Micro-grid scheduling method and device, computer readable storage medium and electronic equipment

Abstract

The invention belongs to the technical field of micro-grid dispatching, and particularly relates to a micro-grid dispatching method and device, a computer readable storage medium and electronic equipment. The method comprises the following steps: acquiring day-ahead predicted power data and time-of-use electricity price of the micro-grid; performing day-ahead scheduling on the microgrid according to the day-ahead predicted power data and the time-of-use electricity price to obtain a day-ahead scheduling result; obtaining intra-day predicted power data of the micro-grid; according to the intra-day predicted power data, the day-ahead scheduling result and the time-of-use electricity price, performing intra-day scheduling on the micro-grid to obtain an intra-day scheduling result; wherein the intra-day scheduling energy storage charging and discharging power in the intra-day scheduling result is consistent with the day-ahead scheduling energy storage charging and discharging power in the day-ahead scheduling result; acquiring real-time power data of the micro-grid; according to the real-time power data and the intra-day scheduling result, performing real-time scheduling on the micro-grid to obtain a real-time scheduling result; wherein the target of real-time scheduling is to minimize the scheduling result deviation between the real-time scheduling result and the intra-day scheduling result.

Description

Technical Field

[0001] This application belongs to the field of microgrid dispatching technology, and in particular relates to a microgrid dispatching method, device, computer-readable storage medium and electronic device. Background Technology

[0002] A microgrid is a small-scale power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, loads, monitoring and protection devices, etc. The microgrid was proposed to enable the flexible and efficient application of distributed power sources and solve the grid connection problems of a large number and diverse range of distributed power sources. Developing and extending microgrids can fully promote the large-scale integration of distributed power sources and renewable energy, achieving highly reliable supply of multiple energy forms to loads. It is an effective way to realize an active distribution network, enabling the transition from traditional power grids to smart grids.

[0003] Because energy supply and demand relationships and price fluctuations in microgrids vary across different time scales, multi-time-scale optimization scheduling strategies can better adapt to these changes. Multi-time-scale optimization scheduling typically includes multiple stages such as day-ahead scheduling, intraday scheduling, and real-time scheduling. Among these, intraday scheduling and real-time scheduling have smaller time scales and struggle to take into account global information over larger time scales, thus easily falling into local optima and resulting in poor overall scheduling performance. Summary of the Invention

[0004] In view of this, embodiments of this application provide a microgrid scheduling method, apparatus, computer-readable storage medium, and electronic device to solve the problem of poor scheduling performance in existing microgrid scheduling methods.

[0005] A first aspect of this application provides a microgrid scheduling method, which may include:

[0006] Obtain day-ahead forecast power data and time-of-use electricity prices for microgrids;

[0007] Based on the day-ahead forecast power data and time-of-use pricing, day-ahead scheduling is performed on the microgrid to obtain the day-ahead scheduling results of the microgrid;

[0008] Obtain intraday power forecast data for microgrids;

[0009] Based on the intraday forecast power data, the day-ahead dispatch results, and the time-of-use electricity price, the microgrid is dispatched intraday to obtain the intraday dispatch results of the microgrid; among them, the intraday dispatch energy storage charging and discharging power in the intraday dispatch results is consistent with the day-ahead dispatch energy storage charging and discharging power in the day-ahead dispatch results.

[0010] Obtain real-time power data of the microgrid;

[0011] Based on real-time power data and intraday scheduling results, the microgrid is scheduled in real time to obtain the real-time scheduling results of the microgrid; the objective of real-time scheduling is to minimize the scheduling result deviation between the real-time scheduling results and the intraday scheduling results.

[0012] Using the above method, the energy storage charging and discharging power scheduled a day earlier can be used in the intraday scheduling process, so that global information on a larger time scale can play a role in the intraday scheduling process. On this basis, the goal of minimizing the scheduling result deviation between the real-time scheduling result and the intraday scheduling result can be achieved in the real-time scheduling process, so that global information on a larger time scale can also play a role in the real-time scheduling process. This helps to alleviate the situation where the final scheduling result falls into a local optimum and can effectively improve the overall scheduling effect.

[0013] In one specific implementation of the first aspect, the day-ahead dispatch results may include the day-ahead dispatch energy storage charging and discharging power and the day-ahead dispatch grid power purchase and sale power;

[0014] Based on day-ahead power forecasts and time-of-use pricing, day-ahead dispatching is performed on the microgrid to obtain the day-ahead dispatching results, which may include:

[0015] The total daytime dispatch cost of the microgrid is determined based on the day-ahead forecast power data, time-of-use electricity price, day-ahead dispatch energy storage charging and discharging power, and day-ahead dispatch grid power purchase and sale.

[0016] Based on the constraints of the microgrid, the day-ahead dispatching energy storage charging and discharging power and the day-ahead dispatching grid power purchase and sale power are solved with the objective function of minimizing the total day-ahead dispatching cost.

[0017] By using the above method, day-ahead scheduling based on the constraints and objective function of the microgrid can yield more accurate day-ahead scheduling results.

[0018] In one specific implementation of the first aspect, the total day-ahead dispatch cost of the microgrid is determined based on day-ahead forecast power data, time-of-use pricing, day-ahead dispatched energy storage charging and discharging power, and day-ahead dispatched grid power purchase and sale. This may include:

[0019] Determine the day-ahead dispatch cost of photovoltaic power generation for the microgrid based on the day-ahead forecast power data;

[0020] The day-ahead dispatch power purchase and sale cost of the microgrid is determined based on the day-ahead dispatch power purchase and sale and the time-of-use electricity price.

[0021] The day-ahead dispatch energy storage charging and discharging power is used to determine the day-ahead dispatch energy storage charging and discharging cost of the microgrid;

[0022] The total day-ahead dispatch cost of the microgrid is determined based on the day-ahead dispatch cost of photovoltaic power generation, the day-ahead dispatch cost of purchasing and selling electricity from the grid, and the day-ahead dispatch cost of charging and discharging energy storage.

[0023] Using the above methods, we can comprehensively consider the costs of photovoltaic power generation, grid power purchase and sale, and energy storage charging and discharging, and on this basis, we can obtain a more comprehensive and accurate total day-ahead dispatch cost.

[0024] In one specific implementation of the first aspect, the intraday dispatch results may include intraday dispatched energy storage charging and discharging power and intraday dispatched grid power purchase and sale;

[0025] Based on intraday power forecast data, day-ahead dispatch results, and time-of-use pricing, intraday dispatch is performed on the microgrid to obtain the intraday dispatch results, which may include:

[0026] The day-ahead energy storage charging and discharging power is used as the day-intraday energy storage charging and discharging power.

[0027] The total daily dispatch cost of the microgrid is determined based on the intraday forecast power data, time-of-use electricity price, intraday dispatched energy storage charging and discharging power, and intraday dispatched grid power purchase and sale.

[0028] Based on the constraints of the microgrid, the power purchased and sold by the grid during the day is solved with the objective function of minimizing the total cost of intraday dispatch, and the power purchased and sold by the grid during the day is obtained.

[0029] Using the above method, the energy storage charging and discharging power scheduled a day earlier can be used in the intraday scheduling process, so that global information on a larger time scale can play a role in the intraday scheduling process. Moreover, intraday scheduling based on the constraints and objective function of the microgrid can yield more accurate intraday scheduling results.

[0030] In one specific implementation of the first aspect, the total intraday dispatch cost of the microgrid is determined based on intraday forecast power data, time-of-use pricing, intraday dispatched energy storage charging and discharging power, and intraday dispatched grid power purchase and sale. This may include:

[0031] Based on intraday forecast power data, determine the intraday dispatch cost of photovoltaic power generation for the microgrid;

[0032] The intraday dispatch power purchase and sale cost of the microgrid is determined based on the intraday dispatch power purchase and sale and the time-of-use electricity price.

[0033] The intraday dispatch energy storage charging and discharging cost of the microgrid is determined based on the intraday dispatch energy storage charging and discharging power.

[0034] The total daily dispatch cost of the microgrid is determined based on the daily dispatch costs of photovoltaic power generation, the daily dispatch costs of grid power purchase and sale, and the daily dispatch costs of energy storage charging and discharging.

[0035] Using the above methods, we can comprehensively consider the costs of photovoltaic power generation, grid power purchase and sale, and energy storage charging and discharging, and on this basis, we can obtain a more comprehensive and accurate total daily dispatch cost.

[0036] In one specific implementation of the first aspect, the intraday dispatch results may include intraday dispatched energy storage charging and discharging power and intraday dispatched grid power purchase and sale, and the real-time dispatch results may include real-time dispatched energy storage charging and discharging power and real-time dispatched grid power purchase and sale.

[0037] Based on real-time power data and intraday dispatch results, the microgrid is dispatched in real time to obtain the real-time dispatch results, which may include:

[0038] The deviation of the microgrid's dispatch results is determined based on the intraday dispatched energy storage charging and discharging power, intraday dispatched grid power purchase and sale power, real-time dispatched energy storage charging and discharging power, and real-time dispatched grid power purchase and sale power.

[0039] Based on the constraints of the microgrid, the real-time dispatched energy storage charging and discharging power and the real-time dispatched grid power purchase and sale power are solved with the objective function of minimizing the dispatch result deviation.

[0040] Using the above method, the goal is to minimize the deviation between real-time scheduling results and intraday scheduling results during real-time scheduling. This allows global information on a larger time scale to play a role in real-time scheduling. Furthermore, intraday scheduling based on microgrid constraints and objective functions can yield more accurate real-time scheduling results.

