Patent Publication Number: US-2023154079-A1

Title: Distribution system visualization method and computing system

Description:
BACKGROUND 
     Field 
     The present disclosure is generally related to storage systems, and mom specifically, to systems and methods for efficiently and optimally generating visualizations of power distribution network topologies. 
     Related Art 
     Penetration of distributed energy resources (DERs) such as photovoltaic distributed generation (PV-DG), wind farm, and battery storage has grown significantly in the last ten years due to several factors such as policies, incentives, technologies, and cost reduction. This leads to adverse impacts on distribution systems and higher cost of analyzing the grid to accommodate, manage, and mitigate DERs to provide smooth and reliable operation of the grid. To study an impact of DER, a user may require both a distribution feeder model and a distribution planning simulation platform or a computing system. 
     A distribution feeder model is comprised of several classes of objects. Typical distribution feeder models are small, with less than 5,000 objects and typically between 3,000 and 5,000 objects. These small scale distribution feeder models can be visualized in a distribution planning simulation platform with minimal performance problem. 
     With increased penetration of DERs, there are needs to model behind-the-meter assets such as inverters, PV-DGs, battery storage devices, end-use-loads, etc. This adds a large number of objects to a distribution feeder model. Some distribution feeder models with behind-the-meter assets may contain 10,000-30,000 objects. Multiple feeders in a single model may contain over 100,000 objects. However, a computing system has limited resources and a user may suffer performance problems when working with a large feeder model, especially during visualization and editing a model via a distribution planning simulation platform. For example, if a computing system can support up to 5,000 objects, it may become slow and unresponsive when visualizing more than 5,000 objects. 
     Example related art implementations provides systems and simulation platform for distribution system planning. However, these systems do not provide any method, design, visualization, or user interface related to improving visualization performance of behind-the-meter equipment or edge device. 
     Thus, there remains a need for providing a user interface to model, visualize, and edit behind-the-meter equipment or edge device in detail and efficiently. 
     SUMMARY 
     Example implementations disclosed herein provide a distribution system visualization method and computing system for generating a distribution system visualization. Example implementations disclosed herein improve performance and provide an optimal user experience of a distribution planning simulation platform that can be utilized during distribution planning process, especially visualization of a large feeder model with DER and a large number of behind-the-meter assets. For example, a feeder model having 25,000 objects or more. Thus, the implementation disclosed herein can accelerate integration of DER to the grid and provide economic and stable operation of the electricity markets. 
     Example implementations disclosed herein offer significant improvements over the related art implementations by providing a user interface to model, visualize, and edit behind-the-meter equipment or edge devices in detail and efficiently. For example, implementations disclosed here dynamically select objects (e.g., conductive line, transformer, DER, behind-the-meter equipment, and/or edge devices) for generating a visual representation of the topology of a distribution feeder model based on one or more conditions related to the objects. By dynamically selecting and displaying objects, slowdowns and unresponsiveness in the system utilized for the distribution planning process is minimized, and in some cases completely avoided. 
     Example implementations disclosed herein may include setting a limit of objects to be displayed on a first visualization that displays a main map view of the topology of a distribution feeder model. Objects may refer to node objects and link objects that connect two node objects. In some implementations, a total number of the objects may be checked and, in a case where the total number of objects is less than or equal to the limit, implementations disclosed herein may be configured to display all objects on the main map view. In some implementations, alone or in combination, where the total number of objects exceeds the limit, the total number of link objects may be checked and, in a case where the total number of link objects is less than or equal to the limit, implementations disclosed herein may display all link objects on the main map view. In yet further implementations, alone or in combination, where the total number of link objects exceeds the limit, a total number of conductive line objects may be checked and, in a case where the total number of conductive line objects is less than or equal to the limit, implementations disclosed herein may display all conductive line objects on the main map view. Some implementations provide for selecting a portion (e.g., subset) of the conductive line objects based on one or more conditions (e.g., longest length, etc.) related to the conductive line objects, and displaying the selected portion of the conductive line objects. In some examples, the one or more conditions may include, for example, a first condition such as conductive line objects exceeding a length threshold. In some implementations, the one or more conditions may also include, for example, a second condition that is different from the first conditions. An example second condition may be, for example, a random selection method, every other selection method, every two selection method, etc. 
