Simulation of modifications to the power distribution network

Abstract

To provide a system, a method, and a storage medium for obtaining input for simulations of electrical power grid operations and presenting results of the simulations.SOLUTION: A method includes: a step 1702 of providing a user interface including graphics for receiving input for simulations of electrical grid scenarios; a step 1704 of receiving input for a scenario including a proposed modification to the electrical grid; a step 1706 of performing a simulation by modeling the input in a virtual model of an electrical grid; a step 1708 of modifying the user interface; a step 1710 of receiving a selection from a menu of options for modifying the input; a step 1712 of performing a modified simulation by modeling the modified input in the virtual model of the electrical grid; and a step 1714 of modifying the user interface.SELECTED DRAWING: Figure 17

Description

Technical Field

[0001] (Cross - reference to Related Applications) This patent application claims the benefit of U.S. Provisional Patent Application No. 63 / 196,823, filed on June 4, 2021, and U.S. Provisional Patent Application No. 63 / 177,502, filed on April 21, 2021, the contents of which are incorporated herein by reference.

[0002] (Field of the Invention) [[ID=十三]]This specification relates to power grids, and more particularly to the operation modeling and simulation execution of distribution network systems. [[ID = 14]]

Background Art

[0003] Power grids transmit electricity to loads such as homes and commercial buildings. Power grids are complex and require a large number of commercial, regulatory, legal, and other stakeholders to evaluate and execute investment and operation decisions. To assist in decisions regarding modifications to the distribution network, virtual models of the distribution network can be used to simulate operation under various conditions. <{0000015}>

[0004] Historically, decision - makers have used different tools or methods to evaluate their transmission network investment decisions. This can range from hiring consulting firms to perform evaluations, establishing in - house teams of experts, and leveraging any available technology. Considering the complexity of modeling and evaluation, as well as established decision - making criteria for capital expenditure, rate of return, risk, and reliability, many utilities use three to four software programs, and the interfaces between them are difficult to handle or non - existent. Often, virtual distribution network models are customized and re - implemented across utilities, which leads to fragmentation between utilities.

[0005] The current process not only relies on siloed tools for modeling or evaluation, but also limits the core modeling techniques within these siloed tools. Simplification is achieved using factors such as electrical variables, intraday or temporal forecasts of load or price generation, and the number of nodes considered in the model. Furthermore, these tools use different underlying grid models, leading to significant differences in the results they produce. [Overview of the Initiative]

[0006] In general, this disclosure relates to a system for acquiring inputs for simulating power grid operation and for presenting the results of the simulation. A virtual distribution grid model is used to evaluate and predict the operation of a distribution grid. This disclosure provides a system and method for receiving inputs for a distribution grid scenario, running a simulation of the distribution grid scenario, and displaying a visualization of the simulation results. The system can receive inputs and display the results via a user interface presented on a computer system display. The simulation system can provide results relating to the environmental, reliability, regulatory, and financial impacts of proposed changes to the distribution grid.

[0007] In some implementations, the simulation system can provide a user interface for receiving input for the analysis of a power distribution network project. The user interface may include design tools that can be used to configure proposed changes to the power distribution network configuration. The modified power distribution network configuration may include simulated physical changes to the network, such as the addition and removal of power sources, as well as simulated physical changes, such as virtual load increase scenarios.

[0008] The simulation system can receive data through the user interface indicating the user's selection of baseline data input sources, data indicating the geographical area for analysis, and data indicating the user's selection of the time range for the project. The simulation system can also receive user input for scenarios for analysis through the user interface. A scenario may include one or more proposed changes to the distribution network being simulated. For example, the first scenario may include the addition of a power source to the distribution network. The system can receive user selections for the location and type of the proposed additional power source, as well as the rating of the proposed additional power source. The system can also receive user input indicating simulation assumptions, for example, a assumed annual load increase of 15 percent.

[0009] After executing the requested simulation, the simulation system may modify its user interface to include a visualization of the simulation results for the input scenario. In some cases, the simulation system may present a second user interface showing the visualization. The visualization may include, for example, tables, charts, graphs, and maps. The user interface may also allow the user to adjust evaluation parameters and assumptions after viewing the simulation results. For example, the user interface may include various menus for requesting additional and modified simulations.

[0010] In some examples, the user interface may include a menu of options for modifying input scenarios. The system can receive the modified inputs via the user interface. For example, the system may receive an input modifying the power rating of an additional power supply proposed in the first scenario. Based on the modified inputs, the simulation system can run an updated simulation and display the updated results for the first scenario.

[0011] In some examples, the user interface may include selectable options for inputting additional scenarios. The system may receive a selection of these selectable options for inputting additional scenarios via the user interface. In response to receiving a selection for inputting additional scenarios, the system may modify the user interface to include graphics indicating one or more fields for receiving input for simulating a power grid scenario. The system may then receive input for the second scenario via the user interface. For example, the second scenario may include an upgrade of existing power sources.

[0012] The results displayed through the user interface may include comparison views showing the evaluated parameters of each of multiple scenarios compared to each other and compared to a baseline scenario. For example, the user interface may show trend lines of power quality over time for each of the baseline data input, the first scenario, and the second scenario, shown on the same graph. The user interface may also show a map view showing the characteristics of the distribution network simulated based on each of the scenarios. The simulation results provided through the user interface may change over time. For example, the results may be displayed for a user-selected point in time or duration within the project's time range. In some examples, the results may be aggregated and / or averaged over the simulated duration.

[0013] Generally, innovative embodiments of the subject matter described herein can be realized by computer implementation methods, which include: providing a user interface including graphics showing one or more fields for receiving inputs for simulating a power grid scenario for display; receiving inputs to a scenario via the user interface, the inputs including the geographic location of the scenario, the time scale of the scenario, and proposed modifications to the power grid; running a simulation of the scenario by modeling the inputs in a virtual model of the power grid; modifying the user interface to include graphics, the graphics showing one or more visualizations of the simulation results and an optional menu for modifying the inputs; receiving a selection from an optional menu for modifying the inputs via the user interface; running a modified simulation by modeling the modified inputs in a virtual model of the power grid; and modifying the user interface to include graphics showing one or more visualizations of the simulation results compared to the results of the modified simulation.

[0014] In general, other innovative aspects of the subject matter described herein can be realized by computer implementation methods, which include the steps of: providing a first user interface for receiving inputs for the simulation of a power distribution network scenario for display; receiving inputs to a scenario via the first user interface, the inputs including a geographical location to the scenario, a time scale to the scenario, and proposed modifications to the power distribution network; performing a simulation of the scenario by modeling the inputs in a virtual model of the power distribution network; and providing a second user interface for display. The Face includes the steps of: providing a second user interface including one or more visualizations of the simulation results and an optional menu for modifying the inputs; receiving a selection from the optional menu for modifying the inputs via the second user interface; performing a modified simulation by modeling the modified inputs in a virtual model of a power distribution network; and providing an updated second user interface for display presentation, wherein the updated second user interface includes one or more visualizations of the simulation results compared with the modified simulation results.

[0015] These and other implementations may include, individually or in combination, the following features: In some implementations, the display includes a first display. The method includes receiving input for a second scenario via a user interface presented on a second display, the input including a second proposed modification to a power distribution network; performing a second simulation by modeling the input for the second scenario in a virtual model of the power distribution network; and providing a second user interface for presentation on the first display, which includes one or more visualizations of the simulation results compared to the results of the second simulation.

[0016] In some implementations, the method includes receiving input for a second scenario via a second user interface presented on a second display, wherein the input includes a second proposed modification to a power distribution network; performing a second simulation by modeling the input for the second scenario in a virtual model of the power distribution network; and modifying the user interface to include graphics showing one or more visualizations of the simulation results compared to the results of the second simulation.

[0017] In some implementations, a scenario includes a specific distribution network configuration, and the steps of running a simulation for the scenario include adjusting a virtual model of the distribution network to represent the specific distribution network configuration, and determining the characteristics of the adjusted virtual model of the distribution network under various simulated conditions.

[0018] In some implementations, a particular power distribution network configuration includes at least one of the following: added or removed power sources, upgraded assets, or added or removed connections.

[0019] In some implementations, the various simulated conditions include at least one of various environmental conditions or various load conditions.

[0020] In some implementations, a scenario includes specific conditions, and the steps of running a simulation for the scenario include adjusting a virtual model of the distribution network to represent the specific conditions, and determining the characteristics of the adjusted virtual model of the distribution network in various simulated distribution network configurations.

[0021] In some implementations, the specific conditions include at least one of the following: specific environmental conditions or specific load conditions.

[0022] In some implementations, various simulated power grid configurations include at least one of the following: added and removed power sources, upgraded assets, or added or removed connections.

[0023] In some implementations, the step of performing a simulation of a scenario by modeling the input in a virtual model of the power distribution network includes the step of performing a baseline simulation for the geographical location and time scale included in the input, and the simulation results include the effect of the proposed modifications on the results of the baseline simulation.

[0024] In some implementations, the modified input includes a second proposed modification to the power distribution network, which differs from the proposed modification, and the results of the modified simulation include the effect of the second proposed modification on the results of the baseline simulation.

[0025] In some implementations, the method includes performing a simulation on a baseline scenario for a geographical location and a time scale included in the input. The user interface includes graphics that show one or more visualizations of the results of the simulation for a scenario compared to the results of the simulation for the baseline scenario.

[0026] In some implementations, the method includes using a set of rules to evaluate a proposed modification and providing a notification that the proposed modification violates at least one rule of the set of rules for display presentation.

[0027] In some implementations, each rule included in the set of rules includes at least one of laws, regulations, equipment limitations, operational limitations, or industry standards.

[0028] In some implementations, a virtual model of a power distribution network includes a virtual model of real-world power distribution network assets.

[0029] In some implementations, the geographical location includes the location of a selected feeder of a real-world power distribution network.

[0030] In some implementations, the method includes accessing a virtual model of a power distribution network in response to receiving an input for a scenario, the virtual model including a plurality of different model configurations, accessing the virtual model, and selecting, based on the input for the scenario, (i) a simulation mode including a resolution and a scale of the simulation and (ii) one of the plurality of different model configurations. The step of performing a simulation for the scenario includes performing the simulation in the selected simulation mode using the selected model configuration.

