Online simulation verification method and device for source network load storage collaborative optimization scheduling

Abstract

The invention discloses an on-line simulation verification method and device for source network load storage collaborative optimization scheduling, and relates to the technical field of simulation verification processing, and the method comprises the steps: carrying out the simulation of each regulation and control time period of a scheduling plan of a source network load storage system through an on-line simulation system; the on-line simulation system is constructed by a thermal power simulation module, a wind power simulation module, a photovoltaic power generation simulation module and an energy storage system simulation module in the micro-grid, the real-time performance of the on-line simulation system is optimized by adopting a model order reduction mode, and network operation state information is evaluated through a scheduling plan evaluation index system. The scheduling plan evaluation index system considers the updating frequency of the scheduling plan, optimizes the real-time performance of the simulation verification process, and evaluates the scheduling plan effect through the scheduling plan evaluation index system. Therefore, the purposes of optimizing the real-time performance of online simulation verification in the online simulation verification process of the source network load storage collaborative optimization scheduling and evaluating the scheduling plan effect are achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of simulation verification processing, more particularly, to an online simulation verification method and device for source-grid-load-storage collaborative optimization scheduling. BACKGROUND

[0002] Source-grid-load-storage collaborative optimization scheduling is an energy management technology, which aims to improve the consumption capacity of new energy, enhance the stability of the power grid, and reduce the overall energy cost and carbon emissions by coordinating the four core links of power supply (source), power grid (grid), load (load), and energy storage (storage) in the power system.

[0003] In the existing source-grid-load-storage collaborative optimization scheduling, the update time of the scheduling plan (i.e., the time interval between each two generated scheduling curves) may be short, as low as minutes / seconds, which leads to the online simulation verification of source-grid-load-storage collaborative optimization scheduling being unable to respond quickly, resulting in poor real-time performance and the inability to evaluate the scheduling plan effect.

[0004] Therefore, how to optimize the real-time performance of online simulation verification in the process of online simulation verification of source-grid-load-storage collaborative optimization scheduling and how to evaluate the scheduling plan effect are problems that need to be solved urgently. SUMMARY

[0005] Therefore, the present application discloses an online simulation verification method and device for source-grid-load-storage collaborative optimization scheduling, aiming to optimize the real-time performance of online simulation verification in the process of online simulation verification of source-grid-load-storage collaborative optimization scheduling and to evaluate the scheduling plan effect.

[0006] In order to achieve the above-mentioned purpose, the disclosed technical solution is as follows:

[0007] The first aspect of the present application discloses an online simulation verification method for source-grid-load-storage collaborative optimization scheduling, which comprises:

[0008] obtaining a source-grid-load-storage system scheduling plan;

[0009] simulating each control period of the source-grid-load-storage system scheduling plan by an online simulation system to obtain a simulation result; wherein the online simulation system is at least optimized and constructed by a thermal power simulation module, a wind power simulation module, a photovoltaic power generation simulation module, and a storage system simulation module in a microgrid;

[0010] performing power flow calculation on the microgrid network according to the simulation result, each load node, each voltage control node, and the balance node to obtain network operation state information of each control period in the scheduling plan;

[0011] The network operation state information is evaluated by a dispatch plan evaluation index system to complete the process of online simulation verification of source network load storage collaborative optimization dispatch.

[0012] Preferably, the source network load storage system dispatch plan includes:

[0013] The source network load storage system dispatch plan that meets the preset dispatch condition is obtained from the dispatch platform, wherein the preset dispatch condition is determined by the dispatch control time interval of the day-ahead plan, the total length of the intra-day plan, and the update frequency of the intra-day plan; the source network load storage system dispatch plan at least includes the thermal power generation dispatch plan, the wind power generation dispatch plan, the photovoltaic power generation dispatch plan, the energy storage system charging and discharging plan, the electricity consumption plan of the adjustable load, and the predicted power of the load other than the adjustable load, wherein the predicted power of the load other than the adjustable load at least includes the active power and the reactive power.

[0014] Preferably, the simulation result at least includes the thermal power simulation power information, the wind power simulation power information, the photovoltaic power simulation power information, and the energy storage simulation power information, wherein the simulation of each control period of the source network load storage system dispatch plan is performed by the online simulation system to obtain the simulation result, including:

[0015] The power instruction is obtained from the source network load storage system dispatch plan.

[0016] The update frequency of the intra-day plan is determined.

[0017] The module type of the thermal power simulation module, the wind power simulation module, the photovoltaic power simulation module, and the energy storage system simulation module of the micro-grid in the online simulation system is determined according to the update frequency, wherein the module type at least includes the reduced order module or the non-reduced order module.

[0018] The thermal power simulation module, the wind power simulation module, the photovoltaic power simulation module, and the energy storage system simulation module of the determined module type are controlled to operate according to the power instruction.

[0019] The corresponding simulation of each control period of the source network load storage system dispatch plan is performed by the operating modules to obtain the thermal power simulation power information, the wind power simulation power information, the photovoltaic power simulation power information, and the energy storage simulation power information.

[0020] Preferably, the execution process of the thermal power simulation module includes:

[0021] When the coordinated control system in the thermal power simulation module receives the power instruction and the frequency deviation, the main steam valve opening degree of the steam turbine and the boiler steam quantity generated by the boiler are calculated by the power instruction and the frequency deviation, wherein the frequency deviation is the deviation between the actual output frequency of the thermal power generator and the target frequency.

[0022] The steam flow into the steam turbine and the output power of the steam turbine are changed by the coordinated control system, the main steam valve opening degree of the steam turbine and the amount of boiler steam generated by the boiler, so that the generator outputs the thermal power simulation power information according to the thermal power simulation target in the source-grid-load-storage system scheduling plan, and the thermal power simulation power information is sent to the micro-grid.

[0023] Preferably, the execution process of the wind power simulation module comprises:

[0024] When the wind power simulation module receives the wind power prediction power in the source-grid-load-storage system scheduling plan and the meteorological prediction wind speed from the meteorological center, if the wind power prediction power is greater than 0 and less than the rated power of the wind turbine generator, the prediction wind speed is calculated according to the preset wind speed calculation formula;

[0025] If the wind power prediction power is equal to the rated power of the wind turbine generator, and the meteorological prediction wind speed at the current time is less than the rated wind speed of the wind turbine, the rated wind speed of the wind turbine is determined as the prediction wind speed;

[0026] If the wind power prediction power is equal to the rated power of the wind turbine generator, and the meteorological prediction wind speed is greater than the cut-out wind speed, the cut-out wind speed of the wind turbine is determined as the prediction wind speed;

[0027] If the wind power prediction power is equal to 0, the meteorological prediction wind speed at the current time is greater than the cut-in wind speed of the wind turbine and less than the cut-out wind speed of the wind turbine, the cut-in wind speed of the wind turbine is determined as the prediction wind speed;

[0028] If the prediction wind speed is less than or equal to the rated wind speed of the wind turbine, the pitch adjustment control system in the wind power simulation module stops working;

[0029] If the prediction wind speed is greater than the rated wind speed of the wind turbine, the pitch adjustment control system in the wind power simulation module adjusts the pitch angle to keep the actual speed of the wind turbine consistent with the rated wind speed of the wind turbine, ensures that the output power of the generator is consistent with the rated power of the wind turbine generator, and determines the output power of the generator as the wind power simulation power information.