     Example implementations may further include a stand-by functionality, where the visualization of the topology awaits further inputs, for example, from a user via a user interface. Some example implementations may be configured to dynamically display additional link and/or node objects based on an input selecting an object. For example, in response to a user selection of an object not currently displayed on a main map view (e.g., displayed in a second visualization of the distribution feeder model and selection input thereon), implementations disclosed herein may dynamically display the selected object on the main map view. Optionally, the selected object may be highlighted on the main map view to assist pinpoint identification of the selected object. As another optional aspect, the selected object may be hidden on the main map view after a certain time period to reduce the impact on the resource utilization required to display the selected object. The input may select a plurality of objects for display on the main map view. As another example, implementations herein may be configured to dynamically display additional objects up to the limit based on a zoom level. 
     Some node objects in the distribution feeder model may contain one or more children objects. Some example implementations may be configured to display such parent objects in the main map view, while not displaying the children objects in the main map view. For example, a child map view may be provided in visualization, separate from the main map view, that displays a parent object with any children object(s) to reduce the utilization of the limited resource of the system. 
     Some example implementations may be configured to display one or more graphical indicators next to an object name in a tree diagram indicative that the associated object contains one or more children object(s). Some example implementations may be configured to display an object, which has one or more children object(s), using a graphical indicator indicative that the object has one or more children objects. The graphical indicator may be, for example, an edge or an outline generated around the object in the main map view. 
     Aspects of the present disclosure can involve a power distribution network visualization method. The method involves setting a limit of objects of the power distribution network to be displayed on a map, the objects comprising at least nodes and links between the nodes, the links comprising at least conductive lines; when the total number of the objects exceeds a limit, selecting one or more subsets of the conductive lines based on one or more conditions related to the conductive lines; and generating a first visualization displaying the map comprising a subset of the objects including the one or more subsets of the conductive lines, wherein a number of displayed objects is less than or equal to the limit. 
     Aspects of the present disclosure can involve a power distribution network visualization system. The system involves one or more memories configured to store a program, and one or more processors coupled to the one or more memories. The one or more processors may be configured to execute the instructions to: set a limit of objects of the power distribution network to be displayed on a map, the objects comprising at least nodes and links between the nodes, the links comprising conductive lines; when the total number of the objects exceeds a limit, select one or more subsets of the conductive lines based on one or more conditions related to the conductive lines; and generate a first visualization displaying the map comprising a subset of the objects including the one or more subsets of the conductive lines, wherein a number of displayed objects is less than or equal to the limit. 
     Aspects of the present disclosure can involve a non-transitory computer-readable medium, storing instructions for generating a visualization of a power distribution network. The instructions can involve: setting a limit of objects of the power distribution network to be displayed on a map, the objects comprising at least nodes and links between the nodes, the links comprising conductive lines; when the total number of the objects exceeds a limit, selecting one or more subsets of the conductive lines based on one or more conditions related to the conductive lines; and generating a first visualization displaying the map comprising a subset of the objects including the one or more subsets of the conductive lines, wherein a number of displayed objects is less than or equal to the limit. 
     Aspects of the present disclosure can involve an apparatus for generating a visualization of a power distribution network. The apparatus involving a means for setting a limit of objects of the power distribution network to be displayed on a map, the objects comprising at least nodes and links between the nodes, the links comprising at least conductive lines; when the total number of objects exceeds a limit, a means for selecting one or more subsets of the conductive lines based on one or more conditions related to the conductive lines; and a means for generating a first visualization displaying the map comprising a subset of the objects including the one or more subsets of the conductive lines, wherein a number of displayed objects is less than or equal to the limit. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The detailed description is set forth with reference to the accompanying figures. The figures are examples and not intended to limit the scope of the claims. The use of the same reference numbers in different figures indicates similar or identical items or features. 
         FIG.  1    illustrates an example visualization of a distribution feeder model in the form of a tree diagram, in accordance with example implementations disclosed herein. 
         FIG.  2    illustrates example visualizations of a topology of the distribution feeder model of  FIG.  1    in a main map view, in accordance with example implementations disclosed herein. 
         FIG.  3    illustrates example plots of information related to lengths of link object and a number of link objects, in accordance with example implementations disclosed herein. 
         FIG.  4    illustrates an example visualization of a child map view of the distribution feeder model of  FIG.  1   , in accordance with example implementations disclosed herein. 
         FIG.  5    illustrates a portion of the tree diagram shown in  FIG.  1    with examples of graphic indicator(s) indicative of object visualization characteristics, in accordance with example implementations disclosed herein. 