[0031] In general, other innovative aspects of the subject matter described herein can be realized by computer implementation methods, which include the steps of: providing a user interface including graphics showing one or more fields for receiving inputs for simulating a power grid scenario for display; receiving a first input for a first scenario via the user interface; performing a first simulation for the first scenario by modeling the first input in a virtual model of a power grid in response to receiving the first input; and modifying the user interface to include graphics, the graphics including one or more visualizations of the results of the first simulation for the first scenario and inputs additional scenarios. The process includes: modifying a user interface to include selectable options for; modifying the user interface to include graphics showing one or more fields for receiving input for a simulation of a power grid scenario in response to receiving a selection of selectable options for entering an additional scenario; receiving a second input for a second scenario via the user interface; performing a second simulation for the second scenario by modeling the second input in a virtual model of the power grid in response to receiving the second input; and modifying the user interface to include graphics showing one or more visualizations of the results of the first simulation compared to the results of the second simulation.

[0032] In general, other innovative aspects of the subject matter described herein can be realized by computer implementation methods, which include the steps of: providing a first user interface for receiving inputs for simulating a power grid scenario for display; receiving a first input for a first scenario via the first user interface; performing a first simulation for the first scenario by modeling the first input in a virtual model of the power grid in response to receiving the first input; and providing a second user interface for display, the second user interface including one or more visualizations of the results of the first simulation for the first scenario and selectable options for inputting additional scenarios. The steps include: providing a user interface; providing a first user interface for display presentation in response to receiving a selection of selectable options for inputting an additional scenario; receiving a second input for a second scenario via the first user interface; performing a second simulation for the second scenario by modeling the second input in a virtual model of a power distribution network in response to receiving the second input; and providing an updated second user interface for display presentation, wherein the updated second user interface includes one or more visualizations of the results of the first simulation compared with the results of the second simulation.

[0033] These and other implementations may include the following features individually or in combination. In some implementations, the display includes a first display. The method includes the steps of: receiving a third input for a third scenario via a user interface presented on a second display; performing a third simulation by modeling the third input for the third scenario in a virtual model of a power distribution network; and providing a second user interface for presentation on the first display, which includes one or more visualizations of the results of the first simulation compared with the results of the third simulation.

[0034] In some implementations, the method includes the steps of: receiving a third input for a third scenario through a second user interface presented on a second display; performing a third simulation by modeling the third input for the third scenario in a virtual model of a power distribution network; and modifying the user interface to include graphics showing one or more visualizations of the results of a first simulation compared with the results of the third simulation.

[0035] In some implementations, the first scenario includes a specific distribution network configuration, and the step of performing a first simulation for the first scenario includes the steps of adjusting a virtual model of the distribution network to represent the specific distribution network configuration, and determining the characteristics of the adjusted virtual model of the distribution network under various simulated conditions.

[0036] In some implementations, a particular power distribution network configuration includes at least one of the following: added or removed power sources, upgraded assets, or added or removed connections.

[0037] In some implementations, the various simulated conditions include at least one of various environmental conditions or various load conditions.

[0038] In some implementations, the first scenario includes specific conditions, and the step of performing a first simulation for the first scenario includes the steps of adjusting a virtual model of the distribution network to represent the specific conditions, and determining the characteristics of the adjusted virtual model of the distribution network in various simulated distribution network configurations.

[0039] In some implementations, the specific conditions include at least one of the following: specific environmental conditions or specific load conditions.

[0040] In some implementations, various simulated power grid configurations include at least one of the following: added and removed power sources, upgraded assets, or added or removed connections.

[0041] In some implementations, the first input includes the first proposed modification to the power distribution network. The step of performing a first simulation for a first scenario by modeling the first input in a virtual model of the power distribution network includes the step of performing a baseline simulation for the geographical location and time scale included in the first input, and the results of the first simulation include the effect of the first proposed modification on the results of the baseline simulation.

[0042] In some implementations, the second input includes a second proposed modification to the power distribution network that differs from the first proposed modification, and the results of the second simulation include the effect of the second proposed modification on the results of the baseline simulation.

[0043] In some implementations, the method includes the step of performing a simulation of a baseline scenario for the geographical location and time scale included in the input. The user interface includes graphics that show one or more visualizations of the simulation results for the first scenario compared to the simulation results for the baseline scenario.

[0044] In some implementations, the method includes the steps of evaluating a first input and a second input using a set of rules, and displaying a notification that either the first input or the second input violates at least one rule from the set of rules.

[0045] In some implementations, each rule included in the set of rules contains at least one of the following: a law, regulation, equipment restriction, operational restriction, or industry standard.

[0046] In some implementations, the virtual model of the power distribution network includes a virtual model of real-world power distribution network assets.

[0047] In some implementations, the geographical location includes the location of a selected feeder in the real-world power distribution network.

[0048] In some implementations, the method includes the step of accessing a virtual model of a power distribution network in response to receiving input for a first scenario, the virtual model comprising several different model configurations, and the step of selecting (i) a simulation mode, including the resolution and scale of the simulation, and (ii) one of several different model configurations, based on the input for the first scenario. The step of running a simulation for the first scenario includes running the simulation using the selected model configuration in the selected simulation mode.

[0049] The subject matter described herein can be implemented in various embodiments and may result in one or more of the following advantages.

[0050] The disclosed technology can be used to integrate numerous factors related to power grid investment decisions into a single dynamic interface, through which the underlying data can be shared across different simulation engines and analytical tools that can be implemented across physical, financial, environmental, and regulatory domains.

[0051] The disclosed technology can simultaneously analyze multiple power grid investment schemes and share and compare them in comparative views, which may include data visualizations in table views or charts. These visualizations can provide information showing how different power grid planning decisions deliver different financial and non-financial returns. Comparative views can be presented showing differences between scenarios regarding environmental, reliability, and regulatory impacts. The interface can dynamically return results, allowing users to adjust evaluation parameters and assumptions, with updated results being returned almost instantly. Results can be directly shared with other users in various file formats.

[0052] Simulations performed using the disclosed technology may include details at both transient levels and on time scales of years or decades. Simulations may cover very short periods to analyze short-term effects such as peak demand behavior. Simulations may also cover very long periods to analyze long-term effects such as cumulative emissions and long-term financial returns. The disclosed simulation system can capture the behavior of an asset over its typical lifespan.

[0053] The disclosed technology provides a user-friendly design tool that can be used to configure multiple new power distribution network configurations. The new configurations may include proposed physical changes to the power distribution network, changes to non-physical model inputs such as virtual load increase scenarios, or both.

[0054] The disclosed technology can be used to predict the behavior of potential new configurations, which accurately attribute physical changes in the power grid to a set of effects on the grid. The effects can be evaluated for characteristics such as power flow, operating costs, utilization rates, emission impacts, compliance with regulatory requirements, and fire risk.

[0055] The simulation system may include APIs for relevant existing inputs that take input from various sources such as IoT-enabled datasets, regulatory reports, OEMs, load / generation and weather forecasts, cost assumptions, flexibility parameters / schedules for distributed energy resources (DERs) and demand response, and resilience parameters such as acceptable downtime for assets.

[0056] The simulation system can implement machine learning models to predict load patterns, power generation, weather, cost forecasts, and DER behavior, and provide forward-looking simulations. Machine learning can also predict maintenance requirements and downtime based on historical power outage and equipment lifecycle data.

[0057] The simulation system can perform high-speed simulations over various dynamic power grid operating conditions over a simulated period, for example, based on historical power grid data. The simulation can include predicted operating conditions over discrete time intervals, for example, over each time period of a simulated year.

[0058] A further technical advantage of the simulation system is its ability to simulate the operation of the power distribution network under various predicted load conditions, including variations due to factors such as seasonal, calendar, and time-of-day influences. The simulation system can simulate the operation of the power distribution network at multiple locations. The simulation system can simulate various electrical operating characteristics, such as current, voltage, power factor, and load, at multiple locations over a long simulation period.

[0059] The simulation system can model a complete power transmission and distribution system, including the electrical characteristics of the distribution network components, active loads and generators with their associated predicted behavior, and centralized and distributed control. The distribution network model can enable simulations across any time scale of interest, e.g., from nanoseconds to years, and any geographical area of ​​interest, e.g., from centimeters to thousands of kilometers.

[0060] Other implementations of the above embodiments include corresponding systems, devices, and computer programs configured to perform the operation of the method and encoded on a computer storage device. Details of one or more embodiments of the subject matter described herein are given in the accompanying drawings and the following description. Other features, embodiments, and advantages of the subject matter will become apparent from the description, drawings, and claims. [Brief explanation of the drawing]

[0061] [Figure 1] This document presents an exemplary system for simulating modifications to the power distribution network. [Figure 2] An exemplary input user interface is shown, displaying a list of planned projects. [Figure 3] This shows an exemplary input user interface for a new project plan. [Figure 4] This section shows an exemplary input user interface illustrating detailed input for a new project plan. [Figure 5] This shows an exemplary input user interface that illustrates the input for adding a scenario. [Figure 6] This shows an exemplary input user interface that illustrates inputs for simulated changes in a scenario. [Figure 7] This section shows an exemplary input user interface that illustrates options for simulated changes in a scenario. [Figure 8]This section provides an exemplary input user interface for modifying inputs in response to simulated load changes in a scenario. [Figure 9] This section shows an exemplary input user interface illustrating detailed inputs for simulated asset upgrade changes in a scenario. [Figure 10] An exemplary output user interface is shown, illustrating a comparison of power quality under increased load scenarios. [Figure 11] An exemplary output user interface is shown, illustrating a comparison of load profiles and peak demand in a load increase scenario. [Figure 12] An exemplary output user interface is shown, illustrating a comparison of violations under a load increase scenario. [Figure 13] This provides an exemplary output user interface that shows options for modifying inputs to address future power shortages. [Figure 14] An exemplary output user interface is shown, illustrating a cost comparison of options for addressing future power shortages. [Figure 15A] An exemplary output user interface is shown, illustrating a comparison of violations against options for addressing future power shortages. [Figure 15B] An exemplary output user interface is shown, illustrating a comparison of violations against options for addressing future power shortages. [Figure 16] This provides an exemplary output user interface that shows a comparison of emissions for options to address future power shortages. [Figure 17] This document illustrates an exemplary process for simulating modifications to a power distribution network, including modifying previously modeled scenarios. [Figure 18] This document presents an exemplary process for simulating modifications to the power grid, including simulating multiple different scenarios. [Figure 19] This is a diagram illustrating an exemplary server system for simulating modifications to the power distribution network. [Modes for carrying out the invention]

[0062] Figure 1 shows an exemplary system 100 for simulating modifications to a power distribution network. System 100 includes a power grid simulation server 110 and a user device 102. Server 110 includes a power distribution network model 115 and a simulation engine 120. User device 102 can communicate with server 110, for example, via a network 105.

