Distributed energy information modeling method for in-situ coordination control of active power distribution network

Abstract

The invention provides a distributed energy information modeling method for on-site coordination control of an active power distribution network, and belongs to the technical field of power grid control. Comprising the following steps: based on intelligent electronic equipment and a distributed energy system, establishing an equipment side information model according to an IEC61850 standard; according to an IECCIM expansion principle, distributed energy CIM expansion is carried out on the power system information model at a master station side; performing static topology model fusion and measurement model fusion on the equipment side information model and the electric power system information model after CIM expansion; and constructing a fusion model by utilizing a protocol mapping mode, and mapping data of the equipment side information model and the power system information model by utilizing the fusion model. According to the invention, the problem of model fusion between the terminal equipment and the distributed energy and the master station system is solved, a unified lightweight object-oriented information model for distributed energy cooperative control is established, and reliable and real-time exchange of equipment-equipment and equipment-master station information is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of power grid control, and in particular relates to a distributed energy information modeling method for local coordinated control of an active distribution network. Background Art

[0002] There are a large number of distributed energy resources with certain regulation and response capabilities in the active distribution network, including distributed generation resources, energy storage resources, electric vehicle resources and flexible load resources, etc. These resources are characterized by dispersion, small capacity and diverse types. These distributed energy resources are connected to the distribution network in large quantities and run in parallel, which brings new challenges to the planning and operation of the distribution network.

[0003] The traditional distribution network is based on the "grid-load" dual structure. It is a one-way power distribution network based on power supply from the grid and power consumption by users. It belongs to the "grid (grid) - load (load)" dual structure. On this basis, the operation and management of the grid are relatively simple. The changing demand of the load can be adapted by dispatching the overall grid, or the balance of power can be achieved through effective control of the load and demand-side management. After the distributed energy is connected to the distribution network, it is necessary to realize the coordinated control and management of the source, network, load and storage. The management mode of the distribution network is no longer centralized dispatching and control. It is necessary to adopt a combination of centralized and decentralized modes to carry out operation and management. All links related to the operation, control, management and planning of the distribution network need to be upgraded accordingly as the unbalanced development between the grid and the load caused by the access of distributed energy.

[0004] As the penetration rate of distributed energy access to the distribution network continues to increase, the original balance is gradually broken, and the distribution network gradually forms a four-element structure of "source-grid-load-storage". The access of the source not only destroys the original one-way power flow of grid-load, but also forms a mixture of multiple flows of grid-load, source-load, and source-grid. The access of energy storage to the distribution network brings opportunities for two-way regulation of the grid, but due to the volatility and randomness of the "source", it is difficult for the newly formed four-element structure to form a stable balance, and the traditional distribution network model can no longer meet the monitoring needs. It is mainly reflected in the following aspects: Model problem: It is difficult to integrate the full models of multiple standards. Although IEC61850 specifies the mapping between the 61850 model and the IEC60870-5-101 / 104 protocol, 101 / 104 itself is a non-object-oriented protocol. The transmitted semantic information and communication rules must be tightly coupled together. The functions are not defined as a complete and independent architecture. It is mainly used to solve the problem of real-time data transmission and exchange. It has poor scalability and cannot realize all functional applications supported by the 61850 model. It cannot solve the problems of object-oriented services such as device plug-and-play.

[0005] Protocol issues: The IEC60870-5-101 / 104 protocol is a communication protocol for serial transmission of power grid telecontrol information and real-time data over the network. The semantic information and communication rules it transmits are tightly coupled, and its functions are not defined as a complete and independent architecture. It mainly solves the problem of real-time data exchange. It has poor scalability, cannot support object-oriented services, and cannot implement cloud-edge information interaction and peer-to-peer edge-to-edge communication applications for semi-structured / unstructured data types.

[0006] Smart device access and operation and maintenance issues: The rapid development of the power distribution Internet of Things has brought about access issues for a large number of smart devices. Distribution terminals (FTU, DTU), distribution transformer terminals (TTU), smart low-voltage circuit breakers, charging piles, electric vehicles, distributed power sources, etc. have not yet unified access standards, and cannot achieve device-level plug-and-play and information interoperability, resulting in a huge amount of work in installation, operation and maintenance, debugging, and replacement, which has greatly hindered the in-depth application of the power distribution Internet of Things technology.

[0007] Distributed application issues: Since the models and protocols are not object-oriented and have poor scalability, the distribution network is heavily dependent on the control center from the source, network, energy storage, and load. Information cannot be exchanged on-site between each link and device, and on-site distributed functional applications are not truly realized, highlighting security, reliability, and rationality issues. Summary of the invention

[0008] In view of the deficiencies in the prior art, the present invention provides a distributed energy information modeling method for on-site coordinated control of an active distribution network.

[0009] In order to solve one, part or all of the above technical problems, the technical solution adopted by the present invention is: A distributed energy information modeling method for local coordinated control of an active distribution network, comprising: S1. Based on intelligent electronic devices and distributed energy systems, establish a device-side information model in accordance with the IEC61850 standard; S2. Based on the extension principle of IECCIM, the power system information model is extended with CIM for distributed energy at the master station side; S3, fusion of static topology model and measurement model for the equipment side information model and the power system information model after CIM expansion; S4. Construct a fusion model by using protocol mapping, and use the fusion model to map the data of the device side information model and the power system information model.

[0010] Further, step S1 includes: Construct the intelligent electronic device information model according to the IEC61850 specification; construct the distributed energy information model according to the IEC61850 specification; Construct the device side information model based on the intelligent electronic device information model and distributed energy information model.