[0041] In one specific implementation of the first aspect, determining the microgrid's dispatch result deviation based on intraday dispatched energy storage charging and discharging power, intraday dispatched grid power purchase and sale, real-time dispatched energy storage charging and discharging power, and real-time dispatched grid power purchase and sale may include:

[0042] The energy storage dispatch deviation of the microgrid is determined based on the real-time dispatch energy storage charging and discharging power and the intraday dispatch energy storage charging and discharging power.

[0043] The grid dispatch deviation of the microgrid is determined based on the real-time dispatch power purchase and sale power and the intraday dispatch power purchase and sale power.

[0044] The scheduling deviation of the microgrid is determined based on the energy storage scheduling deviation and the grid scheduling deviation.

[0045] Using the above methods, we can comprehensively consider the deviations of energy storage dispatch and grid dispatch, and on this basis, we can obtain more comprehensive and accurate dispatch result deviations.

[0046] In one specific implementation of the first aspect, determining the microgrid scheduling result deviation based on the energy storage scheduling deviation and the grid scheduling deviation may include:

[0047] Based on the first weight corresponding to the energy storage dispatch deviation, the energy storage dispatch deviation is weighted to obtain the weighted energy storage dispatch deviation.

[0048] Based on the second weight corresponding to the power grid dispatch deviation, the power grid dispatch deviation is weighted to obtain the weighted power grid dispatch deviation.

[0049] The scheduling deviation of the microgrid is determined based on the weighted energy storage scheduling deviation and the weighted grid scheduling deviation.

[0050] Using the above method, energy storage dispatch deviation and grid dispatch deviation can be weighted according to their respective weights, thereby allowing for flexible adjustment of their roles in the final dispatch result deviation.

[0051] A second aspect of the embodiments of this application provides a microgrid dispatching device, which may include:

[0052] The first acquisition module is used to acquire the day-ahead forecast power data and time-of-use electricity price of the microgrid;

[0053] The day-ahead scheduling module is used to perform day-ahead scheduling of the microgrid based on the day-ahead predicted power data and time-of-use electricity price, and obtain the day-ahead scheduling results of the microgrid;

[0054] The second acquisition module is used to acquire intraday predicted power data of the microgrid;

[0055] The intraday dispatch module is used to perform intraday dispatch of the microgrid based on intraday predicted power data, day-ahead dispatch results, and time-of-use electricity prices, and obtain the intraday dispatch results of the microgrid; wherein, the intraday dispatch energy storage charging and discharging power in the intraday dispatch results is consistent with the day-ahead dispatch energy storage charging and discharging power in the day-ahead dispatch results;

[0056] The third acquisition module is used to acquire real-time power data of the microgrid;

[0057] The real-time scheduling module is used to perform real-time scheduling of the microgrid based on real-time power data and intraday scheduling results, and obtain the real-time scheduling results of the microgrid. The objective of real-time scheduling is to minimize the scheduling result deviation between the real-time scheduling results and the intraday scheduling results.

[0058] The aforementioned device allows the storage charging and discharging power scheduled before the day to be used during intraday scheduling, thus enabling global information on a larger time scale to play a role in intraday scheduling. Based on this, the goal is to minimize the scheduling result deviation between real-time scheduling and intraday scheduling during real-time scheduling, thereby enabling global information on a larger time scale to also play a role in real-time scheduling. This helps to alleviate the situation where the final scheduling result falls into a local optimum and can effectively improve the overall scheduling effect.

[0059] In one specific implementation of the second aspect, the day-ahead dispatch results may include the day-ahead dispatch energy storage charging and discharging power and the day-ahead dispatch grid power purchase and sale power;

[0060] The day-ahead scheduling module may include:

[0061] The day-ahead dispatch total cost determination submodule is used to determine the day-ahead dispatch total cost of the microgrid based on day-ahead forecast power data, time-of-use electricity price, day-ahead dispatch energy storage charging and discharging power, and day-ahead dispatch grid power purchase and sale.

[0062] The day-ahead dispatch solution submodule is used to solve for the day-ahead dispatch energy storage charging and discharging power and the day-ahead dispatch grid purchase and sale power based on the constraints of the microgrid and with the objective function of minimizing the total day-ahead dispatch cost.

[0063] By using the aforementioned device, more accurate day-ahead scheduling results can be obtained by performing day-ahead scheduling based on the constraints and objective function of the microgrid.

[0064] In one specific implementation of the second aspect, the day-ahead scheduling total cost determination submodule may include:

[0065] The day-ahead dispatch photovoltaic power generation cost determination unit is used to determine the day-ahead dispatch photovoltaic power generation cost of the microgrid based on the day-ahead predicted power data.

[0066] The day-ahead dispatching grid power purchase and sale cost determination unit is used to determine the day-ahead dispatching grid power purchase and sale cost of the microgrid based on the day-ahead dispatching grid power purchase and sale and the time-of-use electricity price;

[0067] The day-ahead dispatch total cost determination unit is used to determine the day-ahead dispatch energy storage charging and discharging cost of the microgrid based on the day-ahead dispatch energy storage charging and discharging power.

[0068] The total day-ahead dispatch cost of the microgrid is determined based on the day-ahead dispatch cost of photovoltaic power generation, the day-ahead dispatch cost of purchasing and selling electricity from the grid, and the day-ahead dispatch cost of charging and discharging energy storage.

[0069] The aforementioned device allows for a comprehensive consideration of various factors, including photovoltaic power generation costs, grid power purchase and sale costs, and energy storage charging and discharging costs. Based on this, a more comprehensive and accurate total day-ahead dispatch cost can be obtained.

[0070] In one specific implementation of the second aspect, the intraday dispatch results may include intraday dispatched energy storage charging and discharging power and intraday dispatched grid power purchase and sale;

[0071] The intraday scheduling module may include:

[0072] The energy storage charging and discharging power determination submodule is used to use the day-ahead dispatched energy storage charging and discharging power as the day-intraday dispatched energy storage charging and discharging power.

[0073] The intraday dispatch total cost determination submodule is used to determine the intraday dispatch total cost of the microgrid based on intraday predicted power data, time-of-use electricity price, intraday dispatch energy storage charging and discharging power, and intraday dispatch grid power purchase and sale.

[0074] The intraday scheduling solution submodule is used to solve for the intraday power purchase and sale of the grid based on the constraints of the microgrid, with the objective function of minimizing the total intraday scheduling cost, and obtain the intraday power purchase and sale of the grid.

[0075] The aforementioned device allows the energy storage charging and discharging power scheduled a day earlier to be used during intraday scheduling, thus enabling global information on a larger time scale to play a role in intraday scheduling. Furthermore, intraday scheduling based on the constraints and objective function of the microgrid can yield more accurate intraday scheduling results.

[0076] In one specific implementation of the second aspect, the submodule for determining the total intraday scheduling cost may include:

[0077] The intraday dispatch photovoltaic power generation cost determination unit is used to determine the intraday dispatch photovoltaic power generation cost of the microgrid based on intraday predicted power data.

[0078] The intraday dispatch grid power purchase and sale cost determination unit is used to determine the intraday dispatch grid power purchase and sale cost of the microgrid based on the intraday dispatch grid power purchase and sale and time-of-use electricity price;

[0079] The intraday dispatch energy storage charging and discharging cost determination unit is used to determine the intraday dispatch energy storage charging and discharging cost of the microgrid based on the intraday dispatch energy storage charging and discharging power.

[0080] The intraday dispatch total cost determination unit is used to determine the intraday dispatch total cost of the microgrid based on the intraday dispatch photovoltaic power generation cost, intraday dispatch grid power purchase and sale cost, and intraday dispatch energy storage charging and discharging cost.

[0081] The aforementioned device allows for a comprehensive consideration of various factors, including photovoltaic power generation costs, grid power purchase and sale costs, and energy storage charging and discharging costs. Based on this, a more comprehensive and accurate total daily dispatch cost can be obtained.

[0082] In one specific implementation of the second aspect, the intraday dispatch results may include intraday dispatched energy storage charging and discharging power and intraday dispatched grid power purchase and sale, and the real-time dispatch results may include real-time dispatched energy storage charging and discharging power and real-time dispatched grid power purchase and sale.

[0083] The real-time scheduling module may include:

[0084] The dispatch result deviation determination submodule is used to determine the dispatch result deviation of the microgrid based on the intraday dispatched energy storage charging and discharging power, intraday dispatched grid power purchase and sale power, real-time dispatched energy storage charging and discharging power, and real-time dispatched grid power purchase and sale power.

[0085] The real-time scheduling solution submodule is used to solve for the real-time scheduling energy storage charging and discharging power and the real-time scheduling grid power purchase and sale power based on the constraints of the microgrid and with the objective function of minimizing the scheduling result deviation.

[0086] With the above-mentioned device, the goal is to minimize the deviation between the real-time scheduling result and the intraday scheduling result during the real-time scheduling process. This allows global information on a larger time scale to play a role in the real-time scheduling process. Moreover, intraday scheduling based on the constraints and objective function of the microgrid can yield more accurate real-time scheduling results.

[0087] In one specific implementation of the second aspect, the scheduling result deviation determination submodule may include:

[0088] The energy storage dispatch deviation determination unit is used to determine the energy storage dispatch deviation of the microgrid based on the real-time dispatch energy storage charging and discharging power and the intraday dispatch energy storage charging and discharging power.

[0089] The grid dispatch deviation determination unit is used to determine the grid dispatch deviation of the microgrid based on the real-time dispatch grid power purchase and sale power and the intraday dispatch grid power purchase and sale power.

[0090] The dispatch result deviation determination unit is used to determine the dispatch result deviation of the microgrid based on the energy storage dispatch deviation and the grid dispatch deviation.

[0091] The aforementioned device allows for comprehensive consideration of factors such as energy storage dispatch deviation and grid dispatch deviation, resulting in a more comprehensive and accurate dispatch result deviation.

