Optimized scheduling method, system and equipment based on multi-stage micro-grid, and medium

Abstract

The invention belongs to the technical field of power distribution network optimal scheduling, and discloses an optimal scheduling method, system, equipment and medium based on a multistage micro-grid, and the method comprises the steps: building a micro-grid operation optimization model based on the equipment parameter information of each micro-grid in combination with the electricity purchasing and selling price of a common connection point of the micro-grid, and solving to obtain a micro-grid optimal scheduling strategy; a micro-grid group operation optimization model is constructed and solved until the difference value of the two solutions is within a preset range or reaches a preset number of iterations, and an optimal scheduling strategy of the micro-grid group is obtained; and establishing a power distribution network operation optimization model, and iteratively solving the power distribution network operation optimization model until the difference value of the two solutions is within a preset range or reaches a preset iteration number, thereby obtaining an optimal scheduling strategy of the power distribution network. According to the method, maximum autonomous optimal scheduling of each layer and each level of the micro-grid-micro-grid group-power distribution network is realized, and the safety and reliability of each level of the power distribution network are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of distribution network optimization dispatching, and in particular to an optimization dispatching method, system, equipment and medium based on a multi-level microgrid. Background Art

[0002] With the deepening of global energy transformation, the rapid development of renewable energy and distributed energy technologies, the traditional centralized power system is accelerating its transformation towards distributed, intelligent and regional autonomy. As an important part of the modern power system, microgrids can achieve efficient utilization and flexible scheduling of local energy by integrating distributed power sources, energy storage systems and power loads. In this context, the coordinated optimization of multi-level energy systems has become a key direction of technological innovation in the power industry. How to achieve intelligent scheduling, resource sharing and energy balance at the level of microgrids, microgrid clusters and distribution networks has become a key scientific issue in promoting the intelligent development of power systems.

[0003] Microgrid is the basic unit of distributed energy system, which consists of distributed power generation, energy storage, load and control equipment, and can operate in two modes: grid-connected and islanded. Existing microgrid optimization and dispatching technologies mainly focus on improving energy utilization efficiency and reducing operating costs. They achieve dynamic balance of local energy by coordinating the output of distributed power sources, the charging and discharging strategies of energy storage systems, and load response. At the microgrid group level, multiple microgrids explore the possibility of resource sharing and collaborative optimization through energy and information interaction. The optimization dispatching at the distribution network level is committed to coordinating distributed energy, load demand and energy storage systems from a global perspective, balancing regional energy supply and demand, and ensuring the safety and economy of system operation.

[0004] However, the existing multi-level energy system optimization scheduling methods have many limitations. First, due to the intermittent and random nature of renewable energy, scheduling at the microgrid level faces huge uncertainty challenges; second, resource coordination and goal consistency between microgrid groups are difficult to achieve effectively, and the depth and breadth of resource sharing are limited; third, the scheduling algorithms at the distribution network level often lack accurate characterization of the operating characteristics of the underlying microgrids and microgrid groups, making it difficult to achieve true multi-level collaborative optimization. These technical shortcomings have resulted in the inability of existing methods to fully tap the potential of distributed energy systems, restricting the in-depth development of power systems towards intelligence and low carbonization.

[0005] Therefore, how to provide a multi-level maximized autonomous optimization scheduling solution for microgrids, microgrid clusters, and distribution networks has become an urgent problem to be solved. Summary of the invention

[0006] The embodiments of the present invention provide an optimization scheduling method, system, device and medium based on a multi-level microgrid to solve the problem that scheduling at the microgrid level in the prior art faces huge uncertainty challenges, resource coordination and target consistency between microgrid groups are difficult to effectively achieve, and the scheduling algorithm at the distribution network level often lacks an accurate characterization of the operating characteristics of the lower-level microgrids and microgrid groups, making it difficult to achieve true multi-level collaborative optimization.

[0007] In order to have a basic understanding of some aspects of the disclosed embodiments, a brief summary is given below. This summary is not intended to be a general review, nor is it intended to identify key / important components or to delineate the scope of protection of these embodiments. Its only purpose is to present some concepts in a simple form as a preface to the detailed description that follows.

[0008] According to a first aspect of an embodiment of the present invention, an optimization scheduling method based on a multi-level microgrid is provided.

[0009] In one embodiment, the optimization scheduling method based on a multi-level microgrid includes:

[0010] Based on the equipment parameter information of each microgrid, combined with the initial power purchase price and initial power selling price of the microgrid public connection point, a microgrid operation optimization model is constructed, the microgrid operation optimization model is solved to obtain the optimal dispatching strategy of the microgrid, and the microgrid plan characteristics are determined and uploaded to the microgrid group control center;

[0011] According to the microgrid plan characteristics received by the microgrid control center, a microgrid operation optimization model is constructed, and the microgrid operation optimization model is iteratively solved until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid or the preset number of iterations of the microgrid is reached, the optimal dispatching strategy of the microgrid is obtained, and the microgrid plan characteristics are determined and uploaded to the distribution network control center;

[0012] Based on the microgrid plan characteristics uploaded by the microgrid control center and the power purchase and sales prices of the public connection points set up in the distribution network, a distribution network operation optimization model is established, and the distribution network operation optimization model is iteratively solved until the absolute result difference between the two iterative solutions is within the preset difference range of the distribution network or reaches the preset number of iterations of the distribution network, so as to obtain the optimal dispatching strategy of the distribution network.

[0013] In one embodiment, based on the equipment parameter information of each microgrid, combined with the initial power purchase price and initial power selling price of the microgrid public connection point, a microgrid operation optimization model is constructed, the microgrid operation optimization model is solved to obtain the optimal dispatching strategy of the microgrid, and the microgrid plan characteristics are determined and uploaded to the microgrid group control center, including:

[0014] Initialize the equipment parameter information of each microgrid, and set the initial power purchase price and initial power sales price of the microgrid public connection point;

[0015] Based on the initial electricity purchase price and initial electricity selling price of the microgrid public connection point, the objective function of the minimum operation cost of the microgrid is constructed with the goal of minimizing the electricity purchase cost of the microgrid. In addition, the microgrid operation optimization model is constructed by combining the microgrid active power balance constraint, microgrid energy storage device constraint, shiftable load shifting time period constraint and shiftable load maximum power constraint.

[0016] Solve the microgrid operation optimization model and obtain the optimal dispatching strategy of different microgrids in each microgrid group;

[0017] According to the optimal dispatching strategy of the microgrid, determine the planning characteristics of the microgrid, and upload the planning characteristics of the microgrid to the microgrid control center;

[0018] Among them, the microgrid planning characteristics include equivalent power unit power curve, microgrid aggregated energy storage parameters, microgrid charging power curve and microgrid discharging power curve.

[0019] In one embodiment, the expression of the microgrid minimum operating cost objective function is:

[0020]

[0021] In the formula, F MG,i,j is the electricity purchase cost of the microgrid; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t,i,j The price of electricity sold by microgrid to microgrid group purchase; and are the electricity purchase price and electricity sales price of the microgrid to the microgrid group respectively; Support prices between microgrids; and They are the support price received and the support price given by the microgrid respectively; is the planned input and output power of the microgrid at time t; is the inter-microgrid support power at time t.

[0022] In one embodiment, according to the microgrid plan characteristics received by the microgrid control center, a microgrid operation optimization model is constructed, and the microgrid operation optimization model is iteratively solved until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid or reaches the preset number of iterations of the microgrid, the optimal scheduling strategy of the microgrid is obtained, and the microgrid plan characteristics are determined, and uploaded to the distribution network control center, including:

[0023] Based on the microgrid plan characteristics uploaded by each microgrid in the microgrid group and the purchase and sale electricity prices of the public connection points set by the upper power grid, the objective function of maximizing the autonomous operation of the microgrid group is constructed, and combined with the active power balance constraints of the microgrid group, the corresponding microgrid group operation optimization model is constructed;

[0024] Iteratively solve the microgrid operation optimization model to obtain the optimal dispatching strategy for the microgrid;

[0025] Calculate the absolute difference between the two iterative solution results before and after the microgrid operation optimization model, and compare the absolute difference with the predetermined difference range of the microgrid;

[0026] When the comparison result shows that the absolute difference is within the predetermined difference range of the microgrid group, the microgrid group plan characteristics are determined according to the optimal dispatching strategy of the microgrid group, and the microgrid group plan characteristics are uploaded to the distribution network control center;

[0027] When the comparison result shows that the absolute difference is outside the predetermined difference range of the microgrid group, it is determined whether the number of iterative solutions of the microgrid group operation optimization model exceeds the preset number of iterations of the microgrid group. If the number of iterative solutions is less than or equal to the preset number of iterations of the microgrid group, the support power of each microgrid is updated, and the microgrid operation optimization model is constructed; if the number of iterative solutions is greater than the preset number of iterations of the microgrid group, the microgrid group plan characteristics are determined according to the optimal dispatching strategy of the microgrid group, and the microgrid group plan characteristics are uploaded to the distribution network control center;

[0028] Among them, the microgrid group planning characteristics include the microgrid group aggregated equivalent power unit power curve, the microgrid group aggregated energy storage parameters, the microgrid group charging power curve and the microgrid group discharge power curve.