[0011] Furthermore, the method for constructing an intelligent electronic device information model includes: Define the model data class of IED equipment according to IEC61850; Make a complete description of the functions and principles of the bay layer IED based on actual conditions; Analyze the logical structure of IED based on object-oriented thinking, and replace the actual IED with logical devices; decouple the functions of IED, select appropriate logical nodes for each function, set the data and data attributes contained in each logical node, find out the data flow between logical nodes, and further analyze it using the unified modeling language tool; After completing the information model attributes of the IED, select the corresponding ACSI service according to the IEC61850 standard, specify the corresponding abstract communication service as the functional service of the information model for the information model attributes, and configure the ACSI control block attributes to form a complete intelligent electronic device information model.

[0012] Furthermore, the method for constructing a distributed energy information model includes: Based on the IEC61850 standard, a distributed energy hierarchical information model is constructed; Establishing logical nodes for distributed energy management; The distributed generation system, energy storage system, electric vehicle charging system and SVG reactive compensation device are modeled separately.

[0013] Furthermore, step S2 includes: expanding the photovoltaic class, energy storage class and wind power class of distributed energy in the power system resource class of the power system information model on the master station side.

[0014] Further, step S3 includes: Preprocess the equipment side information model and the power system information model; The preprocessed device-side information model and power system information model are fused into static topology model and measurement model.

[0015] Furthermore, the method for preprocessing the device side information model and the power system information model includes: Add new models for the missing parts in the equipment side information model and the power system information model according to their own modeling specifications; Relate the same objects that exist in both models; If some objects are better described using the IEC61970 specification, the corresponding model in the power system information model is modified according to the IEC61970 modeling specification; if some objects are better described using the IEC61850 specification, the corresponding model in the device side information model is modified according to the IEC61850 modeling specification; For the missing parts in both the equipment side information model and the power system information model, they are newly created synchronously according to their own modeling specifications; and the missing parts of the enumeration are supplemented.

[0016] Furthermore, the method for fusing static topology models includes: fusing static topology models outside the substation and fusing static topology models inside the substation.

[0017] The method for integrating the static topology model outside the substation includes: integrating the topology information of the autonomous control area of ​​the IEC61968 active distribution network and the distributed energy into the second static topology model of the power system information model, adding the common equipment and conductive equipment outside the substation to the common equipment and conductive equipment enumeration types already in the second static topology model; adding the final entity equipment class to the conductive equipment or common equipment enumeration type of the second static topology model respectively; The method for fusing the static topology model outside the substation includes: the inter-class relationship between objects and containers in the substation and the object class jointly modeled by IEC61968 and IEC61850, based on the first static topology model in the equipment side information model, fusing the model into the first static topology model, modifying the parts of the first static topology model that are different from it; fusing the functions, sub-functions, sub-equipment models in the substation in the second static topology model and the association relationship between logical nodes and power system resources into the first static topology model.

[0018] Furthermore, the method for fusing measurement models includes: fusing the second measurement model in the power system information model into the first measurement model in the device side information model.

[0019] Further, step S4 includes: Build a fusion model using the DDS real-time IoT communication protocol; The device side information model and the power system information model are mapped into the fusion model.

[0020] Furthermore, the method of mapping the device side information model and the power system information model to the fusion model includes: Map the request / response service, request / non-response service, distributed general substation event, distributed sampling measurement value, report and log service group setting control of ACSI service in the device side information model to DDS topic; Based on the standardized service description language, the feeder groups and substations in the power system information model are mapped to the DDS domain to build the communication of IED devices.

[0021] Furthermore, the method for establishing communication of IED devices includes: Define the domain name of the IED communication data space and determine the communication scope of the IED; Define the topics that the IED communicates in its communication data space; Create an IDL file to define the data structure to be communicated; Use software middleware that complies with DDS communication specifications to convert IDL into program development language; Modify the variable assignment and communication frequency of specific communication data as required; Design and modify QoS configuration files according to requirements and establish service quality strategies that meet IED requirements.

[0022] The IEC61850 standard defines the information model for distributed energy information exchange and the communication and control interface for distributed energy equipment. The data model and logical nodes provided by IEC61850 can be used to expand the information modeling of key distributed energy equipment. It is understandable that the communication and control interface of new energy power equipment, as a type of distributed energy equipment, has been defined in the IEC61850 standard.

[0023] However, the IEC61850 standard is not sufficient to support the communication between new energy power equipment and other equipment in the power grid. The reason is that most of the distribution master stations in the power grid are modeled based on the common information model (CIM) of the IEC61970 standard, and the description of the topology model, measurement and control model are different from the IEC61850 standard.

[0024] During the research process, it was found that the data model based on the IEC61850 standard focuses on the specific control of the equipment, while the CIM model based on the IEC61970 standard focuses on the overall analysis of the power system. Since the model based on the IEC61850 standard and the CIM model have completely different semantics, direct data exchange cannot be achieved.

[0025] During the research process, it was also found that since both standards use an object-oriented approach to establish data models, it is possible to establish a corresponding mapping relationship and a connection between the models of the two standards, thereby realizing the expansion of the IEC61850 data model of new energy systems and equipment in the CIM model.

[0026] Aiming at the demand for rapid communication and processing of massive data in distribution networks and supporting distributed energy collaborative control for feeder autonomy, the present invention provides a distributed energy information modeling method for on-site coordinated control of active distribution networks, solves the problem of model fusion between terminal devices and master station systems, establishes a unified, lightweight, object-oriented information model for distributed energy collaborative control, and realizes reliable and real-time exchange of information between devices and between devices and between devices and master stations.