[0063] In some examples, the power distribution model 115, the simulation engine 120, or both can be isolated from the server 110 and communicate with the server 110 via the network 105. The network 105 may include public and / or private networks and may include the internet.

[0064] The user device 102 may be an electronic device such as a computing device. For example, the user device 102 may be a desktop computer, laptop computer, smartphone, mobile phone, tablet, PDA, etc.

[0065] Server 110 is a server system and may include one or more computing devices. In some implementations, Server 110 may be part of a cloud computing platform. Server 110 may be maintained and operated by, for example, a power company or a third-party power distribution network operator.

[0066] System 100 displays a first user interface, such as an input user interface 106, to the user via the user device 102. The input user interface 106 may include an input form that allows the user to input a simulation request 108.

[0067] In some examples, the simulation request 108 may include a request for analysis of a first scenario, such as a power distribution network project. The simulation system can receive data through the input user interface 106 indicating the user's selection of baseline data input sources, data indicating the geographical area for analysis, and data indicating the user's selection of a time range for the project. In some examples, the geographical location may include the location of selected feeders in a real-world power distribution network. In some examples, the time range may include the start and stop times of the simulation. The start and stop times may each include a calendar date and time, with or without a specified time zone.

[0068] The simulation system can also receive user input for scenarios for analysis via the input user interface 106. A scenario may include one or more proposed changes to the distribution network being simulated. For example, a first scenario may include the addition of power sources to the distribution network. The system can receive user selections for the location and type of the proposed additional power sources, as well as the ratings of the proposed additional power sources. The system can also receive user input indicating simulation assumptions. In some examples, the user may provide inputs including a text code file encoding grid information, a drawn diagram encoding grid information, and data in spreadsheet format.

[0069] The input user interface 106 may include design tools that can be used to configure proposed modifications to the power distribution network configuration. These design tools may include, for example, forms, type fields, and drag-and-drop selections. The design tools may allow the user to add and remove various grid assets and connections between grid assets. In some examples, the design tools may include an editable map of the power distribution network. For example, the design tools may allow the user to drag and drop virtual power sources to locations on the power distribution network as represented in the map view. In another example, the design tools may allow the user to draw buildings to locations on the power distribution network as represented in the map view and to draw or drag and drop connections between the buildings and the power distribution network.

[0070] The modified power grid configuration may include simulated physical changes to the power grid, such as the addition and removal of power sources, as well as simulated non-physical changes, such as virtual load increase scenarios. An exemplary configuration may include, for example, added or removed power sources, upgraded assets, or added or removed connections. For assets being added or modified, the input user interface 106 may include options for providing asset characteristics, such as the electrical rating of the grid asset. Options for providing asset characteristics may include, for example, text fields, drop-down menus, selectable buttons, etc. An exemplary input user interface 106 is shown in Figures 2 to 9.

[0071] The user device 102 sends a simulation request 108 to the power grid simulation server 110, for example, via the network 105. The simulation request 108 includes parameters entered by the user, such as location, scenario, modification, data source, filter, and requested output. The simulation engine 120 receives the simulation request 108.

[0072] In response to receiving the simulation request 108, the simulation engine 120 accesses the virtual power grid model 115. In some examples, the power distribution grid model 115 is stored in a database, which is either stored by or accessible from the server 110. The power distribution grid model 115 can be a model of a real-world power grid that transmits power to loads such as residential and commercial buildings.

[0073] The distribution network model 115 may include a topological representation of the transmission network or a portion of the transmission network. The details of the distribution network model 115 are sufficient to enable accurate simulation and representation of the steady-state, dynamic, and transient operation of the distribution network.

[0074] The simulation engine 120 selects a model configuration 116 for the virtual power distribution network model 115. The selected model configuration 116 may include, for example, one or more layers, versions, and data sources. The simulation engine 120 also selects a simulation mode for the simulation. The simulation mode may include the time scale, time resolution, spatial scale, and spatial resolution of the simulation.

[0075] The simulation engine 120 performs a simulation or a series of simulations for a first scenario by modeling the input in a virtual power distribution network model 115. In some examples, the simulation can be performed using a real-time input data stream from field sensors. In some examples, the simulation can be performed using historical data from sensors, as well as estimates of historical and future parameters, such as expected load characteristics at a given moment and location, as input. Based on the simulation or a series of simulations, the simulation engine 120 outputs simulation results 122.

[0076] The simulation server 110 outputs the simulation results 122 to the user device 102. The user device 102 can display the simulation results 122 for user viewing, for example, through the output user interface 126.

[0077] The user device 102 modifies the user interface to display the simulation results 122 to the user, for example, as shown in the output user interface 126. The output user interface 126 can display a visualization 130 of the simulation results for an input scenario, for example, a first scenario. The visualization can include, for example, tables, charts, graphs, and maps. The user interface can also allow the user to adjust evaluation parameters and assumptions after viewing the simulation results. For example, the user interface can include various menus, including options for requesting additional and modified simulations. In some examples, the output user interface 126 can include an optional menu 128 for modifying the input scenario and an optional menu 132 for inputting additional scenarios. Exemplary output user interfaces 126 are shown in Figures 10 to 16.

[0078] The user device 102 can receive selections from an optional menu 128 for modifying an input scenario via the output user interface 126. For example, the user device 102 can receive an input to modify the power rating of an additional power supply proposed in the first scenario. The user device 102 sends the modified simulation request to the power grid simulation server 110, for example, via the network 105. The simulation engine 120 receives the modified simulation request.

[0079] Based on the modified simulation request, the simulation engine 120 can execute an updated simulation. For example, the simulation engine 120 can execute a modified simulation or a series of simulations by modeling the modified inputs in the virtual power distribution network model 115.

[0080] The simulation engine 120 can provide the user device 102 with the updated results of the modified simulation for the first scenario. The user device can view the updated results for the first scenario through an updated user interface, for example, the output user interface 136. The output user interface 136 may include a visualization 138 of the simulation results compared with the modified simulation results.

[0081] In some examples, the user device 102 may receive a selection from a menu of options 132 for inputting an additional scenario via the output user interface 126. In response to receiving a selection for inputting an additional scenario, the user device 102 may modify its user interface to include a graphics drawing field for receiving input, for example, as shown in the input user interface 106 for receiving input for the additional scenario. The user device 102 may then receive input for a second scenario via the input user interface 106. For example, the second scenario may include an upgrade of the currently existing power supply.

[0082] The user device 102 sends an additional simulation request for a second scenario to the power grid simulation server 110, for example, via the network 105. The simulation engine 120 receives the additional simulation request. Based on the additional simulation request, the simulation engine 120 can perform another simulation. For example, the simulation engine 120 can perform a simulation or a series of simulations by modeling the inputs for the second scenario in the virtual power grid model 115.

[0083] The simulation engine 120 can provide the user device 102 with the simulation results for the second scenario. The user device can view the results for the first and second scenarios through an updated user interface, for example, the output user interface 136. The output user interface 136 may include a visualization 138 of the simulation results for the first scenario compared with the simulation results for the second scenario.

[0084] The results displayed through the output user interface 136 may include a comparison view showing the evaluated parameters of each of several scenarios that are compared with each other and compared with a baseline scenario. For example, the user interface may show a trend line of power quality over time for each of the baseline data input, the first scenario, and the second scenario, shown on the same graph. The user interface may also show a map view showing the characteristics of the distribution network simulated based on each of the scenarios. The simulation results provided through the user interface may change over time. For example, the results may be displayed for a user-selected point in time or duration within the project's time range. In some examples, the results may be aggregated, averaged, or both over the simulated duration.

[0085] The results displayed through the output user interface 136 can be used for power distribution network planning and operational decisions. For example, a user can evaluate the displayed results to make decisions about which power sources to operate at different times of the day, week, or year. The displayed results can also assist in decisions regarding power restoration and power shutdown.

[0086] In some examples, users can evaluate the displayed results to make decisions regarding proposed modifications to the power distribution network. For example, a user can input multiple scenarios and see a comparison of the impact of each scenario and the cumulative impact of multiple scenarios. In some implementations, multiple users can each input scenarios into the power grid simulation server 110, and a user interface can be presented to different users for evaluating the scenarios. For example, a user in a power distribution network entity can see the results of scenarios proposed by multiple different contractors. A user in a power grid entity can compare proposed scenarios to determine the financial, operational, and environmental impacts of each proposed scenario.

[0087] In some implementations, the power grid simulation server 110 can use machine learning processes to improve the simulation results over time. For example, the simulation engine 120 can simulate proposed changes to the distribution network and generate simulation results. The proposed changes can then be applied to the real-world distribution network and incorporated into the virtual distribution network model 115. The power grid simulation server 110 can compare the real-world impact of the changes with previous simulation results. Based on this comparison, the power grid simulation server 110 can update the parameters of the virtual distribution network model, the simulation engine 120, or both.

[0088] Figure 2 shows an exemplary input user interface 200 displaying a list of planned projects. The list of planned projects includes a time scale 210 for each scenario and a status 220 for each scenario. The list of planned projects includes the "Kitajima Growth Analysis" project 240. The objective of the described project 240 is to address a 2.2 megawatt (MW) shortage between 2022 and 2026. The user interface 200 includes selectable options 230 for creating a new project to evaluate.

[0089] Figure 3 shows an exemplary input user interface 300 illustrating inputs for a planned project. Specifically, Figure 3 shows an exemplary input user interface 300 illustrating inputs for project 240. The input user interface 300 includes a field for selecting a baseline input 310. The baseline input 310 specifies the source of data to be used in the scenario. In this example, the selected baseline inputs for load and asset data are the most recent load forecast and the most recent asset dataset.

[0090] In some implementations, the baseline input may be set to the default data source. For example, the default data source may include the latest version of the data source. The user interface 300 may allow the user to change the input data source from the default data source.

[0091] Allowing users to select their data sources can improve the reliability of simulation results. For example, users can choose to input data from public or private sources. Users can also run multiple simulations using different data sources to compare the results of simulations using different data sources. In some implementations, the displayed results may be labeled with one or more of the data sources used to generate the results. Thus, users viewing the results can evaluate the accuracy, quality, and consistency of the simulation results.

