differences between GIC of each sub-micro-grid; bringing the voltage reference values of the flexible converter into the voltage outer ring of the constant voltage control to obtain current reference values, so as to realize control of each flexible VSC; and bringing the active power reference values of the DC transformer into the constant power controller to calculate a phase shift angle, so as to realize control of the DC micro-grid interface DCT. The method can realize economic dispatching of active power of each distributed power supply in the micro-grid, and also realizes coordinated optimization control of the micro-grid group system through coordination between each flexible converter and the DC transformer.

Description

Technical Field

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

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

[0003] Microgrid cluster systems are divided into two types: 1) microgrid clusters based on interconnection of power electronic devices; and 2) microgrid cluster systems with flexible DC interconnection. The first type, where microgrids are connected only through a single power electronic device (PED), lacks a DC distribution network and can only connect adjacent feeders. The second type of microgrid cluster system, however, can connect AC and DC microgrids to the DC distribution bus via flexible DC converters and DC transformers, facilitating cross-feed connections between AC and DC microgrids and enabling wider collaborative sharing of grid resources.

[0004] Microgrids primarily employ hierarchical control to achieve electrical quantity restoration and optimized system operation. This hierarchical control includes primary, secondary, and tertiary control. Primary control mainly achieves local coordinated control of the microgrid to maintain electrical quantity stability. In current research, secondary control in microgrids is mainly used to achieve control objectives such as frequency and voltage restoration, and active power proportional allocation. Tertiary control aims to minimize the generation cost of the microgrid, focusing primarily on economic dispatch. Since the generation costs of different distributed generation (DG) systems within a microgrid group vary, a reasonable distributed coordinated optimization dispatch scheme should be designed for the microgrid to minimize operating costs. Therefore, in addition to the coordinated operation of converters between microgrid groups, achieving optimized operation of the entire system is also a key issue.

[0005] Currently, existing solutions for coordinated optimization control of microgrids mainly focus on the single microgrid level. These solutions have several drawbacks: while flexible interconnected microgrid systems offer significant advantages, the diverse interests of different stakeholders, the complexity of multi-terminal AC / DC networks, the multidirectional dynamic flow of power, and the potential conflicts between different control objectives all contribute to the problem. Furthermore, the lack of distributed coordinated optimization control methods within and between microgrids hinders the full realization of the advantages of microgrid systems in high-proportion renewable energy consumption. In severe scenarios, system instability may even occur, impacting the system's economic operation. Summary of the Invention

[0006] Embodiments of the present invention provide a distributed coordination optimization control method for microgrid groups, so as to achieve effective distributed coordination optimization control of microgrid groups.

[0007] To achieve the above objectives, the present invention adopts the following technical solution.

[0008] A distributed coordinated optimization control method for microgrid groups includes:

[0009] Develop optimization objectives and constraints for the microgrid group system, and construct an optimization model for the microgrid group system.

[0010] Solving the optimization model based on the KKT conditions yields the generalized incremental cost characterizing each distributed power source in the microgrid cluster system.

[0011] Based on the difference in generalized incremental cost among the various sub-microgrids, the voltage reference value of the AC microgrid interface flexible DC converter VSC and the active power reference value of the DC transformer DCT of the DC microgrid interface are calculated according to the finite-time consensus algorithm.

[0012] The voltage reference value of the AC microgrid interface flexible DC VSC is substituted into the voltage outer loop of constant voltage control to obtain the current reference value. This current reference value is used as the input of the current inner loop. After tracking by the current inner loop, the control signal of each flexible DC VSC is obtained by combining coordinate transformation, thereby realizing the control of each flexible DC VSC.

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

[0014] Preferably, the step of formulating the optimization objectives and constraints of the microgrid group system and constructing the optimization model of the microgrid group system includes:

[0015] While maintaining the active power balance constraints of the microgrid cluster system, the active power limit constraints of distributed generation (DG) in AC / DC microgrids, and the active power limit constraints of flexible DC VSC and DC DCT transmission, the goal is to minimize the generation cost of all units in the microgrid cluster system. Therefore, the optimization objective and constraints of the microgrid cluster system are formulated, and an optimization model for the microgrid cluster system is constructed, namely:

[0016]