[0029] In one embodiment, the expression of the objective function of maximizing the autonomous operation of the microgrid group is:

[0030] Min FM Gs,i =FP CC,i +FM G

[0031]

[0032] In the formula, F MGs,i is the operating cost of microgrid group i; F PCC,i is the electricity purchase cost of microgrid group i; F MG is the aggregated electricity purchase cost of each microgrid; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t; Support prices between microgrid groups; is the inter-microgrid support power at time t; t,i,j The price of electricity sold by microgrid to microgrid group purchase; Support prices between microgrids; is the planned input and output power of the microgrid at time t; is the inter-microgrid support power at time t.

[0033] In one embodiment, based on the microgrid group plan characteristics uploaded by the microgrid group control center and the purchase and sale electricity prices of the public connection points set by the distribution network, a distribution network operation optimization model is established, and the distribution network operation optimization model is iteratively solved until the absolute result difference between the two iterative solutions is within the predetermined difference range of the distribution network or reaches the preset number of iterations of the distribution network, and the optimal dispatching strategy of the distribution network is obtained, including:

[0034] According to the microgrid group plan characteristics uploaded by each microgrid group in the distribution network and the purchase and sale prices of electricity at the public connection points set up by the distribution network, the distribution network maximizes the autonomous operation objective function, and combines the active power balance constraints of the distribution network to build the corresponding distribution network operation optimization model;

[0035] Iteratively solve the distribution network operation optimization model to obtain the optimal dispatching strategy of the distribution network;

[0036] Calculate the absolute difference between the results of two iterative solutions of the distribution network operation optimization model, and compare the absolute difference with the predetermined difference range of the distribution network;

[0037] When the comparison result shows that the absolute difference is within a predetermined difference range of the distribution network, the distribution network planning characteristics are determined according to the optimal dispatching strategy of the distribution network;

[0038] When the comparison result shows that the absolute difference is outside the preset difference range of the distribution network, it is determined whether the number of iterative solutions of the distribution network operation optimization model exceeds the preset number of iterations of the distribution network. If the number of iterative solutions is less than or equal to the preset number of iterations of the distribution network, the support power of each microgrid is updated, and the microgrid group operation optimization model is constructed; if the number of iterative solutions is greater than the preset number of iterations of the distribution network, the distribution network plan characteristics are determined according to the optimal dispatching strategy of the distribution network;

[0039] Among them, the distribution network planning characteristics include the power purchased and the power sold by the distribution network.

[0040] In one embodiment, the expression of the distribution network maximizing autonomous operation objective function is:

[0041] Min FDN=FPCC+FMGs

[0042]

[0043] In the formula, F DNis the operating cost of the distribution network; F PCC is the electricity purchase cost of the distribution network; F MGs is the aggregated electricity purchase cost of each microgrid group; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t is the electricity purchase and sale price at the public connection point of the distribution network at time t; is the planned input and output power of the public connection point of the distribution network at time t; t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t; Support prices between microgrid groups; is the inter-microgrid support power at time t.

[0044] According to a second aspect of an embodiment of the present invention, an optimization scheduling system based on a multi-level microgrid is provided.

[0045] In one embodiment, the optimization dispatching system based on multi-level microgrid includes:

[0046] The microgrid operation optimization module is used to construct a microgrid operation optimization model based on the equipment parameter information of each microgrid, combined with the initial power purchase price and initial power sales price of the microgrid public connection point, solve the microgrid operation optimization model to obtain the optimal dispatching strategy of the microgrid, and determine the microgrid plan characteristics, and upload them to the microgrid group control center;

[0047] The microgrid operation optimization module is used to construct a microgrid operation optimization model according to the microgrid plan characteristics received by the microgrid control center, iteratively solve the microgrid operation optimization model until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid or reaches the preset number of iterations of the microgrid, obtain the optimal dispatching strategy of the microgrid, determine the plan characteristics of the microgrid, and upload them to the distribution network control center;

[0048] The distribution network operation optimization module is used to establish a distribution network operation optimization model based on the microgrid group plan characteristics uploaded by the microgrid group control center and the purchase and sale electricity prices of the public connection points set by the distribution network, and iteratively solve the distribution network operation optimization model until the absolute result difference between the two iterative solutions is within the predetermined difference range of the distribution network or reaches the preset number of iterations of the distribution network, so as to obtain the optimal dispatching strategy of the distribution network.

[0049] In one embodiment, the microgrid operation optimization module constructs a microgrid operation optimization model based on the equipment parameter information of each microgrid and the initial power purchase price and initial power selling price of the microgrid public connection point, solves the microgrid operation optimization model to obtain the optimal dispatching strategy of the microgrid, and determines the plan characteristics of the microgrid. When uploading to the microgrid group control center, the equipment parameter information of each microgrid is initialized, and the initial power purchase price and initial power selling price of the microgrid public connection point are set; based on the initial power purchase price and initial power selling price of the microgrid public connection point, the microgrid is constructed with the goal of minimizing the power purchase cost of the microgrid. The objective function of minimum operating cost is adopted, and a microgrid operation optimization model is constructed in combination with the active power balance constraint of the microgrid, the energy storage device constraint of the microgrid, the shifting time period constraint of the shiftable load and the maximum power constraint of the shiftable load. The microgrid operation optimization model is solved to obtain different microgrid optimal dispatching strategies in each microgrid group. According to the microgrid optimal dispatching strategy, the microgrid plan characteristics are determined, and the microgrid plan characteristics are uploaded to the microgrid group control center. The microgrid plan characteristics include the equivalent power unit power curve, the microgrid aggregated energy storage parameters, the microgrid charging power curve and the microgrid discharging power curve.

[0050] In one embodiment, the expression of the microgrid minimum operating cost objective function is:

[0051]

[0052] In the formula, F MG,i,j is the electricity purchase cost of the microgrid; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t,i,j The price of electricity sold by microgrid to microgrid group purchase; and are the electricity purchase price and electricity sales price of the microgrid to the microgrid group respectively; Support prices between microgrids; and They are the support price received and the support price given by the microgrid respectively; is the planned input and output power of the microgrid at time t; is the inter-microgrid support power at time t.

[0053] In one embodiment, the microgrid operation optimization module constructs a microgrid operation optimization model according to the microgrid plan characteristics received by the microgrid control center, iteratively solves the microgrid operation optimization model until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid or reaches the preset number of iterations of the microgrid, obtains the optimal scheduling strategy of the microgrid, and determines the microgrid plan characteristics. When uploading to the distribution network control center, based on the microgrid plan characteristics uploaded by each microgrid in the microgrid and the purchase and sale electricity prices of the public connection points set by the upper-level power grid, the microgrid maximizes the autonomous operation objective function, and combines the active power balance constraints of the microgrid to construct the corresponding microgrid operation optimization model; iteratively solves the microgrid operation optimization model to obtain the optimal scheduling strategy of the microgrid; calculates the absolute difference between the two iterative solution results of the microgrid operation optimization model, and compares the absolute difference with the predetermined difference range of the microgrid. comparison; when the comparison result is that the absolute difference is within the preset difference range of the microgrid group, the microgrid group plan characteristics are determined according to the microgrid group's optimal dispatching strategy, and the microgrid group plan characteristics are uploaded to the distribution network control center; when the comparison result is that the absolute difference is outside the microgrid group's preset difference range, it is determined whether the number of iterative solutions of the microgrid group operation optimization model exceeds the microgrid group's preset number of iterations. If the number of iterative solutions is less than or equal to the microgrid group's preset number of iterations, the support power of each microgrid is updated, and a microgrid operation optimization model is constructed; if the number of iterative solutions is greater than the microgrid group's preset number of iterations, the microgrid group plan characteristics are determined according to the microgrid group's optimal dispatching strategy, and the microgrid group plan characteristics are uploaded to the distribution network control center; wherein, the microgrid group plan characteristics include the microgrid group's aggregated equivalent power unit power curve, the microgrid group's aggregated energy storage parameters, the microgrid group's charging power curve, and the microgrid group's discharging power curve.