[0027] Compared with the prior art, the present invention has the following beneficial effects: The present invention constructs an intelligent electronic device information model and a distributed energy information model based on IEC61850, merges the intelligent electronic device information model and the distributed energy information model into a device-side information model, and performs a CIM expansion of distributed energy based on the IEC61970 power system information model. Since the device-side information model and the power system information model adopt different standards, the corresponding communication methods and data definitions are different, and data interaction cannot be performed directly, so the two models are merged to construct an intermediate fusion model, so as to map the data of the device-side information model and the power system information model according to the fusion model, thereby realizing data interaction between the distributed energy system and the power system.

[0028] The new distribution network requires that information can be exchanged efficiently, and must have the flexibility to support large-scale systems, as well as the basis for all parties in the system to access or exit at any time and anywhere. Therefore, the present invention selects DDS as the transport layer and upper layer protocol standard to meet the requirements of real-time, high flexibility and robustness. Finally, based on the standardized service description language (IDL), a mapping relationship is established between the data fields of the protocol and the model class attributes to solve the problems that the traditional power grid communication protocol is non-object-oriented, has poor scalability, and cannot exchange device models. The consumer-grade Internet of Things communication protocol is slightly insufficient in security and real-time performance, and cannot support real-time applications of microgrids.

[0029] The present invention solves the model fusion problem between terminal equipment and distributed energy and the master station system, establishes a unified lightweight object-oriented information model for the coordinated control of distributed energy, and realizes reliable and real-time information exchange between equipment and equipment and between equipment and the master station. The present invention can realize that intelligent electronic devices have plug-and-play functions, can self-describe, self-identify, self-discover, and self-network, without the need for manual configuration of point tables, which can greatly reduce the workload of on-site debugging and maintenance, reduce construction and operation costs, and support efficient real-time information interaction for coordinated control of distributed energy, bringing direct benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The present invention is further described in detail below in conjunction with the accompanying drawings.

[0031] Figure 1 : Flowchart of the present invention; Figure 2 : Schematic diagram of intelligent electronic device model data class based on IEC61850; Figure 3 : Example of logical nodes of a photovoltaic system; Figure 4 : Schematic diagram of the overall architecture of the fusion model of the present invention; Figure 5 : Data communication application model of DDS real-time Internet of Things communication protocol. DETAILED DESCRIPTION

[0032] In order to better understand the present invention, the content of the present invention is further clearly described below in conjunction with the embodiments and the accompanying drawings, but the protection content of the present invention is not limited to the following embodiments. In the following description, a large number of specific details are provided to provide a more thorough understanding of the present invention. However, it is obvious to those skilled in the art that the present invention can be implemented without one or more of these details.

[0033] First, the relevant standards involved in the embodiments of this application are explained: IEC61850: It is a standard that defines the devices within the substation automation system and how they interact with each other, providing a systematic way to describe devices and systems.

[0034] IEC61970: Provides a Common Information Model (CIM). CIM provides a standardized method to describe power system resources as object classes, attributes, and the relationships between them. For ease of management, classes in CIM are organized into multiple packages. Packages are a method of artificially grouping related model elements. A package represents a combination of model elements related to a specific content, often for certain specific application scopes.

[0035] IEC61968: It is part of the CIM model and can be regarded as an extension of IEC61970. It proposes the concept of power equipment assets. The Asset class is a base class for power equipment assets. It mainly models power grid equipment from the perspective of physical equipment entities, focusing on the basic properties of physical equipment, including the classification, properties, and composition of physical equipment.

[0036] In this application, the intelligent electronic device information model, distributed energy information model and device side information model are constructed based on the IEC61850 specification; the power system information model is constructed based on the IEC61970 specification.

[0037] Example 1: See Figure 1-Figure 5The purpose of this embodiment is to provide a distributed energy information modeling method for local coordinated control of an active distribution network, including: S1. Based on intelligent electronic devices and distributed energy systems, establish a device-side information model in accordance with the IEC61850 standard; S2. Based on the extension principle of IECCIM, the power system information model is extended with CIM for distributed energy at the master station side; S3, integrating the static topology model and the measurement model of the equipment side information model and the power system information model after CIM expansion; S4. Use protocol mapping to build a fusion model, and use the fusion model to map the data of the device side information model and the power system information model to achieve data interaction between the distributed energy system and the power system.

[0038] Furthermore, step S1 includes: S11, constructing an intelligent electronic device information model; S12, constructing a distributed energy information model; S13, constructing a device-side information model based on the intelligent electronic device information model and the distributed energy information model.

[0039] Specific: S11. Construct an information model of intelligent electronic devices.

[0040] (1) Define the model data class of intelligent electronic devices (IED) according to IEC61850.

[0041] like Figure 2 As shown in the figure, the model data class of IED is divided into four levels from top to bottom: server, logical device (LD), logical node (LN) and data object (DO); data object includes data and data attributes.

[0042] Modeling principles of physical devices: A physical device is an IED, which is modeled as a device object. A physical device should contain one or more server objects (generally one server object, when the physical device is a gateway, the device can contain multiple server objects). The server object should contain at least one LD object, and each LD object should contain 3-n LN objects.

[0043] Server modeling principles: Server represents the externally visible behavior of a device. Each server should have at least one access point, which can communicate with substation-level devices and process-level devices. In a communication network, a server is a functional node that can provide data or allow other functional nodes to access its resources, and use different access points to communicate with devices at different levels.