[0017] This represents the cost function of the i-th distributed generation (DG) in the k-th AC microgrid (ACMG). This represents the cost function of the j-th distributed generation (DG) in the p-th DC microgrid (DCMG). as well as They are ACMG k The active power, minimum active power, and maximum active power emitted by the i-th DG are given. as well as They are DCMG p The active power, minimum active power, and maximum active power emitted by the j-th DG are given. Let k be the active power transmitted by the k-th VSC. and These represent the minimum and maximum active power transmitted by the k-th VSC, respectively. Let p be the active power transmitted by the p-th DCT. and These represent the minimum and maximum active power transmitted by DCTp, respectively, N. k N represents the number of AC microgrids. ac N represents the number of distributed generators (DGs) within the AC microgrid. p N represents the number of DC microgrids. dc This represents the number of DGs within the DC microgrid. and These represent the total active power generated by the AC microgrid and the DC microgrid, respectively. and These represent the total load size of the AC microgrid and the DC microgrid, respectively.

[0018] Preferably, the step of solving the optimization model based on the KKT conditions to obtain the generalized incremental cost characterizing each distributed power source in the microgrid group system includes:

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

[0020]

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

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

[0023]

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

[0025]

[0026] in, This indicates that the Lagrange function applies to the internal DG of the AC microgrid. i Differentiate the output power. This indicates that the Lagrange function applies to the internal DG of a DC microgrid. j Differentiate the output power; as well as It is the differential term of the cost function with respect to the active power emitted by the DG. It is the Lagrange multiplier corresponding to the case where only the active power balance constraint is considered.

[0027] The generalized incremental cost (GIC) of each DG is calculated based on the KKT conditions as follows:

[0028]

[0029]

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

[0031]

[0032] This equation represents the optimality condition of the microgrid cluster system optimization model. Under the condition that this equation is satisfied, the total power generation cost of the microgrid cluster system is minimized.

[0033] Preferably, the calculation of the voltage reference value of the AC microgrid interface flexible DC VSC and the active power reference value of the DC microgrid interface DCT under distributed coordinated optimization control based on the difference in generalized incremental costs among the various sub-microgrids and using a finite-time consensus algorithm includes:

[0034] To achieve convergence of active power transmission across all converters, a finite-time consensus algorithm is used to calculate the following formula:

[0035]

[0036] In the formula, 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. This algorithm enables the microgrid group system to maintain consistency with the state of its neighboring agents within a finite time. The convergence time is defined as:

[0037]

[0038] In the formula, V(x0) is the Lyapunov-Krasovskii candidate function, and 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 dominant DGs in the AC and DC microgrids, the change in DC voltage of the flexible DC VSC is calculated. This change in DC voltage of each flexible DC VSC is added to its rated voltage to obtain the voltage reference value for the mutual flexible DC VSCs.

[0040]

[0041] In the formula, For VSC k Voltage reference value, For VSC k The rated voltage; c represents the change in DC voltage of the flexible DC VSC. vsc,p and c vsc,k For control parameters, β is an adjustment parameter related to the convergence speed of the controller, where VSC k From the adjacent agent node VSC via the upper-layer communication network m With DCT p To obtain information about the GIC, sig is defined as: sig(x) β =sign(x)·|x| β |·| is the absolute value function; and They are respectively with VSC kThe set of other VSCs and DCTs that perform upper-layer communication. and This is the communication weight between VSCs and DCT in the upper-layer communication network. Its value is 1 if there is communication, and 0 otherwise. and DCMG p DG China j GIC, ACMG k DG China i GIC, ACMG m DG China j GIC, and These are microgrids ACMG k DCMG p and ACMG m The collection dominated by DG in China;

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

[0043]

[0044] Among them, P DCTp,ref DCT p Reference value for transmitted active power, c dct,p and c dct,k β is the control parameter; β is the adjustment parameter related to the convergence speed of the controller, DCT p From the adjacent agent node VSC via the upper-layer communication network k With DCT n Obtain information about the GIC; sig is defined as: sig(x) β =sign(x)·|x| β |·| is the absolute value function; and They are DCT and p The set of other VSCs and DCTs that perform upper-layer communication. and This is the communication weight between VSCs and DCT in the upper-layer communication network. Its value is 1 if there is communication, and 0 otherwise. and ACMG k DG China i Generalized incremental cost, DCMG p DG China j Generalized incremental cost, DCMG n DG China i The generalized incremental cost. and These are microgrids ACMG k DCMG p and DCMG n The collection dominated by DG in China.