         FIG.  6    illustrates an example topology of an example distribution feeder model in a main map view with examples of graphical indicator(s) indicative of child relationship properties of example objects, in accordance with example implementations disclosed herein. 
         FIG.  7    is a flow diagram illustrating an example distribution system visualization method, in accordance with example implementations disclosed herein. 
         FIG.  8    illustrates example methods of selecting a subset of conductive line objects, in accordance with example implementations disclosed herein. 
         FIG.  9    illustrates example visualizations of the topology of the distribution feeder model of  FIG.  1    in main map views displaying link objects, in accordance with example implementations disclosed herein. 
         FIG.  10    illustrates example visualizations of the topology of the distribution feeder model of  FIG.  1    in main maps view displaying 50% of conductive line objects, in accordance with example implementations disclosed herein. 
         FIG.  11    illustrates example visualizations of the topology of the distribution feeder model of  FIG.  1    in main map view displaying 25% of conductive line objects, in accordance with example implementations disclosed herein. 
         FIG.  12    illustrates visualizations of the topology of the distribution feeder model of  FIG.  1    in a main map view at different zoom levels, in accordance with example implementations disclosed herein. 
         FIG.  13    illustrates example visualizations of the distribution feeder model of  FIG.  1    in the form of tree diagrams with example graphical indicators of display status of object classes in a main map view, in accordance with example implementations disclosed herein. 
         FIG.  14    illustrates a system involving one or more equipment and a management apparatus, in accordance with an example implementation. 
         FIG.  15    illustrates an example computing environment with an example computer device suitable for use in some example implementations. 
     
    
    
     DETAILED DESCRIPTION 
     The following detailed description provides details of the figures and example implementations of the present application. Reference numerals and descriptions of redundant elements between figures are omitted for clarity. Terms used throughout the description are provided as examples and are not intended to be limiting. For example, the use of the term “automatic” may involve fully automatic or semi-automatic implementations involving user or administrator control over certain aspects of the implementation, depending on the desired implementation of one of ordinary skills in the art practicing implementations of the present application. Selection can be conducted by a user through a user interface or other input means, or can be implemented through a desired algorithm. Example implementations as described herein can be utilized either singularly or in combination and the functionality of the example implementations can be implemented through any means according to the desired implementations. 
     Further, in the following description, the information is expressed in a table format, but the information may be expressed in any data structure. Further, in the following description, a configuration of each information is an example, and one table may be divided into two or more tables or a part or all of two or more tables may be one table. 
       FIG.  1    illustrates an example visualization  100  of a distribution feeder model Feeder1 in the form of a tree diagram  105 , in accordance with example implementations disclosed herein. Visualization  100  may be generated by a computing system, for example, by computing environment  1500  of  FIG.  15   . The generated visualization  100  may be presented as part of a graphical user interface (GUI) that is displayed on a display of the computing environment and may be interactable by a user view GUI. The visualization may be utilized, for example, as part of distribution planning process, for example, via a distribution planning simulation platform. 
     In the illustrative example of  FIG.  1   , Feeder1 comprises a plurality of link objects and a plurality of node objects. Objects may represent any equipment that transfers electricity from a sub-station, downstream or down the line, to electricity consuming equipment. As used herein, link objects may refer to several classes of objects such as, but not limited to, overhead (OH) lines (also referred to as OH conductors), transmission lines, regulators, switches, transformers, triplex lines, underground lines (or cables), fuses, reclosers, sectionalizers, series reactors, and so on. Furthermore, as used herein, the term “conductive line” or “conductive lines” may refer to one or more classes of link objects, such as but not limited to, OH line objects, underground line objects, transmission line objects, and other similar objects. In some implementations, conductive lines may refer to the OH line object class only, while in others conductive lines may refer to OH lines and other link object classes. As used herein, node objects may refer to several classes of objects such as, but not limited to, nodes, substations, triplex nodes, capacitors, triplex meters, loads, meters, motors, triplex loads, and so on. Each class of objects may comprise a plurality of individual objects, which may be, for example, DER, behind-the-meter equipment, and/or edge devices. In this illustrative example, each node object may be associated with (e.g., in a database storing data of the distribution feeder model) geographic information, such as latitude and longitude coordinates. Each node object may be generated and displayed in a main map view according to the geographic information (e.g., as described in  FIG.  2    below). In the example implementations herein, a link object may be a connector between two node objects, and thus geographic information for displaying each link object may be based on the geographic information for the corresponding nodes. 