[0044] Modeling principles of logical device (LD) objects: LD is a virtual device that aggregates related logical nodes and data. IEC61850 does not specify how LD objects should be divided. Generally, some LN objects with common characteristics are aggregated together to form an LD model.

[0045] Modeling principles of logical nodes (LN): LN is the smallest unit used to exchange data functions. An LN represents a function within a physical device. Data and data attributes belonging to the same functional object should be placed in the same LN. Logical nodes exchange data through logical connections and then perform some specific operations.

[0046] (2) Provide a complete description of the functions and principles of the bay layer IED based on actual conditions.

[0047] (3) Analyze the logical structure of IED based on object-oriented thinking and replace the actual IED with logical devices.

[0048] The object-oriented modeling method uses object-oriented information modeling concepts, such as entities, relationships, attributes, etc., and uses mechanisms such as encapsulation, inheritance, and polymorphism to construct a method that simulates the real system.

[0049] (4) Decouple the functions of the IED, select appropriate logical nodes for each function, set the data and data attributes contained in each logical node, find out the data flow between logical nodes, and further analyze it using the unified modeling language tool.

[0050] (5) After completing the information model attributes of the IED, select the corresponding ACSI service according to the IEC61850 standard, specify the corresponding abstract communication service as the functional service of the information model for the information model attributes, and configure the ACSI control block attributes to form a complete intelligent electronic device information model.

[0051] S12. Construct a distributed energy information model.

[0052] The distributed energy information model adopts the same modeling specifications as the intelligent electronic device information model.

[0053] Distributed energy systems include a variety of equipment, which can be roughly divided into: switchgear, protection equipment, measuring equipment, metering equipment, converter equipment (voltage conversion equipment, current conversion equipment, frequency conversion equipment and power regulation equipment) and energy storage equipment, etc. For different equipment, refer to the object-oriented modeling technology in the IEC61850 standard for the division of levels, define the relevant nodes of each device, so as to build a model for each device, and then build a distributed energy information model of the entire distributed energy system.

[0054] (1) Based on the IEC61850 standard, a hierarchical information model of distributed energy resources (DER) is constructed.

[0055] Distributed energy (DER) architecture is divided into distributed energy units, distributed energy systems, local distributed energy systems, local power systems, power systems, etc. The distributed energy architecture is constructed based on the hierarchical characteristics of the electrical connections of the power system. Multiple groups of distributed energy units of the same type connected to the local bus through electrical connections can form a distributed energy system; multiple distributed energy systems are connected to the local power system through electrical connections, and connected loads can form a local distributed energy system; the local power system plus the local load are connected to the power system through an electrical connection.

[0056] According to the distributed energy architecture, DER units are photovoltaic, cogeneration, fuel cells, energy storage devices and other power generation or energy storage units; distributed energy systems are composed of an independent or multiple groups of similar distributed energy units connected to the bus; the local power system is a local supply and sales power system composed of multiple groups of distributed energy systems and local loads, which can also be called the power system of the local distributed energy system, and is the transmission and distribution system of the public power grid.

[0057] Construct a hierarchical information model of DER. Each intelligent electronic device (IED) in DER contains one or more servers, each server itself contains one or more logical devices, logical devices contain logical nodes, logical nodes contain data objects, and data objects are named by common data classes (CDCs) composed of data attributes. And by adopting instantiated logical node classes (compatible logical node classes) and data classes (compatible data classes) to agree on the intelligent semantics of distributed energy, the effective modeling of DER logical devices is realized.

[0058] (2) Establish logical nodes for distributed energy management.

[0059] Logical nodes corresponding to the logical devices involved in the electrical connection points of the distributed energy system; for example, common characteristics DCRP, operation characteristics DOPR, operation control authority DOPA and operation mode DOPM.

[0060] Logical nodes of the unit controller of the distributed energy system. For example, controller characteristics DRCT, status DRCS, control actions DRCC, active power and reactive power measurement MMXU for self-consumption, and switch closing and opening CSWI.

[0061] Logical nodes of logical devices involved in the power generation system of distributed energy systems, such as operation DGEN, rated parameters DRAT, advanced characteristics DRAZ, synchronization RSYN and PID regulator.

[0062] Logical nodes of logical devices involved in the excitation unit of the distributed energy system, such as excitation rated parameters DREX and excitation operation DEXC.

[0063] The logical node of the speed / frequency controller of the distributed energy system, such as the speed / frequency controller DSFC.

[0064] Logical nodes of the inverter / converter of the distributed energy system, such as rectifier ZRCT, inverter ZINV, nameplate data DRAT of the inverter, intermediate DC measurement MMDC, input AC measurement MMXU, output AC measurement MMXU and group cooling control CCGR for cooling fans.

[0065] The logical nodes of the fuel cell of the distributed energy system, such as the fuel cell controller characteristics DFCL, the fuel cell stack DSTK, the fuel processing module DFPM and the fuel characteristics MFUL.

[0066] The logical nodes of the logical devices involved in the photovoltaic system of the distributed energy system, such as the photovoltaic module rated parameters DPVM, photovoltaic array characteristics DPVA and photovoltaic array controller DPVC, thereby defining the logical nodes of the logical devices involved in the photovoltaic system.

[0067] Logical nodes of logical devices involved in the combined heat and power unit of the distributed energy system, such as controller DCHC, combined heat and power thermal storage DCTS and cooling system CCGR.