[0045] Preferably, the step of substituting the voltage reference value of the AC microgrid interface flexible DC VSC into the voltage outer loop of constant voltage control to obtain the current reference value, using this current reference value as the input of the current inner loop, and after tracking by the current inner loop, obtaining the control signal for each flexible DC VSC by combining coordinate transformation, thereby realizing the control of each flexible DC VSC, includes:

[0046] The voltage reference value of the flexible DC VSC 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 tracking by the current inner loop, the control signal of each flexible DC VSC is obtained by combining the abc / dq0 coordinate transformation, thereby realizing the control of each flexible DC VSC. The control method is as follows:

[0047]

[0048] In the formula, For flexible VSC k d-axis reference value for the current loop; For VSC k DC voltage reference value; For flexible VSC k The actual DC voltage; For flexible VSC k q-axis reference value for the current loop; For flexible VSC k The reactive power reference value; For flexible VSC k Actual reactive power; k p1 and k i1 For the proportional and integral parameters of the d-axis controller; k p2 and k i2 These are the proportional and integral parameters of the q-axis controller; 1 / s represents the integral element.

[0049] Preferably, the step of inputting the active power reference value of the DC microgrid interface DCT into the constant power controller to calculate the phase shift angle, and generating control signals for each DCT through pulse width modulation to achieve control of the DC microgrid interface DCT includes:

[0050] The active power reference value of the DCT is input into the constant power controller to calculate the phase shift angle. Control signals for each DCT are generated through pulse width modulation to achieve control of the DCT at the DC microgrid interface.

[0051]

[0052] In the formula, DCT p The actual active power transmitted, k p3 and k i3 The proportional and integral parameters of the controller are used to obtain the shift ratio through constant power control. Calculate the shift angle α between the turn-on pulses of the switching transistor; T h The switching period is 1 / s; 1 / s represents the integral.

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

[0054] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and will become apparent from the description or may be learned by practice of the invention. Attached Figure Description

[0055] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the following description of the embodiments will be briefly introduced. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0056] Figure 1 A flowchart illustrating a distributed coordination optimization control method for a microgrid group, provided as an embodiment of the present invention;

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

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

[0059] Figure 4 A control block diagram of a flexible DC-DC converter VSC provided in an embodiment of the present invention for a distributed coordination optimization control method for a microgrid group;

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

[0061] Figure 6 and Figure 7The simulation results are shown in the figure. This invention provides a distributed coordination optimization control method for microgrid groups. Detailed Implementation

[0062] 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 denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0063] Those skilled in the art will understand that, unless specifically stated otherwise, the singular forms “a,” “an,” “the,” and “the” used herein may also include the plural forms. It should be further understood that the term “comprising” as used in this specification means the presence of the stated 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 say an element is “connected” or “coupled” to another element, it can be directly connected or coupled to the other element, or there may be intermediate elements. Furthermore, “connected” or “coupled” as used herein can include wireless connections or couplings. The term “and / or” as used herein includes any and all combinations of one or more of the associated listed items.

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

[0065] To facilitate understanding of the embodiments of the present invention, the following will provide further explanation and description with reference to the accompanying drawings and several specific embodiments. These embodiments do not constitute a limitation on the embodiments of the present invention.

[0066] Since the topology of flexible interconnected microgrids includes DC distribution buses, the voltage of these buses also needs to be reasonably controlled within a certain range. Therefore, designing appropriate and effective distributed coordination and optimization control strategies for microgrids is of great significance for achieving frequency and voltage stability and optimal allocation of active power, thereby rapidly improving system stability, economy, and security.