[0030] Preferably, the execution process of the wind power simulation module further comprises:

[0031] The generator output voltage of the generator is obtained;

[0032] If the generator output voltage is less than the grid-connected voltage, it is determined that the actual wind turbine being simulated has a boost module;

[0033] The generator output voltage is rectified and inverted by the boost module.

[0034] Preferably, the execution process of the wind power simulation module comprises:

[0035] when the photovoltaic power generation simulation module receives the photovoltaic power prediction in the source-grid-load-storage system scheduling plan, the photovoltaic power prediction is converted into electric energy by a photovoltaic array in the photovoltaic power generation simulation module;

[0036] the electric energy is inverted by a photovoltaic inverter, and the inverted electric energy is transmitted to the micro-grid.

[0037] Preferably, the execution process of the energy storage system simulation module comprises:

[0038] when the energy storage converter of the energy storage system simulation module receives the on-grid / off-grid command and the selection control mode command, the user grid output power is regulated and controlled by the energy storage converter, the obtained energy storage power instruction in the source-grid-load-storage system scheduling plan and the current state of charge of the energy storage battery;

[0039] The on-grid / off-grid command is a command for whether to access the public grid; the selection control mode command is a command for selecting the control mode of the AC side of the energy storage converter; and the selection control mode command at least includes power and reactive power control, constant voltage and frequency control, droop control or virtual synchronous machine control.

[0040] Preferably, the network operating state information at least includes micro-grid node voltage and line current, and the network operating state information of each regulation period in the scheduling plan is obtained by performing power flow calculation on the micro-grid network according to the simulation result, each load node, each voltage control node and the balancing node, including:

[0041] each power information in the simulation result, the power information in the adjustable load power consumption plan, the predicted power of the load other than the adjustable load and the nominal voltage corresponding to each voltage control node are taken as node given values; wherein the node given values at least include load node given values, voltage control node given values and balancing node given values;

[0042] the micro-grid node voltage and the line current of each regulation period in the scheduling plan are obtained by performing power flow calculation on the micro-grid network according to the node given values.

[0043] The second aspect of the present application discloses an online simulation verification method for source-grid-load-storage collaborative optimization scheduling, which comprises:

[0044] an acquisition unit configured to acquire a source-grid-load-storage system scheduling plan;

[0045] a simulation unit configured to simulate each regulation period of the source-grid-load-storage system scheduling plan by an online simulation system to obtain a simulation result; wherein the online simulation system is at least constructed by a thermal power simulation module, a wind power simulation module, a photovoltaic power generation simulation module and an energy storage system simulation module in a micro-grid.

[0046] a calculation unit configured to perform power flow calculation on the micro-grid network according to the simulation result, the load nodes, the voltage control nodes and the balancing nodes, to obtain network operation state information of each control period in the scheduling plan;

[0047] an evaluation unit configured to evaluate the network operation state information by using a scheduling plan evaluation index system, to complete the online simulation verification process of the source-grid-load-storage collaborative optimization scheduling.

[0048] According to the technical solution, the application discloses an online simulation verification method and device for source-grid-load-storage collaborative optimization scheduling, obtains a source-grid-load-storage system scheduling plan, simulates each control period of the source-grid-load-storage system scheduling plan by using an online simulation system, obtains a simulation result, wherein the online simulation system is constructed by at least a thermal power simulation module, a wind power simulation module, a photovoltaic power generation simulation module and an energy storage system simulation module in a micro-grid, performs power flow calculation on the micro-grid network according to the simulation result, the load nodes, the voltage control nodes and the balancing nodes, to obtain network operation state information of each control period in the scheduling plan, and evaluates the network operation state information by using a scheduling plan evaluation index system, to complete the online simulation verification process of the source-grid-load-storage collaborative optimization scheduling.

[0049] The application has the following beneficial effects: the online simulation system is constructed by at least a thermal power simulation module, a wind power simulation module, a photovoltaic power generation simulation module and an energy storage system simulation module in a micro-grid, the online simulation system is optimized in real time by using model reduction, the network operation state information is evaluated by using a scheduling plan evaluation index system, the scheduling plan evaluation index system considers the update frequency of the scheduling plan, optimizes the real time of the simulation verification process, and evaluates the scheduling plan effect by using the scheduling plan evaluation index system, so as to realize the purposes of optimizing the real time of the online simulation verification and evaluating the scheduling plan effect in the online simulation verification process of the source-grid-load-storage collaborative optimization scheduling. BRIEF DESCRIPTION OF DRAWINGS

[0050] In order to more clearly illustrate the technical solutions of the embodiments of the application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiment or prior art description. Obviously, the drawings in the following description only constitute the embodiments of the application, and those skilled in the art can obtain other drawings according to the provided drawings without any creative effort.

[0051] Figure 1 A flowchart of an online simulation verification method for source-grid-load-storage collaborative optimization scheduling disclosed by the embodiments of the application.

[0052] Figure 2 A schematic diagram of a thermal power simulation module disclosed by an embodiment of the present application;

[0053] Figure 3 A schematic diagram of a wind power simulation module disclosed by an embodiment of the present application;

[0054] Figure 4 A schematic diagram of a photovoltaic power generation simulation module disclosed by an embodiment of the present application;

[0055] Figure 5 A schematic diagram of an energy storage system simulation module disclosed by an embodiment of the present application;

[0056] Figure 6 A schematic diagram of a dispatch plan evaluation index system disclosed by an embodiment of the present application;

[0057] Figure 7 A structural schematic diagram of an online simulation verification device for source-grid-load-storage collaborative optimization dispatch disclosed by an embodiment of the present application;

[0058] Figure 8 A structural schematic diagram of an electronic device disclosed by an embodiment of the present application. DETAILED DESCRIPTION

[0059] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without any creative work fall within the protection scope of the present application.

[0060] In the present application, the term “comprises”, “comprising” or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or further includes elements inherent to such a process, method, article or device. Without more limitations, the element defined by the statement “comprises a” does not exclude the presence of another identical element in the process, method, article or device including the element.

[0061] As known from the background, in the existing source-grid-load-storage collaborative optimization dispatch, the update time of the dispatch plan can be short, as low as minute / second level, so that the online simulation verification of the source-grid-load-storage collaborative optimization dispatch cannot respond quickly, resulting in poor real-time performance.

[0062] To solve the above problems, the application discloses an online simulation verification method and device for source-network-load-storage collaborative optimization scheduling, which simulates each regulation period of the source-network-load-storage system scheduling plan through an online simulation system, the online simulation system is constructed by a thermal power simulation module, a wind power simulation module, a photovoltaic power generation simulation module and an energy storage system simulation module in a microgrid, the online simulation system real-time is optimized by using model reduction, the network operation state information is evaluated through a scheduling plan evaluation index system, the scheduling plan evaluation index system considers the update frequency of the scheduling plan, optimizes the real-time of the simulation verification process, and evaluates the scheduling plan effect through the scheduling plan evaluation index system, so as to realize the purposes of optimizing the real-time of the online simulation verification and evaluating the scheduling plan effect in the process of the online simulation verification for the source-network-load-storage collaborative optimization scheduling. The specific implementation manner is specifically explained through the following embodiments.

