Digital-twin-based load management digital-physical hybrid simulation method and system

Abstract

The present application relates to the technical field of simulation, in particular to a digital-twin-based load management digital-physical hybrid simulation method and system, the simulation system includes a flexible setting simulation source and actual equipment for configuring engineering to realize the simulation of user-side changing scenes and build a simulation experiment platform, the beneficial effect is that: through the platform of fusing digital twin and semi-physical simulation, the simulation of new load management system is used, in the simulation process, the development and verification of strategy, scene definition, time scale and fault simulation are adjusted, the simulation according to events and the model of mapping real equipment and physical characteristics is deduced, the precision of simulation is improved, and the adaptation range of simulation is increased.

Description

Technical Field

[0001] This invention relates to the field of simulation technology, specifically to a digital twin-based load management digital-physical hybrid simulation method and system. Background Technology

[0002] Currently, most load management system simulation verification platforms are designed from the perspective of power grid operation, focusing on power grid dispatch and overall process verification. They consider the optimal power flow problem under steady-state conditions more. At present, load management system simulation verification is mainly used to verify the processes of demand response and orderly power consumption. Although some systems have the characteristics of semi-physical simulation, which enables them to connect to real equipment, they are still focused on the effect verification under steady-state conditions. The platform lacks sufficient research on equipment-level verification and flexible control characteristics.

[0003] In the process of building a new load management system, there are no good commissioning and testing methods, and it is difficult to determine typical days and typical scenarios. Real systems are limited by normal user operation, insufficient intelligence, and atypical equipment composition, which are insufficient to support the verification and evaluation of load management strategies.

[0004] During the simulation process, there are shortcomings in scenario definition, time scale, fault simulation, and strategy verification. Currently, load management simulation verification platforms mainly focus on the simulation of business processes such as demand response and orderly power consumption, and all of them are based on the perspective of the power grid dispatching system (top-down). However, they do not adequately consider the specific and overall interactive tasks of mixed resources consisting of photovoltaic, storage, charging, air conditioning, and flexible loads. The time scale cannot adapt to the needs of different scenarios. Semi-physical simulation only considers real equipment and digital models without considering the assistance of physical experimental equipment, and there is little consideration for faults at different levels. Summary of the Invention

[0005] The purpose of this invention is to provide a digital twin-based load management digital-physical hybrid simulation method and system to solve the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution:

[0007] A digital twin-based load management digital-physical hybrid simulation system, the simulation system comprising:

[0008] This simulation experiment platform is built to flexibly configure different combinations of simulation sources and actual equipment for engineering projects, enabling the simulation of ever-changing user-side scenarios.

[0009] Create mechanistic models of independent devices based on physical mechanisms;

[0010] Create detailed power electronics models based on the typical specifications of typical equipment in the industry;

[0011] Based on historical data and through data analysis, typical daily conditions and typical operating conditions of photovoltaics are generated by measuring irradiance or photovoltaic system power generation.

[0012] Generate typical daily and typical load curves based on industry energy load data, and provide interfaces for user customization and importing historical data;

[0013] Create a mirrored digital model for communication aggregation of remote devices or systems;

[0014] Using scenario generation methods, typical system topologies are generated based on data provided by customers or data in a pre-built database.

[0015] Using B / S architecture visualization software, a system is formed by dragging and connecting CAD components corresponding to the model to generate a target digital twin image for simulation verification.

[0016] Preferably, the simulation source equipment includes physical simulation sources (photovoltaic simulator, battery simulator, power grid simulator), physical experimental devices (air conditioning chiller experimental device, user load experimental device, natural gas power generation experimental device), real equipment (photovoltaic converter, energy storage converter, charging pile, etc.) and digital real-time simulators.

[0017] Preferably, the mechanism model of the device is digitally constructed and created based on a self-portrait of the actual physical operation of the device.

[0018] Preferably, the mechanism model of the equipment includes the logical switching rhythm of equipment operation, fault handling and response, communication settings and control, equipment combination in different scenarios, and a self-portrait of energy flow operation.

[0019] Preferably, the detailed power electronics model is used to support the power consumption characteristics on both the user side and the campus side.