[0067] This invention provides a distributed coordinated optimization control method for microgrid clusters. This method achieves coordinated and optimized operation of the microgrid cluster system by coordinating the control of converters between microgrids. First, optimization objectives and constraints are defined for the microgrid cluster system, and an optimization model of the microgrid cluster system is constructed. The optimization model is solved according to the KKT conditions to obtain the generalized incremental cost (GIC) that characterizes each distributed generation (DG). Then, based on the differences in the GIC among the sub-microgrids, the voltage reference value of the AC microgrid interface flexible DC converter (VSC) and the DC microgrid interface DC transformer (DC converter) under distributed coordinated optimization control are calculated using a finite-time consensus algorithm. The active power reference value of the DC-DC converter is obtained; then, the voltage reference value of the DC-DC converter is substituted 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 tracking by the current inner loop, the control signal of each DC-DC converter is obtained by combining coordinate transformation, thereby realizing the control of each DC-DC converter; constant power control is adopted for all DC transformers. Based on the obtained active power reference value, the phase shift angle is calculated, and 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 coordination optimization control method for microgrid groups provided in this embodiment of the invention is as follows: Figure 1 As shown, the system topology diagram of a distributed coordination optimization control method for microgrid groups provided in this embodiment of the invention is as follows. Figure 2 As shown in the figure, the network communication diagram of a distributed coordination optimization control method for a microgrid group provided in this embodiment of the invention is as follows. Figure 3 As shown. The method includes the following processing steps:

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

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

[0071] Step S30: Based on the difference in generalized incremental cost among the various sub-microgrids, the voltage reference value of the AC microgrid interface flexible DC VSC and the active power reference value of the DC microgrid interface DCT under distributed coordinated optimization control are calculated according to the finite-time consensus algorithm.

[0072] The voltage reference value of the flexible DC converter is input 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 tracking by the current inner loop, the control signal of each flexible DC converter is obtained by combining coordinate transformation, thereby realizing the control of each flexible DC converter.

[0073] The active power reference value of the DC transformer is input into the constant power controller to calculate the phase shift angle. 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.

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

[0075]

[0076] This represents the cost function of the i-th distributed generation (DG) in the k-th AC microgrid (ACMG). This represents the cost function of the j-th distributed generation (DG) in the p-th DC microgrid (DCMG). as well as They are ACMG k The active power, minimum active power, and maximum active power emitted by the i-th DG are given. as well as They are DCMG p The active power, minimum active power, and maximum active power emitted by the j-th DG. Let k be the active power transmitted by the k-th VSC. and These represent the minimum and maximum active power transmitted by the k-th VSC, respectively. Let p be the active power transmitted by the p-th DCT. and These represent the minimum and maximum active power transmitted by DCTp, respectively; N k N represents the number of AC microgrids. ac N represents the number of distributed generators (DGs) within the AC microgrid. p N represents the number of DC microgrids. dc The number of DGs inside the DC microgrid; and These represent the total active power generated by the AC microgrid and the DC microgrid, respectively. and These represent the total load sizes of the AC microgrid and the DC microgrid, respectively. For this microgrid group system, the optimization model considered aims to minimize the generation cost of all units in the microgrid group system while maintaining the system's active power balance constraints, the active power limit constraints of the AC / DC microgrid DG, and the active power limit constraints of the flexible DC VSC and DC DCT transmission.

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

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

[0079]

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

[0081] In steady state, the relationship between the power generated by each microgrid, 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 as follows:

[0084]

[0085] in, This indicates that the Lagrange function applies to the internal DG of the AC microgrid. i Differentiate the output power. This indicates that the Lagrange function applies to the internal DG of a DC microgrid. j Differentiate the output power; as well as It is the differential term of the cost function with respect to the active power emitted by the DG. It is the Lagrange multiplier corresponding to the case where only the active power balance constraint is considered.

[0086] Finally, based on the KKT conditions, the GIC of each DG can be calculated as follows:

[0087]

[0088] After considering the active power inequality constraint, the resulting incremental cost is called the generalized incremental cost, i.e.: It's ACMG k The generalized incremental cost of the i-th DG; It is DCMG p The generalized incremental cost of the j-th distributed generation (DG) in the microgrid. According to the equal incremental cost criterion, all DGs within the entire microgrid group must have the same generalized incremental cost to achieve global economic dispatch, i.e.:

[0089]

[0090] This equation represents the optimality condition of the microgrid cluster system optimization model. Under the condition that this equation is satisfied, the total power generation cost of the microgrid cluster system is minimized.

[0091] Specifically, step S30 includes: the control block diagram of the flexible DC converter VSC of the distributed coordination optimization control method for microgrid groups provided in this embodiment of the invention is as follows: Figure 4 As shown, the control block diagram of the DCT of a distributed coordination optimization control method for a microgrid group provided in this embodiment of the invention is as follows. Figure 5 As shown.

[0092] Based on the differences in generalized incremental costs among the various 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 optimization control are calculated using the finite-time consensus algorithm.