[0092] The input user interface 300 also includes a map view 320 for inputting the geographical location of a scenario. In this example, the geographical location can be input by selecting a power distribution feeder displayed on the map view. In some examples, the geographical location can be input in other ways, such as by drawing boundaries on the map, selecting a town, county, or state, or by inputting latitude and longitude boundaries.

[0093] The input user interface 300 also includes a dropdown menu 330 for entering a time range or time scale for a scenario. In some examples, the time scale can be entered in other ways, such as by typing into a text field, selecting a date on a calendar, or adjusting a slide element on a timeline. In some examples, the time scale can include the start and stop times of the simulation. The start and stop times can include a date and time on a calendar, respectively. In some examples, the start and stop times can include a specified time period for the scenario.

[0094] Figure 4 shows an exemplary input user interface 400 illustrating detailed input for a new project plan. The input user interface 400 displays the options already selected for the project. The input user interface 400 also provides selectable options 420 for adding one or more scenarios.

[0095] The input user interface 400 also displays a list of the scenarios 410 being analyzed. In this example, the simulation server is running a simulation of the baseline scenario 430. The baseline scenario 430 could be, for example, a simulation of a virtual network without modifications or without proposed modifications. In some examples, the simulation of the baseline scenario 430 produces baseline results that assume no changes are made to the current virtual model of a selected portion of the distribution network. The baseline scenario 430 may be analyzed based on selected geographical locations, time scales, and input data sources.

[0096] Figure 5 shows an exemplary input user interface 500 that provides input for adding a scenario. An added scenario may include one or more changes or modifications to the power distribution network. The input user interface 500 includes selectable options 510 for adding changes.

[0097] Figure 6 shows an exemplary input user interface 600 that illustrates the inputs for simulated changes in a scenario. The input user interface 600 shows a list of changes 610 entered via user interface 500.

[0098] In some implementations, the input user interface 600 or other input user interfaces can prompt the user to select specific changes or simulation conditions. The simulation system can prompt for changes and conditions based, for example, on previous simulations requested by the same user or other users. In some examples, the simulation system can prompt for input in a second input field based on input entered in a first input field. For example, the user can input a change that includes adding an electric vehicle charger to the power grid. The simulation system can prompt the user to input a simulation condition that predicts, for example, a 2 percent load increase. In some examples, the proposed predicted load increase can be based on historical load increases. In some examples, the proposed predicted load increase can be based on load increase estimation inputs from other users who have performed similar simulations.

[0099] Figure 7 shows an exemplary input user interface 700 that illustrates options for simulated changes in a scenario. The input user interface 700 includes a drop-down menu 710 that shows various possible changes that can be entered into the simulation.

[0100] Figure 8 shows an exemplary input user interface 800 for modifying inputs for simulated load changes in a scenario. In this example, the updated load increase forecast 810 is input to the user interface 800. The user interface 800 provides the user with the option to select one or more feeders 820 and input an annual load increase rate 830.

[0101] The simulation system can receive inputs indicating changes to a previously requested simulation via the user interface 800. Upon receiving inputs indicating changes, the simulation system can run a modified simulation that includes the changes. When running a modified simulation, the simulation system can bypass the execution of the baseline simulation. For example, since the baseline scenario has already been evaluated, the simulation system can evaluate the modified simulation by comparing it with the previously evaluated baseline results. Therefore, by enabling modifications to the input data, the speed and efficiency of running the simulation can be improved. When running a modified simulation, the simulation system can evaluate the modifications without re-running the initial baseline scenario simulation.

[0102] In some implementations, the simulation system can resolve conflicts between user-inputted changes. For example, a user may input two or more conflicting changes. To manage conflicts, the simulation system may include a set of conflict management rules. The set of conflict management rules may include a hierarchy of conflict resolution. In some examples, the conflict resolution hierarchy may be set by the user. In some examples, the conflict resolution hierarchy may be based on regulations such as laws, codes, or regulations. Illustrative rules may include the minimum amount of power that must be available to a particular feeder, the maximum rating of a grid asset, or the minimum distance between two grid assets.

[0103] In some examples, inputs to a user interface, for example, user interface 800, can be evaluated using a set of rules. This set of rules may include rules based on laws, regulations, equipment restrictions, operational restrictions, industry standards, or any combination thereof. The simulation system may determine that an input violates one or more rules. In response to determining that an input violates one or more rules, the simulation system may provide a notification indicating the rule violation. For example, the simulation system may display a warning via the user interface, for example, user interface 800, that the input violates a rule. The simulation system may then provide the user with options to abandon the rule or edit the input to avoid violating the rule.

[0104] Figure 9 shows an exemplary input user interface 900 illustrating detailed inputs for a simulated asset upgrade change in a scenario. The user interface 900 provides an input field 910 for specifying the rating of the upgraded grid asset.

[0105] Figure 10 shows an exemplary output user interface 1000 illustrating a comparison of power quality under increasing load scenarios. User interface 1000 includes a scenario evaluation graph 1010. Graph 1010 shows power quality over time. The results displayed in graph 1010 show the effect of the proposed modifications on the baseline simulation results. The modifications may include varying levels of electric vehicle (EV) adoption within selected geographical locations. For example, graph 1010 shows baseline results compared to a first proposed modification for medium EV adoption and compared to a second proposed modification for high EV adoption.

[0106] The output user interface 1000 includes a selectable option 1020 in a dropdown menu for duplicating a scenario. In response to the selection of the selectable option 1020, the simulation system can duplicate the selected scenario. The simulation system can then present an input user interface, for example, user interface 800, to receive input data indicating modifications and adjustments to the duplicated scenario. In this way, the system enables the user to generate new scenarios from existing scenarios instead of creating each scenario anew.

[0107] The output user interface 1000 includes a selectable option 1030 for adding a new scenario. In response to the selection of the selectable option 1030, the simulation system can present an input user interface, for example, a user interface 500, to receive input data indicating the parameters of the new scenario. In this way, the system allows the user to generate new scenarios while saving previously executed scenarios. After multiple scenarios have been generated and evaluated, the simulation system can present an output user interface showing the results of the multiple scenarios. The results of the multiple scenarios can be presented, for example, in a comparison view or a cumulative view.

[0108] Figure 11 shows an exemplary output user interface 1100 illustrating a comparison of load profiles and peak demand for increased load scenarios. The user interface 1100 includes a load profile graph 1110 and a peak demand graph 1120 for simulated conditions and configurations.

[0109] Load profile graph 1110 and peak demand graph 1120 show the results of evaluations of scenarios including specific distribution network configurations evaluated under various conditions, respectively. The conditions evaluated may include, for example, environmental conditions and load conditions.

[0110] For example, the load profile shown in Graph 1110 shows the results of simulations of a specific distribution network configuration evaluated under various environmental conditions. Specifically, the environmental conditions include weather conditions corresponding to winter and summer. Similarly, the peak demand graph 1120 shows the results of simulations of a specific distribution network configuration evaluated under various load conditions. Specifically, the load conditions include baseline load, load with EVs at a medium level, and load with EVs at a high level.

[0111] In some cases, the simulation system can evaluate scenarios that include specific conditions or sets of conditions evaluated for different power distribution network configurations. For example, a scenario including stormy weather conditions can be evaluated for power distribution network configurations with one power source, two power sources, or three online power sources. The results of simulations using various power distribution network configurations under specific environmental conditions can be shown in a comparative chart.

[0112] In another example, a scenario including daytime summer load demand conditions can be evaluated for distribution network configurations including configurations where all water heaters are disconnected from the distribution network, configurations where half of all water heaters are disconnected from the distribution network, and configurations where water heaters are not disconnected from the distribution network. The results of simulations using various distribution network configurations under specific load conditions can be shown in a comparative figure.

[0113] Figure 12 shows an exemplary output user interface 1200 illustrating a comparison of violations against increasing load scenarios. The output user interface 1200 includes various graphs that show comparative views between violations in baseline, medium EV adoption, and high EV adoption scenarios.

[0114] Figure 13 shows an exemplary output user interface 1300 that illustrates options for modifying inputs to address future power shortages. The user interface 1300 includes a menu 1310 that contains filters. Filters can be applied to the results to prioritize certain requirements over others. For example, a cost filter can be set to a low level and an emissions filter to a high level to prioritize cost-effectiveness over environmental impact for various scenarios. In some examples, menu 1310 may include options for modifying inputs, such as changing the rating of one or more grid assets, changing the time scale of the scenario, changing the type of power source, changing the location of the power source, etc.

[0115] Figure 14 shows an exemplary output user interface 1400 illustrating a cost comparison of options for addressing future power shortages. In some examples, the cost comparison may include the direct and indirect costs of grid modifications. For example, building a power source in a particular location may result in indirect monetary effects such as tax benefits. The virtual grid model 115 may include a financial model that considers the indirect financial impacts of various grid decisions.

[0116] Figures 15A and 15B show an exemplary output user interface 1500 illustrating a comparison of violations of options for addressing future power shortages. User interface 1500 includes a list of proposed scenarios 1510 for addressing future power shortages. User interface 1500 also includes various graphs illustrating comparisons between the outcomes of different scenarios.

[0117] Figure 16 shows an exemplary output user interface 1600 illustrating a comparison of emissions for options to address future power shortages. The user interface 1600 includes a graph 1610 showing the expected emissions impacts of various proposed scenarios.

[0118] Figure 17 shows an exemplary process 1700 for simulating modifications to a power distribution network, including modifying a previously modeled scenario. Process 1700 can be performed by a simulation system, such as a computing system including a power grid simulation server 110.

[0119] Process 1700 includes providing a user interface for receiving inputs for the simulation of a power distribution network scenario for presentation on a display (1702). The user interface may be, for example, an input user interface 900.

[0120] Process 1700 includes receiving input for a scenario via a user interface (1704). A scenario could be, for example, Project 240, which includes a scenario for addressing a predicted power shortage.

[0121] Process 1700 includes performing a simulation of the scenario by modeling the inputs in a virtual model of the power distribution network (1706). The virtual model of the power distribution network may be, for example, a virtual power distribution network model 115.

[0122] Process 1700 includes modifying the user interface to include visualization of the simulation results (1708). The user interface may be modified to include visualizations such as those shown in the output user interface 1300, which shows values ​​for reliability, cost, and emissions for an input scenario. In some implementations, process 1700 includes providing a second user interface that includes visualization of the results.

