Unified platform for planning and operation of power grid

Abstract

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for simulating power grid behavior. In some examples, a data model associated with a power grid is obtained. The data model stores static data and dynamic data, which may be continuously integrated into the data model based on data streams obtained from data sources associated with attributes of the power grid. A set of interface ports may be instantiated for querying data based on a data model. The query is related to data from at least one of a planning analysis modeling domain or an operational analysis modeling domain of a data model related to the power grid. A query associated with a first planning operation in a planning analysis modeling domain is executed. The query defines one or more nodes of the power grid and relates to a planning analysis domain.

Description

[0001] Cross-reference to related applications

[0002] This application claims priority to U.S. Provisional Application No. 63 / 583,049, filed September 15, 2023. The disclosure of the earlier application is considered part of the disclosure of this application and is incorporated herein by reference. Technical Field

[0003] This specification relates to power grids, and specifically to the planning and operational modeling of power grid systems. Background Technology

[0004] Power grids transmit electricity to loads such as residential and commercial buildings. Virtual models of power grids can be used to simulate operation under various conditions. Summary of the Invention

[0005] The techniques used to simulate the behavior of power grids are described.

[0006] Generally, this disclosure relates to a platform that integrates planning and operation tools associated with a power grid, enabling them to share public data schemas, data repositories, and database views exposed through a public interface (or view). The public interface or view can be associated with different access rights to different portions of data for different user roles. In some cases, users with an operator role can access subsets of data different from those with a planner role. In other cases, based on security configurations for different user roles, different user roles can be associated with different actions. For example, some user roles may be granted only viewing rights, while other user roles may have both viewing and editing rights. Different subsets of data associated with different data attributes accessible through a public view can be defined as accessible to users with different roles or groups.

[0007] Electricity grids can undergo continuous additions and / or changes. New buildings, renewable power plants, stationary storage units, mobile storage units, and expansions of existing buildings, facilities, and loads are some examples of potential changes that can be proposed and made to existing electrical systems, such as distribution feeders. As electricity grids become more complex and operational values ​​approach critical limits, providing information about the grid under different scenarios becomes more important and complex. Detailed interconnection studies can be performed to track the operational characteristics of the grid, collect data from different nodes of the grid, and align this data with data relevant to accurate operational planning. By providing an integrated platform for planning and operational tasks that offers a common view of data related to the electricity grid, the impact of interconnections between different operations related to the same elements of the grid but in different scenarios or domains can be comprehensively assessed and further used to improve the accuracy of operational and planning tasks, and also support continuous improvement processes for assessing the state of the electricity grid.

[0008] Power grid models and corresponding data models can be used to assess and predict operational and potential faults in the power grid. Conventional planning and operational tools are separate and not aligned or interconnected to feed data between each other for synchronization. Performing operational planning analyses may involve analyzing the current topology of the power grid. Operational tools can support the execution of actions related to nodes in the power grid (e.g., closing or opening circuit breakers) and can also feed power grid-related state (dynamic) data and / or historical data related to operations performed on the power grid as input data for operational planning tasks. In some cases, the topology of the power grid may change (e.g., after an outage such as due to natural disasters or severe weather conditions), and some connections between assets may be disrupted. In those cases, planning analyses can be initiated based on information about the current state of the power grid and working in conjunction with the changed topology to perform planning actions (e.g., working on predictions of future states).

[0009] Power grid models (e.g., as virtual models) can be generated to include representations of existing real-world power grid components, representations of planned power grid components, or a combination of representations of existing and planned power grid components.

[0010] In some cases, network modeling and simulation systems can perform simulations in response to requests for simulation results provided through a user interface or automatically triggered requests. These requests may be for outputs showing the operational impact of changes to the power grid, such as adding or removing power sources or loads. In other cases, the request may be for outputs showing the operational impact of events, such as lightning strikes or power outages at power plants connected to the grid.

[0011] The simulation system can use a calibrated high-resolution power grid model. The power grid model can include a model of the completed network, and can also include interconnections that have been approved but not yet constructed. The simulation system can use the power grid model to compare the network condition before the proposed interconnection with the predicted network condition after the proposed interconnection to identify the incremental effects of the interconnection.

[0012] This disclosure describes an implementation of an integrated planning and operation tool supported by a public platform that integrates data from multiple sources as a single source of fact that can be relied upon in both planning and operation use cases. For example, the planning tool can access historical operational data and identify patterns in the system (e.g., “specifications” or “weak links”) for managing power grid performance and use them as input for performing planning analyses. The proposed planning and operation tool is integrated to work with the same data model associated with the physical model of the power grid. The data model can integrate data from different sources (e.g., sensors, external services such as weather providers, traffic condition providers, etc.) and map different data points of the network model (associated with network nodes) to different types of data related to different aspects of the power grid.

[0013] Other embodiments of the foregoing aspects include corresponding systems, apparatuses, and computer programs configured to perform actions of methods encoded on a computer storage device. Details of one or more embodiments of the subject matter described herein are set forth in the accompanying drawings and the following description. Further features, aspects, and advantages of the subject matter will become apparent from the description, drawings, and claims. Attached Figure Description

[0014] Figure 1 An example computer system architecture that can be used to run embodiments of this disclosure is shown.

[0015] Figure 2 This is a flowchart of an example method for exposing an interface to query operational and planning data for an integrated data model view according to embodiments of this disclosure.

[0016] Figure 3 This is a flowchart of an example method for integrating inputs from planning into operation according to embodiments of the present disclosure.

[0017] Figure 4 This is a flowchart of an exemplary method for optimizing a power grid based on simulation of planning operations using real-time operational data, according to embodiments of the present disclosure. Detailed Implementation

[0018] Generally speaking, this disclosure relates to performing planning and operational modeling of power grid systems.

[0019] A power grid is an interconnected network of power sources, electrical loads, and power transmission and regulation components.

[0020] Conventional planning and operation tools are separate and not aligned or interconnected to feed data between each other for synchronization. Performing operation planning analysis may include analyzing the current topology of the power grid. Operation tools may support actions related to nodes in the power grid (e.g., closing or opening circuit breakers) and may also feed power grid-related status (dynamic) data and / or historical data related to operations performed on the power grid as input data for operation planning tasks.