[0093] The finite-time consensus algorithm can be used to achieve rapid convergence of active power transmission between various converters, calculated according to the following formula:

[0094]

[0095] In the formula, c>0 is the control parameter, β∈(0,1) is the parameter representing the system's convergence speed, and sign(x) is the sign function. This algorithm enables the system to maintain consistency with the states of neighboring agents within a finite time, and the convergence time can be defined as:

[0096]

[0097] In the formula, 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 suppression.

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

[0099]

[0100] In the formula, For VSC k Voltage reference value, For VSC k The rated voltage; c represents the change in DC voltage of the flexible DC VSC. vsc,p and c vsc,k Here, β is a control parameter, and it is an adjustment parameter related to the convergence speed of the controller. In the formula, VSC... k From the adjacent agent node VSC via the upper-layer communication network m With DCT p Retrieve information about the GIC. The sig definition is: sig(x) β =sign(x)·|x| β |·| is the absolute value function; and They are respectively with VSC k The set of other VSCs and DCTs that perform upper-layer communication. and This is the communication weight between VSCs and DCT in the upper-layer communication network. Its value is 1 if there is communication, and 0 otherwise. and DCMG p DG China j Generalized incremental cost, ACMG k DG China i Generalized incremental cost, ACMG m DG China j The generalized incremental cost. and These are microgrids ACMG k DCMG p and ACMG m The collection dominated by DG in China.

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

[0102]

[0103] in, DCT p Reference value for transmitted active power, c dct,p and c dct,k β is the control parameter; β is the adjustment parameter related to the convergence speed of the controller. Where, DCT p From the adjacent agent node VSC via the upper-layer communication network k With DCT n Obtain information about the GIC; sig is defined as: sig(x) β =sign(x)·|x| β |·| is the absolute value function; and They are DCT and p The set of other VSCs and DCTs that perform upper-layer communication. and This is the communication weight between VSCs and DCT in the upper-layer communication network. Its value is 1 if there is communication, and 0 otherwise. and ACMG k DG China i Generalized incremental cost, DCMG p DG China j Generalized incremental cost, DCMG n DG China i The generalized incremental cost. and These are microgrids ACMG k DCMG p and DCMG n The collection dominated by DG in China.

[0104] Specifically, step S40 includes: inputting the voltage reference value of the flexible DC converter into the voltage outer loop of the constant voltage control to obtain the current reference value, which is then used as the input of the current inner loop. After tracking by the current inner loop, the control signal for each flexible DC converter is obtained by combining the abc / dq0 coordinate transformation, thereby realizing the control of each flexible DC converter. The control method is as follows:

[0105]

[0106] In the formula, For flexible VSC k d-axis reference value for the current loop; For VSC k DC voltage reference value; For flexible VSC k The actual DC voltage. For flexible VSC k q-axis reference value for the current loop; For flexible VSC k The reactive power reference value; For flexible VSC k Actual reactive power; k p1 and k i1 For the proportional and integral parameters of the d-axis controller; k p2 and k i2 Here are the proportional and integral parameters for the q-axis controller; 1 / s represents the integral element. Based on the controller design above, all flexible DC VSCs work together to stabilize the DC bus voltage, resulting in high reliability of the DC bus voltage.

[0107] The active power reference value of the DC transformer is input into the constant power controller to calculate the phase shift angle. Control signals for each DC transformer are generated through pulse width modulation, enabling control of the DC transformers at the DC microgrid interface and achieving rapid tracking of transmitted active power.

[0108]

[0109] In the formula, DCT p The 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 through constant power control. Then calculate the shift angle α between the switching transistor's conduction pulses; T h The switching period is 1 / s; 1 / s represents the integral. Based on the controller designed above, the DCT... p The transmitted active power can accurately track the reference value. Enables power exchange between AC microgrid groups and DC microgrid groups.

[0110] Example 1

[0111] In this implementation, a distributed coordination optimization control method for microgrid groups is applied to... Figure 2 The example system shown is illustrated in Example 2. This Example 2 is a microgrid group system comprising 2 AC microgrids (4 AC DGs), 2 DC microgrids (4 DC DGs), 2 flexible DC VSCs, and 2 DC DCTs. Using this topology as a computational example, the effectiveness of the distributed coordination optimization control method for microgrid groups proposed in this invention is verified. The simulation results of the distributed coordination optimization control method for microgrid groups provided in Example 2 are shown below. Figure 6 and Figure 7 As shown, the results of verifying the effectiveness of this invention come from Simulink simulation software.