[0054] In one embodiment, the expression of the objective function of maximizing the autonomous operation of the microgrid group is:

[0055] Min FM Gs,i =FP CC,i +FM G

[0056]

[0057] In the formula, F MGs,i is the operating cost of microgrid group i; F PCC,i is the electricity purchase cost of microgrid group i; F MG is the aggregated electricity purchase cost of each microgrid; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t; Support prices between microgrid groups; is the inter-microgrid support power at time t; t,i,j The price of electricity sold by microgrid to microgrid group purchase; Support prices between microgrids; is the planned input and output power of the microgrid at time t; is the inter-microgrid support power at time t.

[0058] In one embodiment, the distribution network operation optimization module establishes a distribution network operation optimization model based on the microgrid group plan characteristics uploaded by the microgrid group control center and the purchase and sale electricity prices of the public connection points set by the distribution network, and iteratively solves the distribution network operation optimization model until the absolute result difference between the two iterative solutions is within the predetermined difference range of the distribution network or reaches the preset number of iterations of the distribution network. When the optimal dispatching strategy of the distribution network is obtained, the distribution network maximization autonomous operation objective function is constructed according to the microgrid group plan characteristics uploaded by each microgrid group in the distribution network and the purchase and sale electricity prices of the public connection points set by the distribution network, and the corresponding distribution network operation optimization model is constructed in combination with the active power balance constraint of the distribution network; the distribution network operation optimization model is iteratively solved to obtain the optimal dispatching strategy of the distribution network; and the distribution network operation optimization model is calculated before and after. The absolute difference between the two iterative solution results is calculated, and the absolute difference is compared with the preset difference range of the distribution network; when the comparison result is that the absolute difference is within the preset difference range of the distribution network, the distribution network plan characteristics are determined according to the optimal dispatching strategy of the distribution network; when the comparison result is that the absolute difference is outside the preset difference range of the distribution network, it is determined whether the number of iterative solutions of the distribution network operation optimization model exceeds the preset number of iterations of the distribution network. If the number of iterative solutions is less than or equal to the preset number of iterations of the distribution network, the support power of each microgrid is updated, and a microgrid group operation optimization model is constructed; if the number of iterative solutions is greater than the preset number of iterations of the distribution network, the distribution network plan characteristics are determined according to the optimal dispatching strategy of the distribution network; wherein, the distribution network plan characteristics include the purchased power and sold power of the distribution network.

[0059] In one embodiment, the expression of the distribution network maximizing autonomous operation objective function is:

[0060] Min FDN=FPCC+FMGs

[0061]

[0062] In the formula, F DN is the operating cost of the distribution network; F PCC is the electricity purchase cost of the distribution network; F MGs is the aggregated electricity purchase cost of each microgrid group; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ tis the electricity purchase and sale price at the public connection point of the distribution network at time t; is the planned input and output power of the public connection point of the distribution network at time t; t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t; Support prices between microgrid groups; is the inter-microgrid support power at time t.

[0063] According to a third aspect of an embodiment of the present invention, a computer device is provided.

[0064] In one embodiment, the computer device includes a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps of the above method when executing the computer program.

[0065] According to a fourth aspect of embodiments of the present invention, a computer-readable storage medium is provided.

[0066] In one embodiment, the computer-readable storage medium stores a computer program, which implements the steps of the above method when executed by a processor.

[0067] The technical solution provided by the embodiment of the present invention may have the following beneficial effects:

[0068] The present invention realizes the optimized scheduling of each level of microgrid-microgrid group-distribution network with maximum autonomy, and achieves the purpose of improving the safety, reliability and flexibility of each level of the distribution network on the basis of maximum autonomous operation of each level.

[0069] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0070] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0071] Figure 1 is a flow chart of an optimization scheduling method based on a multi-level microgrid according to an exemplary embodiment;

[0072] Figure 2 is a specific implementation diagram of an optimization scheduling method based on a multi-level microgrid according to an exemplary embodiment;

[0073] Figure 3 It is a diagram of maximizing autonomous scheduling of each level of three layers of a distribution network in an optimization scheduling method based on a multi-level microgrid according to an exemplary embodiment;

[0074] Figure 4 It is an equivalent aggregation diagram of a microgrid in an optimization scheduling method based on a multi-level microgrid according to an exemplary embodiment;

[0075] Figure 5 is a relationship diagram of each microgrid in a microgrid group in an optimization scheduling method based on a multi-level microgrid according to an exemplary embodiment;

[0076] Figure 6 is a structural block diagram of an optimization scheduling system based on a multi-level microgrid according to an exemplary embodiment;

[0077] Figure 7 The diagram is a schematic diagram showing the structure of a computer device according to an exemplary embodiment. DETAILED DESCRIPTION

[0078] The following description and accompanying drawings fully illustrate the specific embodiments of this article so that those skilled in the art can practice them. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. The scope of the embodiments of this article includes the entire scope of the claims, as well as all available equivalents of the claims. Herein, the terms "first", "second", etc. are only used to distinguish one element from another, without requiring or implying any actual relationship or order between these elements. In fact, the first element can also be called the second element, and vice versa. Moreover, the terms "include", "comprise" or any other variant thereof are intended to cover non-exclusive inclusion, so that the structure, device or equipment including a series of elements includes not only those elements, but also other elements that are not explicitly listed, or also include elements inherent to such structure, device or equipment. In the absence of more restrictions, the elements defined by the sentence "including one..." do not exclude the existence of other identical elements in the structure, device or equipment including the elements. Each embodiment is described in a progressive manner herein, and each embodiment focuses on the differences from other embodiments, and the same and similar parts between the embodiments can be referred to each other.

[0079] The terms "longitudinal", "lateral", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc. in this document indicate the orientation or position relationship based on the orientation or position relationship shown in the drawings, and are only for the convenience of describing this document and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In the description of this document, unless otherwise specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a mechanical connection or an electrical connection, it can also be the internal communication of two elements, it can be a direct connection, or it can be an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to specific circumstances.

[0080] As used herein, unless otherwise specified, the term "plurality" means two or more than two.

[0081] In this document, the character " / " indicates that the preceding and following objects are in an "or" relationship. For example, A / B means: A or B.

[0082] In this article, the term "and / or" is a description of the association relationship between objects, indicating that three relationships may exist. For example, A and / or B means: A or B, or, A and B.

[0083] It should be understood that, although the various steps in the flow chart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the figure may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0084] Each module in the device or system of the present application can be implemented in whole or in part by software, hardware, or a combination thereof. The above modules can be embedded in or independent of a processor in a computer device in the form of hardware, or can be stored in a memory in a computer device in the form of software, so that the processor can call and execute operations corresponding to the above modules.

[0085] In the absence of conflict, the embodiments of the present invention and the features of the embodiments may be combined with each other.

[0086] Figure 1-Figure 5An embodiment of an optimization scheduling method based on a multi-level microgrid of the present invention is shown.

[0087] In this optional embodiment, the optimization scheduling method based on the multi-level microgrid includes:

[0088] Step S101: Based on the equipment parameter information of each microgrid, combined with the initial power purchase price and initial power selling price of the microgrid public connection point, a microgrid operation optimization model is constructed, the microgrid operation optimization model is solved to obtain the microgrid optimal dispatching strategy, and the microgrid plan characteristics are determined and uploaded to the microgrid group control center;

[0089] Specifically, based on the day-ahead power forecast and equipment parameter information of the source, load, storage and other equipment within each microgrid, as well as the initial purchase and sale prices of electricity at the PCC point, an optimization model for maximizing autonomous operation is constructed, and the optimal scheduling result is obtained. The power purchase and sale plan, aggregated energy storage model, and charging and discharging plan that meets the internal load of the microgrid are determined and uploaded to the microgrid group control center.