[0063] It should be noted that the online simulation verification method and device for source-network-load-storage collaborative optimization scheduling provided by the application can be used in the technical field of simulation verification processing, and the above is only an example and does not limit the application field of the online simulation verification method and device for source-network-load-storage collaborative optimization scheduling provided by the application.

[0064] The application scenarios of the application include but are not limited to microgrids. The microgrid refers to 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.

[0065] Reference Figure 1 As shown in the figure, the online simulation verification method for source-network-load-storage collaborative optimization scheduling disclosed by the embodiment of the application mainly includes the following steps:

[0066] S101: Obtain a source-network-load-storage system scheduling plan.

[0067] In S101, the source-network-load-storage system scheduling plan meeting the preset scheduling condition is obtained from the scheduling platform; wherein the preset scheduling condition is determined by the regulation time interval of the day-ahead plan, the total length of the day plan and the update frequency of the day plan; the source-network-load-storage system scheduling plan at least includes thermal power generation scheduling plan, wind power generation scheduling plan, photovoltaic power generation scheduling plan, energy storage system charging and discharging plan, power consumption plan of adjustable load and predicted power of load other than adjustable load, the predicted power of load other than adjustable load at least includes active power and reactive power.

[0068] It should be noted that the source network load storage system scheduling plan includes power instruction information of each simulation module. The source network load storage system scheduling plan can be controlled by a scheduling platform (such as a power grid dispatching center or a microgrid operator) and is divided into day-ahead planning and intra-day planning. The control time interval is not greater than a preset time interval, such as 15 minutes. The total duration of the day-ahead planning can be set to 24 hours (h), and the total duration of the intra-day planning can be set to 4 h and updated every 15 minutes. The preset time interval is set according to the actual situation, and the present application does not make specific limitations.

[0069] The specific content of the source network load storage system scheduling plan includes but is not limited to the start-stop schedule of each unit of thermal power, the power generation power in different time periods, the running state of each unit of wind power, the planned start-stop time, the predicted power, the running state of each inverter of photovoltaic, the planned start-stop time, the predicted power (such as thermal power prediction power, wind power prediction power, photovoltaic power prediction power, etc.), the running state of each converter of energy storage, the charging and discharging time and power, the power consumption plan of adjustable load (such as the running state of each electric vehicle charging pile, the charging time and power arrangement, the start-stop time of each air conditioner and the indoor unit set temperature value, the on-off time of each lamp, etc.), the predicted power of the remaining other loads, etc.

[0070] S102: Simulate each control period of the source network load storage system scheduling plan through an online simulation system to obtain a simulation result; wherein the online simulation system is at least optimized and constructed from a thermal power (thermal power generation) simulation module, a wind power (wind power generation) simulation module, a photovoltaic power generation simulation module and an energy storage system simulation module in the microgrid.

[0071] The online simulation system includes a thermal power simulation module, a wind power simulation module, a photovoltaic power generation simulation module and an energy storage simulation module in the microgrid.

[0072] Each control period refers to dividing the total duration of the scheduling plan into multiple equal periods, one period being a control period, which can be 15 minutes (min), 1 hour, etc., and is determined by the control plan issued by the source network load storage system scheduling plan. For example, all simulations (i.e. thermal power simulation, wind power simulation, photovoltaic power generation simulation, energy storage simulation) are performed 1 h (day-ahead scheduling) or 15 min (intra-day scheduling) before the start of the scheduling plan.

[0073] For a power generation unit that is scheduled to start normally, the power generation power or the predicted power of its scheduling plan is used as a power instruction to control the operation of the above simulation module.

[0074] The simulation result at least includes thermal power simulation power information, wind power simulation power information, photovoltaic power generation simulation power information and energy storage simulation power information.

[0075] Specifically, each regulation period of the source network load storage system scheduling plan is simulated through the online simulation system to obtain the simulation result, as shown in A1-A5.

[0076] A1: Obtain the power instruction from the source network load storage system scheduling plan.

[0077] It should be noted that the power instruction for the thermal power simulation module is the planned power given by the power system dispatch center or the micro-grid operator; the power instruction for the wind power simulation module and the photovoltaic power simulation module is the predicted power; and the power instruction for the energy storage system simulation module is the charging and discharging state and its power of each regulation period.

[0078] The predicted power includes but is not limited to wind power predicted power, photovoltaic power predicted power, etc.

[0079] A2: Determine the update frequency of the intra-day plan.

[0080] A3: Determine the module type of the thermal power simulation module, the wind power simulation module, the photovoltaic power simulation module and the energy storage system simulation module of the micro-grid in the online simulation system according to the update frequency; the model type at least includes a reduced order module or a non-reduced order module.

[0081] It should be noted that whether the simulation module is reduced order is determined by the update frequency of the intra-day plan, and a reduced order module is used when the update frequency of the intra-day plan is less than a preset time. The preset time can be 1 minute (min), 2 min, etc., and the preset time is not specifically limited in the present application.

[0082] For example, when the preset time is 1 min and the update frequency of the intra-day plan is less than 1 min, a reduced order thermal power simulation module, a reduced order wind power simulation module, a reduced order photovoltaic power simulation module and a reduced order energy storage system simulation module are used.

[0083] A4: Control the operation of the thermal power simulation module, the wind power simulation module, the photovoltaic power simulation module and the energy storage system simulation module of the module type according to the power instruction.

[0084] A5: Simulate each regulation period of the source network load storage system scheduling plan through the running modules to obtain thermal power simulation power information, wind power simulation power information, photovoltaic power simulation power information and energy storage simulation power information.

[0085] It should be noted that the regulation period is one regulation period per interval preset period, and the preset period can be 15 min, 1 hour, etc., and the preset period is determined by the above source network load storage system scheduling plan.

[0086] For example, by running the thermal power simulation module, the control period corresponding to the thermal power simulation module of the source-grid-load-storage system scheduling plan is simulated, such as 15 minutes, to obtain the thermal power simulation power information;

[0087] The wind power simulation module is used to simulate the control period corresponding to the wind power simulation module of the source-grid-load-storage system scheduling plan, such as 17 minutes, to obtain the wind power simulation power information.

[0088] The photovoltaic power generation simulation module is used to simulate the control period corresponding to the photovoltaic power generation simulation module of the source-grid-load-storage system scheduling plan, such as 1 hour, to obtain the photovoltaic power generation simulation power information.

[0089] The energy storage simulation module is used to simulate the control period corresponding to the energy storage simulation module of the source-grid-load-storage system scheduling plan, such as 1 hour, to obtain the energy storage simulation power information.

[0090] The execution process of the specific thermal power simulation module (i.e., the thermal power simulation model) is as follows: Figure 2 As shown.

[0091] Figure 2 In the simulation module, when the coordinated control system receives power commands and frequency deviations, it calculates the opening degree of the main steam valve of the steam turbine and the amount of boiler steam generated by the boiler based on the power commands and frequency deviations. The frequency deviation is the deviation between the actual output frequency of the thermal power generator and the target frequency.

[0092] By coordinating the control system, the opening of the main steam valve of the steam turbine, and the amount of boiler steam generated by the boiler, the steam flow rate entering the steam turbine and the output power of the steam turbine are changed, so that the generator outputs the thermal power simulation power information according to the thermal power simulation target in the source-grid-load-storage system scheduling plan, and sends the thermal power simulation power information to the grid (microgrid).