[0123] Process 1700 includes receiving a selection from an optional menu for modifying the input via the user interface (1710). The optional menu could be, for example, menu 1310, which includes a filter.

[0124] Process 1700 includes running a modified simulation by modeling the modified inputs in a virtual model of the power distribution network (1712). The modified simulation may include a simulation run with a filter selected from menu 1310 applied.

[0125] Process 1700 includes modifying the user interface to include visualizations of the simulation results compared to the results of the modified simulation (1714). The user interface may be modified to include visualizations such as those shown in the updated output user interface 1300, which shows updated comparative values ​​for reliability, cost, and emissions for various scenarios.

[0126] Figure 18 shows an exemplary process 1800 for simulating modifications to a power distribution network, which includes simulating several different scenarios. Process 1800 can be executed by a simulation system, such as a computing system including a power grid simulation server 110.

[0127] Process 1800 includes providing a user interface for receiving inputs for simulating a power distribution network scenario for display (1802). The user interface may be, for example, an input user interface 800.

[0128] Process 1800 includes receiving a first input for a first scenario via a user interface (1804). The first input may include, for example, an annual load increase rate 830 for a selected feeder 820.

[0129] Process 1800 includes performing a first simulation for a first scenario by modeling the first input in a virtual model of the power distribution network in response to receiving the first input (1806). Performing a simulation for the first scenario may include simulating the operation of a selected feeder 820 using the input annual load growth rate 830.

[0130] Process 1800 includes modifying the user interface to include a visualization of the results of the first simulation (1808). The user interface may be modified to include a visualization, for example, as shown in the output user interface 1000.

[0131] Process 1800 includes receiving a second input for a second scenario via a user interface (1810). The second input for the second scenario may include, for example, a modified input annual load increase rate 830 for a selected feeder 820.

[0132] Process 1800 includes performing a second simulation for a second scenario by modeling the second input in a virtual model of the power distribution network in response to receiving the second input (1812). Performing the simulation for the second scenario may include simulating the operation of a selected feeder 820 using a modified input annual load increase rate 830.

[0133] Process 1800 includes modifying the user interface to include a visualization of the results of the first simulation compared with the results of the second simulation (1814). The user interface may be modified to include a visualization, for example, as shown in the updated user interface 1000, which shows the simulation results for the first and second scenarios in a comparison view.

[0134] Figure 19 shows an exemplary server system 1900 for simulating modifications to the power distribution network. System 1900 is a more detailed representation of exemplary system 100.

[0135] System 1900 includes a power grid simulation server 110 and a user device 102. Server 110 includes a power distribution network model 115 and a simulation engine 120. User device 102 can communicate with server 110, for example, via network 105.

[0136] In some examples, the power distribution model 115, the simulation engine 120, or both can be isolated from the server 110 and communicate with the server 110 via the network 105. The network 105 can include public and / or private networks and may include the internet.

[0137] The user device 102 may be an electronic device such as a computing device. For example, the user device 102 may be a desktop computer, laptop computer, smartphone, mobile phone, tablet, PDA, etc.

[0138] Server 110 is a server system and may include one or more computing devices. In some implementations, Server 110 may be part of a cloud computing platform. Server 110 may be maintained and operated by, for example, a power company or a third-party power distribution network operator.

[0139] Generally, a user can provide a simulation request 108 to a simulation server 110 through an input user interface 106 provided via a user device 102. The simulation server 110 can perform a simulation to generate a simulation result 122. The simulation server 110 can provide the simulation result 122 to the user device 102. The user device 102 can present the simulation result 122 via an output user interface 126.

[0140] Figure 19 shows the operations performed by System 1900, indicated as stages (A) to (F), each representing a step in an exemplary process for simulating modifications to the power distribution network. Stages (A) to (F) may occur in the order shown, or in a different order. For example, several stages may occur simultaneously.

[0141] System 1900 can perform simulations of power distribution network operation. System 1900 can receive requests for the output of the power distribution network simulation. For example, in stage (A) of Figure 19, System 1900 displays an input user interface 106 on the user device 102. The input user interface 106 may include an input form that allows the user to enter a simulation request 108.

[0142] The input user interface 106 includes input fields for various types of data. For example, the input user interface 106 includes input fields for location, change, scenario, data source, and requested output. In some examples, the user interface 106 may include more or fewer input fields. The user interface 106 may include input fields in various formats. For example, the user interface 106 may include input fields with dropdown menus, slider icons, text input fields, maps, selectable icons, search fields, etc.

[0143] In some examples, the input location may include the center location of the simulation, for example, a street address or latitude and longitude. The location may also include the simulation radius in kilometers, for example. In some examples, the location may include a zip code, town, city, or county. In some examples, the location may be entered by the user through a map display interface. For example, the user may select an area on the map for the simulation. In some examples, the user may draw a boundary for the simulation on the map.

[0144] In an exemplary scenario, the system may receive a request for simulation results showing the real-world electrical impact of a rapid transient event on the load of an electrical feeder when a new solar panel system is connected to the power grid. In this example, the input location can be a geographical radius centered on the location of the added solar panel system. The input change may be the addition of a solar panel system. The input scenario may be a rapid transient event. The data source can be the best available aggregated data. The requested output may be several failures caused by the rapid transient event.

[0145] In another exemplary scenario, the system may receive a request for simulation results indicating recommended actions to address a 2MW power shortage on a grid feeder. In this example, the input location can be the location of the grid feeder. The input change could be a 2MW increase in power output. The input scenario could be normal operation over a year. The data source can be data provided by the utility company. The requested output could be cost and reliability estimates for the recommended actions.

[0146] The input user interface can also include filters. For example, a user can apply filters to filter the simulation results. In the exemplary scenario above, user interface 106 can include filters for reliability and cost. The user can manipulate icons in user interface 106 to set a reliability filter to show only recommended actions with a reliability of over 90 percent. The user can also manipulate input user interface 106 to set a cost filter to show only recommended actions with a cost of less than $2.5M.

[0147] In stage (B) of Figure 19, the user device 102 sends a simulation request 108 to the power grid simulation server 110, for example, via the network 105. The simulation request 108 includes parameters entered by the user, such as location, scenario, modification, data source, filter, and requested output. The simulation engine 120 receives the simulation request 108.

[0148] In response to receiving the simulation request 108, the simulation engine 120 accesses the virtual power grid model 115. In some examples, the power grid model 115 is stored in a database, which is either stored by or accessible from the server 110. The power grid model 115 can be a model of a real-world power grid that transmits power to loads such as residential and commercial buildings.

[0149] In some examples, 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 mechanisms such as tapped magnetic or switched capacitors, network transformers, load transformers, inverters, generators, and various loads. The power grid model 115 may also include line models of medium-voltage distribution lines, such as electrical models. The power grid model 115 may also include electrical models of fixed and switched line capacitors, as well as other power grid components and equipment.

[0150] The distribution network model 115 may include a topological representation of the transmission network or a portion of the transmission network. The details of the distribution network model 115 are sufficient to enable accurate simulation and representation of the steady-state, dynamic, and transient operation of the distribution network. The distribution network model 115 may include various layers 111 and versions 112. The distribution network model 115 may also include data from multiple data sources 113. In some examples, data source 113 may include a “best available” data source containing aggregated data from multiple data sources.

[0151] Layer 111 may include, for example, an environmental layer, a physical layer, and an economic layer. The environmental layer may include data relating to the environmental impact of the power grid. For example, the environmental layer may include data relating to emissions from power sources that supply electricity to the power grid. The physical layer may include data relating to the physical components and operation of the power grid. For example, the physical layer may include data relating to the performance and specifications of equipment. The economic layer may include data relating to the costs of the power grid. For example, the economic layer may include data relating to the costs of operating and maintaining the power grid.

[0152] The distribution network model 115 includes different versions of the same distribution network. Each version can represent the past, present, and future states of the distribution network, including topological changes over time such as the introduction of new assets and changes in switch locations. This makes it possible to analyze past behavior as well as a range of planned or hypothetical scenarios. Different versions of the distribution network model 115 can represent the intended distribution network design, the completed design, the operational design, and future versions representing combinations of planned and hypothetical equipment modifications, additions, removals, and replacements.

[0153] Version 112 may include time-varying versions of the distribution network model. For example, version 112 may include past, present, and future versions of the distribution network model. A historical version may include a version of the model representing the transmission network in the past, for example, the past year, the past five years, or the past ten years. In some examples, the historical version can be used to evaluate the historical performance of the power grid. In some examples, the historical version can be used for trend analysis and comparison. For example, the same simulation can be run using the historical and current versions to identify any trends in power grid performance over time.

[0154] The current version of the distribution network model 115 may include a model of the power grid as designed. The model of the power grid may include a model of the transmission network assets, including the specifications and ratings as designed. The current version of the distribution network model 115 may also include a completed distribution network model. The completed power grid model may include a model of the transmission network assets, including real-world ratings. The completed model can take into account real-world effects such as aging, degradation, and maintenance. The current version of the distribution network model 115 may also include a current operating version. The current operating version may include real-time or near-real-time data of the current operation of the power grid. The current operating version can describe configuration changes, such as changes in switch locations. The current operating version can also describe current failures and outages.

[0155] Future versions of the distribution network model 115 may include versions of the model that represent the planned future configuration of the power grid, for example, one year, five years, or ten years into the future. Future versions of the distribution network model 115 may also include models of planned changes to the transmission network, such as planned distribution network modifications that have not yet been implemented. In this way, the cumulative effects of multiple planned modifications can be modeled.

[0156] In some examples, future versions of the power grid model 115 may include models of previously simulated changes. For example, a user may submit a simulation request based on a version of the power grid model 115 that includes a first proposed change. The simulation server 110 can then save the version of the power grid model 115 that includes the first proposed change. The user may then submit a simulation request based on a version of the power grid model that includes a second proposed change in addition to the first proposed change. In this way, the cumulative effects of multiple proposed modifications can be modeled. In some examples, the first proposed change may be requested by a first user, and the second proposed change may be requested by a second user. The simulation server 110 can run a simulation that incorporates the proposed changes requested by both the first and second users. In this way, the simulation server 110 can enable collaboration among users by simulating the cumulative effects of multiple proposed changes that may be submitted by multiple different users.