[0021] This disclosure describes implementations supporting the integration of planning and operation tools through a public platform that integrates data from multiple sources as a single source of fact that can be relied upon in both planning and operation use cases. For example, planning tools can access historical operational data and identify patterns in the system (e.g., “specifications” or “weak links”) for managing grid performance and use this as input for performing planning analyses. In some cases, planning tools can access historical data to predict the future state of the power grid at a given point in time. The proposed planning and operation tools are integrated to work with the same data model representing the physical power grid. The data model can integrate data from different sources (e.g., sensors, images, surveys, physical inspections, data from external services such as weather providers, traffic condition providers, etc.) and map different data points (related to network nodes) of the network model to different types of data related to different aspects of the power grid.

[0022] In some instances, the integration platform can expose query views of the data model that can be used in planning and / or operational scenarios. Query views can expose the same or different types of data for nodes of the power grid under query-type scenarios. When performing planning analyses, operational task runs, and / or simulations in scenarios involving the planning or modification of the power grid model, the integration platform can support query runs that can correlate different types of data for a given node of the power grid.

[0023] In some instances, an integration platform can support operational and planning tasks related to any or both of the transmission or distribution of electricity. Operational tools may rely on real-time data from sensors and network automation (automatic control). The integration platform may include different management groups and access / input restrictions for different groups or user roles to facilitate the execution of tasks requested by planners or operators interacting with grid-related data. In some cases, users of the integration platform may not have direct access to grid-related data in its raw form, for example, due to considerations of personally identifiable information. In some of those cases, the data available to users may be processed data within permissible limits and suitable for performing actions such as grid planning operations. For example, operational users may control network operations, but planning users may only view current operations and run simulations on a defined planning model without the right to modify the network model. The operation of the power grid can be simulated based on a computer model of the network.

[0024] In some implementations, power grid assets can have different operating parameters or setpoints associated with operation during different states of the power grid. Data on the state of network nodes can be collected as a data stream from sensors or devices monitoring the physical state of the nodes. This time-series data can be used to define the current state of the power grid, as well as to generate average states for unknown temporary performance peaks, and can better represent the state over a predefined time span that reflects the network's regular behavior.

[0025] Figure 1 An example computer system architecture that can be used to run embodiments of this disclosure is shown. System 100 includes an integrated platform environment 105, which includes a power grid model 115, a power grid data model 120, a view panel 125, a query engine 130, a simulation engine 140, a user database 150, and a license configuration 160.

[0026] In some instances, view panel 125 can receive interactions from users (such as user 112) regarding queries related to running operations and / or planning tasks.

[0027] In some instances, when a request is received at view panel 125, view panel 125 can generate a query based on data obtained from the power grid data model 120, and run the query at query engine 120. The query engine can query data from data model 120 and power grid model 115 to provide query results that can be output to the user interface. Query requests can be associated with planning operations that define one or more nodes of the power grid and involve planning domain data from data model 120.

[0028] In some implementations, after running a query and providing output, modifications to the current state of the network can be suggested, where such modifications can be received as user input. Based on the suggested modifications, a simulation of the power grid's behavior can be performed, and a recommendation on whether to adopt the modifications can be provided based on the obtained simulation results. In some cases, the simulated behavior can be evaluated to determine whether the determined new performance of the network associated with the modification is higher than the performance of the network before the modification, for example, by having at least a threshold higher than the performance value. The view panel and query engine 130 can communicate with simulation engine 140 to serve requests from users and provide assessments of the current and future states of the power grid.

[0029] The simulation engine 140 may be provided as one or more computer-executable software modules, hardware modules, or a combination thereof. For example, the simulation engine 120 may be implemented as a block of software code with instructions that cause one or more processors of the simulation server 110 to perform the operations described herein. Additionally or alternatively, the simulation engine 120 may be implemented as electronic circuitry, such as programmable logic circuitry, field-programmable arrays (FPGAs), or application-specific integrated circuits (ASICs).

[0030] The integrated platform environment 110 may be part of a cloud computing platform. The integrated platform environment 110 may be maintained and operated, for example, by an administrator of the power utility or by a third party.

[0031] User equipment 102 can communicate with integrated platform environment 110 via, for example, network 106. Network 106 may include public and / or private networks, and may include the Internet. User equipment 102 may be an electronic device, such as a computing device. User equipment 102 may be, for example, a desktop computer, laptop computer, smartphone, cellular phone, tablet computer, PDA, etc.

[0032] User device 102 may display both an input user interface 107 and an output user interface 108. The input user interface 107 may include input forms to allow users to enter requests, such as queries related to performing planning operations or operational analysis tasks. Typically, users can provide requests or queries through the input user interface. The input user interface includes input fields for various types of data. For example, the input user interface includes input fields for location, change, scenario, data source, and the requested output. In some examples, the input user interface 106 may include more or fewer input fields. The input user interface 106 may include input fields in various formats. For example, the input user interface 106 may include input fields with drop-down menus, slider icons, text input fields, maps, optional icons, search fields, etc.

[0033] In some implementations, the power grid model 115 may include high-resolution electrical models of one or more distribution feeders. The power grid model 115 may include data models of, for example, substation transformers, distribution switches and reclosers, voltage regulation schemes (e.g., tapped magnets or switched capacitors), network transformers, load transformers, inverters, generators, and various loads. The power grid model 115 may include line models, such as electrical models of medium-voltage distribution lines. The power grid model 115 may also include electrical models of stationary and switched line capacitors and other power grid components and equipment.

[0034] The power grid model 115 may include a topological representation of a power grid or a portion thereof. The detail of the power grid model 115 may be sufficient to allow for accurate simulation and evaluation of the power grid's state.

[0035] The power grid model 115 can include different versions of the same power grid. Each version can represent the past, present, and future states of the network, including changes in topology over time, such as the introduction of new assets and changes in switch locations. This enables the analysis of past behavior as well as a range of planned or hypothetical future scenarios. Different versions of the power grid model 115 can represent anticipated power grid designs, as-built designs, operational designs, and future versions representing combinations of planned and hypothetical equipment modifications, additions, removals, and replacements.

[0036] The power grid model 115 can use machine learning to fill in gaps in model information that is unknown or known with low confidence, adapting to different confidence levels. For example, if insufficient connectivity data is provided, the model can be automatically augmented with connectivity information derived from computer vision processing. For instance, the power grid model 115 may include probabilistic models for the electrical properties of network devices, power consumption, power generation, and estimated asset health and asset failures.

[0037] In some implementations, the power grid model 115 may be associated with the data model 120. The data model 120 may include a set of elements organized into a hierarchical structure. The elements of the data model are mapped to at least a portion of data obtained from at least two data streams from power grid nodes, wherein the data from the at least two data streams overlap with a set of attributes of the elements.