[0093] It should be noted that the coordinated control system calculates the opening degree of the main steam valve of the steam turbine and the amount of steam generated by the boiler based on the power command and frequency deviation, so as to change the steam flow rate entering the steam turbine, thereby changing the output power of the steam turbine, and ultimately making the generator power output according to the target.

[0094] The execution process of the specific wind power simulation module (i.e., the wind power simulation model) is as follows: Figure 3 As shown.

[0095] Figure 3 This is a simulation diagram of a single wind turbine unit. Figure 3 The predicted power comes from the dispatch platform. The predicted wind speed comes from the meteorological center. The updated predicted wind speed at different times is determined by the predicted power at that time.

[0096] Figure 3In the process, when the wind power simulation module receives the predicted wind power (P) from the source-grid-load-storage system scheduling plan and the predicted wind speed from the meteorological center, if the predicted wind power (P) is greater than 0 and less than the rated power (P) of the wind turbine generator, N The predicted wind speed (v) is calculated by reverse calculation based on the preset wind speed calculation formula. wind ).

[0097] The preset wind speed calculation formula is shown in formula (1).

[0098] (1)

[0099] in, To predict wind speed; The rated wind speed of the fan; is the wind speed at which the wind turbines enter the wind; P is the predicted power of wind power generation. If it is the total predicted power of all wind turbine units, then the predicted power generation of each unit is allocated proportionally according to the rated power of each unit. This refers to the rated power of the wind turbine.

[0100] like The forecast wind speed at that moment shall be used as the standard, and the forecast wind speed at the current moment (i.e., the forecast wind speed at the current moment when the wind power generation forecast power is equal to the rated power of the wind turbine) shall be less than the rated wind speed of the wind turbine. ), the rated wind speed of the fan (v) N () was determined as the predicted wind speed.

[0101] If the current weather forecast wind speed is greater than the cut-out wind speed, the cut-out wind speed of the wind turbine will be determined as the forecast wind speed.

[0102] If P=0, the current weather forecast wind speed is greater than the wind turbine's cut-in wind speed (v). in The cut-in wind speed is less than the fan's output wind speed, so the fan's input wind speed (v) is lower. in () was determined as the predicted wind speed.

[0103] If the predicted wind speed is less than or equal to the rated wind speed of the fan (v) N The pitch control system in the wind power simulation module stops working and does not perform pitch adjustment; the pitch angle is 0.

[0104] If the predicted wind speed is greater than the rated wind speed of the fan (v N The pitch control system in the wind power simulation module adjusts the pitch angle to keep the actual speed of the wind turbine consistent with the rated wind speed, ensuring that the generator output power matches the rated power of the wind turbine (P). N To maintain consistency, the generator output power is determined as the power information for wind power simulation.

[0105] Wherein, the pitch regulation control system carries out maximum wind energy tracking at rated wind speed, does not carry out pitch regulation, the pitch angle is 0, at high wind speed area (i.e. the wind speed area where the predicted wind speed is greater than the rated wind speed and less than the cut-out wind speed), the pitch is adjusted to make the wind turbine keep constant mechanical energy through wind energy conversion, and ensure that the generator output power is maintained at rated power.

[0106] The generator output voltage of the generator is obtained, and if the generator output voltage is less than the grid-connected voltage, it is determined that the actual wind turbine being simulated (i.e. the actual wind turbine in the wind power simulation module) has a boost module, and the generator output voltage is rectified and inverted through the boost module.

[0107] If the generator output voltage is less than the grid-connected voltage, a boost circuit and a grid-side inverter are combined to form a boost module.

[0108] The rotor-side rectifier is used to convert the AC power output by the wind power generator into DC power to charge the battery to smooth wind power fluctuations, and the battery is charged when the wind power output is greater than the load demand, and the battery is discharged when the wind power output is less than the load demand.

[0109] The grid-side inverter is used to convert the DC power output by the battery into power frequency AC power and synchronously grid-connect.

[0110] The execution process of the specific photovoltaic power generation simulation module (i.e. the photovoltaic power generation simulation model) is as shown in Figure 4 .

[0111] Figure 4 When the photovoltaic power generation simulation module receives the photovoltaic power generation predicted power in the source-grid-load-storage system dispatching plan, the photovoltaic array in the photovoltaic power generation simulation module converts the photovoltaic power generation predicted power into electrical energy, the photovoltaic inverter inverts the electrical energy, and sends the inverted electrical energy to the microgrid.

[0112] Figure 4 The predicted power in the above formula represents the solar energy absorbed by the photovoltaic array, and the power instruction represents the possible light abandonment instruction.

[0113] It should be noted that when the power system does not allow the microgrid to grid-connect the excess power, and the microgrid cannot accommodate the photovoltaic output, the energy management system of the microgrid may issue a light abandonment instruction. At this time, the photovoltaic inverter will adjust the output power according to the power reduction target conveyed by the light abandonment instruction.

[0114] The execution process of the energy storage system simulation module (i.e. the energy storage system simulation model) is as shown in Figure 5 .

[0115] Figure 5When the energy storage system simulation module receives the on-off grid command and the selection control mode command, the energy storage converter controls the user grid output power through the energy storage converter, the obtained energy storage power instruction in the source grid load energy storage scheduling plan, and the current state of charge of the energy storage battery.

[0116] The on-off grid command is whether to access the public grid; the micro-grid is on-grid; the selection control mode command is a command for selecting an alternating current side control mode of the energy storage converter (PCS); and the selection control mode command at least includes power and reactive power control (PQ) control, constant voltage and frequency control (VF) control, droop control, or virtual synchronous machine control.

[0117] The energy storage system selects the alternating current side control mode of the energy storage converter according to the on-off grid mode and the scheduling platform command, including PQ control, VF control, droop control, and virtual synchronous machine control. For the simulation optimization scheduling charge-discharge plan curve under on-grid, the PQ control mode is generally selected. The energy storage converter controls the output power to the user grid according to the power instruction and the current state of charge (SOC) of the battery.

[0118] It should be noted that the simulation model of the load includes a constant power model and an induction motor model. The constant power model is used to represent fixed load; and the induction motor model is used to represent flexible load.

[0119] When real-time response (second / minute level) scheduling is performed, the simulation model is reduced in order to improve the response speed of the simulation model. For the thermal power model, the boiler steam control process is no longer modeled, and the steam pressure is set constant. For the wind power model, since the calculated wind speed of each control period is constant, the generator output power and voltage can be maintained stable in one control period. The “rotor side rectifier, battery, Boost circuit, and grid side inverter” module is replaced with a transformer module, and the transformer module ratio is set according to the current period generator voltage value and grid side voltage value requirement. For the photovoltaic power generation model and the energy storage system model, simulation is no longer performed, and the predicted power and the scheduling plan power are directly used for subsequent link calculation.

[0120] S103: According to the simulation results, each load node (PQ node), each voltage control node (PV node), and the balance node, the network power flow of the micro-grid is calculated to obtain the network operating state information of each control period in the scheduling plan.