[0157] Future versions of the power grid model 115 may take into account expected aging, degradation, failure, and upgrades of components. For example, based on the average lifecycle of a component, future versions of the power grid model 115 may model the degradation of a component up to the end of its life and then consider the planned performance of replacement components. Future versions of the power grid may also take into account planned additions, such as power sources expected to come online on a specific future date.

[0158] In some examples, future versions of the power grid model 115 may change according to dates along the timeline. For example, a user can specify a future date, such as May 6, 2028, to run a simulation. The simulation can then be run against a future version of the power grid corresponding to the date May 6, 2028, including any expected modifications, additions, deletions, replacements, and degradations at that date.

[0159] In some cases, future versions of the power grid model 115 can take into account anticipated environmental and social changes. For example, future versions of the power grid model 115 can take into account climate change at the geographical locations of the power grid. Future versions of the power grid model 115 can also take into account population change, for example, based on a community growth model of the geographical locations of the power grid. Using predicted climate and climate and population changes, future electricity demand from the power grid can be predicted.

[0160] The power grid model 115 can adapt to different levels of confidence by using machine learning to fill gaps where model information is unknown or known with low confidence. For example, if the provided connectivity data is insufficient, the model can be automatically supplemented with connectivity information derived from computer vision processing. For example, the distribution grid model 115 may include probabilistic models of the electrical characteristics, power consumption, generation, and asset failures of distribution grid devices based on estimated asset health.

[0161] The power grid model 115 can also incorporate probabilistic models of external events based on geographical location. For example, the power grid model 115 can incorporate models showing the probability and frequency of events such as earthquakes, floods, hurricanes, volcanic eruptions, and nuclear accidents. The power grid model 115 can incorporate these probabilities into the analysis of long-term power grid operation. For example, the power grid model 115 can be used to predict how often a particular hospital will lose power for more than six hours. The prediction can be generated based on the power grid configuration, equipment capacity, and the predicted frequency of external events.

[0162] The power grid model 115 can derive probabilistic information from past and present versions of the power grid. For example, to predict the impact of future modifications to the power grid, the power grid model 115 can analyze the impact of previous similar modifications to the power grid. The power grid model 115 can also incorporate and analyze historical data from power grids at various geographical locations. In this way, the power grid model 115 can use machine learning to identify trends and patterns in order to predict future equipment performance.

[0163] The data source 113 may include, for example, government sources, utility sources, and grid sensors. Government sources may include data available from government agencies, such as the National Energy Regulatory Commission or state utility commissions. Utility sources may include public utility companies, such as Pacific Gas and Electric or Excel Energy. The data source 113 may also include grid sensors. For example, grid sensors can be placed at various locations in the power grid and can transmit operational data to the power grid simulation server 110. The grid sensor data may include historical grid sensor data, near real-time grid sensor data, or both.

[0164] In some examples, data source 113 may be aggregated into the "best available" data source. For example, data from various data sources can be associated with confidence values. The best available data source may include data from government sources, enterprise sources, and grid sensors. If a data point competes between two or more data sources, the best available data may be selected based on the data source with the highest confidence value for the data point. In some examples, the data source may include versions of data from APIs. For example, weather data may be provided through a weather API offered by a weather service. Therefore, the selected data source may include the latest version of the weather API.

[0165] In some examples, the data source 113 for the simulation can be selected by the user, for example, through the user interface 106. In some examples, the simulation engine 120 can select one or more data sources 113 based on the data provided through the simulation request 108.

[0166] The distribution network model 115 may be adaptable so that a change in one aspect of the distribution network model 115 persists to all other aspects. For example, a new reverse-connected resource may be connected to the power grid. The distribution network model 115 may receive data indicating the new resource from one or more of the data sources 113, for example. The distribution network model 115 may incorporate the new resource into the environmental, physical, and economic layers 111, respectively. The transmission network model 115 may also incorporate the new resource into current and future versions of the model.

[0167] The power grid model 115 can take into account the interdependence of energy systems beyond the power grid, such as the electrical elements of natural gas storage, distribution, and power generation systems. The distribution grid model 115 can model the interaction between two systems. A backup power system interacting with a primary power system is another example, particularly for battery and solar power systems that can replace diesel generator systems. Detailed models of all interaction subsystems can be run along with relevant simulations of all normal, abnormal, and corner conditions.

[0168] The power grid model 115 can be calibrated by using measured power grid data. Measured power grid data may include historical power grid operation data. Historical power grid operation data can be collected during power grid operation over a period of time, e.g., several weeks, several months, or several years. In some examples, historical power grid operation data may be average historical operation data. For example, historical power grid operation data may include the electrical load on substations during a specific time period of the year, averaged over several years. In another example, historical power grid operation data may include the number of voltage violations in the power grid during a specific time period of the year, possibly averaged over several years or otherwise statistically represented.

[0169] In some cases, the power grid model 115 may include assumptions. For example, the power grid model 115 may include measurement data for specific locations in the power grid, but may not include measurement data for other locations. The power grid model 115 may use assumptions to interpolate power grid operation data for locations where measurements are unavailable. Assumptions may include, for example, assumed ratios or relationships between loads in industrial areas of the power grid compared to residential areas of the power grid.

[0170] In some examples, the power grid model 115 may include measurement data for a specific time interval, for example, a specific time, but may not include measurement data for other time intervals. The power grid model 115 may use assumptions to estimate or interpolate power grid operation data for time intervals for which measurements are not available. The assumptions may be, for example, a hypothetical relationship between loads at a particular location at night compared to daytime. In another example, the assumptions may be a hypothetical relationship between the load at a particular location during one hour in summer and the load at the same location during one hour in winter.

[0171] In some examples, the power grid model 115 may include measured data for certain characteristics, such as electrical loads, but may not include measured data for other characteristics. The power grid model 115 can use assumptions to estimate power grid operation data for characteristics for which measurements are not available. The assumptions may be, for example, a hypothetical relationship between load and voltage at a particular location in the power grid.

[0172] In some cases, measurement data can be used to resolve and reduce errors caused by assumptions in the power grid model 115. In some cases, the power grid model 115 can include conservative values ​​in place of missing or incomplete data. In some cases, the power grid model 115 can use worst-case assumptions to enable worst-case analysis.

[0173] In stage (C) of Figure 19, the simulation engine 120 selects a model configuration 116 for the virtual power distribution model 115. The selected model configuration 116 may include, for example, one or more layers 111, versions 112, and data sources 113. The simulation engine 120 selects the model configuration 116 based on the simulation request 108. For example, the simulation request 108 may include a request for the physical impact of transient events on the current power distribution network, modeled to the best available accuracy. Based on the request, the system may select a model configuration that includes the physical layer of the current completed version of the virtual model based on data from the best available combination of data sources.

[0174] In some implementations, the simulation engine 120 includes a set of rules defining various combinations of user inputs for a simulation request 108, and an appropriate simulation model configuration 116 for each combination of user inputs. The simulation engine 120 can select a model configuration 116 for a given simulation request 108 by matching the inputs of the simulation request 108 with one of the input combinations defined in the set of rules. The simulation engine 120 selects a model configuration 116 associated with a particular rule in the set of rules that defines a combination of user inputs similar to that provided with a given simulation request 108.

[0175] In stage (D) of Figure 19, the simulation engine 120 selects a simulation mode 118 for the simulation. The simulation mode 118 may include the time scale, time resolution, spatial scale, and spatial resolution of the simulation.

[0176] Simulation mode 118 can include various time scales. The time scale indicates the simulated duration of the simulation. For example, the simulation can generate data showing predicted power grid operation over a 10-year time scale. Generally, higher time scales correspond to longer durations. For example, a 10-year time scale is larger than a 1-year time scale.

[0177] In some examples, the time scale can include numbers such as milliseconds, seconds, hours, days, or years. In some examples, the simulation may include transient simulations with shorter time scales when the problem is expected to occur in that time domain, while leaving the simulation in the steady-state time domain with a larger time scale when transient effects are not expected.

[0178] Simulation mode 118 can include various time resolutions. Time resolution indicates the level of detail of the simulation in the time dimension. In some examples, time resolution can be the time increment of the simulation's data points. Generally, higher time resolutions correspond to smaller units of time measurement. For example, a time resolution of one second is higher resolution than a time resolution of one minute.

[0179] In some examples, the time resolution can include nanoseconds, milliseconds, seconds, minutes, hours, days, weeks, months, etc. For example, the simulation engine 120 can select a time resolution of milliseconds to model transient events. The simulation engine 120 can select a time resolution of days to model steady-state events. In some examples, the simulation engine 120 can run the simulation at a first time resolution for one part of the simulation and at a second time resolution for another part of the simulation.

[0180] In some examples, the simulation engine 120 can select a time scale and time resolution based at least partially on the amount of data to be generated. For example, a first simulation run over a large time scale (e.g., 10 years) with a high time resolution (e.g., seconds) will generate more data than a second simulation run over a 10-year time scale with a smaller time resolution (e.g., weeks). Therefore, the first simulation is likely to require more processing time, processing power, and data storage compared to the second simulation. Thus, the simulation engine 120 can select an appropriate time scale and time resolution to obtain results without exceeding limits or thresholds related to the amount of data generated.

[0181] Simulation mode 118 can include various spatial scales. The spatial scale indicates the simulated spatial size or extent of the simulation. In some examples, the spatial scale may be a size measured in distance, e.g., kilometers. In some examples, the spatial scale may be a size measured in area, e.g., square kilometers. For example, the simulation may generate data showing predicted power grid operation over a spatial scale of 10 square kilometers. Generally, higher spatial scales correspond to larger spatial distances or areas. For example, a spatial scale of 10 square kilometers is a larger spatial scale than a time scale of square kilometers.

[0182] In some examples, the spatial scale can include meters, kilometers, tens of kilometers, hundreds of kilometers, thousands of kilometers, etc. For example, the simulation engine 120 can simulate large-scale systems at the scale of a fully interconnected network by utilizing distributed computing. The spatial scale can correspond to the geographical area of ​​an electrical feeder or multiple connected electrical feeders. In some examples, the simulation engine 120 can simulate transient events in a simulation mode that includes a spatial scale at the local level. For example, the spatial scale can correspond to the size of a neighborhood, town, or city. In some examples, the simulation engine 120 can simulate large modifications in a simulation mode that includes a spatial scale at the regional level. For example, the spatial scale can correspond to the size of a county, state, or province.