[0038] In some implementations, when a query request is received at view panel 125, where the query is used to run planning operations, data from data model 120 can be invoked, where the data comes from the relevant domain used for the operation.

[0039] In some implementations, view panel 125 may include interfaces from a set of interfaces predefined for different types of queries and use case scenarios. In some instances, different interfaces may be associated with different user groups or users with different user roles. This set of interfaces may be predefined for a set of user groups, including a planner user group and an operations user group. For example, view panel 125 may include a first interface associated with the planner user group, which is associated with the planning analysis modeling domain. In this example, at least a portion of the data from the planning analysis modeling domain is available for editing by users of the planner user group and is only available for viewing by users of the operations user group. Furthermore, at least a portion of the data from the operations analysis modeling domain is available for editing by users of the operations user group and is only available for viewing by users of the planner user group.

[0040] In some instances, the functionality provided through view panel 125 can be configured based on accounts defined for the integration platform and access permissions configured for different user roles. In some instances, different access rights can be granted to different users with specific user roles within the integration platform environment to access specific portions of the data in data model 120. In some cases, users with the operator role can access subsets of data different from those with the planner role. Different subsets of data associated with different data attributes accessible through the public view can be defined as being accessible to users with different roles or groups.

[0041] The integrated platform environment 105 stores user data in a user database 150, including data on user roles and / or user groups. Different accounts can be configured at the platform, and these accounts can include some or all of the roles defined for the platform. Access permissions can be established at the account level, user role / group level, ad hoc configuration, or a combination thereof. The platform environment 105 can store permission configurations 160 for data from the data model 120, as well as the corresponding user roles / groups defined in the user database 150.

[0042] In some implementations, simulations can be performed regarding the behavior of the power grid, including various modifications to at least a portion of the network. Such modifications can be defined according to network model 115. Data model 120 can derive probabilistic information from the history and current version of the power grid model 115, as defined in its current state and previously recorded states. For example, to predict the impact of future modifications to the power grid, the impact of previous similar modifications to the power grid can be considered, and simulations of predefined test scenarios can be run, mimicking key or relevant use cases associated with previous states of the power grid. The power grid model 115 can also incorporate and analyze historical data from the power grid across various geographical locations. In this way, the power grid model 115 can use machine learning to identify trends and patterns to predict future equipment performance.

[0043] The power grid model 115 can be adaptive, such that changes in one aspect of the power grid model 115 persist to all other aspects. For example, a new reverse connection resource can be connected to the power grid. The power grid model 115 can receive and incorporate data indicating the new resource. Such changes in the power grid model 115 can be correlated with corresponding changes in the data model 120 to track data associated with the nodes of the power grid model 115.

[0044] The power grid model 115 can consider the interdependencies of energy systems outside the power grid, such as electrical components of natural gas storage, distribution, and generation systems. The data model 120 can store data for the nodes of the power grid model 115 and model their interactions with other systems. For example, a backup power system interacting with the main power system can be modeled relative to the main power system portion of the power grid model 115. For example, battery and solar power systems can be replaced by diesel generator systems. Detailed models of all interacting subsystems can be executed, with associated simulations of all normal, abnormal, and corner conditions.

[0045] Data model 120 can be calibrated using measured power grid data. Measured power grid data can include historical network operation data. Historical network operation data can be collected over a period of time (e.g., weeks, months, or years). In some examples, historical network operation data can be averaged historical operation data. For example, historical network operation data can include the electrical load of a substation during a specific time period of a year, which is an average over many years. In another example, historical network operation data can include the number of voltage violations in the power grid during a specific time period of a year, possibly on average over many years, or otherwise statistically represented.

[0046] In some examples, data model 120 may include measurement data for certain time intervals (e.g., certain hours) and may not include measurement data for other time intervals for nodes in the power grid. Based on the evaluation of data from data model 120, hypothetical calculations can be performed to estimate or interpolate network operation data for time intervals where measurements are unavailable. Hypotheses may be, for example, hypothetical relationships between loads at a specific location at night compared to daytime, which may be based on evaluations of data related to the operational domain and associated with power grid nodes at a specific location. In another example, a hypothesis may be hypothetical relationships between loads at a specific location during the same time period of a day in summer compared to the same time period of a day in winter.

[0047] In some examples, data model 120 may include measurement data for certain characteristics (e.g., electrical load) and may not include measurement data for other characteristics. Data model 120 may use assumptions to estimate network operating data for characteristics for which its measurements are not available. Assumptions may be, for example, hypothetical relationships between load and voltage at a specific location on the power grid.

[0048] The simulation engine 140 can define the configuration model of the power grid model 115 based on the received query request and the definition or modification of the current state of the power grid model 115.

[0049] In some implementations, the simulation engine 140 includes a rule set that defines various combinations of user inputs for simulating requests and appropriate configuration models for each combination of user inputs to simulate the operation of the power grid and provide predictions of the power grid's state for certain modifications.

[0050] In some implementations, the power grid elements within network model 115 may have different operating parameters or setpoints for steady-state operation compared to transient operation. These parameters may be reflected in elements of data model 120 mapped to the power grid elements within network model 115. For example, a circuit breaker may have a time delay for current or overvoltage tripping, tripping only after a short period of time (a fraction of a second). The power grid network model 115 incorporates network node and load models, which can be used as a first-class dataset for running planning operations within the planning scenario.

[0051] The various network components in a computer model can include two additional sets of operating parameters or setpoints, each associated with a simulation at a different time resolution. The computer model can have separate operating parameters for each component in both steady-state and transient domains. For example, the control settings for a generator can be varied or at least simulated differently at different time scales.

[0052] Locations within the power grid can include geographical locations identified by simulation request 108. For example, a location can include a postal address or latitude and longitude coordinates.

[0053] The simulation engine 140 can then perform a series of simulations. These simulations can be based on, for example, root mean square (RMS), power flow, positive sequence, and / or time-series voltage transient analysis. The amount of data processed during each simulation can depend on the size and framework of the network section being evaluated. The simulations can analyze the predicted impact on all connections to the affected distribution feeder and on all components of the affected distribution feeder. Therefore, the complexity of the simulation can vary depending on the construction of the distribution feeder.