[0090] Step S103: construct a microgrid operation optimization model according to the microgrid plan characteristics received by the microgrid control center, and iteratively solve the microgrid operation optimization model until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid or reaches the preset number of iterations of the microgrid, obtain the optimal dispatching strategy of the microgrid, determine the plan characteristics of the microgrid, and upload them to the distribution network control center;

[0091] Specifically, based on various plans and energy storage models, the microgrid control center constructs a microgrid group maximum autonomous operation optimization model according to the information uploaded by each microgrid and the PCC point purchase and sales prices set by the upper-level power grid to obtain the optimal scheduling result. If the difference between the calculation results of the two iterations is within a certain range, or reaches a preset number of iterations, the microgrid group purchase and sales plan, aggregated energy storage model and charging and discharging plan will be transmitted to the distribution network control center. Otherwise, the updated supporting power and supported power between microgrids will be transmitted to each microgrid to reconstruct the microgrid optimization model and obtain the microgrid group scheduling strategy.

[0092] Step S105: Based on the microgrid plan characteristics uploaded by the microgrid control center and the purchase and sale prices of electricity at the public connection points set by the distribution network, a distribution network operation optimization model is established, and the distribution network operation optimization model is iteratively solved until the absolute result difference between the two iterative solutions is within the predetermined difference range of the distribution network or reaches the preset number of iterations of the distribution network, so as to obtain the optimal dispatching strategy of the distribution network.

[0093] Specifically, based on various plans and energy storage models, the distribution network control center constructs a distribution network maximum autonomous operation optimization model according to the information uploaded by each microgrid control center and the PCC point purchase and sales prices set by the upper-level power grid to obtain the optimal scheduling result. If the difference between the calculation results of the two iterations is within a certain range or reaches a preset number of iterations, the optimal scheduling strategy of the distribution network is output. Otherwise, the updated support power between each microgrid group is transmitted to each microgrid group to rebuild the microgrid group optimization model and obtain the optimal scheduling strategy of the distribution network.

[0094] In this optional embodiment, based on the equipment parameter information of each microgrid, combined with the initial power purchase price and initial power selling price of the microgrid public connection point, a microgrid operation optimization model is constructed, the microgrid operation optimization model is solved to obtain the optimal dispatching strategy of the microgrid, and the microgrid plan characteristics are determined and uploaded to the microgrid group control center, including:

[0095] Step S1011, initializing the equipment parameter information of each microgrid, and setting the initial power purchase price and initial power sales price of the microgrid public connection point;

[0096] Specifically, the information in each microgrid (MG) is initialized, including the day-ahead power forecast of the source, load, and storage as well as the equipment parameter information, and the price set by the distribution network is used as the initial purchase and sale price of electricity at the microgrid's Point of Common Coupling (PCC).

[0097] Step S1013: Based on the initial power purchase price and the initial power selling price of the microgrid public connection point, with the goal of minimizing the power purchase cost of the microgrid, construct a microgrid minimum operation cost objective function, and combine the microgrid active power balance constraint, the microgrid energy storage device constraint, the shiftable load shifting time period constraint and the transferable load maximum power constraint to construct a microgrid operation optimization model;

[0098] Specifically, the optimization model is constructed based on the aggregation of the day-ahead power forecast and parameter information of the source, load, and storage within the ith microgrid in the ith microgrid group, as well as the PCC point purchase and sales prices.

[0099] Specifically, the power generated by the microgrid's new energy power generation equipment is first supplied to its internal load, and the remaining power is stored through the energy storage device. When the microgrid cannot fully absorb the power or the power load requires too much power, the microgrid trades with the microgrid cluster (MGs), which belongs to the maximum autonomous operation mode and constructs the microgrid's minimum operating cost objective function.

[0100] Step S1015, solving the microgrid operation optimization model to obtain different microgrid optimal dispatching strategies in each microgrid group;

[0101] Specifically, the microgrid optimization model is solved. In this embodiment, the CPLEX toolbox solver is used to solve the mixed integer linear programming problem to obtain the optimal scheduling strategy for the jth microgrid in the ith microgrid group, including the microgrid equivalent power unit power curve, the microgrid aggregated energy storage parameters, and the microgrid charging and discharging power curves.

[0102] Step S1017: determine the microgrid plan characteristics according to the microgrid optimal dispatching strategy, and upload the microgrid plan characteristics to the microgrid group control center;

[0103] Among them, the microgrid planning characteristics include equivalent power unit power curve, microgrid aggregated energy storage parameters, microgrid charging power curve and microgrid discharging power curve.

[0104] Specifically, according to the optimal dispatching strategy of the microgrid, the power curve of the equivalent power unit of the microgrid is obtained: Microgrid aggregated energy storage parameters And microgrid charging and discharging power curve And upload to the microgrid control center;

[0105] Specifically, In the formula, The planned input and output power of the microgrid at time t (input is positive and output is negative) is the decision variable of the microgrid optimization problem.

[0106] In this optional embodiment, the expression of the microgrid minimum operating cost objective function is:

[0107]

[0108]

[0109] In the formula, F MG,i,j is the electricity purchase cost of the microgrid; i and j are the jth microgrid in the i-th microgrid group (i=1,2,3,…,N; j=1,2,3,…,M); T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle (t=1,2,3……,T); ρ t,i,j The price of electricity sold by microgrid to microgrid group purchase; and are the electricity purchase price and electricity sales price of the microgrid to the microgrid group respectively; Support prices between microgrids; and They are the support price received and the support price given by the microgrid respectively; is the planned input and output power of the microgrid at time t (input is positive, output is negative), which is the decision variable of the microgrid optimization problem; It is the inter-microgrid support power at time t (positive when supported and negative when output).

[0110] Specifically, the above formula satisfies

[0111] Specifically, the expression of the active power balance constraint of the microgrid is:

[0112]

[0113] In the formula, are the charging power and discharging power of the energy storage device for the internal load of the microgrid at time t respectively; are the charging power and discharging power of the energy storage device used for inter-microgrid support at time t, respectively; represents the photovoltaic power generation power at time t; represents the power required by the conventional load at time t; It represents the power required for the load to be transferred at time t.

[0114] Specifically, the expression of the microgrid energy storage device constraint is:

[0115]

[0116] In the formula, They are the planned charge state and upper and lower limits of the energy storage plan at time t respectively; They are respectively the charging and discharging power limits of the energy storage device at time t; are the charging and discharging efficiency of the energy storage device at time t; E i,j Indicates the rated capacity of the energy storage device; They are the charging and discharging states of the energy storage device at time t, respectively, and are 0-1 variables; They are the charge states of the energy storage device at time t0 and time T respectively.

[0117] Specifically, the expression of the translation period constraint of the translatable load is:

[0118]

[0119] In the formula, Indicates the time when the kth type of transferable load starts to operate; represents the operating time of the kth type of transferable load; represents the number of transferable loads of the kth type;

[0120] Specifically, the expression of the maximum power constraint of the transferable load is:

[0121]

[0122] In the formula, It represents the maximum power of the transferable load at time t.

[0123] In this optional embodiment, according to the microgrid plan characteristics received by the microgrid control center, a microgrid operation optimization model is constructed, and the microgrid operation optimization model is iteratively solved until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid or reaches the preset number of iterations of the microgrid, the optimal scheduling strategy of the microgrid is obtained, and the microgrid plan characteristics are determined, and uploaded to the distribution network control center, including:

[0124] Step S1031: Based on the microgrid plan characteristics uploaded by each microgrid in the microgrid group and the purchase and sale electricity prices of the public connection points set by the upper-level power grid, a microgrid group maximum autonomous operation objective function is constructed, and combined with the active power balance constraint of the microgrid group, a corresponding microgrid group operation optimization model is constructed;

[0125] Specifically, in this method, the microgrid group adopts a maximized autonomous operation mode, and constructs the i-th corresponding microgrid group operation optimization model according to the information uploaded by each microgrid in the microgrid group and the purchase and sale electricity prices of the public connection points set by the upper-level power grid.

[0126] Specifically, in this method, the microgrid group constructs the objective function of maximizing the autonomous operation of the microgrid group by aggregating the plans and models uploaded by each microgrid.