[0020] Preferably, the main equipment for building a microgrid on the user side includes energy storage, photovoltaics, air conditioning, charging piles, power flow switching equipment, and energy loads. Typical specifications of the equipment on the park side include power quality and transient voltage and current characteristics.

[0021] A method for implementing a load management digital-physical hybrid simulation system based on the aforementioned digital twin, the method comprising the following steps:

[0022] S1: Simulation on a time scale. The system constrained by CAD components is a digital twin mirror image. Business process verification is performed by selecting large step size real-time simulation, system transient simulation is performed by selecting small step size real-time simulation, seasonal and other long-term scale simulation is performed by selecting accelerated simulation, and real-time simulation of a certain time segment is achieved in long-term simulation by selecting adaptive simulation step size. This is used to evaluate the performance of strategies or equipment on a long-term scale.

[0023] S2: Through the gateway, the customer's system can be mapped to the streamlined twin image, providing a relatively evidence-based solution for equipment selection or site selection and capacity determination issues in the transformation;

[0024] S3: The simulation system can be flexibly reconfigured through the simulation background management software to simulate the typical equipment specifications and system topology of the source-grid-load-storage system on the load user side;

[0025] S4: In terms of strategy verification, strategies at different levels (distribution master station scheduling strategy, microgrid energy management strategy, equipment coordination strategy) under different scenarios are verified and evaluated. SOA (service-oriented architecture) software is generated through automatic code generation to accelerate the development and verification of control.

[0026] S5: In fault simulation, the simulation background management software is used to edit the events below the task and the occurrence of faults according to the time sequence to form test cases. The digital twin system performs inference according to the events and the model and physical characteristics of the real device.

[0027] Preferably, the simulation verification platform is compatible with different time scales, integrating the testing of equipment manufacturers such as distribution network dispatching, demand response and other business master stations, smart energy unit controllers, energy management systems, and photovoltaic inverters into one platform. One platform completes the testing tasks that were originally performed by multiple platforms. By setting the time scale and simulation step size, it is easy to adjust to different stages of testing content.

[0028] Preferably, the simulation verification platform can simulate regional power grids, integrated energy microgrids, microgrids, new energy power generation, and power electronic loads.

[0029] Preferably, the simulation of the simulation verification platform also includes the simulation of integrated energy microgrids and microgrids.

[0030] Compared with the prior art, the beneficial effects of the present invention are:

[0031] This invention utilizes a platform that integrates digital twins and hardware-in-the-loop simulation for the simulation of novel load management systems. During the simulation process, adjustments are made to aspects such as strategy development and verification, scenario definition, time scale, and fault simulation. This enables deduction based on events and models of real equipment and their physical characteristics, thereby improving the accuracy of the simulation and expanding its applicability. Attached Figure Description

[0032] Figure 1 This is a flowchart of the present invention. Detailed Implementation

[0033] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] Please see Figure 1 The present invention provides a technical solution:

[0035] A digital twin-based load management digital-physical hybrid simulation system, the simulation system comprising:

[0036] This platform organically couples physical simulation sources (photovoltaic simulators, battery simulators, grid simulators), physical experimental devices (air conditioning chiller experimental devices, user load experimental devices, natural gas power generation experimental devices), real equipment (photovoltaic converters, energy storage converters, charging piles, etc.) and a digital real-time simulator to form a flexible simulation experimental platform that is compatible with most scenarios. Different combinations of simulation sources and actual equipment can be flexibly configured through project settings to achieve simulation construction of ever-changing user-side scenarios.

[0037] Based on physical principles, mechanistic models of independent devices and various scenarios are created. For devices whose actual power levels and different operating conditions cannot be determined from actual data, a digital mechanistic model needs to be built based on a self-portrait of the device's actual physical operation. The device mechanistic model includes the logical switching rhythm of device operation, fault handling and response, communication settings, and control. The self-portrait of device combinations and energy flow operation in different scenarios also needs to be modeled using digitized mechanistic models for joint simulation.

[0038] Based on the typical specifications of industry-standard equipment, detailed power electronic models are created. For the user side, the main equipment for building a microgrid includes energy storage, photovoltaics, air conditioning, charging piles, power flow switching equipment, and energy loads. On the park side, the typical specifications of the equipment are as follows. The characteristics of power quality and transient voltage and current components all require the creation of detailed power electronic models to support them.