[0054] For example, simulations can vary depending on the length, power, and number of loads on distribution feeders. Typical distribution feeder lengths can range from approximately one mile to ten miles. Typical distribution feeder power can range from approximately one megawatt to ten megawatts. The number of loads connected to the feeder can range from hundreds to thousands of residential loads. In some cases, there may be as few as a few dozen commercial or industrial loads, and as many as hundreds. A similar situation may arise with transmission lines. For example, simulations can vary depending on the length, power, and number of power sources in the transmission network. Similarly, simulations, simulation parameters, and grid topology can vary significantly based on the location of the grid being simulated (e.g., urban vs. rural, and in different countries).

[0055] The construction of distribution feeders can also vary based on location. In urban environments, residential loads typically share transformers. In rural environments, each residential load may have its own transformer. Three-phase transformers typically serve commercial and industrial loads. Therefore, the number of loads and transformers in a feeder can be as low as a few hundred loads, with rural feeders having several hundred transformers. In urban environments, the number of loads and transformers in a feeder can be as high as thousands of loads and hundreds of single-phase transformers, coupled with dozens or hundreds of larger three-phase loads and transformers.

[0056] In some examples, simulation engine 140 can simulate the operation of multiple feeders. For instance, the simulation may include analyzing the operation of all feeders across a geographic region (e.g., city, county, province, or state). In some cases, simulation engine 120 may model the operation of each individual feeder within a region and may aggregate the results to model the operation of multiple feeders within the region.

[0057] The simulation engine 140 can analyze the expected operation of a power grid by applying historical empirical data to a network model. Historical empirical data can include historical grid characteristics based on, for example, measurements, calculations, estimates, and interpolations. Characteristics can include, for example, load, voltage, current, and power factor. This historical empirical data can represent the operation of a power grid across multiple interconnected components within a specified geographic area. Historical empirical data can represent average grid operating characteristics over a period of time (e.g., weeks, months, or years).

[0058] In some examples, the simulation can cover a range of operating conditions, particularly extreme voltage and load conditions from large-capacity power systems (BPS) and distribution feeders. Simulation engine 140 can simulate corner cases of the system with proposed interconnections added to an existing system. The simulation can also cover grid conditions during both steady-state and transient operation. Simulation engine 140 can accurately simulate the operation of loads and sources, aggregated loads and sources, and decomposed loads and sources.

[0059] Figure 2 This is a flowchart of an example method 200 for exposing an interface to query operational and planning data, according to embodiments of this disclosure. Method 200 can be used in, for example... Figure 1 It runs in the integrated platform environment of 110.

[0060] At point 205, a data model associated with the power grid is obtained. The data model can be essentially similar to... Figure 1 Data model 120. The power grid and its structure and topology can be modeled in network models (such as...). Figure 1 The data model is modeled in a power grid model (115). In some implementations, the data model stores static and dynamic data, both of which are related to the power grid in the time dimension. Static and dynamic data are continuously integrated into the data model based on data streams obtained from a set of data sources related to power grid attributes. In some instances, the data model stores a representation of the power grid, where static data includes information about the location of grid assets, connectivity between assets, and parameters (e.g., rated voltage levels). Dynamic data may include time-series data, which includes historical states of grid assets (e.g., equipment), power flow data, voltage, current, or other data readings over a given time span.

[0061] At position 210, a set of interfaces for querying data based on the data model is exposed. This set of interfaces can be accessed through the platform's view panels (such as...). Figure 1 The view panel 125 is exposed. The interface can receive data-related queries from at least one of the planning analysis modeling domain or the operational analysis modeling domain in the data model related to the power grid.

[0062] In some instances, the functionality for querying the data model can be configured for different user groups in different ways. For example, users with different roles can be granted permission to access different data sets from the data model, each data set being associated with a task performed for that role.

[0063] For example, in planning application scenarios, users in the role of planners can be given direct access to meter data related to one or more assets of the power grid to perform load modeling and forecasting tasks.

[0064] At point 215, at the platform (e.g., in providing an integrated platform environment (such as...) Figure 1 The integrated platform environment (110) loads the interface at the integrated planning and operation platform. This interface is associated with the user of the first user role among the multiple roles defined at the integrated planning and operation platform.

[0065] At position 220, identify a set of access permissions associated with the first user role.

[0066] At point 225, user interface elements are presented within the interface, where each element is associated with an operation that can be performed by the user. These user interface elements can be mapped to corresponding elements in the data model accessible to the first user role.

[0067] At position 230, a query associated with the first planning operation in the planning analysis modeling domain is executed. The query defines one or more nodes of the power grid and relates to the planning analysis modeling domain. The execution of the query is based on data related to the current state of the power grid, which is defined from the data model and relates to one or more nodes of the power grid in the operational analysis modeling domain.

[0068] Figure 3 This is a flowchart of an example method 300 for integrating inputs from planning into operation according to embodiments of the present disclosure. Method 300 can be used in, for example... Figure 1 It runs in the integrated platform environment of 110.

[0069] At point 310, a planning operation is executed via a query view requested by an integrated planning and operations platform. The planning operation relates to the behavior of at least one area of ​​the power grid. The query view exposed by the platform (e.g., similar to...) Figure 1 and Figure 2 The query view can be exposed based on a data model that integrates planning and operational data associated with the power grid. The data model can be essentially similar to... Figure 1 Data model 120. Planning operations are performed based on data related to the current state of the power grid determined by the data model. The execution of planning operations may include the following steps.

[0070] At position 315, determine the first set of values ​​for the corresponding parameter to the set of operational parameters used in the query. The first set of values ​​is associated with the first time dimension.

[0071] At position 320, output from the planning operation is generated, where the output is evaluated according to the planning state criteria.

[0072] At point 325, one or more proposed modifications to the current state of the power grid are identified based on an assessment of the output according to the planning state criteria.

[0073] At point 330, one or more suggested modifications are used to simulate the behavior of at least one region of the power grid.

[0074] At point 335, simulation-based recommendations for modifications to the power grid can be provided.

[0075] Figure 4This is a flowchart illustrating an exemplary method for optimizing a power grid based on simulation of planning operations using real-time operational data, according to embodiments of the present disclosure. Method 400 can be used in, for example... Figure 1 It runs in the integrated platform environment of 110.

[0076] At point 410, data from the power grid is obtained to generate a data model that integrates operational and planning parameters related to the power grid. The data model can be essentially similar to... Figure 1 , Figure 2 and Figure 3 The data models discussed. Network models used in power grids (such as...) Figure 1 The power grid model (115) is defined as a network model that interconnects network nodes in a graphical structure.