[0127] Step S1033, iteratively solving the microgrid operation optimization model to obtain the optimal scheduling strategy for the microgrid;

[0128] Specifically, the microgrid operation optimization model is solved iteratively. In this embodiment, the mixed integer linear programming problem is solved based on the CPLEX toolbox solver to obtain the optimal scheduling result of the microgrid group i.

[0129] Step S1035, calculating the absolute difference between the two iterative solution results before and after the microgrid operation optimization model, and comparing the absolute difference with the predetermined difference range of the microgrid;

[0130] When the comparison result shows that the absolute difference is within the predetermined difference range of the microgrid group, determining the microgrid group plan characteristics according to the microgrid group optimal dispatching strategy, and uploading the microgrid group plan characteristics to the distribution network control center;

[0131] When the comparison result shows that the absolute difference is outside the predetermined difference range of the microgrid group, it is determined whether the number of iterative solutions of the microgrid group operation optimization model exceeds the preset number of iterations of the microgrid group. If the number of iterative solutions is less than or equal to the preset number of iterations of the microgrid group, the support power of each microgrid is updated, and the microgrid operation optimization model is constructed; if the number of iterative solutions is greater than the preset number of iterations of the microgrid group, the microgrid group plan characteristics are determined according to the optimal dispatching strategy of the microgrid group, and the microgrid group plan characteristics are uploaded to the distribution network control center;

[0132] Among them, the microgrid group planning characteristics include the microgrid group aggregated equivalent power unit power curve, the microgrid group aggregated energy storage parameters, the microgrid group charging power curve and the microgrid group discharging power curve.

[0133] Specifically, based on the absolute difference between the two iterative calculation results of the i-th microgrid group, if its value is within the predetermined difference range ε ​​of the microgrid group MGs According to the optimal dispatch result, the power curve of the microgrid cluster aggregate equivalent power unit is obtained. Microgrid group aggregated energy storage parameters ( E i ) and microgrid charging and discharging power curves Upload to the distribution network control center.

[0134] Specifically, based on the absolute difference between the two iterative calculation results of the i-th microgrid group, if its value is within the predetermined difference range ε ​​of the microgrid group MGs In addition, it is further determined whether the number of iterations exceeds the preset number of iterations K of the microgrid group. MGs :If it is judged to be less than or equal to the preset iteration number of the microgrid group, then update the support power of each microgrid And return to step S1013 to reconstruct the optimization model of each microgrid group; if it is judged that it is greater than the preset number of iterations of the microgrid group, the power curve of the aggregated equivalent power unit of the microgrid group is obtained according to its optimal scheduling result Microgrid group aggregated energy storage parameters ( E i ) and microgrid charging and discharging power curves Upload to the distribution network control center.

[0135] Specifically, the above formula satisfies

[0136] In this optional embodiment, the expression of the objective function of maximizing the autonomous operation of the microgrid group is:

[0137] Min F MGs,i =F PCC,i +F MG

[0138]

[0139] In the formula, and They represent the electricity purchase price and electricity sales price of the microgrid group to the distribution network respectively; and Respectively represent the microgrid acceptance support price and support price; F MGs,i is the operating cost of microgrid group i; F PCC,i is the electricity purchase cost of microgrid group i; F MG is the aggregated electricity purchase cost of each microgrid; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t (input is positive and output is negative); Support prices between microgrid groups; is the inter-microgrid support power at time t; t,i,j The price of electricity sold by microgrid to microgrid group purchase; Support prices between microgrids; is the planned input and output power of the microgrid at time t (positive when supported and negative when output); is the inter-microgrid support power at time t; and It is the decision variable of the microgrid group optimization problem.

[0140] Specifically, the above formula satisfies

[0141] Specifically, the expression of the active power balance constraint of the microgrid group is:

[0142]

[0143] In this optional embodiment, based on the microgrid group plan characteristics uploaded by the microgrid group control center and the purchase and sale electricity prices of the public connection points set by the distribution network, a distribution network operation optimization model is established, and the distribution network operation optimization model is iteratively solved until the absolute result difference between the two iterative solutions is within the predetermined difference range of the distribution network or reaches the preset number of iterations of the distribution network, and the optimal dispatching strategy of the distribution network is obtained, including:

[0144] Step S1051: construct a distribution network maximization autonomous operation objective function based on the microgrid group plan characteristics uploaded by each microgrid group in the distribution network and the purchase and sale electricity prices of the public connection points set by the distribution network, and construct a corresponding distribution network operation optimization model in combination with the active power balance constraint of the distribution network;

[0145] Specifically, in this method, the distribution network adopts a maximized autonomous operation mode, and constructs a corresponding optimization model of the distribution network based on the information uploaded by each microgrid group and the PCC point purchase and sales prices.

[0146] Specifically, in this method, the distribution network constructs the objective function of maximizing autonomous operation of the distribution network by aggregating the plans and models uploaded by each microgrid group.

[0147] Step S1053, iteratively solving the distribution network operation optimization model to obtain the optimal dispatching strategy of the distribution network;

[0148] Specifically, the distribution network operation optimization model is solved iteratively. In this embodiment, the mixed integer linear programming problem is solved based on the solver CPLEX toolbox to obtain the optimal dispatching result of the distribution network.

[0149] Step S1055, calculating the absolute difference between the results of two iterative solutions of the distribution network operation optimization model, and comparing the absolute difference with a predetermined difference range of the distribution network;

[0150] When the comparison result shows that the absolute difference is within the predetermined difference range of the distribution network, determining the distribution network planning characteristics according to the distribution network optimal dispatching strategy;

[0151] When the comparison result shows that the absolute difference is outside the predetermined difference range of the distribution network, it is determined whether the number of iterative solutions of the distribution network operation optimization model exceeds the preset number of iterations of the distribution network; if the number of iterative solutions is less than or equal to the preset number of iterations of the distribution network, the support power of each microgrid is updated, and the microgrid group operation optimization model is constructed; if the number of iterative solutions is greater than the preset number of iterations of the distribution network, the distribution network plan characteristics are determined according to the optimal dispatching strategy of the distribution network;

[0152] The distribution network planning characteristics include the power purchase and power sales of the distribution network.

[0153] Specifically, based on the absolute difference between the two iterative calculation results of the distribution network, if its value is within the predetermined difference range ε ​​of the distribution network DN The optimal dispatching strategy of the distribution network is output based on the power purchased and sold by the distribution network.

[0154] Specifically, based on the absolute difference between the two iterative calculation results of the distribution network, if its value is within the predetermined difference range ε ​​of the distribution network DN If the number of iterations exceeds the preset number of iterations K of the distribution network, DN :If it is less than or equal to the preset number of iterations of the distribution network, then update the support power of each microgrid group And return to step S1033 to rebuild the optimization model of each microgrid group, otherwise output the optimal dispatching strategy of the distribution network according to the power purchase and sales of the distribution network.

[0155] In this optional embodiment, the expression of the distribution network maximizing autonomous operation objective function is:

[0156] Min FDN=FPCC+FMGs

[0157]

[0158] In the formula, are the purchase and sale prices of electricity at the PCC point of the distribution network at time t; F DN is the operating cost of the distribution network; F PCC is the electricity purchase cost of the distribution network; F MGs is the aggregated electricity purchase cost of each microgrid group; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t is the electricity purchase and sale price at the public connection point of the distribution network at time t; is the planned input and output power of the public connection point of the distribution network at time t (positive when purchasing electricity and negative when selling electricity); ρ t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t; Support prices between microgrid groups; is the inter-microgrid support power at time t; and are the decision variables in the distribution network optimization problem.

[0159] Specifically, the expression of the active power balance constraint of the distribution network is:

[0160]

[0161] Figure 6 An embodiment of an optimization dispatching system based on a multi-level microgrid of the present invention is shown.