[0068] Logical nodes of logical devices involved in the generation protection unit between the distributed energy system and the power system, such as the basic logical node of relay protection PBRO, relay protection timing PBTC, low frequency protection PTUF and high frequency protection PTOF.

[0069] (3)Distributed power generation system modeling.

[0070] Distributed generation systems such as photovoltaic systems and wind power systems are effectively organized with energy storage units and loads, and can operate autonomously or in parallel with the grid through static switches.

[0071] In order for the distributed generation system to operate automatically, the established logic device needs the following functions: Switchgear Operation: Control and monitor the function of circuit breakers and disconnecting devices; Protection: The function of protecting power equipment and personal safety in the event of a fault. Many distributed generation systems also require a special function of "DC ground fault protection" to reduce the risk of fire and provide power surge protection; Measurement and metering: functions to obtain electrical measurements such as voltage and current; DC to AC conversion: used to control and monitor the inverter functions; Array operation: The function of maximizing the output power of the array. This includes adjusting the array current and voltage levels to obtain the maximum power point (MPP), and manipulating the tracking system to follow the movement of the sun; Island operation: The function of making the distributed generation system and the power system operate synchronously. It includes the anti-island operation requirements mentioned in the interconnection standards; Energy storage: The ability to store excess electricity generated by the system. In small distributed generation systems, batteries are usually used to store energy, while in larger distributed generation systems, compressed air or other methods can be used; Meteorological monitoring: The ability to obtain meteorological measurements such as solar radiation, wind speed and direction, and ambient temperature.

[0072] Taking the photovoltaic system as an example, in addition to the logical nodes required for distributed energy management, photovoltaic logic devices can also include Figure 3 The logical nodes shown.

[0073] (4) Energy storage system modeling.

[0074] An electrical energy storage system (EESS) is a system used for the intermediate storage of electrical energy. The type of storage, the amount of energy, the charge and discharge rates, the self-discharge rate and many other characteristics are technology dependent.

[0075] In the past, EESS was mainly used for backup purposes, providing electricity in emergency situations to replace conventional power sources. Today, EESS that needs to be connected to the grid not only stores electrical energy for later use, but also can provide and / or absorb electrical energy to and / or from the grid according to the operational requirements of the grid operator, aggregator or service provider. The EESS system is both a power generation system and a load system.

[0076] The charging operation of EESS is similar to that of a controllable load absorbing electrical energy from the grid, while the discharging operation is similar to that of a generator supplying power to the grid. Therefore, the characteristics of the energy storage system constructed include: data objects that are independent of the type of energy storage technology, such as charging state, maximum storage energy, charge and discharge round-trip efficiency, self-discharge rate, and capacity degradation rate; and data objects of specific energy storage types.

[0077] When the EESS supports the operation of the grid through a local or remote power management system, its capacity limitations must be taken into account. The information exchanged to determine these limitations includes: EESS attributes and EESS operating characteristics; EESS actual / predicted capacity and status values; EESS settings and direct commands from the power management system; As an option, the management of EESS operating functions can be achieved through mode or planned control.

[0078] To support the operation of new power systems, EESS should make better use of the complex capabilities of EESS, such as load transfer, frequency control, and generation tracking.

[0079] (5)Electric vehicle charging system modeling.

[0080] The participation of electric vehicles in grid regulation and optimization of grid operation is mainly reflected in the following aspects: peak shaving and valley filling, avoiding charging during peak hours through time planning, charging during valley hours, and discharging during peak hours in a planned manner; using electricity instead of fossil fuels will reduce users' transportation costs, such as charging during "low-price periods"; electric vehicles can be used as energy storage for distributed energy in the grid; electric vehicles can provide reactive power to support voltage stability.

[0081] The connection or "information exchange" between power grids, energy operators, electric vehicles and users is an essential component of the future electric vehicle transportation infrastructure.

[0082] From the grid point of view, the operation of AC and DC charging of electric vehicles is very similar. Technically, the difference lies in the placement of the charging equipment, AC charging for embedded charging and DC charging for separated charging, which has an impact on the communication requirements between the electric vehicle and the charging point. The real difference lies in the charging power service provided to the connected electric vehicle. Generally, dedicated off-line DC charging equipment provides higher charging power.

[0083] Therefore, the electric vehicle charging system is modeled from AC charging and DC charging. The electric vehicle can contain the following logical nodes: MMXU, MMTR, ZCAB, ZSAR, XCBR, FSCH, XSWI, DEAO, DEDO, DESE, DEEV, FUSE (DC charging system), XFUS (DC charging system).

[0084] (6) Modeling of SVG reactive power compensation device.

[0085] The basic principle of SVG is to use high-power power electronic devices (such as IGBT) that can be turned off to form a self-commutated bridge circuit, which is connected in parallel to the power grid through a reactor. By properly adjusting the amplitude and phase of the output voltage on the AC side of the bridge circuit, or directly controlling its AC side current, the circuit can absorb or emit reactive current that meets the requirements, thereby achieving the purpose of dynamic reactive power compensation.

[0086] SVG is a typical power electronic device, which consists of three basic functional modules: detection module, control operation module and compensation output module. Its working principle is that the current information of the external CT detection system is then analyzed by the control chip to obtain the current information, such as PF, S, Q, etc.; then the controller gives the compensation drive signal, and finally the inverter circuit composed of the power electronic inverter circuit sends out the compensation current.

[0087] The use of SVG in power grids can improve grid stability, increase transmission capacity, eliminate reactive power impacts, filter harmonics, and balance three aspects of the power grid.

[0088] S13. Construct a device-side information model based on the intelligent electronic device information model and the distributed energy information model.