[0121] In S103, each power information in the simulation result, the power information in the adjustable load electricity plan, the predicted power of the load other than the adjustable load, and the nominal voltage corresponding to each voltage control node are taken as the node given value, and the power flow calculation is performed on the micro-grid network according to the node given value, so as to obtain the micro-grid node voltage and line current of each regulation period in the scheduling plan.

[0122] The node given value at least includes the load node given value, the voltage control node given value, and the balance node given value.

[0123] The voltage control node at least includes the node connected to the power generation equipment and the node connected to the energy storage system; the load node at least includes the node when the energy storage system is charging and the node connected to the load; and the balance node is the micro-grid public connection point.

[0124] The network operation state information includes the micro-grid node voltage and line current of each regulation period in the source network load storage system scheduling plan.

[0125] In combination with the micro-grid primary system wiring and line parameters, the node connected to the power generation equipment is taken as the PV node, the node connected to the energy storage system is taken as the PV node when the energy storage system is discharging and as the PQ node when the energy storage system is charging, the node connected to the load is taken as the PQ node, and the micro-grid public connection point is taken as the balance node. The power information obtained by simulation and the nominal voltage corresponding to each PV node are taken as the above node given value, and the power flow calculation is performed on the micro-grid network, so as to obtain the micro-grid node voltage and line current of each regulation period in the scheduling plan. Taking the day-ahead scheduling plan as an example, assuming that each regulation period is 15 minutes, 96 groups of node voltage and line current will be finally obtained, each group corresponding to one regulation period.

[0126] The specific process of the power flow calculation of the micro-grid network is as follows:

[0127] Step 1: Calculate the resistance R, reactance X, and admittance B of the line and transformer, and assign serial numbers to each node of the network in the order of PQ node, PV node, and balance node. For example, there are 3 PQ nodes, 2 PV nodes, and 1 balance node, the PQ nodes are numbered first, corresponding to ①, ②, and ③, then the PV nodes are numbered, corresponding to ④ and ⑤, and finally the balance node is numbered, corresponding to ⑥.

[0128] Step 2: Calculate the node admittance matrix of the micro-grid network.

[0129] The conductance and admittance parameters of the line and transformer are calculated through formula (2), and the node admittance matrix is generated according to the connection relationship among the nodes, lines, and transformers. The node admittance matrix contains self-admittance and mutual-admittance information.

[0130] (2)

[0131] where Y is the node admittance matrix; R is the resistance; and jX is the reactance.

[0132] Step 3: Iterative solution of node voltage.

[0133] Assign initial voltage to non-PV nodes, set according to nominal voltage;

[0134] According to the current voltage (V , ), calculate (Y , calculate (Y , calculate (Y , calculate (Y .

[0135] (3)

[0136] (4)

[0137] (5)

[0138] (6)

[0139] where P is the active power injected into node i calculated in the kth iteration; k is the iteration number; i and j are the network node numbers; n is the total number of nodes; V is the node voltage amplitude; is the node voltage phase; G ij is the mutual conductance between nodes i and j; B ij is the mutual susceptance between nodes i and j; is the voltage phase difference between nodes i and j; is the reactive power injected into node i calculated in the kth iteration; is the active power given value of node i, from the initial value of PQ node and PV node; is the power deviation of active power; is the power deviation of reactive power; is the active power given value of node i, from the initial value of PQ node.

[0140] According to the current voltage, calculate the Jacobian matrix (Y , and the specific calculation process is shown in formula (7).

[0141] (7)

[0142] Assume that in a system with n nodes, the 1st~mth nodes are PQ nodes, the m+1th~n-1th nodes are PV nodes, and the nth node is a balance node, H is an (n-1)th order matrix, N is an (n-1)×m order matrix, K is an m×(n-1) order matrix, and L is an m order matrix.

[0143] When i≠j, the following formula (8) and formula (9) are obtained.

[0144] (8)

[0145] (9)

[0146] wherein, is the element of the ith row and jth column of the sub-matrix H in the kth iteration calculation; is the element of the ith row and jth column of the sub-matrix L in the kth iteration calculation; is the node voltage amplitude obtained in the kth iteration calculation; is the node voltage amplitude obtained in the kth iteration calculation; is the mutual conductance between nodes i and j; is the mutual susceptance between nodes i and j; is the phase difference between nodes i and j obtained in the kth iteration calculation, i.e. .

[0147] When i=j, the following formula (10), formula (11), formula (12) and formula (13) are obtained.

[0148] (10)

[0149] (11)

[0150] (12)

[0151] (13)

[0152] wherein, is the element of the ith row and ith column of the sub-matrix H in the kth iteration calculation; is the node voltage obtained in the kth iteration calculation; is the reactive power injected by node i obtained in the kth iteration calculation; is the self conductance of node i; is the self susceptance of node i; is the element of the ith row and ith column of the sub-matrix N in the kth iteration calculation; is the active power injected by node i obtained in the kth iteration calculation; The element of the i-th row and the i-th column of the sub-matrix K is calculated for the k-th iteration; The element of the i-th row and the i-th column of the sub-matrix L is calculated for the k-th iteration.

[0153] The node voltage correction amount is calculated by a correction equation and The correction equation is shown in equation (14).

[0154] (14)

[0155] Wherein, ΔP is an (n-1)×1 order matrix; ΔQ is an m×1 order matrix; Δδ is an (n-1)×1 order matrix, ΔV is an m×1 order matrix, and V is an m order diagonal matrix.

[0156] The final node voltage is calculated by the node voltage correction amount and The final node voltage includes the node voltage amplitude and the node voltage phase. The equation for calculating the final node voltage is shown in equation (15).

[0157] (15)

[0158] Wherein, is the node voltage amplitude; is the node voltage amplitude calculated by the k-th iteration; is the node voltage amplitude correction amount; is the node voltage phase; is the node voltage phase calculated by the k-th iteration; is the node voltage phase correction amount.

[0159] Step 4: when the maximum value in , and is less than a preset precision (the preset precision is set according to the actual situation, and the present application does not make specific limitation), the iteration is stopped, the balance node active power and the balance node reactive power are calculated according to all node power balance, and the line current, the active power and the reactive power are calculated according to the current node voltage.

[0160] Wherein, is the power deviation of the active power; is the power deviation of the reactive power; is the node voltage correction value.

[0161] S104: The network operation state information is evaluated by a dispatching plan evaluation index system to complete the online simulation verification process of the source-grid-load-storage collaborative optimization dispatching.

[0162] By evaluating network operation status information through a scheduling plan evaluation index system, evaluation results for security, economic and environmental indicators can be obtained.

[0163] Safety metrics are used to reflect the feasibility of scheduling plans.

[0164] Economic and environmental performance indicators are used to reflect the effectiveness of the scheduling plan.

[0165] Since the standard requires a power prediction accuracy of greater than 85% for wind, solar, and load, the safety test considering the prediction errors of wind, solar, and load involves multiplying the output prediction data of wind, solar, and load given by the dispatch plan by 0.85 and 1.15 respectively, and then re-exercising the simulation operation of the online simulation system in S102 and the power flow calculation process in S103. Then, the transformer load rate, line load rate, and voltage deviation of each node are calculated to test the safety of the dispatch plan under the prediction error.