[0162] In this optional embodiment, the optimization dispatching system based on the multi-level microgrid includes:

[0163] The microgrid operation optimization module 201 is used to construct a microgrid operation optimization model based on the equipment parameter information of each microgrid and the initial power purchase price and initial power selling price of the microgrid public connection point, solve the microgrid operation optimization model to obtain the optimal dispatching strategy of the microgrid, and determine the microgrid plan characteristics, and upload them to the microgrid group control center;

[0164] The microgrid operation optimization module 203 is used to construct a microgrid operation optimization model according to the microgrid plan characteristics received by the microgrid control center, iteratively solve the microgrid operation optimization model until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid or reaches the preset number of iterations of the microgrid, obtain the optimal dispatching strategy of the microgrid, determine the plan characteristics of the microgrid, and upload them to the distribution network control center;

[0165] The distribution network operation optimization module 205 is used to establish a distribution network operation optimization model based on the microgrid group plan characteristics uploaded by the microgrid group control center and the purchase and sale electricity prices of the public connection points set by the distribution network, and iteratively solve the distribution network operation optimization model until the absolute result difference between the two iterative solutions is within the predetermined difference range of the distribution network or reaches the preset number of iterations of the distribution network, so as to obtain the optimal dispatching strategy of the distribution network.

[0166] In this optional embodiment, the microgrid operation optimization module 201 constructs a microgrid operation optimization model based on the equipment parameter information of each microgrid and the initial power purchase price and initial power selling price of the microgrid public connection point, solves the microgrid operation optimization model to obtain the optimal dispatching strategy of the microgrid, and determines the plan characteristics of the microgrid. When uploading to the microgrid group control center, the equipment parameter information of each microgrid is initialized, and the initial power purchase price and initial power selling price of the microgrid public connection point are set; based on the initial power purchase price and initial power selling price of the microgrid public connection point, with the goal of minimizing the power purchase cost of the microgrid, a microgrid operation optimization model is constructed. The objective function of the minimum operation cost of the power grid is combined with the active power balance constraint of the microgrid, the constraint of the microgrid energy storage device, the constraint of the shiftable load shifting time period and the constraint of the maximum power of the transferable load to construct a microgrid operation optimization model; the microgrid operation optimization model is solved to obtain different microgrid optimal dispatching strategies in each microgrid group; according to the microgrid optimal dispatching strategy, the microgrid plan characteristics are determined, and the microgrid plan characteristics are uploaded to the microgrid group control center; wherein, the microgrid plan characteristics include equivalent power unit power curve, microgrid aggregated energy storage parameters, microgrid charging power curve and microgrid discharge power curve.

[0167] In this optional embodiment, the expression of the microgrid minimum operating cost objective function is:

[0168]

[0169] In the formula, F MG,i,j is the electricity purchase cost of the microgrid; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t,i,j The price of electricity sold by microgrid to microgrid group purchase; and are the electricity purchase price and electricity sales price of the microgrid to the microgrid group respectively; Support prices between microgrids; and They are the support price received and the support price given by the microgrid respectively; is the planned input and output power of the microgrid at time t; is the inter-microgrid support power at time t.

[0170] In this optional embodiment, the microgrid group operation optimization module 203 constructs a microgrid group operation optimization model according to the microgrid plan characteristics received by the microgrid group control center, iteratively solves the microgrid group operation optimization model until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid group or reaches the preset number of iterations of the microgrid group, obtains the optimal scheduling strategy of the microgrid group, and determines the microgrid group plan characteristics. When uploading to the distribution network control center, based on the microgrid plan characteristics uploaded by each microgrid in the microgrid group and the purchase and sale electricity price of the public connection point set by the upper-level power grid, the microgrid group maximizes the autonomous operation objective function, and combines the active power balance constraint of the microgrid group to construct the corresponding microgrid group operation optimization model; iteratively solves the microgrid group operation optimization model to obtain the optimal scheduling strategy of the microgrid group; calculates the absolute difference between the two iterative solution results of the microgrid group operation optimization model, and compares the absolute difference with the predetermined difference range of the microgrid group. When the comparison result is that the absolute difference is within the preset difference range of the microgrid group, the microgrid group plan characteristics are determined according to the microgrid group's optimal dispatching strategy, and the microgrid group plan characteristics are uploaded to the distribution network control center; When the comparison result is that the absolute difference is outside the preset difference range of the microgrid group, it is determined whether the number of iterative solutions of the microgrid group operation optimization model exceeds the preset number of iterations of the microgrid group. If the number of iterative solutions is less than or equal to the preset number of iterations of the microgrid group, the support power of each microgrid is updated, and a microgrid operation optimization model is constructed; If the number of iterative solutions is greater than the preset number of iterations of the microgrid group, the microgrid group plan characteristics are determined according to the microgrid group's optimal dispatching strategy, and the microgrid group plan characteristics are uploaded to the distribution network control center; Among them, the microgrid group plan characteristics include the microgrid group aggregated equivalent power unit power curve, the microgrid group aggregated energy storage parameters, the microgrid group charging power curve and the microgrid group discharge power curve.

[0171] In this optional embodiment, the expression of the objective function of maximizing the autonomous operation of the microgrid group is:

[0172] Min FM Gs,i =FP CC,i +FM G

[0173]

[0174] In the formula, F MGs,iis the operating cost of microgrid group i; F PCC,i is the electricity purchase cost of microgrid group i; F MG is the aggregated electricity purchase cost of each microgrid; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t; Support prices between microgrid groups; is the inter-microgrid support power at time t; t,i,j The price of electricity sold by microgrid to microgrid group purchase; Support prices between microgrids; is the planned input and output power of the microgrid at time t; is the inter-microgrid support power at time t.

[0175] In this optional embodiment, the distribution network operation optimization module 205 establishes a distribution network operation optimization model based on the microgrid group plan characteristics uploaded by the microgrid group control center and the purchase and sale electricity prices of the common connection points set in the distribution network, and iteratively solves the distribution network operation optimization model until the absolute result difference between the two iterative solutions is within the predetermined difference range of the distribution network or reaches the preset number of iterations of the distribution network. When the optimal dispatching strategy of the distribution network is obtained, the distribution network maximization autonomous operation objective function is constructed according to the microgrid group plan characteristics uploaded by each microgrid group in the distribution network and the purchase and sale electricity prices of the common connection points set in the distribution network, and the corresponding distribution network operation optimization model is constructed in combination with the active power balance constraint of the distribution network; the distribution network operation optimization model is iteratively solved to obtain the optimal dispatching strategy of the distribution network; and the distribution network operation optimization model is calculated. The absolute difference between the results of the two iterative solutions is calculated, and the absolute difference is compared with the preset difference range of the distribution network; when the comparison result is that the absolute difference is within the preset difference range of the distribution network, the distribution network plan characteristics are determined according to the optimal dispatching strategy of the distribution network; when the comparison result is that the absolute difference is outside the preset difference range of the distribution network, it is determined whether the number of iterative solutions of the distribution network operation optimization model exceeds the preset number of iterations of the distribution network. If the number of iterative solutions is less than or equal to the preset number of iterations of the distribution network, the support power of each microgrid is updated, and a microgrid group operation optimization model is constructed; if the number of iterative solutions is greater than the preset number of iterations of the distribution network, the distribution network plan characteristics are determined according to the optimal dispatching strategy of the distribution network; wherein, the distribution network plan characteristics include the purchased power and sold power of the distribution network.

[0176] In this optional embodiment, the expression of the distribution network maximizing autonomous operation objective function is:

[0177] Min FDN=FPCC+FMGs

[0178]

[0179] In the formula, F DN is the operating cost of the distribution network; F PCC is the electricity purchase cost of the distribution network; F MGs is the aggregated electricity purchase cost of each microgrid group; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t is the electricity purchase and sale price at the public connection point of the distribution network at time t; is the planned input and output power of the public connection point of the distribution network at time t; t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t; Support prices between microgrid groups; is the inter-microgrid support power at time t.

[0180] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 7 As shown. The computer device includes a processor, a memory and a network interface connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store static information and dynamic information data. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, the steps in the above method embodiment are implemented.

[0181] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation on the computer device to which the solution of the present invention is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0182] In addition, the present invention also provides a computer device, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiment when executing the computer program.

[0183] In addition, the present invention further provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps in the above method embodiment are implemented.

[0184] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0185] The present invention is not limited to the structures which have been described above and shown in the drawings, and various modifications and changes may be made without departing from the scope thereof. The scope of the present invention is limited only by the appended claims.