[0089] According to the connection relationship between distributed energy and IDE, the intelligent electronic device information model and the distributed energy information model are integrated into the device side information model.

[0090] Further, in step S2, the power system information model on the master station side adopts the CIM specification (IECCIM) of IEC61970. The CIM specification uses the unified modeling language (UML) expression method to define CIM as a group of packages. The entire CIM is divided into the following packages: core package, topology package, wire package, outage package, protection package, SCADA package, measurement package, load model package, power generation package, production package, power generation dynamic package, domain package, energy plan package, reservation package, financial package, asset package; each package in CIM contains one or more class diagrams, which graphically display all classes in the package and their relationships. Then, each class is defined in text form according to the attributes of the class and the relationship with other classes. The basic classes included in CIM are: substation class, reference voltage class, interval class, conductive equipment class, endpoint class, equipment container, current relay class, protection equipment class, power system resource class, etc.

[0091] The IIEC61970 standard also provides CIM extension guidelines, which extend existing classes by adding attribute values ​​and properties, adding new class extensions through inheritance or association, and adding new packages as applications increase.

[0092] On the master station side, the CIM expansion of the power system information model for distributed energy involves the wire package (Wires), two sub-packages in the generation package (Generation), namely the power production package (Production) and the generation dynamics package (Generation Dynamics) and the domain package (Domaino).

[0093] At the same time, the photovoltaic, energy storage, wind power and other related categories of distributed energy are expanded in the power system resource category of the power system information model. Specifically, different types of distributed energy are expanded through the different access modes of distributed energy, namely power electronics access category and generator access category. The power electronics access type distributed energy is expanded to battery category, distributed photovoltaic category, inverter access wind power category, etc. in the power system information model, and the generator access type distributed energy is expanded to photovoltaic power station category, wind power station category, and cogeneration category in the power system information model.

[0094] Furthermore, in step S3, due to the different specifications adopted by the device side information model (based on IEC61850) and the power system information model (based on IEC61970), the corresponding communication methods and data definitions are different, and data interaction cannot be performed directly. Therefore, the two models need to be merged so as to realize data interaction between the distributed energy system and the power system based on the data of the mapped device side information model and the power system information model.

[0095] Step S3 includes: S31, preprocessing the device side information model and the power system information model; S32, performing static topology model fusion and measurement model fusion on the preprocessed device side information model and the power system information model.

[0096] Specific: S31. Preprocess the equipment side information model and the power system information model.

[0097] (1) For the missing parts in the equipment side information model and the power system information model, new modeling is added according to their own modeling specifications.

[0098] (2) Associating the same objects that exist in both models; (3) If some objects are better described using the IEC61970 specification, the corresponding model in the power system information model is modified according to the IEC61970 modeling specification; if some objects are better described using the IEC61850 specification, the corresponding model in the device side information model is modified according to the IEC61850 modeling specification; (4) For the missing parts in both the equipment side information model and the power system information model, they are rebuilt synchronously according to their own modeling specifications; (5) Supplement the missing parts of the enumeration.

[0099] S32, performing static topology model fusion and measurement model fusion on the preprocessed device-side information model and the power system information model.

[0100] (1) Static topology model fusion.

[0101] The power system information model includes the first static topology model of the IEC61968 specification. After the power system information model is extended by the CIM of distributed energy, the first static topology model also includes the relevant extended parts.

[0102] The equipment side information model also includes the second static topology model of the IEC61850 specification, which is mainly the SCL substation model (corresponding to the Substation part of the SCL configuration file), that is, describing the relationship between the equipment, logical nodes, functions, and containers in the substation. The second static topology model is expressed using UML.

[0103] The first static topology model and the second static topology model differ in three main aspects: modeling scope, definition method of the same object, and definition of inter-class relationships. When integrating static topology models, it is necessary to minimize changes to existing standards and make the descriptions of static topology models in the two standards as consistent as possible.

[0104] The static topology model that needs to be integrated is mainly divided into two parts, one is the static topology model outside the substation, and the other is the static topology model inside the substation: Since the second static topology model cannot express the part outside the substation, the off-station topology related classes of IEC61968, that is, the topology information of the autonomous control area of ​​the active distribution network and distributed energy, are integrated into the second static topology model. The models that need to be integrated outside the station can be divided into three parts: non-equipment class, conductive / ordinary equipment class, and inter-class relationship. Among them, the non-equipment class and inter-class relationship outside the IEC61968 station are not originally included in IEC61850, so they need to be newly created, and the ordinary equipment and conductive equipment outside the station need to be added to the existing ordinary equipment and conductive equipment enumeration types of the second static topology model, and the final entity equipment class (such as DER Inverter, PV Array, etc.) is added to the conductive equipment or ordinary equipment enumeration type of the second static topology model.

[0105] The part within the substation needs to be divided into four parts for fusion. Among them, the inter-class relationship between objects and containers and the object class jointly modeled by IEC61968 and IEC61850 are based on the first static topology model. The model is merged into the first static topology model, and the different parts of the first static topology model are modified; the relationship between functions, sub-functions, sub-equipment models and logical nodes and power system resources is a unique part of IEC61850. They are not involved in the IEC61968 model. Therefore, this part of the second static topology model is merged into the first static topology model, and this part of the model is newly created in accordance with the class naming and inter-class association construction style of IEC61968.

[0106] (2) Fusion of measurement models.