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

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

[0114] Table 1 Circuit parameters of the microgrid group system

[0115]

[0116] Table 2 Control parameters of the microgrid group system

[0117]

[0118] The total simulation time is 4 seconds, and the step size is 1×10. -5 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 group layer (MGC-layer) controllers activate. 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 of the Global Interchange Controllers (GICs) for all distributed grids (DGs) in ACMGs and DCMGs are presented. Before t=2s, the GICs of all DGs are inconsistent. After t=2s, the MG-layer and MGC-layer controllers bring all GICs into consistency. Even with load changes, the GICs remain consistent. Therefore, global economic dispatch of the microgrid group system is 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 scheduling under our proposed controller. Figure 7 (b) indicates that the voltage of the DC distribution network remains around the rated value of 750V as the operating conditions change, and it has high reliability. Figure 7(c) shows the output active power of all DGs in ACMG1. After the load on ACMG1 increases at t = 4s, DG1, due to its lower cost factor, shares more active power. Therefore, it reaches a maximum value of 20kW between t = 4s and t = 10s, and then is limited to this value and no longer changes.

[0120] Figure 7 (d) shows the quota factor corresponding to each DG in ACMG1. It can be seen that the quota factor of DG1... It becomes greater than 0 after t = 4s, and remains 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 on DCMG1 decreases from 65kW to 45kW, it returns to its original state.

[0121] Figure 7 (e) and (f) represent the active power transmitted by VSC and DCT, respectively, and their limit factors. At t = 6s, when the load of DCMG1 increases from 45kW to 65kW, the active power transmitted by both VSC2 and DCT1 reaches its maximum value of 20kW, and is then limited to this value and no longer changes. 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 on DCMG1 decreases from 65kW to 45kW, Figure 7 (e) and (f) show that the active power transmitted by VSC2 and DCT1, as well as their respective limit factors, have been restored to their previous levels. Therefore, the results above demonstrate that the proposed control method achieves the limit on the converter's transmitted power.

[0122] Figure 7 (g) and (h) show that after the controllers of the MG-layer and MGC-layer are activated at t = 2s, the frequency of ACMG1 and the average voltage of all DGs in DCMG1 are controlled to the desired values ​​of 50Hz and 375V, respectively. 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 distributed coordinated optimization control method for microgrid cluster systems proposed in this invention can ensure that control objectives within and between microgrids are achieved simultaneously. Furthermore, it considers the power output constraints of distributed generation (DG) within the microgrid and the transmission power capacity constraints of variable transmission control systems (VSCs) and distributed transmission control devices (DCTs) between microgrids, effectively preventing the risk of microgrid overload.

[0124] In summary, this invention achieves coordinated and optimized operation of a microgrid cluster system by coordinating the control of converters between microgrids. To optimize a microgrid cluster system, an optimization model is constructed based on the established optimization objectives and constraints. The model is then solved using the KKT conditions to obtain the generalized incremental cost (GIC) characterizing each distributed generation (DG). Next, based on the differences in GIC among the sub-microgrids, the voltage reference values ​​for the AC microgrid interface flexible DC converter (VSC) and the active power reference values ​​for the DC microgrid interface DC transformer (DCT) under distributed coordinated optimization control are calculated using a finite-time consensus algorithm. Furthermore, the voltage reference values ​​of the VSCs are input into the constant voltage control outer loop to obtain current reference values, which serve as the input to the current inner loop. After tracking through the current inner loop, coordinate transformation is used to obtain the control signals for each VSC, thus controlling each VSC. Finally, the active power reference values ​​of the DC transformers are input into the constant power controller to calculate the phase shift angle. Pulse width modulation is then used to generate control signals for each DC transformer, thus controlling the DC transformer at the DC microgrid interface. Through these steps, the goal of global economic dispatch for the entire microgrid cluster can be achieved. Finally, simulations were performed on a microgrid group simulation system containing 2 ACMGs, 2 DCMGs, 2 flexible DC VSCs, and 2 DC DCTs based on the MATLAB / Simulink platform, verifying the effectiveness of the control method proposed in this invention.

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

[0126] Those skilled in the art should understand that Figure 2 The number of various network elements shown may be less than that in an actual network for the sake of simplicity, but such omissions are undoubtedly on the premise that they do not affect the clear and sufficient disclosure of the embodiments of the invention.