[0092] In one specific implementation of the second aspect, the scheduling result deviation determination unit may include:

[0093] The first weighting sub-unit is used to weight the energy storage scheduling deviation according to the first weight corresponding to the energy storage scheduling deviation, so as to obtain the weighted energy storage scheduling deviation.

[0094] The second weighting subunit is used to weight the power grid dispatching deviation according to the second weight corresponding to the power grid dispatching deviation, so as to obtain the weighted power grid dispatching deviation.

[0095] The dispatch result deviation determination subunit is used to determine the dispatch result deviation of the microgrid based on the weighted energy storage dispatch deviation and the weighted grid dispatch deviation.

[0096] The aforementioned device allows for the weighting of energy storage dispatch deviations and grid dispatch deviations according to their respective weights, thereby enabling flexible adjustment of their roles in the final dispatch result deviation.

[0097] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of any of the above-described microgrid scheduling methods.

[0098] A fourth aspect of this application provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of any of the above-described microgrid scheduling methods.

[0099] The fifth aspect of this application provides a computer program product, including a computer program, which, when run, causes any of the above-described microgrid scheduling methods to be executed. Attached Figure Description

[0100] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0101] Figure 1 This is a flowchart of one embodiment of a microgrid scheduling method in this application.

[0102] Figure 2 This is a schematic diagram of the current day's scheduling results;

[0103] Figure 3 This is a schematic diagram of the intraday scheduling results for a single transaction.

[0104] Figure 4 This is a schematic diagram of intraday scheduling that operates on a rolling cycle.

[0105] Figure 5 This is a schematic diagram of the intraday scheduling results, which are executed on a rolling basis over a periodic period.

[0106] Figure 6 A schematic diagram of real-time scheduling that operates on a periodic rolling basis;

[0107] Figure 7 This is a schematic diagram of the real-time scheduling results that run on a periodic rolling basis.

[0108] Figure 8 This is a schematic diagram of the cloud-edge-device system architecture used for microgrid scheduling and control in the embodiments of this application;

[0109] Figure 9 This is a structural diagram of one embodiment of a microgrid dispatching device according to the present application.

[0110] Figure 10 This is a schematic block diagram of an electronic device according to an embodiment of this application. Detailed Implementation

[0111] To make the inventive objectives, features, and advantages of this application more apparent and understandable, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the embodiments described below are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0112] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0113] It should also be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of the application. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0114] It should also be further understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0115] As used in this specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrase "if determined" or "if [the described condition or event] is detected" may be interpreted, depending on the context, as "once determined," "in response to determination," "once [the described condition or event] is detected," or "in response to detection of [the described condition or event]."

[0116] Furthermore, in the description of this application, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0117] A microgrid is a small-scale power generation and distribution system composed of distributed power sources, energy storage devices, energy conversion devices, loads, monitoring and protection devices, etc. The microgrid was proposed to enable the flexible and efficient application of distributed power sources and solve the grid connection problems of a large number and diverse range of distributed power sources. Developing and extending microgrids can fully promote the large-scale integration of distributed power sources and renewable energy, achieving highly reliable supply of multiple energy forms to loads. It is an effective way to realize an active distribution network, enabling the transition from traditional power grids to smart grids.

[0118] Because energy supply and demand relationships and price fluctuations in microgrids vary across different time scales, multi-time-scale optimization scheduling strategies can better adapt to these changes. Multi-time-scale optimization scheduling typically includes multiple stages such as day-ahead scheduling, intraday scheduling, and real-time scheduling. Among these, intraday scheduling and real-time scheduling have smaller time scales and struggle to take into account global information over larger time scales, thus easily falling into local optima and resulting in poor overall scheduling performance.

[0119] In view of this, embodiments of this application provide a microgrid scheduling method, apparatus, computer-readable storage medium, and electronic device to solve the problem of poor scheduling performance in existing microgrid scheduling methods.

[0120] In this embodiment, the energy storage charging and discharging power scheduled before the day can be used in the intraday scheduling process, so that global information on a larger time scale can play a role in the intraday scheduling process. On this basis, the goal of minimizing the scheduling result deviation between the real-time scheduling result and the intraday scheduling result can be achieved in the real-time scheduling process, so that global information on a larger time scale can also play a role in the real-time scheduling process. This helps to alleviate the situation where the final scheduling result falls into a local optimum and can effectively improve the overall scheduling effect.

[0121] The subject of this application method can be an electronic device, including but not limited to desktop computers, laptops, handheld computers, servers, and other computing devices.

[0122] Please see Figure 1 One embodiment of a microgrid dispatching method in this application may include:

[0123] Step S101: Obtain the day-ahead forecast power data and time-of-use electricity price of the microgrid.

[0124] Day-ahead scheduling refers to the pre-scheduling of the microgrid's operation plan for the future day-ahead scheduling period based on the predicted power demand and supply situation before the start of each day-ahead scheduling cycle, in order to ensure that the microgrid can maintain balance and stability during that period.

[0125] The day-ahead scheduling cycle can be flexibly set according to the actual situation, including but not limited to 1 day, 2 days or other values. The day-ahead scheduling cycle can be divided into several day-ahead scheduling periods. The specific division method of the day-ahead scheduling period can be flexibly set according to the actual situation, including but not limited to dividing the day-ahead scheduling period with a step size of 15 minutes, 30 minutes or other values.

[0126] As an example, in one specific implementation of this application, the daily scheduling cycle can be set to 1 day, and the daily scheduling time period can be divided in 15-minute increments, dividing one daily scheduling cycle into 96 daily scheduling time periods. For example, the time period from 0:00 to 0:15 can be designated as the 1st daily scheduling time period, the time period from 0:15 to 0:30 as the 2nd daily scheduling time period, the time period from 0:30 to 0:45 as the 3rd daily scheduling time period, and so on, with the time period from 23:30 to 23:45 designated as the 95th daily scheduling time period, the time period from 23:45 to 24:00 as the 96th daily scheduling time period, and so on. It should be noted that the above method of dividing the daily scheduling time period is only an example. In practical applications, the length of each daily scheduling time period can be flexibly set according to specific circumstances, and the lengths of different daily scheduling time periods can be the same or different.

[0127] The day-ahead forecast power data refers to the power data of the electrical equipment in the microgrid during each day-ahead scheduling period in the next day-ahead scheduling cycle, which is predicted before the start of the next day-ahead scheduling cycle. It may include, but is not limited to, the power generation of photovoltaic equipment (denoted as day-ahead forecast photovoltaic power generation) and the power of electrical load equipment (denoted as day-ahead forecast electrical load power).

[0128] Time-of-use (TOU) pricing can include, but is not limited to, TOU purchase price and TOU sales price. TOU purchase price refers to the price at which a microgrid purchases electricity from the grid at different times, while TOU sales price refers to the price at which a microgrid sells electricity to the grid at different times.

[0129] Step S102: Based on the day-ahead forecast power data and time-of-use electricity price, perform day-ahead scheduling on the microgrid to obtain the day-ahead scheduling results of the microgrid.

[0130] The day-ahead dispatch results may include, but are not limited to, the charging and discharging power of energy storage devices in the microgrid during each day-ahead dispatch period in the next day-ahead dispatch cycle (referred to as day-ahead dispatch energy storage charging and discharging power) and the power purchased and sold by the microgrid to the grid during each day-ahead dispatch period in the next day-ahead dispatch cycle (referred to as day-ahead dispatch grid power purchased and sold).

[0131] In this embodiment, the total day-ahead dispatch cost of the microgrid can be determined based on day-ahead predicted power data, time-of-use tariffs, day-ahead dispatched energy storage charging and discharging power, and day-ahead dispatched grid power purchase and sale. Based on the constraints of the microgrid, the day-ahead dispatched energy storage charging and discharging power and the day-ahead dispatched grid power purchase and sale are solved with the objective function of minimizing the total day-ahead dispatch cost, thus obtaining the day-ahead dispatched energy storage charging and discharging power and the day-ahead dispatched grid power purchase and sale.

[0132] The total cost of day-ahead dispatch may include, but is not limited to, the cost of day-ahead dispatch of photovoltaic power generation, the cost of day-ahead dispatch of grid power purchase and sale, and the cost of day-ahead dispatch of energy storage charging and discharging.

[0133] Based on day-ahead power forecasts, the day-ahead dispatch cost of photovoltaic (PV) power generation for a microgrid can be determined. For example, the day-ahead dispatch cost of PV power generation can be calculated using the PV power generation model shown below:

[0134]

[0135] Where t is the sequence number of the day-ahead scheduling period, 1≤t≤T, and T is the total number of day-ahead scheduling periods. Let K be the predicted photovoltaic power generation for the t-th day-ahead scheduling period, where Δt is the duration of the day-ahead scheduling period, and K is the value of K. PVO This is a preset photovoltaic power generation operation and maintenance cost coefficient, the specific value of which can be flexibly set according to actual conditions. To adjust the cost of photovoltaic power generation in advance.

[0136] The day-ahead power purchase and sale cost of a microgrid can be determined based on the day-ahead power purchase and sale volume and time-of-use pricing. For example, the day-ahead power purchase and sale cost can be calculated based on the grid model shown in the following formula:

[0137]

[0138] in, Let be the time-of-use electricity price for the t-th day-ahead dispatch period. Let be the time-of-use electricity price for the t-th day-ahead dispatch period. Let be the power purchased by the grid during the t-th day-ahead dispatch period. Let be the power output of the power grid during the t-th day-ahead dispatch period. This refers to the current electricity purchase and sale costs of the power grid.