[0107] The power system information model includes the first measurement model of the IEC61968 specification, and the equipment side information model includes the second measurement model of the IEC61850 specification. The first measurement model and the second measurement model differ in three main aspects: the measurement value data structure and data type, timestamp, quality, unit type, and the association between the measurement and the static topology model. Measurement is unidirectional uplink information, so it is only necessary to ensure that the first measurement model can support the second measurement model so that the measurement can be easily identified or converted into IEC61968 messages on the master station side, that is, the second measurement model should be integrated into the first measurement model, and the second measurement model does not need to be changed, that is, unidirectional integration. The fusion steps are as follows: based on the data type of the measurement value of the second measurement model, modify the AnalogValue, DiscreteValue, and AccumulatorValue classes of the first measurement model; based on the SIUnit and multiplier attribute enumerations of the second measurement model, expand the enumeration values ​​of the UnitSymbol class and UnitMultiplier class of the first measurement model; based on the TimeStamp class of the second measurement model, modify the precision of the DateTime class of the first measurement model; based on the Quality class of the second measurement model, expand the Quality61850 and Validity classes of the first measurement model.

[0108] Furthermore, step S4 includes: S41, building a fusion model using a DDS (Data Distribution Service) real-time Internet of Things communication protocol; S42, mapping the device side information model and the power system information model into the fusion model.

[0109] DDS adopts a data-centric information exchange model. Some applications (publishers) publish data, and then remote applications (subscribers) that are interested in it obtain the data. Publishers and subscribers are independent of each other. They only care about how to transmit data in real time and reliably with minimal communication load. Figure 5 This step uses DDS to build a fusion model.

[0110] The method of mapping the device side information model and the power system information model to the fusion model includes: (1) Map the request / response service, request / non-response service, distributed general substation event, distributed sampling measurement value, report and log service group setting control of ACSI service in the device side information model to DDS topic; (2) Based on the standardized service description language (IDL), the feeder groups and substations in the power system information model are mapped to the DDS domain to build the communication of IED devices.

[0111] The method of mapping distributed general substation events to DDS topics: Distributed general substation events are directly mapped into the many-to-many publish / subscribe paradigm provided by DDS. Depending on the granularity required by the system, each event (or a fixed set of events) is mapped into a topic. On the other hand, each node interested in receiving an event must subscribe to the topic containing the event. Regarding the most relevant QoS parameters for such events, the transmission priority must be set to the highest level in the backbone and the reliability must be set to reliable to ensure that the event is delivered correctly.

[0112] Approach to Mapping Distributed Sampled Measured Values ​​(SMVs) to DDS Topics: Distributed sampled measured values ​​are mapped into the many-to-many publish / subscribe paradigm provided by DDS. Each monitored variable (or a fixed set of variables) is mapped into a topic, so the producer IED writes data into the topic to publish the information and other IEDs subscribe to the topic as per the application needs. Due to the nature of most substation automation systems, usually only the last available sample is relevant. Therefore, the history window parameter can be kept at a minimum of one sample and the reliability parameter can be set to best effort. The priority of each topic must be set based on the measured variable in the medium and high priority range. Due to the cyclical nature of this type of traffic, the deadline parameter can be enforced with a value slightly higher than the sampling period.

[0113] Methods for Mapping Reporting and Logging Services (RL) to DDS Topics: Mapping distributed sampling measurements to the DDS low-priority many-to-one publish / subscribe paradigm. The DDS standard provides an efficient mechanism for applications, called reporting, to track changes to subscribed system objects. Instead of periodically polling data attribute values, applications can group data attributes of interest into a dataset and ask the logical node hosting the dataset to report any changes to the members of the dataset.

[0114] Method to map request / no response services (RNR) to DDS topics: Map the distributed sampling measurements into the DDS client / server paradigm, where a single client requests a service from a provider (server). This is achieved by using one topic per service and identifying the server in the topic body. Since no response will be sent, the Reliability must be set to Reliable. The priority of these services is set to low, as most services of this class are typically non-critical.

[0115] Method for mapping request / response services (RR) to DDS topics: Unlike request / non-response services, they are synchronous blocking C / S calls (i.e. the client remains blocked until a response is received from the server). This behavior is achieved by using a pair of topics: one for the request and the other for the response. The client writes the request to the request topic and performs a blocking read until the response topic is received. This traffic is prioritized the lowest because these services are often used for non-critical operations.

[0116] The method of establishing the communication of IED devices includes: (1) Define the domain name of the IED communication data space and determine the communication scope of the IED; (2) Define the topics for IED communication in its communication data space; (3) Create an IDL file to define the data structure to be communicated; (4) Use software middleware that complies with the DDS communication specification to convert IDL into a programming language; (5) Modify the variable assignment and communication frequency of specific communication data according to needs; (6) Design and modify QoS configuration files according to requirements and establish service quality strategies that meet IED requirements; (7) Compile the code test executable file.

[0117] The overall architecture of the fusion model after protocol mapping between IEC61850+IECCIM object-oriented information model (i.e., equipment side information model and power system information model) and DDS is as follows: Figure 4As shown. The terminal side realizes functions such as device self-discovery, self-registration, data interaction, and topology synchronization based on object-oriented information model and DDS IoT communication. The IoT front-end server is deployed in the security access area to realize terminal equipment association configuration, communication condition monitoring, data interaction, topology management and other functions. The master station side is adaptively transformed to automatically generate terminals and maintain primary and secondary association relationships based on terminal registration and association information, and complete terminal information data analysis, application and display functions. The data information of the intelligent terminal is converted into an E file by the front end of the security access area and then transmitted to the production control area through the isolation device; the front-end server receives the file and parses the real-time data, converts it into a message of the D5000 platform and sends it to SCADA.