Claims

1. An optimization scheduling method based on a multi-level microgrid, characterized in that: The optimization dispatching method based on multi-level microgrid includes: Based on the equipment parameter information of each microgrid, combined with the initial power purchase price and initial power selling price of the microgrid public connection point, a microgrid operation optimization model is constructed, the microgrid operation optimization model is solved to obtain the optimal dispatching strategy of the microgrid, and the microgrid plan characteristics are determined and uploaded to the microgrid group control center; According to the microgrid plan characteristics received by the microgrid control center, a microgrid operation optimization model is constructed, and the microgrid operation optimization model is iteratively solved until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid or the preset number of iterations of the microgrid is reached, the optimal dispatching strategy of the microgrid is obtained, and the microgrid plan characteristics are determined and uploaded to the distribution network control center; Based on the microgrid plan characteristics uploaded by the microgrid control center and the power purchase and sales prices of the public connection points set up in the distribution network, a distribution network operation optimization model is established, and the distribution network operation optimization model is iteratively solved until the absolute result difference between the two iterative solutions is within the preset difference range of the distribution network or reaches the preset number of iterations of the distribution network, so as to obtain the optimal dispatching strategy of the distribution network.

2. The optimization scheduling method based on a multi-level microgrid according to claim 1 is characterized in that: The device parameter information of each microgrid is combined with the initial power purchase price and initial power selling price of the microgrid public connection point to build a microgrid operation optimization model, solve the microgrid operation optimization model to obtain the microgrid optimal dispatching strategy, and determine the microgrid plan characteristics, which are uploaded to the microgrid group control center, including: Initialize the equipment parameter information of each microgrid, and set the initial power purchase price and initial power sales price of the microgrid public connection point; Based on the initial electricity purchase price and initial electricity selling price of the microgrid public connection point, the objective function of the minimum operation cost of the microgrid is constructed with the goal of minimizing the electricity purchase cost of the microgrid. In addition, the microgrid operation optimization model is constructed by combining the microgrid active power balance constraint, microgrid energy storage device constraint, shiftable load shifting time period constraint and shiftable load maximum power constraint. Solve the microgrid operation optimization model to obtain the optimal dispatching strategy for different microgrids in each microgrid group; According to the optimal dispatching strategy of the microgrid, determine the planning characteristics of the microgrid, and upload the planning characteristics of the microgrid to the microgrid group control center; Among them, the microgrid planning characteristics include equivalent power unit power curve, microgrid aggregated energy storage parameters, microgrid charging power curve and microgrid discharging power curve.

3. The optimization scheduling method based on a multi-level microgrid according to claim 2 is characterized in that: The expression of the objective function of the minimum operating cost of the microgrid is: In the formula, F MG,i,j is the electricity purchase cost of the microgrid; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the duration of a scheduling period; t is a certain moment in the scheduling cycle; ρ t,i,j The price of electricity sold by microgrid to microgrid group purchase; and are the electricity purchase price and electricity sales price of the microgrid to the microgrid group respectively; Support prices between microgrids; and They are the support price received and the support price given by the microgrid respectively; is the planned input and output power of the microgrid at time t; is the inter-microgrid support power at time t.

4. The optimization scheduling method based on a multi-level microgrid according to claim 1 is characterized in that: The microgrid group operation optimization model is constructed according to the microgrid plan characteristics received by the microgrid group control center, and the microgrid group operation optimization model is iteratively solved until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid group or the preset number of iterations of the microgrid group is reached, the optimal dispatching strategy of the microgrid group is obtained, and the microgrid group plan characteristics are determined, and uploaded to the distribution network control center, including: Based on the microgrid plan characteristics uploaded by each microgrid in the microgrid group and the purchase and sale electricity prices of the public connection points set by the upper power grid, the objective function of maximizing the autonomous operation of the microgrid group is constructed, and combined with the active power balance constraints of the microgrid group, the corresponding microgrid group operation optimization model is constructed; Iteratively solve the microgrid operation optimization model to obtain the optimal dispatching strategy for the microgrid; Calculate the absolute difference between the two iterative solution results before and after the microgrid operation optimization model, and compare the absolute difference with the predetermined difference range of the microgrid; When the comparison result shows that the absolute difference is within the predetermined difference range of the microgrid group, determining the microgrid group plan characteristics according to the microgrid group optimal dispatching strategy, and uploading the microgrid group plan characteristics to the distribution network control center; When the comparison result shows that the absolute difference is outside the predetermined difference range of the microgrid group, it is determined whether the number of iterative solutions of the microgrid group operation optimization model exceeds the preset number of iterations of the microgrid group. If the number of iterative solutions is less than or equal to the preset number of iterations of the microgrid group, the support power of each microgrid is updated, and the microgrid operation optimization model is constructed; if the number of iterative solutions is greater than the preset number of iterations of the microgrid group, the microgrid group plan characteristics are determined according to the optimal dispatching strategy of the microgrid group, and the microgrid group plan characteristics are uploaded to the distribution network control center; Among them, the microgrid group planning characteristics include the microgrid group aggregated equivalent power unit power curve, the microgrid group aggregated energy storage parameters, the microgrid group charging power curve and the microgrid group discharging power curve.

5. The optimization scheduling method based on multi-level microgrid according to claim 4 is characterized in that: The expression of the objective function of maximizing the autonomous operation of the microgrid group is: Min FM Gs,i =FP CC,i +FM G In the formula, F MGs,i is the operating cost of microgrid group i; F PCC,i is the electricity purchase cost of microgrid group i; F MG is the aggregated electricity purchase cost of each microgrid; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the duration of a scheduling period; t is a certain moment in the scheduling cycle; ρ t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t; Support prices between microgrid groups; is the inter-microgrid support power at time t; t,i,j The price of electricity sold by microgrid to microgrid group purchase; Support prices between microgrids; is the planned input and output power of the microgrid at time t; is the inter-microgrid support power at time t.

6. The optimization scheduling method based on multi-level microgrid according to claim 4 is characterized in that: The distribution network operation optimization model is established based on the microgrid group plan characteristics uploaded by the microgrid group control center and the purchase and sale electricity prices of the public connection points set by the distribution network, and the distribution network operation optimization model is iteratively solved until the absolute result difference between the two iterative solutions is within the predetermined difference range of the distribution network or reaches the preset number of iterations of the distribution network, and the optimal dispatching strategy of the distribution network is obtained, including: According to the microgrid group plan characteristics uploaded by each microgrid group in the distribution network and the purchase and sale prices of electricity at the public connection points set up by the distribution network, the distribution network maximizes the autonomous operation objective function, and combines the active power balance constraints of the distribution network to build the corresponding distribution network operation optimization model; Iteratively solve the distribution network operation optimization model to obtain the optimal dispatching strategy of the distribution network; Calculate the absolute difference between the results of two iterative solutions of the distribution network operation optimization model, and compare the absolute difference with a predetermined difference range of the distribution network; When the comparison result shows that the absolute difference is within the predetermined difference range of the distribution network, determining the distribution network planning characteristics according to the distribution network optimal dispatching strategy; When the comparison result shows that the absolute difference is outside the predetermined difference range of the distribution network, it is determined whether the number of iterative solutions of the distribution network operation optimization model exceeds the preset number of iterations of the distribution network; if the number of iterative solutions is less than or equal to the preset number of iterations of the distribution network, the support power of each microgrid is updated, and the microgrid group operation optimization model is constructed; if the number of iterative solutions is greater than the preset number of iterations of the distribution network, the distribution network plan characteristics are determined according to the optimal dispatching strategy of the distribution network; The distribution network planning characteristics include the power purchase and power sales of the distribution network.

7. The optimization scheduling method based on multi-level microgrid according to claim 6 is characterized in that: The expression of the objective function of maximizing autonomous operation of the distribution network is: Min FDN=FPCC+FMGs In the formula, F DN is the operating cost of the distribution network; F PCC is the electricity purchase cost of the distribution network; F MGs is the aggregated electricity purchase cost of each microgrid group; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t is the electricity purchase and sale price at the public connection point of the distribution network at time t; is the planned input and output power of the public connection point of the distribution network at time t; t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t; Support prices between microgrid groups; is the inter-microgrid support power at time t.