[0139] The above power grid model must meet the following constraints:

[0140]

[0141] in, The preset maximum power purchase capacity from the grid. These are the preset maximum grid power outputs; their specific values ​​can be flexibly set according to actual conditions. This is a power purchase status indicator for the t-th day-ahead scheduling period, with a value of 1 or 0. A value of 1 indicates that the microgrid is in a power purchase state during the t-th day-ahead scheduling period, meaning it is purchasing electricity from the grid. A value of 0 indicates that the microgrid is in a power sale state during the t-th day-ahead scheduling period, meaning it is selling electricity to the grid. This is a power sales status indicator for the t-th day-ahead scheduling period, with a value of 1 or 0. A value of 1 indicates that the microgrid is in a power sales state during the t-th day-ahead scheduling period, meaning it is selling electricity to the grid. A value of 0 indicates that the microgrid is in a power purchase state during the t-th day-ahead scheduling period, meaning it is purchasing electricity from the grid. The power purchased and sold by the power grid in the day-ahead dispatch is represented by a positive or negative sign. A positive value indicates the power purchased, and a negative value indicates the power sold.

[0142] The day-ahead dispatch cost of energy storage can be determined based on the day-ahead dispatch power of the energy storage system. For example, the day-ahead dispatch cost of energy storage can be calculated based on the energy storage battery model shown in the following formula:

[0143]

[0144] Among them, C BTO (t) represents the operating cost of the scheduling period on the t-th day, C BTM (t) represents the maintenance cost for the t-th day-ahead scheduling period. This refers to the cost of charging and discharging energy storage in the day-to-day scheduling.

[0145] Based on the battery discharge depth model based on the rainflow counting method and the battery loss model based on the throughput method, the operating cost of the energy storage battery during the t-day scheduling period can be expressed as:

[0146]

[0147]

[0148] in, Let be the energy storage charging power for the t-th day-ahead scheduling period. Let C be the energy storage discharge power during the t-th day-ahead scheduling period. in N represents the initial investment cost. rl (t) represents the battery cycle life during the t-th day-ahead scheduling period, D od (t) represents the battery charge / discharge depth during the t-th day-ahead scheduling period, i.e., the ratio of battery charge / discharge amount to rated capacity, E BT This refers to the capacity of the energy storage battery.

[0149] The above-mentioned function for calculating operating costs is an inverse proportional high-order composite function. To facilitate optimization, a quadratic function as shown below can be used for fitting:

[0150]

[0151] Where j1, j2, and j3 are the parameters of the fitted quadratic function.

[0152] The maintenance cost of the energy storage battery during the dispatch period on the t-th day can be expressed as:

[0153]

[0154] Among them, K BTM This is the preset energy storage battery maintenance cost coefficient, and its specific value can be flexibly set according to the actual situation.

[0155] The model of an energy storage battery charging and discharging device can be represented as:

[0156]

[0157] Where SOC(t) represents the state of charge of the energy storage battery during the t-th day-ahead scheduling period, and SOC(t+1) represents the state of charge of the energy storage battery during the (t+1)-th day-ahead scheduling period. The preset charging efficiency, The specific values ​​of E and E can be flexibly set according to actual conditions, representing the preset discharge efficiency. r (t) represents the remaining charge of the energy storage battery during the scheduling period on the t-th day, and δ is the preset self-discharge rate, the specific value of which can be flexibly set according to the actual situation.

[0158] The above-mentioned energy storage battery charging and discharging equipment model must meet the following constraints:

[0159]

[0160] in, The preset maximum energy storage charging power, These are the preset maximum energy storage and discharge power; their specific values ​​can be flexibly set according to actual conditions. This is a charging status indicator for the energy storage battery during the scheduling period on the t-th day. Its value is either 1 or 0. A value of 1 indicates that the energy storage battery is charging during the scheduling period on the t-th day, while a value of 0 indicates that the energy storage battery is discharging during the scheduling period on the t-th day. This is a discharge status indicator for the energy storage battery during the scheduling period on the t-th day. Its value is either 1 or 0. A value of 1 indicates that the energy storage battery is in a discharging state during the scheduling period on the t-th day, while a value of 0 indicates that the energy storage battery is in a charging state during the scheduling period on the t-th day. This represents the day-ahead scheduled charging and discharging power of the energy storage battery during the t-th day-ahead scheduling period. The sign indicates the charging and discharging power; a positive value represents the discharging power, and a negative value represents the charging power. The preset lower limit for power conversion. The preset power conversion upper limit can be flexibly set according to the actual situation. init and T represent the initial and final times of the day-ahead scheduling cycle, respectively. To ensure that the scheduling plan has the ability to be executed in the long term, the energy storage battery state should be periodic, that is, the remaining capacity should be the same at the beginning and end of the scheduling.

[0161] In addition, the above-mentioned device models must also meet the following system power balance constraints:

[0162]

[0163] in, Let be the day-ahead predicted electrical load power for the t-th day-ahead scheduling period.

[0164] After calculating the day-ahead dispatch cost of photovoltaic power generation, the day-ahead dispatch cost of purchasing and selling electricity from the grid, and the day-ahead dispatch cost of charging and discharging energy storage, the total day-ahead dispatch cost of the microgrid can be determined based on these costs, as shown in the following formula:

[0165]

[0166] Among them, C dayahead This represents the total day-ahead dispatch cost of the microgrid.

[0167] Through the above process, we can comprehensively consider the costs of photovoltaic power generation, grid power purchase and sale, and energy storage charging and discharging, and on this basis, we can obtain a more comprehensive and accurate total day-ahead dispatch cost.

[0168] Based on the constraints of the microgrid, and with minimizing the total day-ahead dispatch cost as the objective function, the day-ahead dispatch energy storage charging and discharging power and the day-ahead dispatch grid power purchase and sale power are solved to obtain the day-ahead dispatch energy storage charging and discharging power and the day-ahead dispatch grid power purchase and sale power.

[0169] Using the day-ahead predicted photovoltaic power generation, day-ahead predicted electrical load, time-of-use electricity purchase price, and time-of-use electricity sales price as input parameters, and the day-ahead dispatched energy storage charging and discharging power and the day-ahead dispatched grid power purchase and sale power as decision variables, a corresponding mathematical programming model can be constructed based on the above constraints and with minimizing the total day-ahead dispatch cost as the objective function. This model is denoted as the day-ahead optimal dispatch model, and solving this model yields the corresponding day-ahead dispatch results. Through the above process, day-ahead dispatch based on the constraints and objective function of the microgrid can achieve more accurate day-ahead dispatch results.

[0170] Figure 2 The diagram shows the day-ahead dispatch results, illustrating the photovoltaic power generation, electrical load, time-of-use electricity purchase price, time-of-use electricity sales price, energy storage charging and discharging power, and grid power generation for each day-ahead dispatch period (15 minutes) within the day-ahead dispatch cycle (1 day as an example). It can be seen that under the objective of economic optimization, when electricity prices are low, priority is given to grid power supply to meet electrical load demand and charge energy storage; when electricity prices are high, priority is given to energy storage discharging, combined with peak-valley arbitrage based on photovoltaic power generation.

[0171] Step S103: Obtain intraday predicted power data for the microgrid.

[0172] Intraday scheduling refers to the pre-scheduling of the microgrid's operation plan for the upcoming intraday scheduling period based on predicted power demand and supply before the start of each intraday scheduling cycle, in order to ensure that the microgrid can maintain balance and stability during that period.

[0173] The intraday scheduling cycle can be flexibly set according to the actual situation, including but not limited to 4 hours, 6 hours or other values. The intraday scheduling cycle can be divided into several intraday scheduling periods. The specific division method of the intraday scheduling period can be flexibly set according to the actual situation, including but not limited to dividing the intraday scheduling period with a step size of 15 minutes, 30 minutes or other values.

[0174] As an example, in one specific implementation of this application, the daily scheduling cycle can be set to 4 hours, and the daily scheduling time slots can be divided in 15-minute increments, dividing one daily scheduling cycle into 16 daily scheduling time slots. For example, if the daily scheduling cycle is from 4:00 to 8:00, the time slot from 4:00 to 4:15 can be designated as the first daily scheduling time slot, the time slot from 4:15 to 4:30 as the second daily scheduling time slot, the time slot from 4:30 to 4:45 as the third daily scheduling time slot, and so on. The time slot from 7:30 to 23:45 can be designated as the 15th daily scheduling time slot, the time slot from 7:45 to 24:00 as the 16th daily scheduling time slot, and so on. It should be noted that the above method of dividing the daily scheduling time slots is only an example. In practical applications, the length of each daily scheduling time slot can be flexibly set according to specific circumstances. The lengths of different daily scheduling time slots can be the same or different.

[0175] Intraday forecast power data refers to the power data of electrical equipment in the microgrid during each intraday scheduling period in the next intraday scheduling cycle, which is predicted before the start of the next intraday scheduling cycle. It may include, but is not limited to, the power generation of photovoltaic equipment (denoted as intraday forecast photovoltaic power generation) and the power of electrical load equipment (denoted as intraday forecast electrical load power).

[0176] Step S104: Based on the intraday predicted power data, the day-ahead dispatch results, and the time-of-use electricity price, perform intraday dispatch on the microgrid to obtain the intraday dispatch results of the microgrid.

[0177] Intraday dispatch results may include, but are not limited to, the charging and discharging power of energy storage devices in the microgrid during each intraday dispatch period in the next intraday dispatch cycle (referred to as intraday dispatch energy storage charging and discharging power), and the power purchased and sold by the microgrid to the grid during each intraday dispatch period in the next intraday dispatch cycle (referred to as intraday dispatch grid power purchased and sold).