[0118] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Other modifications or equivalent substitutions made to the technical solution of the present invention by ordinary technicians in the field should be included in the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solution of the present invention.

Claims

1. A distributed energy information modeling method for local coordinated control of active distribution networks, characterized in that: include: S1. Based on intelligent electronic devices and distributed energy systems, establish a device-side information model in accordance with the IEC61850 standard; S2. Based on the extension principle of IECCIM, the power system information model is extended with CIM for distributed energy at the master station side; S3, integrating the static topology model and the measurement model of the equipment side information model and the power system information model after CIM expansion; S4. Construct a fusion model by using protocol mapping, and use the fusion model to map the data of the device side information model and the power system information model.

2. The distributed energy information modeling method for local coordinated control of active distribution network according to claim 1 is characterized in that: Step S1 includes: Construct the intelligent electronic device information model according to IEC61850 specification; Construct distributed energy information model according to IEC61850 specification; Construct the device side information model based on the intelligent electronic device information model and distributed energy information model.

3. The distributed energy information modeling method for local coordinated control of active distribution network according to claim 2 is characterized in that: The method for constructing an information model of an intelligent electronic device includes: defining a model data class of an IED device according to IEC61850; making a complete description of the functions and principles of an interval layer IED according to actual conditions; analyzing the logical structure of the IED according to object-oriented thinking, and replacing the actual IED with a logical device; performing a decoupling analysis on the functions of the IED, selecting appropriate logical nodes for each function, setting the data and data attributes contained in each logical node, finding out the data flow between logical nodes, and further analyzing it using a unified modeling language tool; after completing the information model attributes of the IED, selecting the corresponding ACSI service according to the IEC61850 standard, specifying the corresponding abstract communication service as the functional service of the information model for the attributes of the information model, and configuring the ACSI control block attributes to form a complete information model of an intelligent electronic device; The method for constructing a distributed energy information model includes: constructing a distributed energy layered information model based on the IEC61850 standard; establishing a logical node for distributed energy management; and modeling a distributed power generation system, an energy storage system, an electric vehicle charging system, and an SVG reactive compensation device respectively.

4. The distributed energy information modeling method for local coordinated control of active distribution network according to claim 1 is characterized in that: Step S3 includes: Preprocess the equipment side information model and the power system information model; The preprocessed equipment side information model and power system information model are fused into static topology model and measurement model.

5. The distributed energy information modeling method for local coordinated control of active distribution network according to claim 4 is characterized in that: The method for preprocessing the device side information model and the power system information model includes: Add new models for the missing parts in the equipment side information model and the power system information model according to their own modeling specifications; Relate the same objects that exist in both models; If some objects are better described using the IEC61970 specification, the corresponding model in the power system information model is modified according to the IEC61970 modeling specification; if some objects are better described using the IEC61850 specification, the corresponding model in the device side information model is modified according to the IEC61850 modeling specification; For the missing parts in both the equipment side information model and the power system information model, they are newly created synchronously according to their own modeling specifications; and the missing parts of the enumeration are supplemented.

6. The distributed energy information modeling method for local coordinated control of active distribution network according to claim 4 is characterized in that: The method of merging the static topology model includes: merging the static topology model outside the substation and merging the static topology model inside the substation; The method for integrating the static topology model outside the substation includes: integrating the topology information of the autonomous control area of ​​the IEC61968 active distribution network and the distributed energy into the second static topology model of the power system information model, adding the common equipment and conductive equipment outside the substation to the common equipment and conductive equipment enumeration types already in the second static topology model; adding the final entity equipment class to the conductive equipment or common equipment enumeration type of the second static topology model respectively; The method for fusing the static topology model outside the substation includes: the inter-class relationship between objects and containers in the substation and the object class jointly modeled by IEC61968 and IEC61850, based on the first static topology model in the equipment side information model, fusing the model into the first static topology model, modifying the parts of the first static topology model that are different from it; fusing the functions, sub-functions, sub-equipment models in the substation in the second static topology model and the association relationship between logical nodes and power system resources into the first static topology model.

7. The distributed energy information modeling method for local coordinated control of active distribution network according to claim 4 is characterized in that: The method for fusing measurement models includes: fusing a second measurement model in a power system information model into a first measurement model in a device-side information model.

8. The distributed energy information modeling method for local coordinated control of active distribution network according to claim 1 is characterized in that: Step S4 includes: Build a fusion model using the DDS real-time IoT communication protocol; The device side information model and the power system information model are mapped into the fusion model.

9. The distributed energy information modeling method for local coordinated control of active distribution network according to claim 8 is characterized in that: The method of mapping the device side information model and the power system information model to the fusion model includes: Map the request / response service, request / non-response service, distributed general substation event, distributed sampling measurement value, report and log service group setting control of ACSI service in the device side information model to DDS topic; Based on the standardized service description language, the feeder groups and substations in the power system information model are mapped to the DDS domain to build the communication of IED devices.

10. The distributed energy information modeling method for local coordinated control of active distribution network according to claim 9 is characterized in that: The method of establishing the communication of IED devices includes: Define the domain name of the IED communication data space and determine the communication scope of the IED; Define the topics that the IED communicates in its communication data space; Create an IDL file to define the data structure to be communicated; Use software middleware that complies with DDS communication specifications to convert IDL into program development language; Modify the variable assignment and communication frequency of specific communication data as required; Design and modify QoS configuration files according to requirements and establish service quality strategies that meet IED requirements.

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