[0166] Because model downgrading implies a certain degree of distortion in voltage and current data, and in order to ensure the response speed of simulation verification and evaluation, the real-time response scheduling plan no longer focuses on "voltage deviation" and "safety test considering wind, solar and load prediction errors" in the indicator system, but only focuses on indicators at the energy level and above. This can reduce the amount of computation in the simulation verification process and keep up with the speed of real-time response.

[0167] A schematic diagram of the specific scheduling plan evaluation index system, such as... Figure 6 As shown.

[0168] Safety indicators include transformer load rate. Line load rate and voltage deviation .

[0169] Transformer load rate The calculation formula is shown in formula (16):

[0170] (16)

[0171] in, This refers to the load current on the secondary side of the transformer. This is the rated current on the secondary side of the transformer.

[0172] Line load rate The calculation formula is shown in formula (17):

[0173] (17)

[0174] in, This represents the actual power transmitted by the line. This refers to the rated power of the line.

[0175] Voltage deviation The calculation formula is shown in equation (18):

[0176] (18)

[0177] wherein, is the actual line voltage; is the rated line voltage.

[0178] The economic indicators include electricity sales revenue , thermal power generation cost, electricity purchase cost C, network loss cost, energy storage cycle life consumption LTC and demand response compensation fee.

[0179] Electricity sales revenue The calculation formula is shown in equation (19):

[0180] (19)

[0181] wherein, is the electricity purchase price of the micro-grid from the electricity market at t period, is the power sent to the micro-grid at t period; τ is the length of each period.

[0182] Thermal power generation cost = total thermal power generation × standard coal consumption rate × fuel unit price.

[0183] The calculation formula of electricity purchase cost C is shown in equation (20):

[0184] (20)

[0185] wherein, is the electricity purchase price from the grid; is the electricity quantity that needs to be purchased from the grid at t period; τ is the length of each period.

[0186] The calculation formula of network loss cost is shown in equation (21):

[0187] (21)

[0188] wherein, is the network loss cost; is the electricity purchase price from the grid; τ is the length of each period; k is the number of lines in the micro-grid; is the phase current of the i-th line; is the single-phase resistance of the i-th line.

[0189] The calculation formula of energy storage cycle life consumption LTC is shown in equation (22):

[0190] (22)

[0191] wherein, is the total energy storage system charge and discharge energy in the dispatch period; is the energy storage rated system rated capacity; is the number of charge and discharge cycles when the maximum available capacity of the energy storage system is reduced to X% of the rated capacity.

[0192] Demand response compensation cost = effective response load × call time × compensation unit price × response speed coefficient × load response rate coefficient.

[0193] The environmental protection indicators include clean energy consumption rate, clean energy generation proportion, and total carbon emission in a day.

[0194] Clean energy consumption rate = energy storage and new energy consumption in the dispatch period ÷ total new energy generation.

[0195] Clean energy generation proportion = total new energy generation in a day ÷ total generation inside the microgrid.

[0196] Total carbon emission in a day = (thermal power generation + total electricity purchase from the grid in a day) × electricity carbon factor.

[0197] The application corresponds to an evaluation index system of an online simulation system; a model reduction method is used to optimize the real-time performance of the simulation system; a wind power model for simulation verification based on predicted power with a following function. The wind power model for simulation verification in the scheme is more consistent with the actual physical process; the index system for evaluating the dispatch plan of the online simulation system is supplemented; the update frequency of the dispatch plan is set, and the real-time performance of the simulation verification process is optimized.

[0198] The beneficial effects of the embodiments of the application are: the online simulation system simulates each control period of the source-grid-load-storage system dispatch plan, the online simulation system is constructed by a thermal power simulation module, a wind power simulation module, a photovoltaic power generation simulation module, and an energy storage system simulation module in the microgrid, a model reduction method is used to optimize the real-time performance of the online simulation system, the network operation state information is evaluated through the dispatch plan evaluation index system, the dispatch plan evaluation index system considers the update frequency of the dispatch plan, optimizes the real-time performance of the simulation verification process, and evaluates the effect of the dispatch plan through the dispatch plan evaluation index system, thereby realizing the purposes of optimizing the real-time performance of the online simulation verification in the process of online simulation verification of source-grid-load-storage collaborative optimization dispatch and evaluating the effect of the dispatch plan.

[0199] Based on the above embodiments Figure 1 A kind of online simulation verification method of source-grid-load-storage collaborative optimization dispatch is disclosed, and the embodiments of the application also correspond to disclose a kind of online simulation verification device of source-grid-load-storage collaborative optimization dispatch, as Figure 7As shown, the online simulation verification device for source-grid-load-storage collaborative optimization scheduling includes:

[0200] The acquisition unit 701 is configured to acquire a source-grid-load-storage system scheduling plan.

[0201] The simulation unit 702 is configured to simulate each regulation period of the source-grid-load-storage system scheduling plan through an online simulation system to obtain simulation results; wherein the online simulation system is at least constructed by a thermal power simulation module, a wind power simulation module, a photovoltaic power generation simulation module, and an energy storage system simulation module in the micro-grid.

[0202] The calculation unit 703 is configured to perform power flow calculation on the micro-grid network according to the simulation results, each load node, each voltage control node, and the balancing node to obtain network operating state information of each regulation period in the scheduling plan.

[0203] The evaluation unit 704 is configured to evaluate the network operating state information through a scheduling plan evaluation index system to complete the process of online simulation verification of source-grid-load-storage collaborative optimization scheduling.

[0204] Further, the acquisition unit 701 is specifically configured to acquire a source-grid-load-storage system scheduling plan that meets a preset scheduling condition from a scheduling platform; wherein the preset scheduling condition is determined by a regulation time interval of a day-ahead plan, a total time length of an intra-day plan, and an update frequency of the intra-day plan; the source-grid-load-storage system scheduling plan at least includes a thermal power generation scheduling plan, a wind power generation scheduling plan, a photovoltaic power generation scheduling plan, an energy storage system charging and discharging plan, an electricity consumption plan of adjustable load, and a predicted power of load other than the adjustable load. The predicted power of load other than the adjustable load at least includes active power and reactive power.

[0205] Further, the simulation results at least include thermal power simulation power information, wind power simulation power information, photovoltaic power generation simulation power information, and energy storage simulation power information, and the simulation unit 702 includes:

[0206] The first acquisition module is configured to acquire power instructions from the source-grid-load-storage system scheduling plan.

[0207] The first determination module is configured to determine the update frequency of the intra-day plan.

[0208] The second determination module is configured to determine the module type of the thermal power simulation module, the wind power simulation module, the photovoltaic power generation simulation module, and the energy storage system simulation module in the micro-grid in the online simulation system according to the update frequency; the module type at least includes a reduced order module or a non-reduced order module.

[0209] The control module is configured to control the thermal power simulation module, the wind power simulation module, the photovoltaic power generation simulation module, and the energy storage system simulation module of the determined module type to operate according to the power instructions.

[0210] an emulation module, configured to perform corresponding emulation on each regulation period of the source-grid-load-storage system scheduling plan by each module in operation, to obtain thermal power emulation power information, wind power emulation power information, photovoltaic power emulation power information, and storage power emulation power information.