[0077] At point 420, input is obtained as a result of a simulation run of the planning operation, which is based on modifications to at least one parameter value of at least one planning parameter from a data model of the power grid. The simulation run can be substantially similar to... Figure 3 The simulation discussed at points 325 and 330 is also relevant. The input obtained at point 415 may include proposed modifications to the parameter values ​​for at least one operating parameter of at least one network node in the power grid. For example, this can be achieved through... Figure 1 The view panel receives such input.

[0078] At 430, at least a portion of the first behavior of the power grid is simulated based on the modification of the parameter value of at least one operating parameter of at least one network node in the network model.

[0079] At 440, the simulation results from the first action are provided as output, where the output may include modifications to the power grid that define an improved state of the power grid.

[0080] This disclosure generally describes methods, software, and systems for computer-based visualization of power grids. The computing system can receive various power grid data from multiple sources. The power grid data may include different temporal and spatially related characteristics of the power grid. These characteristics may include, for example, power flow, voltage, power factor, feeder utilization, and transformer utilization. These characteristics may be coupled; for example, some characteristics may affect other characteristics and / or their temporal and spatial dependencies may be related.

[0081] Data sources can include satellite and aerial imagery databases, publicly available government power grid databases, and utility provider databases. Sources can also include sensors installed within the power grid by network operators or others, such as power meters, ammeters, voltmeters, or other sensing devices connected to the grid. Data sources can include databases and sensors used in high-voltage transmission and medium-voltage distribution, as well as low-voltage power consumption systems.

[0082] The data may include, but is not limited to, map data, transformer locations and capacities, feeder locations and capacities, load locations, or combinations thereof. The data may also include measurement data from various points in the power grid, such as voltage, power, current, power factor, phase, and phase balance between lines. In some examples, the data may include historically measured power grid data. In some examples, the data may include real-time measured power grid data. In some examples, the data may include analog data. In some examples, the data may include a combination of measured and analog data.

[0083] The embodiments of the subject matter and functional operations described in this specification can be implemented in digital electronic circuits, in tangibly implemented computer software or firmware, or in computer hardware, including the structures disclosed in this specification and their structural equivalents, or combinations thereof. Embodiments of the subject matter described in this specification can be implemented as one or more computer programs, i.e., one or more modules of computer program instructions encoded on a tangible, non-transitory program carrier, for execution by a data processing apparatus or for controlling the operation of a data processing apparatus. The computer storage medium can be a machine-readable storage device, a machine-readable storage substrate, a random or serial access memory device, or combinations thereof.

[0084] The term "data processing apparatus" refers to data processing hardware and encompasses all kinds of devices, apparatuses, and machines for processing data, including, for example, programmable processors, computers, or multiple processors or computers. The apparatus may also be or further include special-purpose logic circuitry, such as a central processing unit (CPU), a field-programmable gate array (FPGA), or an application-specific integrated circuit (ASIC). In some embodiments, the data processing apparatus and / or special-purpose logic circuitry may be hardware-based and / or software-based. The apparatus may optionally include code that creates an operating environment for computer programs, such as code constituting processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of these. This disclosure contemplates the use of data processing apparatuses with or without conventional operating systems (e.g., Linux, UNIX, Windows, Mac OS, Android, iOS, or any other suitable conventional operating system).

[0085] A computer program, also referred to or described as a program, software, software application, module, software module, script, or code, can be written in any form of programming language, including compiled or interpreted languages, or declarative or procedural languages, and can be deployed in any form, including as a standalone program or as a module, component, subroutine, or other unit suitable for use in a computing environment. A computer program may, but does not necessarily, correspond to a file in a file system. A program may be stored as a portion of a file containing other programs or data, for example, as one or more scripts stored in a markup language document, as a single file dedicated to the program in question, or as multiple coordination files, for example, as a file storing one or more modules, subroutines, or code portions. A computer program may be deployed on a single computer or located at a single site or distributed across multiple sites and interconnected by a communication network for execution. While portions of a program shown in the various figures are depicted as separate modules implementing various features and functions through various objects, methods, or other processes, a program may alternatively and appropriately include multiple submodules, third-party services, components, libraries, etc. Conversely, the features and functions of various parts may be appropriately combined into a single part.

[0086] The processes and logic flows described in this specification can be executed by one or more programmable computers that execute one or more computer programs to perform functions by manipulating input data and generating outputs. The processes and logic flows can also be executed by dedicated logic circuitry, and the device can be implemented as dedicated logic circuitry, such as a central processing unit (CPU), a field-programmable gate array (FPGA), or an application-specific integrated circuit (ASIC).

[0087] Computers suitable for executing computer programs include, for example, central processing units (CPUs) that may be based on general-purpose or special-purpose microprocessors or both, or any other type. Typically, the CPU receives instructions and data from read-only memory or random access memory or both. The basic components of a computer are the CPU for executing or running instructions and one or more memory devices for storing instructions and data. Typically, a computer will also include one or more mass storage devices for storing data, such as disks, magneto-optical disks, or optical disks, or operatively coupled to receive data from or transfer data to or both. However, a computer does not need to have such devices. Furthermore, a computer can be embedded in another device, such as a mobile phone, a personal digital assistant (PDA), a mobile audio or video player, a game console, a global positioning system (GPS) receiver, or a portable storage device, such as a universal serial bus (USB) flash drive, to name a few.

[0088] Computer-readable media (temporary or non-temporary, as the case may be) suitable for storing computer program instructions and data include all forms of non-volatile memory, media, and memory devices, including, for example, semiconductor memory devices such as EPROM, EEPROM, and flash memory devices; disks such as internal hard disks or removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. Memory can store a variety of objects or data, including caches, classes, frames, applications, backup data, jobs, web pages, web page templates, database tables, repositories storing business and / or dynamic information, and any other suitable information including any parameters, variables, algorithms, instructions, rules, constraints, or references to them. Additionally, memory may include any other suitable data, such as logs, policies, security or access data, report files, and others. Processors and memory may be supplemented by or incorporated into dedicated logic circuitry.

[0089] To provide interaction with the user, embodiments of the subject matter described in this specification can be implemented on a computer having a display device for displaying information to the user (e.g., a CRT (cathode ray tube), LCD (liquid crystal display), or plasma monitor) and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback; and input from the user can be received in any form, including acoustic, voice, or tactile input. Additionally, the computer can interact with the user by sending documents to and receiving documents from the device used by the user; for example, by sending a webpage to a web browser on the user's client device in response to a request received from a web browser.