[0039] Based on historical data and through data analysis, typical daily conditions and typical operating conditions of photovoltaics are generated by measuring irradiance or photovoltaic system power generation.

[0040] Generate typical daily and typical load curves based on industry energy load data, and provide interfaces for user customization and importing historical data;

[0041] Create a mirrored digital model for communication aggregation of remote devices or systems;

[0042] Using scenario generation methods, typical system topologies are generated based on data provided by customers or data in a pre-built database.

[0043] Using B / S architecture visualization software, a system is formed by dragging and connecting CAD components corresponding to the model to generate a target digital twin image for simulation verification.

[0044] A digital twin-based hybrid digital-physical simulation method for load management.

[0045] Example 1:

[0046] Problem: Existing technologies mostly employ large-step real-time simulation on a time scale, lacking the ability to perform seasonal simulations, and also do not support the ability to perform small-step simulations of microgrid stability, harmonics, and other scenarios.

[0047] Simulation on a time scale, the system constrained by CAD components is a digital twin mirror image. Business process verification is performed by selecting large step size real-time simulation, system transient simulation is performed by selecting small step size real-time simulation, seasonal and other long-term scale simulation is performed by selecting accelerated simulation, and real-time simulation of a certain time segment is achieved in long-term simulation by selecting adaptive simulation step size, which is used to evaluate the performance of strategies or equipment on a long-term scale.

[0048] Example 2: Based on Example 1;

[0049] Problem: Existing technologies primarily consider the needs of power grid dispatching in scenario definition, such as demand response operations, especially peak shaving and renewable resource consumption scenarios. They do not adequately consider scenarios such as microgrids, smart buildings, and electric vehicle charging stations. While interfaces for building scenarios using device controls (digital models) are provided, they do not fully utilize big data technologies for scenario generation or clustering methods to reduce the number of scenarios. The semi-physical interfaces only consider connecting real devices, failing to account for the limitations of real devices in simulation verification, such as limited operating conditions and difficulty in obtaining internal data. Furthermore, they cannot easily aggregate remote device data on a local simulation verification platform.

[0050] The gateway can map the customer's system to the integrated twin image, providing a relatively evidence-based solution for equipment selection or site selection and capacity determination in the transformation. The simulation system can be flexibly reconstructed through the simulation backend management software, simulating typical equipment specifications and system topology of the source-grid-load-storage system on the load user side. The simulation verification platform is compatible with different time scales, integrating the testing of distribution network scheduling, demand response and other business master stations, smart energy unit controllers, energy management systems, photovoltaic inverters and other equipment manufacturers into one platform, completing the testing tasks of multiple platforms in one platform. By setting the time scale and simulation step size, it is easy to adjust to different stages of testing content. The simulation verification platform can simulate regional power grids, integrated energy microgrids, microgrids, new energy power generation and power electronic loads. The simulation of the simulation verification platform also includes the simulation of integrated energy microgrids and microgrids.

[0051] Example 3: Based on Example 2;

[0052] Problem: In terms of strategy verification, existing load management simulation verification systems mostly provide verification for existing strategies. They do not offer convenient interfaces for researching new strategies, and when strategies are used in production environments, secondary development is required, followed by further verification.

[0053] In terms of strategy verification, strategies at different levels (distribution master station scheduling strategy, microgrid energy management strategy, and equipment coordination strategy) under different scenarios are verified and evaluated. SOA (service-oriented architecture) software is generated through automatic code generation methods to accelerate the development and verification of control.

[0054] Example 3: Based on Example 2;

[0055] Problem: Current load management systems largely neglect fault simulation in their technology. With the integration of new source-load devices at the load side of the power grid, in addition to traditional HVAC and charging piles, an increasing number of locally aggregated hybrid resources such as solar power, energy storage, charging, and air conditioning are being connected to the grid. Energy management systems responsible for this local aggregation are highly sensitive to equipment faults, communication faults, and AC / DC faults, particularly regarding relay protection. Furthermore, faults require close attention in the overall interactive process.