[0178] In this embodiment of the application, the intraday energy storage charging and discharging power in the intraday scheduling result is consistent with the day-ahead energy storage charging and discharging power in the day-ahead scheduling result. That is, the energy storage charging and discharging power of the day-ahead scheduling can be used in the intraday scheduling process, so that global information on a larger time scale can play a role in the intraday scheduling process.

[0179] In this embodiment, the day-ahead dispatched energy storage charging and discharging power can be used as the intraday dispatched energy storage charging and discharging power. Based on the intraday predicted power data, time-of-use electricity price, intraday dispatched energy storage charging and discharging power, and intraday dispatched grid power purchase and sale, the total intraday dispatched cost of the microgrid is determined. Based on the constraints of the microgrid, the intraday dispatched grid power purchase and sale is solved with minimizing the total intraday dispatched cost as the objective function, thereby obtaining the intraday dispatched grid power purchase and sale.

[0180] The total cost of intraday dispatch may include, but is not limited to, the cost of intraday dispatch of photovoltaic power generation, the cost of intraday dispatch of grid power purchase and sale, and the cost of intraday dispatch of energy storage charging and discharging.

[0181] Based on intraday power forecast data, the intraday dispatch cost of photovoltaic (PV) power generation for a microgrid can be determined. For example, the intraday dispatch cost of PV power generation can be calculated based on the PV power generation model shown in the following formula:

[0182]

[0183] Where t is the sequence number of the intraday scheduling period, 1≤t≤T, and T is the total number of intraday scheduling periods. Let Δt be the predicted photovoltaic power generation for the t-th intraday scheduling period, where Δt is the duration of the intraday scheduling period. To manage the cost of photovoltaic power generation within the day.

[0184] The intraday power purchase and sale cost of a microgrid can be determined based on the intraday dispatch grid power and time-of-use pricing. For example, the intraday dispatch grid power purchase and sale cost can be calculated based on the grid model shown in the following formula:

[0185]

[0186] in, Let be the time-of-use electricity price for the t-th intraday dispatch period. Let be the time-of-use electricity price for the t-th intraday dispatch period. Let be the power purchased by the power grid during the t-th intraday dispatch period. Let be the power output of the power grid during the t-th intraday dispatch period. The cost of purchasing and selling electricity on the power grid during the day.

[0187] The above power grid model must meet the following constraints:

[0188]

[0189]

[0190]

[0191] in, This is a power purchase status indicator for the t-th day's dispatch period, with a value of 1 or 0. A value of 1 indicates that the microgrid is in a power purchase state during the t-th day's dispatch period, meaning it is purchasing electricity from the grid. A value of 0 indicates that the microgrid is in a power sale state during the t-th day's dispatch period, meaning it is selling electricity to the grid. This is a power sales status indicator for the t-th day's dispatch period, with a value of 1 or 0. A value of 1 indicates that the microgrid is in a power sales state during the t-th day's dispatch period, meaning it is selling electricity to the grid. A value of 0 indicates that the microgrid is in a power purchase state during the t-th day's dispatch period, meaning it is purchasing electricity from the grid. The power purchased and sold by the power grid during the day is represented by a positive or negative sign. A positive value indicates the power purchased, and a negative value indicates the power sold.

[0192] The intraday dispatched energy storage charging and discharging power can be used to determine the intraday dispatched energy storage charging and discharging cost of the microgrid. It's important to note that this is achieved by directly using the day-ahead dispatched energy storage charging and discharging power for the same time period as the intraday dispatched energy storage charging and discharging power. This represents the intraday scheduled charging and discharging power of the energy storage battery during the t-th day's scheduling period. The sign indicates the charging and discharging power; a positive value represents the discharging power, and a negative value represents the charging power. To and The day-ahead dispatched energy storage charging and discharging power during the same period. The intraday dispatched energy storage charging and discharging power is known, therefore it can be directly substituted into the aforementioned energy storage charging and discharging cost calculation formula to obtain the intraday dispatched energy storage charging and discharging cost, denoted as .

[0193] In addition, the above-mentioned device models must also meet the following system power balance constraints:

[0194]

[0195] in, Let be the predicted daily electrical load power for the t-th intraday scheduling period.

[0196] After calculating the intraday dispatch costs of photovoltaic power generation, grid power purchase and sale, and energy storage charging and discharging, the total intraday dispatch cost of the microgrid can be determined based on these costs, as shown in the following formula:

[0197]

[0198] Among them, C intraday This represents the total daily dispatch cost of the microgrid.

[0199] Using the above methods, we can comprehensively consider the costs of photovoltaic power generation, grid power purchase and sale, and energy storage charging and discharging, and on this basis, we can obtain a more comprehensive and accurate total daily dispatch cost.

[0200] Based on the constraints of the microgrid, the power purchased and sold by the grid during the day can be obtained by minimizing the total cost of intraday dispatching as the objective function.

[0201] Using intraday dispatched energy storage charging and discharging power (adopting day-ahead dispatched energy storage charging and discharging power), intraday predicted photovoltaic power generation, intraday predicted electrical load, time-of-use electricity purchase price, and time-of-use electricity sales price as input parameters, and intraday dispatched grid power purchase and sales as decision variables, a corresponding mathematical programming model can be constructed based on the above constraints and minimizing the total intraday dispatch cost as the objective function. This model is denoted as the intraday optimal dispatch model, and solving this model yields the corresponding intraday dispatch results. Through the above process, the day-ahead dispatched energy storage charging and discharging power can be used in the intraday dispatch process, allowing global information on a larger time scale to play a role in the intraday dispatch process. Moreover, intraday dispatch based on the constraints and objective function of the microgrid can yield more accurate intraday dispatch results.

[0202] Figure 3 The diagram shows the results of a single intraday dispatch, which displays the photovoltaic power generation, electrical load, time-of-use electricity purchase price, time-of-use electricity sales price, energy storage charging and discharging power, and grid power purchase and sales power for each intraday dispatch period (15 minutes) within the intraday dispatch cycle (taking 4 hours as an example).

[0203] like Figure 4 As shown, intraday scheduling is a rolling operation with the duration of intraday scheduling periods as the cycle. Taking an intraday scheduling cycle of 4 hours and an intraday scheduling period of 15 minutes as an example, intraday scheduling can be rolled 96 times in a day, and each intraday scheduling can obtain the intraday scheduling result of the next intraday scheduling cycle. Figure 5 The diagram shows the results of daily scheduling on a rolling basis, which displays the photovoltaic power generation, electrical load, time-of-use electricity purchase price, time-of-use electricity sales price, energy storage charging and discharging power, and grid power purchase and sales for each scheduling period within a day.

[0204] Compared to day-ahead scheduling, intraday scheduling is closer to the actual operating time of the microgrid. Intraday predicted power data is more accurate than day-ahead predicted power data, so the intraday scheduling results obtained based on this are also more accurate.

[0205] Step S105: Obtain real-time power data of the microgrid.

[0206] Real-time dispatch refers to the real-time scheduling of the microgrid's operation plan based on the intraday dispatch results and the real-time power demand and supply situation, in order to ensure the safe and efficient operation of the microgrid.

[0207] Real-time power data refers to the power data of electrical equipment in a microgrid that is collected in real time. It may include, but is not limited to, the power generation of photovoltaic equipment (referred to as real-time photovoltaic power generation), the power of electrical load equipment (referred to as real-time electrical load power), the charging and discharging power of energy storage equipment (referred to as real-time energy storage charging and discharging power), and the power purchased and sold by the microgrid to the grid (referred to as real-time grid power purchase and sale).

[0208] Step S106: Based on real-time power data and intraday scheduling results, perform real-time scheduling of the microgrid to obtain the real-time scheduling results of the microgrid.

[0209] Real-time dispatch results may include, but are not limited to, the charging and discharging power of energy storage devices in the microgrid (denoted as real-time dispatch energy storage charging and discharging power) and the power purchased and sold by the microgrid to the grid (denoted as real-time dispatch grid power purchased and sold).

[0210] In this embodiment, the dispatching result deviation of the microgrid can be determined based on the intraday dispatched energy storage charging and discharging power, the intraday dispatched grid power purchase and sale power, the real-time dispatched energy storage charging and discharging power, and the real-time dispatched grid power purchase and sale power. Based on the constraints of the microgrid, the real-time dispatched energy storage charging and discharging power and the real-time dispatched grid power purchase and sale power are solved with the objective function of minimizing the dispatching result deviation, thereby obtaining the real-time dispatched energy storage charging and discharging power and the real-time dispatched grid power purchase and sale power.

[0211] Specifically, the energy storage dispatch deviation of the microgrid can be determined based on the real-time dispatched energy storage charging and discharging power and the intraday dispatched energy storage charging and discharging power. The specific calculation method for the energy storage dispatch deviation of the microgrid can be flexibly set according to the actual situation, and may include, but is not limited to, calculating the absolute value of the difference between the real-time dispatched energy storage charging and discharging power and the intraday dispatched energy storage charging and discharging power, as well as calculating the square of the difference between the real-time dispatched energy storage charging and discharging power and the intraday dispatched energy storage charging and discharging power, etc.

[0212] As an example, the absolute value of the difference between the real-time dispatched energy storage charging and discharging power and the intraday dispatched energy storage charging and discharging power can be taken as the energy storage dispatch deviation of the microgrid, as shown in the following formula:

[0213]

[0214] in, To schedule the charging and discharging power of energy storage in real time, To and The intraday dispatch power of energy storage charging and discharging during the same period, D BTThis refers to the energy storage dispatch deviation of the microgrid.

[0215] The grid dispatch deviation of a microgrid can be determined based on the real-time dispatch power purchase and sale and the intraday dispatch power purchase and sale. The specific calculation method for the energy storage dispatch deviation of a microgrid can be flexibly set according to the actual situation, and may include, but is not limited to, calculating the absolute value of the difference between the real-time dispatch power purchase and sale and the intraday dispatch power purchase and sale, as well as calculating the square of the difference between the real-time dispatch power purchase and sale and the intraday dispatch power purchase and sale, etc.