[0090] The term "graphical user interface" or GUI can be used in the singular or plural to describe one or more graphical user interfaces and each display of a particular graphical user interface. Therefore, a GUI can refer to any graphical user interface, including but not limited to a web browser, touchscreen, or command-line interface (CLI) that processes information and effectively presents the results to a user. Typically, a GUI may include multiple user interface (UI) elements, some or all of which are associated with a web browser, such as interactive fields, dropdown lists, and buttons that can be operated by a business suite user. These and other UI elements may be related to or represent the functionality of the web browser.

[0091] The embodiments of the subject matter described in this specification can be implemented in a computing system that includes back-end components (e.g., as a data server), or middleware components (e.g., an application server), or front-end components (e.g., a client computer with a graphical user interface or a web browser through which a user can interact with the embodiments of the subject matter described in this specification), or any combination of one or more such back-end, middleware, or front-end components. The components of the system can be interconnected via digital data communication (e.g., a communication network) of any form or medium. Examples of communication networks include local area networks (LANs), wide area networks (WANs) (e.g., the Internet), and wireless local area networks (WLANs).

[0092] A computing system may include clients and servers. Clients and servers are typically geographically separated and usually interact via a communication network. The client-server relationship is established by computer programs running on the respective computers and having a client-server relationship with each other.

[0093] While this specification contains numerous specific implementation details, these should not be construed as limiting the scope of any system or the scope of the claims, but rather as descriptions of features specific to a particular implementation of a particular system. Certain features described in the context of individual implementations may also be implemented in combination in a single implementation. Conversely, various features described in the context of a single implementation may also be implemented individually or in any suitable sub-combination in multiple implementations. Furthermore, although features may be described above as functioning in certain combinations and even initially claimed in this way, in some cases one or more features from the claimed combination may be removed from the combination, and the claimed combination may be for sub-combinations or variations thereof.

[0094] Similarly, although the operations are depicted in a specific order in the accompanying drawings, this should not be construed as requiring these operations to be performed in the specific order shown or sequentially, or to perform all the shown operations to achieve the desired result. In some cases, multitasking and parallel processing may be helpful. Furthermore, the separation of the various system modules and components in the above embodiments should not be construed as requiring such separation in all embodiments, and it should be understood that the described program components and systems can generally be integrated together in a single software product or packaged into multiple software products.

[0095] Specific embodiments of the subject matter have been described. Other embodiments, modifications, and substitutions of the described embodiments are within the scope of the appended claims and will be apparent to those skilled in the art.

[0096] For example, the actions described in the claims can be performed in different orders and still achieve the desired result.

[0097] Therefore, the above description of the exemplary embodiments does not limit or restrict this disclosure. Other changes, substitutions, and modifications are possible without departing from the spirit and scope of this disclosure.

[0098] Although this application is defined in the appended claims, it should be understood that the invention may also be defined (alternatively or alternatively) according to the following embodiments:

[0099] Example 1. A computer-implemented method comprising:

[0100] A data model associated with a power grid is obtained, wherein the data model stores static data and dynamic data, both of which are related to the power grid in a time dimension, and wherein the static data and the dynamic data are continuously integrated into the data model based on data streams obtained from a set of data sources associated with the attributes of the power grid;

[0101] Expose a set of interfaces for querying data based on the data model, wherein the query is related to data from at least one of the planning analysis modeling domain or the operation analysis modeling domain in the data model, and the data model is related to the power grid; and

[0102] Run a query associated with a first planning operation in the planning analysis modeling domain, wherein the query defines one or more nodes of a power grid and relates to the planning analysis modeling domain, and wherein running the query is based on data related to the current state of the power grid, the current state of the power grid being based on data defined from a data model, the data being related to one or more nodes of the power grid in the operational analysis modeling domain.

[0103] Example 2. According to the method described in Example 1, obtaining the data model includes:

[0104] The data model associated with the power grid is generated by defining elements of the data model to map to attributes of the power grid, wherein the attributes are associated with nodes of the power grid and the topology of the power grid.

[0105] Example 3. The method according to any of the preceding examples, wherein the data model comprises a set of elements organized in a hierarchical structure, wherein the elements of the data model are mapped to data obtained from at least two data streams for the power grid node, wherein the data from the at least two data streams overlap with a set of attributes of the elements.

[0106] Example 4. The method according to any of the preceding examples, wherein obtaining the data model includes:

[0107] Data is obtained from each of the set of data sources, wherein the data source is associated with a node of the power grid, wherein the data source is a sensor installed for a switch node portion of the power grid, and wherein the sensor provides real-time sensor data as time-series data collected in a first time period.

[0108] Example 5. The method according to any of the foregoing examples, wherein exposing the set of interfaces includes:

[0109] At the integrated planning and operation platform, load the interface associated with the user of the first user role among the multiple roles defined at the integrated planning and operation platform;

[0110] Identify a set of access permissions associated with the first user role; and

[0111] The interface presents user interface elements associated with operations that can be performed by the user, wherein the user interface elements are mapped to corresponding elements of the data model, and the elements are accessible to the first user role.

[0112] Example 6. The method according to any of the preceding examples, wherein obtaining the data model includes defining the data model based on the current topology of the power grid, wherein the method further includes:

[0113] Obtain data for nodes defined in the current topology of the power grid;

[0114] Receive an update to the current topology of the power grid, the update being associated with at least one current node of the power grid and / or an additional node that modifies the topology of the power grid;

[0115] Perform a performance simulation of the power grid with the updated topology to determine the state of the power grid associated with the update; and

[0116] In response to determining that the state of the power grid associated with the update in the current topology is associated with successful performance, a method for modifying the power grid is provided.

[0117] Example 7. The method according to Example 6, the method comprising:

[0118] In response to determining that the state of the power grid is associated with unacceptable performance, the current topology is further modified to include the received update and to include further updates to the power grid to compensate for the received update; and

[0119] In response to determining that the new state of the power grid after the further modifications is associated with successful performance, instructions are provided for modifying the power grid based on the received update and the further update.

[0120] Example 8. The method according to any of the preceding examples, wherein the set of interfaces is predefined for a set of user groups, including a planner user group and an operations user group, wherein a first interface associated with the planner user group is associated with a planning analysis modeling domain, wherein at least a portion of the data from the planning analysis modeling domain is accessible for editing by users of the planner user group and is accessible for viewing only by users of the operations user group, and wherein at least a portion of the data from the operations analysis modeling domain is accessible for editing by users of the operations user group and is accessible for viewing only by users of the planner user group.