[0127] Those skilled in the art will understand that the accompanying drawings are merely schematic diagrams of one embodiment, and the modules or processes shown in the drawings are not necessarily essential for implementing the present invention.

[0128] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that the present invention can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of the present invention, or the part 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, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of the present invention.

[0129] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, for apparatus or system embodiments, since they are basically similar to method embodiments, the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. The apparatus and system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[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 variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A distributed coordinated optimization control method for a microgrid group, characterized in that, include: Develop optimization objectives and constraints for the microgrid group system, and construct an optimization model for the microgrid group system. Solving the optimization model based on the KKT conditions yields the generalized incremental cost characterizing each distributed power source in the microgrid cluster system. Based on the difference in generalized incremental cost among the various sub-microgrids, the voltage reference value of the AC microgrid interface flexible DC converter VSC and the active power reference value of the DC transformer DCT of the DC microgrid interface are calculated according to the finite-time consensus algorithm. The voltage reference value of the AC microgrid interface flexible DC VSC is substituted into the voltage outer loop of constant voltage control to obtain the current reference value. This current reference value is used as the input of the current inner loop. After tracking by the current inner loop, the control signal of each flexible DC VSC is obtained by combining coordinate transformation, thereby realizing the control of each flexible DC VSC. The active power reference value of the DC microgrid interface DCT is input 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. The aforementioned process of defining the optimization objectives and constraints for the microgrid group system and constructing an optimization model for the microgrid group system includes: While maintaining the active power balance constraints of the microgrid cluster system, the active power limit constraints of distributed generation (DG) in AC / DC microgrids, and the active power limit constraints of flexible DC VSC and DC DCT transmission, the goal is to minimize the generation cost of all units in the microgrid cluster system. Therefore, the optimization objective and constraints of the microgrid cluster system are formulated, and an optimization model for the microgrid cluster system is constructed, namely: Representing the k In the ACMG (Alternating Current Microgrid) of the first ACMG i The cost function of a DG Representing the p The first DC microgrid DCMG j The cost function of a DG , as well as They are ACMG k The Middle i The active power, minimum active power, and maximum active power generated by each DG. , as well as They are DCMG p The Middle j The active power, minimum active power, and maximum active power generated by each DG. For the first k The active power transmitted by each VSC. and The first k The minimum and maximum active power of each VSC transmission. For the first p The active power transmitted by each DCT. and These represent the minimum and maximum active power transmitted by DCTp, respectively. The number of AC microgrids. The number of DGs within the AC microgrid. The number of DC microgrids. This represents the number of distributed generation (DG) units within the DC microgrid. and These represent the total active power generated by the AC microgrid and the DC microgrid, respectively. and These refer to the total load size of the AC microgrid and the DC microgrid, respectively. The method of solving the optimization model based on the KKT conditions to obtain the generalized incremental cost characterizing each distributed power source in the microgrid group system includes: Formulate a Lagrangian characterization for the optimization model. Lagrange Function, that is: L( x )represent Lagrange function, where x The independent variable representing the input. The Lagrange multiplier representing the active power balance constraint corresponds to the dual variable related to the demand-supply balance equation in the microgrid optimal scheduling problem, which is the incremental cost; where, The limit factor represents the active power limit constraint issued by each DG in the AC and DC microgrids. Limits representing the transmission power limits of VSC and DCT; In steady state, the relationship between the power generated by each microgrid, the power transmitted by the VSC and DCT, and the load in the system is expressed as follows: The KKT conditions representing the optimization model are as follows: in, express Lagrange Functions for DG within AC microgrids i Differentiate the output power. express Lagrange Functions for the internal DG of a DC microgrid j Differentiate the output power; as well as It is the differential term of the cost function with respect to the active power emitted by the DG. It is the Lagrange multiplier corresponding to the case where only the active power balance constraint is considered. The generalized incremental cost (GIC) of each DG is calculated based on the KKT conditions as follows: It's ACMG k The Middle i A DG GIC, It is DCMG p The Middle j According to the equal incremental cost criterion, for each DG in the entire microgrid group, all DGs must have the same generalized incremental cost, i.e.: Among them, the above The calculation formula is the optimality condition of the microgrid group system optimization model. Under the condition of satisfying this formula, the total power generation cost of the microgrid group system is minimized.