[0216] As an example, the absolute value of the difference between the real-time dispatched power purchase and sale and the intraday dispatched power purchase and sale can be taken as the grid dispatch deviation of the microgrid, as shown in the following formula:

[0217]

[0218] in, To enable real-time scheduling of power purchase and sale on the power grid, To and The intraday power purchase and sale volume of the power grid during the same period, D G This refers to the grid dispatch deviation of the microgrid.

[0219] The dispatching deviation of the microgrid can be determined based on the energy storage dispatching deviation and the grid dispatching deviation. Specifically, the energy storage dispatching deviation can be weighted according to the first weight corresponding to the energy storage dispatching deviation to obtain the weighted energy storage dispatching deviation, and the grid dispatching deviation can be weighted according to the second weight corresponding to the grid dispatching deviation to obtain the weighted grid dispatching deviation. The dispatching deviation of the microgrid can then be determined based on the weighted energy storage dispatching deviation and the weighted grid dispatching deviation, as shown in the following formula:

[0220] D realtime =d G ·D G +d BT ·D BT

[0221] Where, d BT As the first weight corresponding to the energy storage dispatch deviation, d G As the second weight corresponding to the grid dispatch deviation, the specific values ​​of both can be flexibly set according to the actual situation, D realtime This represents the dispatching deviation of the microgrid. Based on the above formula, the energy storage dispatching deviation and the grid dispatching deviation can be weighted according to their corresponding weights, thereby allowing for flexible adjustment of their roles in the final dispatching deviation.

[0222] Through the above process, we can comprehensively consider the deviations of energy storage dispatch and grid dispatch, and on this basis, we can obtain a more comprehensive and accurate dispatch result deviation.

[0223] The constraints still need to consider the operating conditions of each device to limit the power adjustment. The energy storage battery charging and discharging equipment model must meet the following constraints:

[0224]

[0225] like but

[0226] like but

[0227] in, For real-time energy storage charging and discharging power, For real-time state of charge, This is the preset lower limit for energy storage power adjustment. The preset upper limit for energy storage power adjustment can be flexibly set according to actual conditions.

[0228] The power grid model must meet the following constraints:

[0229]

[0230]

[0231] in, For real-time power purchase and sale on the power grid, The preset lower limit for grid power adjustment. These are the preset upper limits for grid power adjustment; the specific values ​​of both can be flexibly set according to actual conditions.

[0232] In addition, the above-mentioned device models must also meet the following system power balance constraints:

[0233]

[0234] in, Real-time photovoltaic power generation. This represents the real-time electrical load power.

[0235] Based on the constraints of the microgrid, and with minimizing the scheduling result deviation as the objective function, the real-time scheduling energy storage charging and discharging power and the real-time scheduling grid power purchase and sale power are solved, thus obtaining the real-time scheduling energy storage charging and discharging power and the real-time scheduling grid power purchase and sale power.

[0236] Using real-time photovoltaic power generation, real-time electrical load, real-time energy storage charging and discharging power, real-time grid power purchase and sale, intraday dispatched energy storage charging and discharging power, and intraday dispatched grid power purchase and sale as input parameters, and real-time dispatched energy storage charging and discharging power and real-time dispatched grid power purchase and sale as decision variables, and based on the aforementioned constraints, minimizing the dispatch result deviation as the objective function, a corresponding mathematical programming model can be constructed. This model is denoted as the real-time dispatch model, and solving it yields the corresponding real-time dispatch results. Through this process, minimizing the dispatch result deviation between real-time and intraday dispatch results can be achieved during real-time dispatch, allowing global information on a larger time scale to play a role in the real-time dispatch process. Furthermore, intraday dispatch based on the constraints and objective function of the microgrid can yield more accurate real-time dispatch results.

[0237] like Figure 6 As shown, real-time scheduling operates on a rolling basis according to the real-time scheduling cycle. The real-time scheduling cycle can be flexibly set according to the actual situation. Generally, it is advisable to set it to 1 minute to 5 minutes, or it can be set to other values. The duration of a single real-time scheduling can be regarded as a single moment.

[0238] Taking a real-time scheduling cycle of 3 minutes as an example, real-time scheduling can be rolled out 480 times a day, and each real-time scheduling can obtain the real-time scheduling result within a real-time scheduling cycle. Figure 7 The diagram shows the real-time scheduling results of the rolling operation on a cycle, which displays the photovoltaic power generation, electrical load power, energy storage charging and discharging power, and grid power purchase and sale power for each real-time scheduling cycle within a day.

[0239] The aforementioned day-ahead scheduling, intraday scheduling, and real-time scheduling can be performed by electronic devices in the cloud. After receiving the real-time scheduling results of the microgrid, the electronic devices in the cloud can send them to electronic devices at the edge.

[0240] Edge-end electronic devices use the received real-time dispatch results as an operational reference to perform real-time control of the microgrid. Specifically, they can detect the stability of voltage and frequency within the microgrid and control and adjust the output of controllable equipment in real time, such as adjusting generator output based on real-time load demand and controlling the charging and discharging of energy storage systems. Specific implementation technologies may include, but are not limited to, Automatic Generation Control (AGC) and Automatic Voltage Control (AVC). AGC monitors real-time changes in system generation and load and automatically adjusts the power output of energy storage and generators to compensate for these changes, ensuring a match between actual load and generation capacity, thereby preventing system collapse due to load fluctuations and guaranteeing continuous power supply to the microgrid. AVC monitors voltage levels within the microgrid and automatically adjusts reactive power distribution to ensure voltage fluctuations remain within a suitable range, improving power quality. Based on real-time dispatch results and equipment operation information, edge-end electronic devices, with the primary objective of microgrid voltage and frequency stability, issue equipment control commands to end-level electronic devices, thereby executing real-time dispatch results while maintaining the safe and stable operation of the microgrid. The real-time control cycle can be flexibly set according to the actual situation. It is generally advisable to set it to 1 to 60 seconds, or it can be set to other values. The duration of a single real-time control can be regarded as a single moment.

[0241] The terminal's electronic devices can execute device control commands issued by edge-end electronic devices to achieve final device control. The specific control method depends on the device type. Simultaneously, it is responsible for real-time collection of energy data, environmental parameters, and other device operation information from the microgrid, and uploading this information to the edge or cloud for processing and analysis. The real-time control cycle can be flexibly set according to actual conditions, generally preferably in the millisecond range, but other values ​​can also be used. The duration of a single device control operation can be considered a single moment.

[0242] Figure 8The diagram illustrates the cloud-edge-device system architecture used for microgrid scheduling and control in this embodiment of the application. As shown, cloud-based electronic devices sequentially perform day-ahead scheduling, intraday scheduling, and real-time scheduling. Day-ahead scheduling uses the microgrid's day-ahead predicted power data and time-of-use pricing as input, and solves for the day-ahead scheduling result based on a day-ahead optimized scheduling model. Intraday scheduling uses the microgrid's intraday predicted power data, day-ahead scheduling result, and time-of-use pricing as input, and solves for the intraday scheduling result based on an intraday optimized scheduling model. Real-time scheduling uses the microgrid's real-time power data and intraday scheduling result as input, and solves for the real-time scheduling result based on a real-time scheduling model. Edge-based electronic devices perform real-time control, using the received real-time scheduling result as a reference, aiming for stable voltage and frequency in the microgrid, and generating device control commands. Terminal-based electronic devices execute the device control commands, controlling the devices to achieve controlled operation, and acquiring real-time device operation information. Placing day-ahead, intraday, and real-time scheduling in the cloud enables dynamic adjustment of resource allocation based on actual needs, adapting to microgrid scheduling scenarios of varying scales and complexities. Placing real-time control at the edge significantly reduces data transmission latency, allowing scheduling commands to be rapidly transmitted to terminal devices, thus improving scheduling accuracy and efficiency. Upon receiving control commands, each terminal device can quickly collect data and process it.

[0243] By employing a system architecture that integrates cloud-based scheduling, edge control, and terminal execution, the overall scheduling and control of the energy management system can be considered. This allows the microgrid to issue control commands based on its comprehensive operational status and scheduling plan under uncertain operating conditions. Combined with system operation control strategies, this enables coordinated and efficient operation at all levels of the system. Specifically, cloud-based scheduling formulates macro-level scheduling plans, grasping global information to achieve economic efficiency; edge control, based on the scheduling plan and the microgrid's voltage and frequency conditions, issues control commands to maintain stable system operation and ensure power quality; and terminal execution is implemented at each device, responsible for executing the control commands issued by the edge. The functionality of these three main parts in the integrated architecture enables the economical and stable operation of the microgrid. Moreover, this system architecture decouples scheduling and control functions, allowing for clearer division of labor in the algorithm system, purer goal setting, and ensuring that each part achieves its own objective to achieve safe, efficient, and economical system operation. It also improves the flexibility of microgrid system expansion.

[0244] In summary, the embodiments of this application can utilize the energy storage charging and discharging power scheduled before the day during intraday scheduling, thereby enabling global information on a larger time scale to play a role in intraday scheduling. Based on this, the goal of minimizing the scheduling result deviation between real-time scheduling results and intraday scheduling results can be achieved during real-time scheduling, thus enabling global information on a larger time scale to also play a role in real-time scheduling. This helps to alleviate the situation where the final scheduling result falls into a local optimum and can effectively improve the overall scheduling effect.

[0245] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0246] A microgrid scheduling method corresponding to the above embodiment, Figure 9 This paper shows a structural diagram of an embodiment of a microgrid dispatching device provided in this application.