[0121] Example 9. A non-transitory computer-readable medium coupled to one or more processors and storing instructions thereon that, when executed by the one or more processors, cause the one or more processors to perform operations according to any one of Examples 1 to 8.

[0122] Example 10. A system comprising:

[0123] Computing devices; and

[0124] A computer-readable storage device coupled to the computing device and having instructions stored thereon, which, when executed by the computing device, cause the computing device to perform operations according to any one of Examples 1 to 8.

[0125] Example 11. A computer-implemented method comprising:

[0126] Running a planning operation requested via a query view exposed by an integrated planning and operations platform, wherein the planning operation relates to the behavior of at least one area of ​​a power grid, wherein the query view is based on a data model that integrates planning and operations data associated with the power grid, wherein the planning operation is run based on data related to the current state of the power grid, the current state of the power grid being determined based on the data model, wherein running the planning operation includes:

[0127] Determine a first rent value for a corresponding parameter from a set of operational parameters associated with the query, wherein the first set of values ​​is associated with a first time dimension;

[0128] The planning operation generates an output to evaluate the output according to planning status criteria; and

[0129] Based on the evaluation of the output according to the planning status criteria, identify one or more proposed modifications to the current state of the power grid;

[0130] The behavior of at least said area of ​​the power grid is simulated using one or more of the proposed modifications; and

[0131] Based on the simulation, recommendations for modifications to the power grid are provided.

[0132] Example 12. The method according to Example 11, the method comprising:

[0133] Instantiate the integrated planning and operation platform to expose views of the data model associated with corresponding types of tasks to be performed on the power grid, wherein the types of tasks include operation tasks and planning tasks.

[0134] Example 13. According to the method of Example 11 or Example 12, wherein the data model stores static data and dynamic data, both of which are related to the power grid in the time dimension, and wherein the static data and the dynamic data are continuously integrated into the data model based on data streams obtained from a set of data sources associated with the attributes of the power grid.

[0135] Example 14. The method according to any one of Examples 11 to 13, the method comprising:

[0136] A set of interfaces is exposed for querying data based on the data model, wherein the query is related to data from at least one of the planning analysis modeling domains of the data model, the data model being related to the power grid, and wherein the query view is embedded in at least one of the interfaces in the set of interfaces.

[0137] Example 15. The method according to any one of Examples 11 to 14, wherein determining the first set of values ​​includes:

[0138] In the planning analysis modeling domain of the data model, queries related to planning operations are generated and run, wherein the queries define one or more nodes of the power grid and relate to the planning analysis modeling domain, and wherein the running of the queries is based on data related to the current state of the power grid, the current state of the power grid being based on data definitions from the data model, the data relating to one or more nodes of the power grid in the operation analysis modeling domain.

[0139] Example 16. The method according to any one of Examples 11 to 15, wherein the data model comprises a set of elements organized in a hierarchical structure, wherein the elements of the data model are mapped with data mappings obtained from at least two data streams for nodes of the power grid, wherein the data from the at least two data streams overlap with a set of attributes of the elements.

[0140] Example 17. According to the method of Example 14, wherein the set of interfaces is predefined for a set of user groups, including a planner user group and an operations user group, wherein a first interface associated with the planner user group is associated with a planning analysis modeling domain, wherein at least a portion of the data from the planning analysis modeling domain is accessible to edit by users of the planner user group and is accessible to view only by users of the operations user group, and wherein at least a portion of the data from the operations analysis modeling domain is accessible to edit by users of the operations user group and is accessible to view only by users of the planner user group.

[0141] Example 18. A non-transitory computer-readable medium coupled to one or more processors and having instructions stored thereon, which, when executed by the one or more processors, cause the one or more processors to perform operations according to any one of Examples 11 to 17.

[0142] Example 19. A system comprising:

[0143] Computing devices; and

[0144] A computer-readable storage device coupled to the computing device and having instructions stored thereon, which, when executed by the computing device, cause the computing device to perform operations according to any one of Examples 11 to 17.

[0145] Example 20. A computer-implemented method for managing a power grid, the method comprising:

[0146] Data from the power grid is obtained to generate a data model that integrates operational and planning parameters related to the power grid, wherein the power grid is defined by a network model that interconnects network nodes in a graphical structure.

[0147] As the result of a simulation run of the planning operation, the input is obtained based on a modification of at least one parameter value of at least one planning parameter from the data model of the power grid, and the input includes a proposed modification of the parameter value of at least one operating parameter for at least one network node of the power grid.

[0148] Simulate a first behavior of at least said portion of the power grid based on modifications to parameter values ​​of at least one operating parameter of at least one network node used in the network model; and

[0149] The simulation results from the first action are provided as output to define modifications to the power grid.

[0150] Example 21. The method according to Example 20, the method comprising:

[0151] Generate the data model, which includes a set of elements organized into a hierarchical structure.

[0152] Example 22. The method according to any one of Examples 20 to 21, wherein the data model is generated based on a data stream associated with each of the network nodes of the network model, wherein at least one network node is associated with at least two data streams, the at least two data streams having an overlapping set of attributes with respect to the elements of the data model.

[0153] Example 23. The method according to any one of Examples 20 to 22, wherein the elements of the data model are mapped with data obtained from at least two data streams for nodes of the network model, and the nodes of the power grid are mapped to network nodes of the network model.

[0154] Example 24. The method according to any one of Examples 20 to 23, wherein the network model is used to evaluate and predict the operation and performance of the power grid.

[0155] Example 25. The method according to any one of Examples 20 to 24, comprising:

[0156] - To run a simulation of the planning operation based on modifications to at least one parameter value of at least one planning parameter from the data model of the power grid; and

[0157] At least one new parameter value for the at least one planning parameter is determined from the data model associated with the improved state of the planning operation, wherein the at least one new parameter value is used for the first behavior of at least the portion of the power grid.

[0158] Example 26. The method according to any one of Examples 20 to 25 further includes:

[0159] In response to evaluating the simulation results from simulating the first behavior,

[0160] The modification to the power grid is defined to include adding network nodes to the power grid, wherein adding the network nodes includes updating the network model to define the relationship between the added network nodes and at least a portion of the network nodes in the power grid, and

[0161] Based on the simulation results, the added node is configured according to the new parameter value of the parameter in the at least one operating parameter.