[0211] Further, the simulation unit 702 of the execution process of the thermal power emulation module comprises:

[0212] a first calculation module, configured to calculate, when the coordinated control system in the thermal power emulation module receives a power instruction and a frequency deviation, a main steam valve opening degree of a steam turbine and a boiler steam quantity generated by a boiler according to the power instruction and the frequency deviation, wherein the frequency deviation is a deviation between an actual output frequency of a thermal power generator and a target frequency;

[0213] an output sending module, configured to change a steam flow entering the steam turbine and change an output power of the steam turbine according to the main steam valve opening degree of the steam turbine and the boiler steam quantity generated by the boiler by the coordinated control system, so that the generator outputs the thermal power emulation power information according to a thermal power emulation target in the source-grid-load-storage system scheduling plan, and sends the thermal power emulation power information to the micro-grid.

[0214] Further, the simulation unit 702 of the execution process of the wind power emulation module comprises:

[0215] a second calculation module, configured to, when the wind power emulation module receives a wind power prediction power in the source-grid-load-storage system scheduling plan and a meteorological prediction wind speed from a meteorological center, if the wind power prediction power is greater than 0 and less than a rated power of a wind turbine generator, calculate the prediction wind speed according to a preset wind speed calculation formula by backstepping;

[0216] a third determination module, configured to, if the wind power prediction power is equal to the rated power of the wind turbine generator, and the meteorological prediction wind speed at a current time is less than a rated wind speed of the wind turbine, determine the rated wind speed of the wind turbine as the prediction wind speed;

[0217] a fourth determination module, configured to, if the wind power prediction power is equal to the rated power of the wind turbine generator, and the meteorological prediction wind speed is greater than a cut-out wind speed, determine the cut-out wind speed of the wind turbine as the prediction wind speed;

[0218] a fifth determination module, configured to, if the wind power prediction power is equal to 0, the meteorological prediction wind speed at the current time is greater than a cut-in wind speed of the wind turbine and less than the cut-out wind speed of the wind turbine, determine the cut-in wind speed of the wind turbine as the prediction wind speed;

[0219] a stopping module, configured to, if the prediction wind speed is less than or equal to the rated wind speed of the wind turbine, stop a pitch adjustment control system in the wind power emulation module from working;

[0220] The sixth determining module is configured to, if the predicted wind speed is greater than the rated wind speed of the wind turbine, adjust the pitch angle of the wind turbine in the pitch regulation control system in the wind power simulation module to keep the actual rotating speed of the wind turbine consistent with the rated wind speed of the wind turbine, ensure that the output power of the generator is consistent with the rated power of the wind turbine, and determine the output power of the generator as the wind power simulation power information.

[0221] Further, the method further comprises:

[0222] The second obtaining module is configured to obtain the generator output voltage of the generator.

[0223] The seventh determining module is configured to, if the generator output voltage is less than the grid-connected voltage, determine that the actual wind turbine being simulated has a boost module.

[0224] The rectification and inversion module is configured to rectify and invert the generator output voltage through the boost module.

[0225] Further, the simulation unit 702 of the execution process of the photovoltaic power generation simulation module comprises:

[0226] The conversion module is configured to, when the photovoltaic power generation simulation module receives the predicted photovoltaic power in the source-grid-load-storage system dispatching plan, convert the predicted photovoltaic power into electrical energy through the photovoltaic array in the photovoltaic power generation simulation module.

[0227] The inversion and sending module is configured to invert the electrical energy through the photovoltaic inverter and send the inverted electrical energy to the micro-grid.

[0228] Further, the simulation unit 702 of the execution process of the energy storage system simulation module comprises:

[0229] The receiving and regulating module is configured to, when the energy storage converter of the energy storage system simulation module receives the on / off-grid command and the selection control mode command, regulate the user grid output power through the energy storage converter, the obtained energy storage power instruction in the source-grid-load-storage system dispatching plan, and the current state of charge of the energy storage battery; wherein, the on / off-grid command is an on / off-grid command of whether to access the public grid; the selection control mode command is a command of selecting the control mode of the AC side of the energy storage converter; the selection control mode command at least includes power and reactive power control, constant voltage and frequency control, droop control, or virtual synchronous machine control.

[0230] Further, the calculation unit 703 comprises:

[0231] The eighth determining module is configured to take each power information in the simulation result, the power information in the adjustable load power consumption plan, the predicted power of the load other than the adjustable load, and the nominal voltage corresponding to each voltage control node as a node given value; wherein, the node given value at least includes a load node given value, a voltage control node given value, and a balance node given value.

[0232] a third calculation module, configured to perform power flow calculation on the micro-grid network according to the given value of the node, to obtain the micro-grid node voltage and line current of each regulation period in the scheduling plan.

[0233] The embodiment of the present application has the beneficial effects that: each regulation period of the source-grid-load-storage system scheduling plan is simulated by the online simulation system, the online simulation system is constructed by a thermal power simulation module, a wind power simulation module, a photovoltaic power simulation module and an energy storage system simulation module in the micro-grid, the real-time performance of the online simulation system is optimized by using model reduction, the network operation state information is evaluated by the scheduling plan evaluation index system, the scheduling plan evaluation index system considers the update frequency of the scheduling plan, the real-time performance of the simulation verification process is optimized, and the scheduling plan effect is evaluated by the scheduling plan evaluation index system, so as to realize the purposes of optimizing the real-time performance of the online simulation verification in the process of the online simulation verification of the source-grid-load-storage collaborative optimization scheduling and evaluating the scheduling plan effect.

[0234] The embodiment of the present application also provides a storage medium, which comprises stored instructions, wherein the instructions control a device where the storage medium is located to perform the online simulation verification method for the source-grid-load-storage collaborative optimization scheduling.

[0235] The embodiment of the present application also provides an electronic device, a structural schematic diagram of which is shown in Figure 8 The electronic device specifically comprises a memory 801 and one or more than one instruction 802, wherein the one or more than one instruction 802 is stored in the memory 801 and is configured to perform the online simulation verification method for the source-grid-load-storage collaborative optimization scheduling by performing the one or more than one instruction 802 by one or more than one processor 803.

[0236] For each method embodiment described above, in order to simply describe, the method embodiments are all described as a series of action combinations, but those skilled in the art should know that the present application is not limited to the action sequence described, because according to the present application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should know that the embodiments described in the specification all belong to preferred embodiments, and the actions and modules involved are not necessarily essential to the present application.

[0237] It should be noted that each embodiment in the specification is described in a progressive manner, and each embodiment mainly describes the differences from other embodiments, and the same and similar parts of each embodiment can be known by referring to each other. For the device embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be known by referring to the part of the method embodiment.

[0238] The steps in the methods of the embodiments of the present application can be adjusted in sequence, combined and deleted according to actual needs.

[0239] Finally, it should be noted that in this document, relational terms such as first and second and the like can be used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions.

[0240] The above description of the disclosed embodiments enables a person skilled in the art to implement or use the present application. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

[0241] The above is only the preferred embodiments of the present application, and it should be pointed out that for ordinary skilled in the art, several improvements and refinements can be made without departing from the principles of the present application, and these improvements and refinements should be considered as the protection scope of the present application.