[0056] In terms of fault simulation, the simulation backend management software is used to edit the events below the task and the occurrence of faults according to the time sequence to form test cases. The digital twin system performs inference based on the events and the model and physical characteristics of the real device.

[0057] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A digital-twinning load management digital-physical hybrid simulation method, characterized by: The method comprises the following steps: S1: simulation on a time scale, the system constrained by the CAD component is the embodiment of the digital twin mirror image, verification of the business process is carried out through real-time simulation with a large step size, simulation of the system transient is carried out through real-time simulation with a small step size, simulation of seasonal long time scales is carried out through accelerated simulation, real-time simulation of a certain time section in long time simulation is realized through adaptive simulation step size, and the performance of a strategy or equipment on a long time scale is evaluated; S2: the system of a customer can be mapped into the digital twin mirror image through a gateway, and a relatively reliable scheme is provided for the selection of a device to be transformed or the selection of a site and a capacity; S3: the simulation system is flexibly reconfigured through a simulation background management software, and typical equipment specifications and system topologies of a source-grid-load-storage system on the user side are simulated; S4: in terms of strategy verification, different levels of strategies under different scenarios are verified and evaluated, SOA software is generated through an automatic code generation method, and the development and verification progress of control is accelerated; S5: in terms of fault simulation, test cases are edited and constituted according to time sequences through the simulation background management software, the digital twin system deduces according to events, models and physical characteristics of mapped real devices.

2. The load management digital-physical hybrid simulation method of digital twin according to claim 1, wherein: The simulation verification platform is compatible with different time scales, integrates test of devices such as a power distribution network dispatching, a demand response business master station, a smart energy unit controller, an energy management system and a photovoltaic inverter from device manufacturers together, and can be adjusted to different stage test contents through setting of time scales and simulation step sizes.

3. The load management digital-physical hybrid simulation method of digital twin according to claim 1, wherein: The simulation verification platform can simulate regional power grids, comprehensive energy microgrids, microgrids, new energy power generation and power electronic loads.

4. The load management digital-physical hybrid simulation method of digital twin according to claim 3, wherein: The simulation of the simulation verification platform also comprises simulation of comprehensive energy microgrids and microgrids.

5. A digitally-twinning load management digital-physical hybrid simulation system, characterized by: The digital twin load management digital-physical hybrid simulation method in any one of claims 1-4 is applied to the simulation system, and the simulation system comprises: A simulation experiment platform built for flexibly setting simulation sources and different combination conditions of actual devices to realize simulation of user side scenes in various changes; Mechanism models of independent devices are created according to physical mechanisms; Power electronic detailed models are created according to typical specifications of typical devices in the industry; Typical days and typical working conditions of photovoltaics are generated through irradiance or photovoltaic system power generation power according to a method of data analysis based on historical data; Typical days and typical load curves are generated according to industrial energy load data, and an interface for user-defined and imported historical data is provided; Mirror digital models for communication aggregation of remote devices or systems are created; Typical system topologies are generated according to data provided by a customer or data in a pre-set database through a scene generation method; A visual software based on B / S architecture is used to generate a target digital twin mirror image for simulation verification by dragging and connecting CAD components corresponding to models to form a system.

6. The digitally-twinred load management digital-physical hybrid simulation system of claim 5, wherein: The simulation source devices comprise physical simulation sources, physical experiment devices, real devices and digital real-time simulation machines.

7. The load management digital-physical hybrid simulation system of claim 5, wherein: The mechanism model of the device is a self-portrait of the actual physical operation of the device, created by digital construction.

8. The digitally-twinred load management digital-physical hybrid simulation system of claim 7, wherein: The mechanism model of the device contains the logical switching rhythm of the device operation, the handling of faults, the communication given and control, the combination of the device under different scenes, and the self-portrait of the energy flow operation.

9. The load management digital-physical hybrid simulation system of claim 5, wherein: The power electronics detailed model is used to support the power consumption characteristics of the user side and the park side.

10. The digitally-twinred load management digital-physical hybrid simulation system of claim 9, wherein: The main devices of the user side to build a microgrid include energy storage, photovoltaic, air conditioner, charging pile, tide mutual aid device, and energy load. The typical specifications of the park side devices include power quality and transient voltage and current characteristics.

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