[0183] Simulation mode 118 can include various spatial resolutions. Spatial resolution indicates the level of detail of the simulation in the physical dimension. In some examples, spatial resolution can be the linear interval between the simulation's data points. In other examples, spatial resolution can be the size of an area represented by a single reference point. Generally, higher spatial resolution corresponds to smaller units of spatial measurement. For example, a spatial resolution of 1 meter is a higher resolution than a spatial resolution of 1 kilometer.

[0184] In some examples, the spatial resolution can include centimeters, meters, tens of meters, kilometers, etc. The simulation engine 120 can perform simulations across a range of granularities with respect to model details. The power grid model 115 includes models of various levels of power generation resources, including bulk power and distributed resources, conventional power plants and intermittent renewable energy, and energy storage systems. The simulation mode 118 can include a spatial resolution corresponding to the subcomponent granularity when analyzing ultra-local effects. The simulation mode 118 can include a spatial resolution corresponding to a higher level of model granularity when analyzing broader system-level effects. In some examples, the simulation mode 118 can include a higher spatial resolution at a specific location in the power grid and a lower spatial resolution at other locations in the power grid. For example, the simulation engine 120 can select a higher spatial resolution (e.g., centimeters) to model a portion of the power grid (e.g., a portion of the power grid occupying one-tenth of a kilometer). The simulation engine can select a lower spatial resolution, for example, tens of meters, to model a different part of the power grid, for example, a portion of the grid occupying 10 square kilometers.

[0185] In some examples, the simulation engine 120 can select the spatial scale and spatial resolution based at least partially on the amount of data to be generated. For example, a first simulation run over a large spatial scale (e.g., 100 kilometers) with a high spatial resolution (e.g., centimeters) will generate more data than a second simulation run over a spatial scale of 100 kilometers with a smaller spatial resolution (e.g., 10 meters). Therefore, the first simulation is likely to require more processing time, processing power, and data storage compared to the second simulation. Thus, the simulation engine 120 can select an appropriate spatial scale and spatial resolution to obtain results without exceeding limits or thresholds related to the amount of data to be generated.

[0186] The simulation engine 120 is adaptive and can fully utilize the details provided by the power distribution model 115. The simulation engine 120 can switch between different simulation modes 118 based on the appropriate scale and resolution for the event being simulated. For example, the simulation engine 120 can simulate steady-state power flow before and after a capacitor switching event, and can model the capacitor switching event itself in the time domain to analyze electromagnetic transient phenomena.

[0187] The simulation engine 120 can switch between subnetwork models with different levels of detail depending on the electrical distance of the subnetwork to the event being simulated. For example, the simulation engine 120 can simulate a distribution feeder connected to a power transmission system as a single load, and then switch to a full feeder model when simulating a fault near its substation.

[0188] The simulation engine 120 can simulate the behavior of active and controllable devices on a power grid, including bulk power generation, transmission and distribution system control, and distributed energy resources such as solar power generation and battery systems.

[0189] The simulation engine 120 can simulate the distribution of voltage and current values ​​by treating the simulation as a stochastic process. Each simulation step can sample from the provided distribution of electrical characteristics, load, and power generation. Performing many of these simulations makes it possible to estimate the distribution over the results and define confidence intervals around the predicted behavior.

[0190] The simulation engine 120 is based on the concept of electromagnetic transient phenomena, but can perform simulations that can be applied to various details and various aspects of combined electrical, mechanical, thermal, and hydrocarbon fuel subsystems. For example, the simulation engine 120 can simulate a low-inertia, highly intermittent power distribution network with a high proportion of electronic interfaces such as inverters between both the power source and the load.

[0191] Simulated grid data can be based on simulating the operation of the grid during a simulated period. Simulated grid data may include several different temporal and spatial dependency characteristics of the grid. The simulated period may be, for example, a simulated month, week, or year. In some examples, the simulated period may be the period between an input start time and an input stop time. For example, the period may have a start time of 12:00 PM EST on April 30, 2025, and a stop time of 11:00 AM EST on May 22, 2025.

[0192] In some examples, the simulation engine 120 can generate simulated power grid data or simulation results for each hour of a simulated period, for example, a simulated year. The simulation may include predicted loads and transients over the course of a simulated year based on historical data. For example, the predicted load may vary based on predicted seasonal influences (e.g., weather conditions) and calendar influences (e.g., weekends, holidays).

[0193] Locations within the power grid may include geographical locations identified by the simulation request. For example, a location may include a postal address or latitude and longitude coordinates.

[0194] The simulation engine 120 can then perform a series of simulations. These simulations may be based, for example, on root-mean-square (RMS), power flow, positive-sequence, and / or time-series voltage transient analysis. The amount of data processed during each simulation may depend on the size and framework of the distribution feeder being evaluated. The simulations can analyze the predicted impact on all connections to the affected distribution feeder and all components of the affected distribution feeder. Therefore, the complexity of the simulations may vary depending on the structure of the distribution feeder.

[0195] For example, the simulation may vary depending on the length, power, and number of loads in the distribution feeder. A typical distribution feeder may range in length from approximately 1 to 10 miles. A typical distribution feeder may range in power from approximately 1 to 10 megawatts. The number of loads connected to the feeder may range from several hundred to several thousand residential loads. In some cases, there may also be a few dozen commercial or industrial loads, and several hundred commercial or industrial loads.

[0196] The structure of a power distribution feeder can also be modified based on location. In urban environments, residential loads typically share transformers. In rural environments, each residential load may have a separate transformer. Commercial and industrial loads are typically supplied by three-phase transformers. Therefore, the number of loads and transformers in a feeder can be as few as several hundred loads with several hundred transformers in a rural feeder. In urban environments, the number of loads and transformers in a feeder can be as many as several thousand loads with several hundred single-phase transformers, which can be coupled with tens or hundreds of larger three-phase loads and transformers.

[0197] In some cases, the simulation engine 120 can simulate the operation of multiple feeders. For example, the simulation may include an analysis of the operation of all feeders across a geographical area, such as a city, county, province, or state. In some cases, the simulation engine 120 can model the operation of each individual feeder within the area and aggregate the results to model the operation of multiple feeders within the area.

[0198] In some cases, the simulation engine 120 can model the operational influence of multiple feeders on each other. For example, multiple feeders may be connected to a shared substation transformer. The simulation engine 120 can simulate the transient effects of one feeder on another feeder connected to the same transformer. In some cases, the simulation engine 120 can model the redirection of energy to specific loads. For example, regulations or other requirements may necessitate prioritizing power to loads such as hospitals. Prioritization may be performed manually by an operator or by automatic redirection. The simulation engine 120 can run a simulation while considering the redirection of power to higher-priority loads.

[0199] The simulation engine 120 can analyze the expected operation of a power grid by applying empirical historical data to a power grid model. The empirical historical data can include, for example, historical power grid characteristics based on measured values, calculated values, estimates, and interpolation. These characteristics can include, for example, load, voltage, current, and power factor. The empirical historical data can represent the power grid operation of multiple interconnected components within a specified geographical area. The empirical historical data can represent average power grid operation characteristics over a period of time, such as several weeks, months, or years.

[0200] In some examples, the simulation can cover a range of operating conditions, particularly under extreme voltages from bulk power systems (BPS) and extreme loads on distribution feeders. The simulation engine 120 can simulate a corner case of a system in which the proposed interconnection is added to an existing system. The simulation can also cover distribution network conditions during steady-state and transient operation. The simulation engine 120 can accurately simulate the operation of loads and sources, aggregated loads and sources, and isolated loads and sources.

[0201] Based on a series of simulations, the simulation engine 120 outputs simulation results 122. The simulation results may include time-varying power grid characteristics at different locations in the power grid during the simulated period.

[0202] In stage (E) of Figure 19, the simulation server 110 outputs the simulation results 122 to the user device 102. The user device 102 can display the simulation results 122 for viewing by the user, for example, through the output user interface 126.

[0203] In stage (F) of Figure 19, the user device 102 displays the simulation results 122 to the user through the output user interface 126. The output user interface 126 can, for example, display graphs, charts, and tables showing the simulation results. In some examples, the output user interface 126 can display a visualization of the simulation results 122 in a two-dimensional and / or three-dimensional map view. The output user interface 126 can also display data including the expected effects of the proposed changes to the power distribution network. The expected effects may include environmental impacts such as cost and emissions changes, and changes in the reliability of the power distribution network. The output user interface 126 may be interactive to allow the user to review the results. For example, the user can select individual tests, periods, or locations, for example, using a computer mouse, to view detailed simulation results for each.

[0204] This disclosure generally describes computer-implemented methods, software, and systems for power grid visualization. The computing system can receive various power grid data from multiple sources. The power grid data may include different temporal and spatial dependent characteristics of the power grid. These characteristics may include, for example, power flow, voltage, power factor, feeder utilization, and transformer utilization. These characteristics can be combined. For example, some characteristics may influence others, and / or their temporal and spatial dependencies may be relevant.

[0205] Data sources may include satellite, aerial imagery databases, publicly available government power grid databases, and utility provider databases. Sources may also include sensors installed within the power grid by the grid operator or others, such as power meters, ammeters, voltmeters, or other sensing devices connected to the power grid. Data sources may include databases and sensors for both high-voltage transmission and medium-voltage distribution systems, as well as low-voltage utilization systems.

[0206] 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 measured data from various points in the distribution network, such as voltage, power, current, power factor, phase, and line-to-line phase balance. In some examples, the data may include historically measured network data. In some examples, the data may include real-time measured network data. In some examples, the data may include simulated data. In some examples, the data may include a combination of measured and simulated data.

[0207] Implementations of the subject matter and functional operations described herein may be implemented in digital electronic circuits, tangibly embodied computer software or firmware, computer hardware, or one or more combinations thereof, including the structures disclosed herein and their structural equivalents. Implementations of the subject matter described herein may be implemented as one or more modules of computer programs, i.e., computer program instructions encoded on a tangible non-temporary program carrier for execution by a data processing device or for controlling the operation of a data processing device. Computer storage media may be machine-readable storage devices, machine-readable storage boards, random or serial access memory devices, or one or more combinations thereof.

[0208] The term “data processing device” refers to data processing hardware and encompasses all kinds of devices, machines, and equipment for processing data, including, for example, a programmable processor, a computer, or multiple processors or computers. The device may also be, or further include, a dedicated logic circuit, such as a Field Programmable Gate Array (FPGA) or an Application-Specific Integrated Circuit (ASIC). In some implementations, the data processing device and / or dedicated logic circuit may be hardware-based and / or software-based. The device may optionally include code that constitutes an execution environment for computer programs, such as processor firmware, a protocol stack, a database management system, an operating system, or a combination of one or more of these. This disclosure assumes the use of the data processing device with or without a conventional operating system, such as Linux, UNIX, Windows, Mac OS, Android, iOS, or any other suitable conventional operating system.