[0247] In this embodiment, a microgrid dispatching device may include:

[0248] The first acquisition module 901 is used to acquire the day-ahead forecast power data and time-of-use electricity price of the microgrid;

[0249] The day-ahead scheduling module 902 is used to perform day-ahead scheduling of the microgrid based on the day-ahead predicted power data and time-of-use electricity price, and obtain the day-ahead scheduling result of the microgrid;

[0250] The second acquisition module 903 is used to acquire intraday predicted power data of the microgrid;

[0251] The intraday dispatch module 904 is used to perform intraday dispatch on the microgrid based on intraday predicted power data, day-ahead dispatch results and time-of-use electricity prices, and obtain the intraday dispatch results of the microgrid; wherein, the intraday dispatch energy storage charging and discharging power in the intraday dispatch results is consistent with the day-ahead dispatch energy storage charging and discharging power in the day-ahead dispatch results;

[0252] The third acquisition module 905 is used to acquire real-time power data of the microgrid;

[0253] The real-time scheduling module 906 is used to perform real-time scheduling of the microgrid based on real-time power data and intraday scheduling results, and obtain the real-time scheduling results of the microgrid; the objective of real-time scheduling is to minimize the scheduling result deviation between the real-time scheduling results and the intraday scheduling results.

[0254] The aforementioned device allows the storage charging and discharging power scheduled before the day to be used during intraday scheduling, thus enabling global information on a larger time scale to play a role in intraday scheduling. Based on this, the goal is to minimize the scheduling result deviation between real-time scheduling and intraday scheduling during real-time scheduling, thereby enabling global information on a larger time scale to also play a role in real-time scheduling. This helps to alleviate the situation where the final scheduling result falls into a local optimum and can effectively improve the overall scheduling effect.

[0255] In one specific implementation of this application embodiment, the day-ahead dispatch result may include the day-ahead dispatch energy storage charging and discharging power and the day-ahead dispatch grid power purchase and sale power;

[0256] The day-ahead scheduling module may include:

[0257] The day-ahead dispatch total cost determination submodule is used to determine the day-ahead dispatch total cost of the microgrid based on day-ahead forecast power data, time-of-use electricity price, day-ahead dispatch energy storage charging and discharging power, and day-ahead dispatch grid power purchase and sale.

[0258] The day-ahead dispatch solution submodule is used to solve for the day-ahead dispatch energy storage charging and discharging power and the day-ahead dispatch grid purchase and sale power based on the constraints of the microgrid and with the objective function of minimizing the total day-ahead dispatch cost.

[0259] By using the aforementioned device, more accurate day-ahead scheduling results can be obtained by performing day-ahead scheduling based on the constraints and objective function of the microgrid.

[0260] In one specific implementation of this application embodiment, the day-ahead scheduling total cost determination submodule may include:

[0261] The day-ahead dispatch photovoltaic power generation cost determination unit is used to determine the day-ahead dispatch photovoltaic power generation cost of the microgrid based on the day-ahead predicted power data.

[0262] The day-ahead dispatching grid power purchase and sale cost determination unit is used to determine the day-ahead dispatching grid power purchase and sale cost of the microgrid based on the day-ahead dispatching grid power purchase and sale and the time-of-use electricity price;

[0263] The day-ahead dispatch total cost determination unit is used to determine the day-ahead dispatch energy storage charging and discharging cost of the microgrid based on the day-ahead dispatch energy storage charging and discharging power.

[0264] The total day-ahead dispatch cost of the microgrid is determined based on the day-ahead dispatch cost of photovoltaic power generation, the day-ahead dispatch cost of purchasing and selling electricity from the grid, and the day-ahead dispatch cost of charging and discharging energy storage.

[0265] The aforementioned device allows for a comprehensive consideration of various factors, including photovoltaic power generation costs, grid power purchase and sale costs, and energy storage charging and discharging costs. Based on this, a more comprehensive and accurate total day-ahead dispatch cost can be obtained.

[0266] In one specific implementation of this application embodiment, the intraday dispatch result may include the intraday dispatched energy storage charging and discharging power and the intraday dispatched grid power purchase and sale power;

[0267] The intraday scheduling module may include:

[0268] The energy storage charging and discharging power determination submodule is used to use the day-ahead dispatched energy storage charging and discharging power as the day-intraday dispatched energy storage charging and discharging power.

[0269] The intraday dispatch total cost determination submodule is used to determine the intraday dispatch total cost of the microgrid based on intraday predicted power data, time-of-use electricity price, intraday dispatch energy storage charging and discharging power, and intraday dispatch grid power purchase and sale.

[0270] The intraday scheduling solution submodule is used to solve for the intraday power purchase and sale of the grid based on the constraints of the microgrid, with the objective function of minimizing the total intraday scheduling cost, and obtain the intraday power purchase and sale of the grid.

[0271] The aforementioned device allows the energy storage charging and discharging power scheduled a day earlier to be used during intraday scheduling, thus enabling global information on a larger time scale to play a role in intraday scheduling. Furthermore, intraday scheduling based on the constraints and objective function of the microgrid can yield more accurate intraday scheduling results.

[0272] In one specific implementation of this application embodiment, the intraday scheduling total cost determination submodule may include:

[0273] The intraday dispatch photovoltaic power generation cost determination unit is used to determine the intraday dispatch photovoltaic power generation cost of the microgrid based on intraday predicted power data.

[0274] The intraday dispatch grid power purchase and sale cost determination unit is used to determine the intraday dispatch grid power purchase and sale cost of the microgrid based on the intraday dispatch grid power purchase and sale and time-of-use electricity price;

[0275] The intraday dispatch energy storage charging and discharging cost determination unit is used to determine the intraday dispatch energy storage charging and discharging cost of the microgrid based on the intraday dispatch energy storage charging and discharging power.

[0276] The intraday dispatch total cost determination unit is used to determine the intraday dispatch total cost of the microgrid based on the intraday dispatch photovoltaic power generation cost, intraday dispatch grid power purchase and sale cost, and intraday dispatch energy storage charging and discharging cost.

[0277] The aforementioned device allows for a comprehensive consideration of various factors, including photovoltaic power generation costs, grid power purchase and sale costs, and energy storage charging and discharging costs. Based on this, a more comprehensive and accurate total daily dispatch cost can be obtained.

[0278] In one specific implementation of this application embodiment, the intraday dispatch result may include the intraday dispatched energy storage charging and discharging power and the intraday dispatched grid power purchase and sale power, and the real-time dispatch result may include the real-time dispatched energy storage charging and discharging power and the real-time dispatched grid power purchase and sale power.

[0279] The real-time scheduling module may include:

[0280] The dispatch result deviation determination submodule is used to determine the dispatch result deviation of the microgrid based on the intraday dispatched energy storage charging and discharging power, intraday dispatched grid power purchase and sale power, real-time dispatched energy storage charging and discharging power, and real-time dispatched grid power purchase and sale power.

[0281] The real-time scheduling solution submodule is used to solve for the real-time scheduling energy storage charging and discharging power and the real-time scheduling grid power purchase and sale power based on the constraints of the microgrid and with the objective function of minimizing the scheduling result deviation.

[0282] With the above-mentioned device, the goal is to minimize the deviation between the real-time scheduling result and the intraday scheduling result during the real-time scheduling process. This allows global information on a larger time scale to play a role in the real-time scheduling process. Moreover, intraday scheduling based on the constraints and objective function of the microgrid can yield more accurate real-time scheduling results.

[0283] In one specific implementation of this application embodiment, the scheduling result deviation determination submodule may include:

[0284] The energy storage dispatch deviation determination unit is used to determine the energy storage dispatch deviation of the microgrid based on the real-time dispatch energy storage charging and discharging power and the intraday dispatch energy storage charging and discharging power.

[0285] The grid dispatch deviation determination unit is used to determine the grid dispatch deviation of the microgrid based on the real-time dispatch grid power purchase and sale power and the intraday dispatch grid power purchase and sale power.

[0286] The dispatch result deviation determination unit is used to determine the dispatch result deviation of the microgrid based on the energy storage dispatch deviation and the grid dispatch deviation.

[0287] The aforementioned device allows for comprehensive consideration of factors such as energy storage dispatch deviation and grid dispatch deviation, resulting in a more comprehensive and accurate dispatch result deviation.

[0288] In one specific implementation of this application embodiment, the scheduling result deviation determination unit may include:

[0289] The first weighting sub-unit is used to weight the energy storage scheduling deviation according to the first weight corresponding to the energy storage scheduling deviation, so as to obtain the weighted energy storage scheduling deviation.

[0290] The second weighting subunit is used to weight the power grid dispatching deviation according to the second weight corresponding to the power grid dispatching deviation, so as to obtain the weighted power grid dispatching deviation.

[0291] The dispatch result deviation determination subunit is used to determine the dispatch result deviation of the microgrid based on the weighted energy storage dispatch deviation and the weighted grid dispatch deviation.

[0292] The aforementioned device allows for the weighting of energy storage dispatch deviations and grid dispatch deviations according to their respective weights, thereby enabling flexible adjustment of their roles in the final dispatch result deviation.

[0293] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the devices, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0294] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0295] Figure 10 A schematic block diagram of an electronic device provided in an embodiment of this application is shown. For ease of explanation, only the parts related to the embodiment of this application are shown.

[0296] like Figure 10 As shown, the electronic device 10 of this embodiment includes: a processor 100, a memory 101, and a computer program 102 stored in the memory 101 and executable on the processor 100. When the processor 100 executes the computer program 102, it implements the steps described in the various microgrid scheduling method embodiments above, for example... Figure 1 Steps S101 to S106 are shown. Alternatively, when processor 100 executes computer program 102, it implements the functions of each module / unit in the above-described device embodiments, for example... Figure 9 The functions of modules 901 to 906 are shown.