2. The method according to claim 1, characterized in that, The voltage reference value of the AC microgrid interface flexible DC VSC and the active power reference value of the DC microgrid interface DCT, calculated using the finite-time consensus algorithm based on the difference in generalized incremental costs among the various sub-microgrids, include: To achieve convergence of active power transmission across all converters, a finite-time consensus algorithm is used to calculate the following formula: In the formula, , is a control parameter. , is a parameter representing the convergence speed of a microgrid group system. sign ( x () is the sign function. This algorithm enables the microgrid group system to maintain state consistency with neighboring agents within a finite time. The convergence time is defined as: In the formula, It is a Lyapunov-Krasovskii candidate function. This 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 GIC between the dominant DGs in the AC and DC microgrids, the change in DC voltage of the flexible DC VSC is calculated. This change in DC voltage of each flexible DC VSC is added to its rated voltage to obtain the voltage reference value for the mutual flexible DC VSCs. In the formula, For VSC k Voltage reference value, For VSC k Rated voltage; This represents the change in DC voltage of the flexible DC VSC. and For control parameters, It is an adjustment parameter related to the convergence speed of the controller, where VSC k From the adjacent agent node VSC via the upper-layer communication network m With DCT p Obtain GIC information, sig Defined as: , It is an absolute value function; and They are respectively with VSC k The remaining VSCs and DCTs that perform upper-layer communication. , and This is the communication weight between VSC and DCT in the upper-layer communication network. Its value is 1 if there is communication, and 0 otherwise. , and DCMG p DG China j GIC, ACMG k DG China i GIC, ACMG m DG China j GIC, , and These are microgrids ACMG k DCMG p and ACMG m The collection dominated by DG in China; The active power reference value of the DC microgrid interface DCT under distributed coordinated optimization control is calculated based on the finite-time consensus algorithm, namely: in, DCT p Reference value for transmitted active power. and For control parameters; These are adjustment parameters related to the convergence speed of the controller, DCT. p From the adjacent agent node VSC via the upper-layer communication network k With DCT n Obtain GIC information; sig Defined as: , It is an absolute value function; and They are DCT and p The remaining VSCs and DCTs that perform upper-layer communication. , and This is the communication weight between VSC and DCT in the upper-layer communication network. Its value is 1 if there is communication, and 0 otherwise. , and ACMG k DG China i Generalized incremental cost, DCMG p DG China j Generalized incremental cost, DCMG n DG China i The generalized incremental cost, , and These are microgrids ACMG k DCMG p and DCMG n The collection dominated by DG in China.

3. The method according to claim 2, characterized in that, The process involves inputting the voltage reference value of the AC microgrid interface flexible DC VSC into the constant voltage control outer loop to obtain the current reference value, using this current reference value as the input of the current inner loop, and after tracking by the current inner loop, combining coordinate transformation to obtain the control signal for each flexible DC VSC, thereby realizing the control of each flexible DC VSC. This includes: The voltage reference value of the flexible DC VSC 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 tracking by the current inner loop, the control signal of each flexible DC VSC is obtained by combining the abc / dq0 coordinate transformation, thereby realizing the control of each flexible DC VSC. The control method is as follows: In the formula, For flexible VSC k Current loop d Axis reference value; For VSC k DC voltage reference value; For flexible VSC k The actual DC voltage; For flexible VSC k Current loop q Axis reference value; For flexible VSC k The reactive power reference value; For flexible VSC k The actual reactive power; and For the proportional and integral parameters of the d-axis controller; and For the proportional and integral parameters of the q-axis controller; 1 / This indicates the integration process.

4. The method according to claim 2, characterized in that, The method of inputting the active power reference value of the DC microgrid interface DCT into the constant power controller to calculate the phase shift angle, and generating control signals for each DCT through pulse width modulation to achieve control of the DC microgrid interface DCT includes: The active power reference value of the DCT is input into the constant power controller to calculate the phase shift angle. Control signals for each DCT are generated through pulse width modulation to achieve control of the DCT at the DC microgrid interface. In the formula, DCT p The actual active power transmitted and The proportional and integral parameters of the controller are used to obtain the shift ratio through constant power control. Calculate the shift angle between the turn-on pulses of the switching transistor. ; For the switching cycle; 1 / This represents the integral.

Images