[0209] Computer programs, which may be referred to or described as programs, software, software applications, modules, software modules, scripts, or code, can be written in any form of programming language, including compiled languages ​​or interpreted languages, or declarative languages ​​or procedural languages, and can be deployed in any form, including as standalone programs or as modules, components, subroutines, or other units suitable for use in a computing environment. A program may, but may not, correspond to a file in a file system. A program may be stored in a part of a file that holds other programs or data, for example, in a markup language document, in a single file dedicated to the program in question, or in a set of collaborative files, for example, in one or more scripts stored in a file that stores one or more modules, subprograms, or parts of code. A computer program can be deployed to run on one computer, or on multiple computers located in one site or distributed across multiple sites and interconnected by a communication network. While the parts of a program shown in various diagrams are shown as individual modules that implement various features and functions through various objects, methods, or other processes, a program may instead include several submodules, third-party services, components, libraries, etc., as needed. Conversely, the characteristics and functions of various components can be combined into a single component as needed.

[0210] The processes and logic flows described herein can be executed by one or more programmable computers running one or more computer programs to perform functions by acting on input data and producing outputs. The processes and logic flows can also be carried out by dedicated logic circuits, such as FPGAs (Field-Programmable Gate Arrays) or ASICs (Application-Specific Integrated Circuits), and the devices can also be implemented as such.

[0211] A computer suitable for running computer programs may, for example, be based on a general-purpose or dedicated microprocessor, or both, or any other type of central processing unit. Generally, the central processing unit receives instructions and data from read-only memory, random-access memory, or both. Essential elements of a computer are a central processing unit for executing or running instructions, and one or more memory devices for storing instructions and data. Generally, a computer also includes one or more mass storage devices for storing data, such as magnetic disks, magneto-optical disks, or optical disks, or is operablely coupled to them to receive data from them, transfer data to them, or both. However, a computer is not required to have such devices. Furthermore, a computer can be incorporated into other devices, for example, mobile phones, electronic organizers (PDAs), mobile audio or video players, game consoles, Global Positioning System (GPS) receivers, or portable storage devices, such as Universal Serial Bus (USB) flash drives, to name just a few.

[0212] Computer-readable media (temporary or non-temporary as necessary) suitable for storing computer program instructions and data include, for example, all forms of non-volatile memory, including semiconductor memory devices such as EPROM, EEPROM, and flash memory devices, magnetic disks such as internal hard disks or removable disks, magneto-optical disks, and CD-ROM and DVD-ROM disks. Memory may store a variety of objects or data, including caches, classes, frameworks, applications, backup data, jobs, web pages, web page templates, database tables, repositories for storing business and / or dynamic information, and any other appropriate information, including any parameters, variables, algorithms, instructions, rules, constraints, or references thereto. Furthermore, memory may also include any other appropriate data, such as logs, policies, security or access data, and report files. The processor and memory may be complemented by or incorporated into dedicated logic circuits.

[0213] To provide user interaction, embodiments of the subject matter described herein may be implemented on a computer, which may have a display device for displaying information to the user, such as a cathode ray tube (CRT), liquid crystal display (LCD), or plasma monitor, and a pointing device such as a keyboard and mouse or trackball, to which the user can provide input to the computer. Other types of devices may be used similarly to provide user interaction, for example, the feedback provided to the user may be any form of sensory feedback, such as visual feedback, auditory feedback, or tactile feedback, and input from the user may be received in any form, including acoustic, speech, or tactile input. In addition, the computer may interact with the user by sending documents to and receiving documents from devices used by the user, for example, by sending a web page to a web browser on the user's client device in response to a request received from a web browser.

[0214] The term "graphical user interface" or GUI may be used in the singular or plural form to describe one or more graphical user interfaces and each of the displays of a particular graphical user interface. Therefore, a GUI can represent any graphical user interface, including but not limited to web browsers, touchscreens, or command-line interfaces (CLIs) that process information and efficiently present the results to the user. Generally, a GUI may include several user interface (UI) elements, some or all of which are associated with a web browser, such as interactive fields, pull-down 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.

[0215] Embodiments of the subject matter described herein may be implemented in a computing system that includes, for example, a data server as a backend component, or a middleware component, such as an application server, or a frontend component, such as a client computer having a graphical user interface or a web browser through which a user can interact with the embodiment of the subject matter described herein, or in any combination of one or more such backend, middleware, or frontend components. The components of the system may be interconnected by any form or medium of digital data communication, such as a communication network. Examples of communication networks include local area networks (LANs), such as the Internet, and wide area networks (WANs).

[0216] A computing system can include clients and servers. Clients and servers are generally geographically separated from each other and typically interact via a communication network. The client-server relationship arises from computer programs running on each computer that have a client-server relationship with each other.

[0217] This specification includes details of many specific implementations, but these should not be interpreted as limitations on the scope of any system or the scope of what can be claimed, but rather as descriptions of features that may be specific to a particular embodiment of a particular system. Certain features described herein in the context of separate 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 in multiple implementations, separately or in any preferred partial combination. Furthermore, features are described above as functioning in a particular combination and may initially be claimed as such, but one or more features from a claimed combination may, in some cases, be excluded from the combination, and the claimed combination may be a partial combination or a variation of a partial combination.

[0218] Similarly, although the operations are depicted in a specific order in the drawings, this should not be understood as requiring that such operations be performed in a specific or sequential order shown, or that all exemplified operations be performed, in order to achieve the desired result. In certain circumstances, multitasking and parallel processing may be beneficial. Furthermore, the separation of various system modules and components in the embodiments described above should not be understood 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 in multiple software products.

[0219] Specific embodiments of the subject matter have been described. Other embodiments, modifications, and substitutions of the described embodiments are within the scope of the following claims, as will be apparent to those skilled in the art.

[0220] For example, the actions described in the claims can be performed in a different order, and the desired results can still be achieved.

[0221] Therefore, the above description of exemplary implementations does not define or limit this disclosure. Other changes, substitutions, and modifications are also possible without departing from the intent and scope of this disclosure.

Claims

1. A computer implementation method, The steps include providing a user interface for receiving input for simulating a power distribution network scenario for display purposes, The step of receiving input for a modification scenario via the user interface, wherein the input is: The geographical location of the aforementioned revised scenario, The timescale of the aforementioned revised scenario, A step of receiving the input, including a proposed modification to the power distribution network, The steps include: performing a simulation of the modified scenario by modeling the input in a virtual model of the power distribution network; A step of performing a simulation of a baseline scenario for the geographical location and time scale included in the input, wherein the baseline scenario does not include the proposed modifications to the power distribution network. A computer implementation method comprising the step of modifying a user interface to generate a modified user interface that includes one or more visualizations of the results of the simulation for the modified scenario, compared with the results of the simulation for the baseline scenario.

2. The user interface includes one or more selectable options for the baseline scenario, and the method is The steps include receiving the selection of selectable options for the baseline scenario via the user interface, The computer implementation method according to claim 1, comprising the step of performing the simulation for the baseline scenario based on the selection of the selectable options.

3. The computer implementation method according to claim 2, wherein each of the one or more selectable options specifies a source of data used when simulating the baseline scenario.

4. The computer implementation method according to claim 3, wherein the source of data used when simulating the baseline scenario includes load prediction for the power distribution network.

5. The computer implementation method according to claim 3, wherein the source of data used when simulating the baseline scenario includes a dataset of power distribution network assets.

6. The computer implementation method according to claim 3, wherein the modified user interface displays a representation of at least one source of data used when simulating the baseline scenario.

7. The modified user interface includes an optional menu for updating the input, and the computer implementation method is The steps include receiving a selection from the menu of options for updating the input via the user interface, The steps include: running an updated simulation by modeling the updated inputs in the virtual model of the power distribution network; The computer implementation method according to claim 1, comprising the step of modifying the user interface to include one or more visualizations of the results of the simulation for the modified scenario, compared with the results of the updated simulation.

8. The computer implementation method according to claim 1, wherein the step of performing the simulation for the modified scenario includes the step of determining the characteristics of the virtual model of the power distribution network under various simulated conditions.

9. The computer implementation method according to claim 8, wherein the various simulated conditions include at least one of various environmental conditions or various load conditions.

10. The computer implementation method according to claim 1, wherein the proposed modification to the power distribution network includes at least one of the following: added or removed power sources, upgraded assets, or added or removed connections.

11. The computer implementation method according to claim 1, wherein the results of the simulation include the effect of the proposed modifications on the results of the simulation for the baseline scenario.

12. A step of evaluating the results of the simulation for the modified scenario using a set of rules, A step of determining that the result of the simulation for the modified scenario violates at least one rule from the set of rules, The computer implementation method according to claim 1, comprising the step of providing, for presentation on the display, a notification that the result of the simulation for the modified scenario violates at least one of the set of rules.

13. The computer implementation method according to claim 12, wherein each rule included in the set of rules comprises at least one of a law, regulation, equipment restriction, operational restriction, or industrial standard.

14. The computer implementation method according to claim 1, wherein the virtual model of the power distribution network includes a virtual model of real-world power distribution network assets.

15. The computer implementation method according to claim 1, wherein the geographical location includes the location of a selected feeder in a real-world power distribution network.

16. In response to receiving the input for the modification scenario, the step of accessing the virtual model of the power distribution network, wherein the virtual model includes a plurality of different model configurations, Based on the input to the modified scenario, the steps include: (i) selecting a simulation mode including the resolution and scale of the simulation; and (ii) selecting a model configuration from among the plurality of different model configurations. The computer implementation method according to claim 1, wherein the step of performing the simulation for the modified scenario includes the step of performing the simulation in the selected simulation mode using the selected model configuration.

17. A system comprising one or more computers and one or more storage devices storing instructions, wherein, when an instruction is executed by one or more computers, the system is operable to cause one or more computers to implement the computer implementation method described in any one of claims 1 to 16.

18. A non-temporary computer storage medium encoded with instructions, wherein, when executed by one or more computers, the instructions cause one or more computers to implement the computer implementation method described in any one of claims 1 to 16.

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