8. An optimization dispatching system based on multi-level microgrid, characterized in that: The optimization dispatching system based on multi-level microgrid includes: The microgrid operation optimization module is used to construct a microgrid operation optimization model based on the equipment parameter information of each microgrid, combined with the initial power purchase price and initial power sales price of the microgrid public connection point, solve the microgrid operation optimization model to obtain the optimal dispatching strategy of the microgrid, and determine the microgrid plan characteristics, and upload them to the microgrid group control center; The microgrid operation optimization module is used to construct a microgrid operation optimization model according to the microgrid plan characteristics received by the microgrid control center, iteratively solve the microgrid operation optimization model until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid or reaches the preset number of iterations of the microgrid, obtain the optimal dispatching strategy of the microgrid, determine the plan characteristics of the microgrid, and upload them to the distribution network control center; The distribution network operation optimization module is used to establish a distribution network operation optimization model based on the microgrid group plan characteristics uploaded by the microgrid group control center and the purchase and sale electricity prices of the public connection points set by the distribution network, and iteratively solve the distribution network operation optimization model until the absolute result difference between the two iterative solutions is within the predetermined difference range of the distribution network or reaches the preset number of iterations of the distribution network, so as to obtain the optimal dispatching strategy of the distribution network.

9. The optimization dispatching system based on multi-level microgrid according to claim 8, characterized in that: The microgrid operation optimization module constructs a microgrid operation optimization model based on the equipment parameter information of each microgrid and the initial power purchase price and initial power selling price of the microgrid public connection point, solves the microgrid operation optimization model to obtain the optimal dispatching strategy of the microgrid, and determines the plan characteristics of the microgrid. When uploading to the microgrid group control center, the equipment parameter information of each microgrid is initialized, and the initial power purchase price and initial power selling price of the microgrid public connection point are set; based on the initial power purchase price and initial power selling price of the microgrid public connection point, the microgrid minimum operation optimization model is constructed with the goal of minimizing the power purchase cost of the microgrid. The operation cost objective function is adopted, and the microgrid operation optimization model is constructed in combination with the microgrid active power balance constraint, the microgrid energy storage device constraint, the shifting time period constraint of the shiftable load and the maximum power constraint of the shiftable load. The microgrid operation optimization model is solved to obtain different microgrid optimal dispatching strategies in each microgrid group. According to the microgrid optimal dispatching strategy, the microgrid plan characteristics are determined, and the microgrid plan characteristics are uploaded to the microgrid group control center. The microgrid plan characteristics include the equivalent power unit power curve, the microgrid aggregated energy storage parameters, the microgrid charging power curve and the microgrid discharging power curve.

10. The optimization dispatching system based on multi-level microgrid according to claim 9, characterized in that: The expression of the objective function of the minimum operating cost of the microgrid is: In the formula, F MG,i,j is the electricity purchase cost of the microgrid; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the duration of a scheduling period; t is a certain moment in the scheduling cycle; ρ t,i,j The price of electricity sold by microgrid to microgrid group purchase; and are the electricity purchase price and electricity sales price of the microgrid to the microgrid group respectively; Support prices between microgrids; and They are the support price received and the support price given by the microgrid respectively; is the planned input and output power of the microgrid at time t; is the inter-microgrid support power at time t.

11. The optimization dispatching system based on multi-level microgrid according to claim 8, characterized in that: The microgrid group operation optimization module constructs a microgrid group operation optimization model according to the microgrid plan characteristics received by the microgrid group control center, iteratively solves the microgrid group operation optimization model until the absolute difference between the results of the two iterative solutions is within the predetermined difference range of the microgrid group or reaches the preset number of iterations of the microgrid group, obtains the optimal scheduling strategy of the microgrid group, and determines the microgrid group plan characteristics. When uploading to the distribution network control center, based on the microgrid plan characteristics uploaded by each microgrid in the microgrid group and the purchase and sale electricity price of the public connection point set by the upper power grid, the microgrid group maximizes the autonomous operation objective function, and combines the active power balance constraint of the microgrid group to construct the corresponding microgrid group operation optimization model; iteratively solves the microgrid group operation optimization model to obtain the optimal scheduling strategy of the microgrid group; Calculate the absolute difference between the two iterative solution results before and after the microgrid operation optimization model, and compare the absolute difference with the predetermined difference range of the microgrid; When the comparison result shows that the absolute difference is within the predetermined difference range of the microgrid group, determining the microgrid group plan characteristics according to the microgrid group optimal dispatching strategy, and uploading the microgrid group plan characteristics to the distribution network control center; When the comparison result shows that the absolute difference is outside the predetermined difference range of the microgrid group, it is determined whether the number of iterative solutions of the microgrid group operation optimization model exceeds the preset number of iterations of the microgrid group; if the number of iterative solutions is less than or equal to the preset number of iterations of the microgrid group, the support power of each microgrid is updated, and the microgrid operation optimization model is constructed; If the number of iterative solutions is greater than the preset number of iterations of the microgrid group, the microgrid group plan characteristics are determined according to the optimal scheduling strategy of the microgrid group, and the microgrid group plan characteristics are uploaded to the distribution network control center; wherein the microgrid group plan characteristics include the microgrid group aggregated equivalent power unit power curve, the microgrid group aggregated energy storage parameters, the microgrid group charging power curve and the microgrid group discharge power curve.

12. The optimization dispatching system based on multi-level microgrid according to claim 11, characterized in that: The expression of the objective function of maximizing the autonomous operation of the microgrid group is: Min FM Gs,i =FP CC,i +FM G In the formula, F MGs,i is the operating cost of microgrid group i; F PCC,i is the electricity purchase cost of microgrid group i; F MG is the aggregated electricity purchase cost of each microgrid; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the duration of a scheduling period; t is a certain moment in the scheduling cycle; ρ t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t; Support prices between microgrid groups; is the inter-microgrid support power at time t; t,i,j The price of electricity sold by microgrid to microgrid group purchase; Support prices between microgrids; is the planned input and output power of the microgrid at time t; is the inter-microgrid support power at time t.

13. The optimization dispatching system based on multi-level microgrid according to claim 11, characterized in that: The distribution network operation optimization module establishes a distribution network operation optimization model based on the microgrid group plan characteristics uploaded by the microgrid group control center and the purchase and sale electricity prices of the public connection points set by the distribution network, and iteratively solves the distribution network operation optimization model until the absolute result difference between the two iterative solutions is within the predetermined difference range of the distribution network or reaches the preset number of iterations of the distribution network. When the optimal dispatching strategy of the distribution network is obtained, the distribution network maximization autonomous operation objective function is constructed according to the microgrid group plan characteristics uploaded by each microgrid group in the distribution network and the purchase and sale electricity prices of the public connection points set by the distribution network, and the corresponding distribution network operation optimization model is constructed in combination with the active power balance constraint of the distribution network; the distribution network operation optimization model is iteratively solved to obtain the optimal dispatching strategy of the distribution network; Calculate the absolute difference between the results of two iterative solutions of the distribution network operation optimization model, and compare the absolute difference with a predetermined difference range of the distribution network; When the comparison result shows that the absolute difference is within the predetermined difference range of the distribution network, determining the distribution network planning characteristics according to the distribution network optimal dispatching strategy; When the comparison result is that the absolute difference is outside the predetermined difference range of the distribution network, it is determined whether the number of iterative solutions of the distribution network operation optimization model exceeds the preset number of iterations of the distribution network; if the number of iterative solutions is less than or equal to the preset number of iterations of the distribution network, the support power of each microgrid is updated, and the microgrid group operation optimization model is constructed; if the number of iterative solutions is greater than the preset number of iterations of the distribution network, the distribution network plan characteristics are determined according to the optimal dispatching strategy of the distribution network; wherein the distribution network plan characteristics include the power purchase and power sales of the distribution network.

14. The optimization dispatching system based on multi-level microgrid according to claim 13, characterized in that: The expression of the objective function of maximizing autonomous operation of the distribution network is: Min FDN=FPCC+FMGs In the formula, F DN is the operating cost of the distribution network; F PCC is the electricity purchase cost of the distribution network; F MGs is the aggregated electricity purchase cost of each microgrid group; i and j are the jth microgrid in the i-th microgrid group; T is the number of time periods in a scheduling cycle; ΔT is the length of a scheduling period; t is a certain moment in the scheduling cycle; ρ t is the electricity purchase and sale price at the public connection point of the distribution network at time t; is the planned input and output power of the public connection point of the distribution network at time t; t,i The price of electricity purchased and sold by the microgrid group to the distribution network; is the planned input and output power of the microgrid group at time t; Support prices between microgrid groups; is the inter-microgrid support power at time t.

15. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

16. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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