[0162] Example 27. A non-transitory computer-readable medium coupled to one or more processors and having instructions stored thereon, which, when executed by the one or more processors, cause the one or more processors to perform operations according to any one of Examples 20 to 26.

[0163] Example 28. A system comprising:

[0164] Computing devices; and

[0165] A computer-readable storage device coupled to the computing device and having instructions stored thereon, which, when executed by the computing device, cause the computing device to perform operations according to any one of Examples 20 to 26.

Claims

1. A computer-implemented method, comprising: Running a planning operation requested via a query view exposed by an integrated planning and operations platform, wherein the planning operation relates to the behavior of at least one area of ​​a power grid, wherein the query view is based on a data model that integrates planning and operations data associated with the power grid, wherein the planning operation is run based on data related to the current state of the power grid, the current state of the power grid being determined based on the data model, wherein running the planning operation includes: Determine a first set of values ​​for a corresponding parameter from a set of operational parameters associated with the requested planning operation, wherein the first set of values ​​is associated with a first time dimension; The planning operation generates an output to evaluate the output according to planning status criteria; and Based on the evaluation of the output according to the planning status criteria, identify one or more proposed modifications to the current state of the power grid; The behavior of at least said area of ​​the power grid is simulated using one or more of the proposed modifications; and Based on the simulation, recommendations for modifications to the power grid are provided.

2. The method according to claim 1, wherein the method comprises: Instantiate the integrated planning and operation platform to expose views of the data model associated with corresponding types of tasks to be performed on the power grid, wherein the types of tasks include operation tasks and planning tasks.

3. The method according to claim 1 or claim 2, wherein the method comprises: Obtaining the data model associated with the power grid, wherein obtaining the data model includes: The data model associated with the power grid is generated by defining elements of the data model to map to attributes of the power grid, wherein the attributes are associated with nodes of the power grid and the topology of the power grid. [Claims 4 and 2].

4. The method of claim 3, wherein obtaining the data model comprises defining the data model according to the current topology of the power grid, wherein the method further comprises: Obtain data for nodes defined in the current topology of the power grid; Receive an update on the current topology of the power grid, the update being associated with at least one current node of the power grid and / or an additional node that modifies the topology of the power grid; Perform a performance simulation of the power grid with the updated topology to determine the state of the power grid associated with the update; and In response to determining that the state of the power grid associated with the update in the current topology is associated with successful performance, instructions for modifying the power grid are provided.

6. .

5. The method according to claim 4, wherein the method comprises: In response to determining that the state of the power grid is associated with unacceptable performance, the current topology is further modified to include the received update and to include further updates to the power grid to compensate for the received update; and In response to determining that the new state of the power grid after the further modifications is associated with successful performance, instructions are provided for modifying the power grid based on the received update and the further update.

7. .

6. The method according to any one of the preceding claims, wherein the data model stores static data and dynamic data, both of which are related to the power grid in a time dimension, and wherein the static data and dynamic data are continuously integrated into the data model based on data streams obtained from a set of data sources associated with attributes of the power grid.

7. The method according to any one of the preceding claims, wherein the method comprises: A set of interfaces is exposed for querying data based on the data model, wherein the query is related to data from at least one of the planning analysis modeling domains of the data model, which is related to the power grid, and wherein the query view is embedded in at least one of the interfaces in the set of interfaces.

8. The method of claim 7, wherein exposing the set of interfaces comprises: At the integrated planning and operation platform, an interface associated with the user of the first user role among the multiple roles defined at the integrated planning and operation platform is loaded. Identify a set of access permissions associated with the first user role; and The interface presents user interface elements associated with operations that can be performed by the user, wherein the user interface elements are mapped to corresponding elements of the data model, and the elements are accessible to the first user role. [Original copyright 5].

9. The method according to any one of the preceding claims, wherein determining the first set of values ​​comprises: In the planning analysis modeling domain of the data model, a query associated with the planning operation is generated and executed, wherein the query defines one or more nodes of the power grid and relates to the planning analysis modeling domain, and wherein the execution of the query is based on data related to the current state of the power grid, the current state of the power grid being based on data definitions from the data model, the data being related to one or more nodes of the power grid in the operation analysis modeling domain.

10. The method according to any one of the preceding claims, wherein the data model comprises a set of elements organized into a hierarchical structure, wherein the elements of the data model are mapped to data obtained from at least two data streams for nodes of the power grid, wherein the data from the at least two data streams overlap with a set of attributes of the elements.

11. The method of any one of claims 7 to 10, wherein the set of interfaces is predefined for a set of user groups, the user groups including a planner user group and an operations user group, wherein a first interface associated with the planner user group is associated with a planning analysis modeling domain, wherein at least a portion of the data from the planning analysis modeling domain is accessible to edit by users of the planner user group and is accessible to view only by users of the operations user group, and wherein at least a portion of the data from the operations analysis modeling domain is accessible to edit by users of the operations user group and is accessible to view only by users of the planner user group.

12. The method according to any one of the preceding claims, wherein the method comprises: The input is obtained as the result of a simulation run of the planning operation, which is based on a modification of at least one parameter value of at least one planning parameter from the data model of the power grid, and the input includes a proposed modification of the parameter value of at least one operating parameter of at least one network node of the power grid. The first behavior of at least said portion of the power grid is simulated based on the modification of the parameter value of at least one operating parameter of at least one network node used in the network model; and The simulation results from the first action are provided as output to define modifications to the power grid.

13. The method of claim 12, comprising: The simulation of the planning operation is performed based on the modification of the value of at least one planning parameter of the data model from the power grid. and Determine at least one new parameter value for the at least planning parameter from the data model associated with the improved state of the planning operation, wherein the at least one new parameter value is used for the first behavior of at least the portion of the power grid.

14. The method according to any one of claim 12 or 13, further comprising: In response to evaluating the simulation results from simulating the first behavior, The modification to the power grid is defined to include adding network nodes to the power grid, wherein adding the network nodes includes updating the network model to define the relationship between the added network nodes and at least a portion of the network nodes in the power grid, and Based on the simulation results, the added node is configured according to the new parameter value of the parameter in the at least one operating parameter.

15. A non-transitory computer-readable medium coupled to one or more processors and storing instructions thereon that, when executed by the one or more processors, cause the one or more processors to perform the operation of the method according to any one of claims 1 to 14.

16. A system comprising: Computing devices; and A computer-readable storage device coupled to the computing device and having instructions stored thereon, which, when executed by the computing device, cause the computing device to perform the operation of the method according to any one of claims 1 to 14.

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