[0297] For example, computer program 102 may be divided into one or more modules / units, one or more of which are stored in memory 101 and executed by processor 100 to complete this application. One or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of computer program 102 in electronic device 10.

[0298] Electronic device 10 may include, but is not limited to, computing devices such as desktop computers, laptops, handheld computers, and servers. Those skilled in the art will understand that... Figure 10 This is merely an example of electronic device 10 and does not constitute a limitation on electronic device 10. It may include more or fewer components than shown, or combine certain components, or different components. For example, electronic device 10 may also include input / output devices, network access devices, buses, etc.

[0299] The processor 100 can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0300] The memory 101 can be an internal storage unit of the electronic device 10, such as a hard disk or RAM of the electronic device 10. The memory 101 can also be an external storage device of the electronic device 10, such as a plug-in hard disk, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the electronic device 10. Furthermore, the memory 101 can include both internal and external storage units of the electronic device 10. The memory 101 is used to store computer programs and other programs and data required by the electronic device 10. The memory 101 can also be used to temporarily store data that has been output or will be output.

[0301] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0302] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0303] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0304] In the embodiments provided in this application, it should be understood that the disclosed devices / electronic devices and methods can be implemented in other ways. For example, the device / electronic device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0305] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0306] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0307] If an integrated module / unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable storage medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. It should be noted that the content included in the computer-readable storage medium can be appropriately added or removed according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, the computer-readable storage medium does not include electrical carrier signals and telecommunication signals.

[0308] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A microgrid dispatching method, characterized in that, include: Obtain day-ahead forecast power data and time-of-use electricity prices for microgrids; Based on the day-ahead predicted power data and the time-of-use electricity price, day-ahead scheduling is performed on the microgrid to obtain the day-ahead scheduling result of the microgrid; Obtain the intraday predicted power data of the microgrid; Based on the intraday predicted power data, the day-ahead scheduling results, and the time-of-use electricity price, the microgrid is scheduled intraday to obtain the intraday scheduling results of the microgrid; wherein, the intraday scheduling energy storage charging and discharging power in the intraday scheduling results is consistent with the day-ahead scheduling energy storage charging and discharging power in the day-ahead scheduling results. Obtain the real-time power data of the microgrid; Based on the real-time power data and the intraday scheduling results, the microgrid is scheduled in real time to obtain the real-time scheduling results of the microgrid; wherein, the objective of real-time scheduling is to minimize the scheduling result deviation between the real-time scheduling results and the intraday scheduling results.

2. The microgrid dispatching method according to claim 1, characterized in that, The day-ahead dispatch results include the day-ahead dispatch energy storage charging and discharging power and the day-ahead dispatch grid power purchase and sale power. The step of performing day-ahead scheduling on the microgrid based on the day-ahead predicted power data and the time-of-use electricity price to obtain the day-ahead scheduling result of the microgrid includes: The total daytime dispatch cost of the microgrid is determined based on the daytime forecast power data, the time-of-use electricity price, the daytime dispatched energy storage charging and discharging power, and the daytime dispatched grid power purchase and sale power. Based on the constraints of the microgrid, the day-ahead dispatching energy storage charging and discharging power and the day-ahead dispatching grid power purchase and sale power are solved with the objective function of minimizing the total day-ahead dispatching cost.

3. The microgrid dispatching method according to claim 2, characterized in that, The determination of the total day-ahead dispatch cost of the microgrid based on the day-ahead predicted power data, the time-of-use tariff, the day-ahead dispatched energy storage charging and discharging power, and the day-ahead dispatched grid power purchase and sale includes: Based on the day-ahead predicted power data, determine the day-ahead dispatch cost of photovoltaic power generation for the microgrid; The day-ahead dispatch power purchase and sale cost of the microgrid is determined based on the day-ahead dispatch power purchase and sale and the time-of-use electricity price. The day-ahead dispatch energy storage charging and discharging cost of the microgrid is determined based on the day-ahead dispatch energy storage charging and discharging power. The total day-ahead dispatch cost of the microgrid is determined based on the day-ahead dispatch cost of photovoltaic power generation, the day-ahead dispatch cost of electricity purchase and sale from the grid, and the day-ahead dispatch cost of energy storage charging and discharging.

4. The microgrid dispatching method according to any one of claims 1 to 3, characterized in that, The intraday dispatch results include intraday dispatched energy storage charging and discharging power and intraday dispatched grid power purchase and sale; The step of performing intraday scheduling on the microgrid based on the intraday predicted power data, the day-ahead scheduling results, and the time-of-use electricity price to obtain the intraday scheduling results of the microgrid includes: The day-ahead energy storage charging and discharging power is used as the intraday energy storage charging and discharging power. The total daily dispatch cost of the microgrid is determined based on the intraday predicted power data, the time-of-use electricity price, the intraday dispatched energy storage charging and discharging power, and the intraday dispatched grid power purchase and sale. Based on the constraints of the microgrid, the power purchased and sold by the intraday dispatching grid is solved with the objective function of minimizing the total intraday dispatching cost, and the power purchased and sold by the intraday dispatching grid is obtained.

5. The microgrid dispatching method according to claim 4, characterized in that, The determination of the total daily dispatch cost of the microgrid based on the intraday predicted power data, the time-of-use electricity price, the intraday dispatched energy storage charging and discharging power, and the intraday dispatched grid power purchase and sale includes: Based on the intraday predicted power data, determine the intraday dispatch cost of photovoltaic power generation for the microgrid; The intraday dispatch power purchase and sale cost of the microgrid is determined based on the intraday dispatch power purchase and sale and the time-of-use electricity price. The intraday dispatch energy storage charging and discharging cost of the microgrid is determined based on the intraday dispatch energy storage charging and discharging power. The total daily dispatch cost of the microgrid is determined based on the daily dispatch cost of photovoltaic power generation, the daily dispatch cost of grid power purchase and sale, and the daily dispatch cost of energy storage charging and discharging.

6. The microgrid dispatching method according to any one of claims 1 to 5, characterized in that, The intraday dispatch results include intraday dispatched energy storage charging and discharging power and intraday dispatched grid power purchase and sale; the real-time dispatch results include real-time dispatched energy storage charging and discharging power and real-time dispatched grid power purchase and sale. The step of performing real-time scheduling on the microgrid based on the real-time power data and the intraday scheduling results to obtain the real-time scheduling results of the microgrid includes: The deviation of the microgrid's dispatch result is determined based on the intraday dispatched energy storage charging and discharging power, the intraday dispatched grid power purchase and sale power, the real-time dispatched energy storage charging and discharging power, and the real-time dispatched grid power purchase and sale power. Based on the constraints of the microgrid, the real-time dispatched energy storage charging and discharging power and the real-time dispatched grid power purchase and sale power are solved with the objective function of minimizing the dispatch result deviation, thus obtaining the real-time dispatched energy storage charging and discharging power and the real-time dispatched grid power purchase and sale power.

7. The microgrid dispatching method according to claim 6, characterized in that, The step of determining the dispatch result deviation of the microgrid based on the intraday dispatched energy storage charging and discharging power, the intraday dispatched grid power purchase and sale power, the real-time dispatched energy storage charging and discharging power, and the real-time dispatched grid power purchase and sale power includes: The energy storage scheduling deviation of the microgrid is determined based on the real-time scheduled energy storage charging and discharging power and the intraday scheduled energy storage charging and discharging power. The grid dispatch deviation of the microgrid is determined based on the real-time dispatch power purchase and sale power and the intraday dispatch power. The scheduling result deviation of the microgrid is determined based on the energy storage scheduling deviation and the power grid scheduling deviation.

8. The microgrid dispatching method according to claim 7, characterized in that, The step of determining the dispatch result deviation of the microgrid based on the energy storage dispatch deviation and the grid dispatch deviation includes: The energy storage scheduling deviation is weighted according to the first weight corresponding to the energy storage scheduling deviation to obtain the weighted energy storage scheduling deviation. The power grid dispatch deviation is weighted according to the second weight corresponding to the power grid dispatch deviation to obtain the weighted power grid dispatch deviation. The scheduling result deviation of the microgrid is determined based on the weighted energy storage scheduling deviation and the weighted grid scheduling deviation.

9. A microgrid dispatching device, characterized in that, include: The first acquisition module is used to acquire the day-ahead forecast power data and time-of-use electricity price of the microgrid; The day-ahead scheduling module is used to perform day-ahead scheduling of the microgrid based on the day-ahead predicted power data and time-of-use electricity price, and obtain the day-ahead scheduling results of the microgrid; The second acquisition module is used to acquire intraday predicted power data of the microgrid; The intraday dispatch module is used to perform intraday dispatch of the microgrid based on intraday predicted power data, day-ahead dispatch results, and time-of-use electricity prices, and obtain the intraday dispatch results of the microgrid; wherein, the intraday dispatch energy storage charging and discharging power in the intraday dispatch results is consistent with the day-ahead dispatch energy storage charging and discharging power in the day-ahead dispatch results; The third acquisition module is used to acquire real-time power data of the microgrid; The real-time scheduling module is used to perform real-time scheduling of the microgrid based on real-time power data and intraday scheduling results, and obtain the real-time scheduling results of the microgrid. The objective of real-time scheduling is to minimize the scheduling result deviation between the real-time scheduling results and the intraday scheduling results.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements the steps of the microgrid scheduling method as described in any one of claims 1 to 8.

11. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the microgrid scheduling method as described in any one of claims 1 to 8.

12. A computer program product, comprising a computer program, characterized in that, When the computer program is run, the microgrid scheduling method as described in any one of claims 1 to 8 is executed.

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