Claims

1. An online simulation verification method for source-network-load-storage collaborative optimization scheduling, characterized in that, The method comprises: acquiring a source-grid-load-storage system scheduling plan; simulating each regulation period of the source-grid-load-storage system scheduling plan through an online simulation system to obtain simulation results; wherein the online simulation system is constructed by at least a thermal power simulation module, a wind power simulation module, a photovoltaic power simulation module and an energy storage system simulation module in a microgrid; performing power flow calculation on the microgrid network according to the simulation results, each load node, each voltage control node and the balancing node to obtain network operation state information of each regulation period in the scheduling plan; evaluating the network operation state information through a scheduling plan evaluation index system to complete the process of online simulation verification of source-grid-load-storage collaborative optimization scheduling.

2. The method of claim 1, wherein, The acquisition of the source-grid-load-storage system scheduling plan comprises: acquiring a source-grid-load-storage system scheduling plan meeting preset scheduling conditions from a scheduling platform; wherein the preset scheduling conditions are determined by the regulation time interval of the day-ahead plan, the total length of the day-ahead plan and the update frequency of the day-ahead plan; the source-grid-load-storage system scheduling plan at least includes a thermal power generation scheduling plan, a wind power generation scheduling plan, a photovoltaic power generation scheduling plan, an energy storage system charging and discharging plan, an electricity consumption plan of adjustable load and a predicted power of load other than adjustable load, which at least includes active power and reactive power.

3. The method of claim 1, wherein, The simulation results at least include thermal power simulation power information, wind power simulation power information, photovoltaic power simulation power information and energy storage simulation power information, and the simulation of each regulation period of the source-grid-load-storage system scheduling plan through the online simulation system to obtain the simulation results comprises: acquiring power instructions from the source-grid-load-storage system scheduling plan; determining the update frequency of the day-ahead plan; determining the module type of the thermal power simulation module, the wind power simulation module, the photovoltaic power simulation module and the energy storage system simulation module of the microgrid in the online simulation system according to the update frequency; the model type at least includes a reduced order module or a non-reduced order module; controlling the thermal power simulation module, the wind power simulation module, the photovoltaic power simulation module and the energy storage system simulation module of the module type to run according to the power instructions; performing corresponding simulation on each regulation period of the source-grid-load-storage system scheduling plan through each module running to obtain the thermal power simulation power information, the wind power simulation power information, the photovoltaic power simulation power information and the energy storage simulation power information.

4. The method of claim 1, wherein, The execution process of the thermal power simulation module comprises: when the coordinated control system in the thermal power simulation module receives power instructions and frequency deviation, calculating the main steam valve opening degree of the steam turbine and the amount of boiler steam generated by the boiler through the power instructions and the frequency deviation; wherein the frequency deviation is the deviation between the actual output frequency of the thermal power generator and the target frequency. The coordinated control system, the main steam valve opening degree of the steam turbine and the boiler steam quantity generated by the boiler change the steam flow entering the steam turbine and the output power of the steam turbine, so that the generator outputs the thermal power simulation power information according to the thermal power simulation target in the source network load storage system scheduling plan, and the thermal power simulation power information is sent to the micro-grid.

5. The method of claim 1, wherein, The execution process of the wind power simulation module includes: When the wind power simulation module receives the wind power prediction power in the source network load storage system scheduling plan and the meteorological prediction wind speed from the meteorological center, if the wind power prediction power is greater than 0 and less than the rated power of the wind turbine generator, the prediction wind speed is calculated according to the preset wind speed calculation formula; If the wind power prediction power is equal to the rated power of the wind turbine generator, and the meteorological prediction wind speed at the current time is less than the rated wind speed of the wind turbine, the rated wind speed of the wind turbine is determined as the prediction wind speed; If the wind power prediction power is equal to the rated power of the wind turbine generator, and the meteorological prediction wind speed is greater than the cut-out wind speed, the cut-out wind speed of the wind turbine is determined as the prediction wind speed; If the wind power prediction power is equal to 0, the meteorological prediction wind speed at the current time is greater than the cut-in wind speed of the wind turbine and less than the cut-out wind speed of the wind turbine, the cut-in wind speed of the wind turbine is determined as the prediction wind speed; If the prediction wind speed is less than or equal to the rated wind speed of the wind turbine, the pitch adjustment control system in the wind power simulation module stops working; If the prediction wind speed is greater than the rated wind speed of the wind turbine, the pitch adjustment control system in the wind power simulation module adjusts the pitch angle to keep the actual speed of the wind turbine consistent with the rated wind speed of the wind turbine, ensures that the output power of the generator is consistent with the rated power of the wind turbine generator, and determines the output power of the generator as the wind power simulation power information.

6. The method of claim 5, wherein, Further including: Obtaining the generator output voltage of the generator; If the generator output voltage is less than the grid-connected voltage, it is determined that the actual wind turbine being simulated has a boost module; Rectifying and inverting the generator output voltage through the boost module.

7. The method of claim 1, wherein, The execution process of the photovoltaic power generation simulation module includes: When the photovoltaic power generation simulation module receives the photovoltaic power prediction power in the source network load storage system scheduling plan, the photovoltaic power prediction power is converted into electrical energy through the photovoltaic array in the photovoltaic power generation simulation module; The electrical energy is inverted through the photovoltaic inverter, and the inverted electrical energy is sent to the micro-grid.

8. The method of claim 1, wherein, The execution process of the energy storage system simulation module includes: When the energy storage converter of the energy storage system simulation module receives the on / off grid command and the selection control mode command, the output power of the user grid is regulated and controlled through the energy storage converter, the obtained energy storage power instruction in the source network load storage system scheduling plan and the current state of charge of the energy storage battery; The on / off grid command is the on / off grid command of whether to access the public grid; the selection control mode command is the command of selecting the control mode of the AC side of the energy storage converter; the selection control mode command at least includes power and reactive power control, constant voltage and frequency control, droop control or virtual synchronous machine control.

9. The method of claim 1, wherein, The network operation state information at least includes micro-grid node voltage and line current, the power flow calculation is carried out on the micro-grid network according to the simulation result, each load node, each voltage control node and balance node, and the network operation state information of each regulation period in the scheduling plan is obtained, including: The power information in the simulation result, the power information in the adjustable load power consumption plan, the predicted power of the load except the adjustable load and the nominal voltage corresponding to each voltage control node are taken as node given values;Wherein, the node given values at least include load node given values, voltage control node given values and balance node given values; The power flow calculation is carried out on the micro-grid network according to the node given values, and the micro-grid node voltage and the line current of each regulation period in the scheduling plan are obtained.

10. An online simulation verification device for source-network-load-storage collaborative optimization scheduling, characterized in that, The device comprises: An acquisition unit is configured to acquire a source grid load storage system scheduling plan; A simulation unit is configured to simulate each regulation period of the source grid load storage system scheduling plan through an online simulation system to obtain a simulation result, wherein the online simulation system is at least constructed by a thermal power simulation module, a wind power simulation module, a photovoltaic power generation simulation module and an energy storage system simulation module in the micro-grid; A calculation unit is configured to perform power flow calculation on the micro-grid network according to the simulation result, each load node, each voltage control node and balance node, and obtain network operation state information of each regulation period in the scheduling plan; An evaluation unit is configured to evaluate the network operation state information through a scheduling plan evaluation index system to complete the process of online simulation verification of source grid load storage collaborative optimization scheduling.

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