     In some example implementations, the visualization  100  may include parenthetical numbers adjacent to objects in the tree diagram  105 . The number may indicate a number of objects underneath the object class associated with the number. That is, in the illustrative Feeder1, there are 5000 link objects, which includes 2500 individual OH lines, 10 individual regulators, 1220 individual transformers, and 1220 individual triplex lines. Similar information is provided for the number of node objects and each respective node object class (e.g., 7000 node objects). Underneath each object class may be a listing of each object with identifying information and geographic information. 
     The visualization  100  may also include child objects tree  110 . Child objects are objects that belong to (e.g., associated with) a parent object and shares the same geographic information as the parent object. In the example of  FIG.  1   , there are 5,000 objects considered as children objects for Feeder1. 
     Thus, in this illustrative example, there are a total of 27,000 objects (e.g., link, node, and child objects), belonging to various classes and geographic information, that can be shown in a main map view. 
     While the foregoing discussion is made with reference to Feeder1, such reference is provided as an illustrative example only. Example implementations provided herein may include a plurality of distribution feeder models as shown in  FIG.  1    (e.g., FeederA, FeederB, etc.). Each feeder model may be represented by corresponding tree diagram underneath, which includes respective link, node, and child objects. 
       FIG.  2    illustrates example visualizations  215  and  225  a topology of the distribution feeder model of  FIG.  1    in main map views  210  and  220 , in accordance with example implementations disclosed herein.  FIG.  2    illustrates a main map view  210  depicting a first visualization  215  displaying all objects of the distribution feed model Feeder1 (e.g., over 27,000 objects) from sub-station  217  and a main map view  220  depicting a second visualization  225  displaying only link objects of the distribution feed model Feeder1. The graphical representation of the objects in visualizations  215  and  225  are based, in part, on the geographic information of the node objects included in Feeder1. That is, for example, each node and link object in the main map views  210  and  220  are positioned based on the geographic information associated with each node and link object. 
     Visualizations  215  and/or  225  may be generated by a computing system, for example, by computing environment  1500  of  FIG.  15   . The generated visualizations  210  and/or  220  may be presented as part of a graphical user interface (GUI) that is displayed on a display of the computing environment and may be interactable by a user view GUI and visualization may be utilized, for example, as part of distribution planning process, such as via a distribution planning simulation platform. 
     As noted above the visualization  215  displays all objects of Feeder1. In this case, child objects that belong to residential and generators group, especially behind-the-meter objects such as house, inverter, solar, and battery, may share the same geographic information. Displaying objects with the same geographic information is redundant and does not assist in displaying connectivity among objects properly. In addition, such information may not provide useful information to a user regarding the topology. 
     This redundancy in displaying all objects of large distribution feeder models at the same time causes slowdowns in computing systems displaying the information due to unnecessary utilization of computing resources. Thus, the system may become unresponsive, for example, due to trying to load all objects at once. For example, if the system resources can efficiently support up to 5,000 objects, displaying lower than 2,500 objects provides rapid response for a user to use the system efficiently. Between displaying between 2,500 to 5,000 objects may cause the system to slow down, while providing sufficient response. However, at 5,000 objects or more, the system may become unresponsive. 
     Referring to main map view  220 , the visualization  225  displays only the link objects. The total number of all link objects in Feeder1 is 5,000 (e.g., a combination of 2,500 overhead line objects and 2,500 of the other link objects such as regulator, switch, transformer, and triplex line). 
     From a whole feeder model viewpoint (e.g., viewing the entire topology of the distribution feeder model), displaying only link objects may be a good representation of the topology. However, example implementations disclosed herein are configured to further reduce the number of objects to be displayed, while maintaining a good representation of the topology of the distribution feeder model, as describe below, for example, in connection to  FIG.  3   . 
     Thus, example implementations disclosed herein may take into consideration that certain link objects may be relatively longer than other link objects. For example, overhead line objects (e.g., object  227  is an example illustrative of a longer line representative of an overhead line object) are relatively longer in length and display on the main map view as longer lines while other link objects relatively shorter in length may be shown as shorter lines or dots in the main map view (e.g., object  229 ). 
       FIG.  3    illustrates example plots  310  and  320  of information related to link object lengths and number of link objects of the example of the distribution feeder model Feeder1. 
     Plot  310  illustrates an example histogram of lengths of link object of the distribution feeder model Feeder1 from  FIG.  1   . In some examples, plot  310  may illustrate a histogram of lengths of all link objects, while, in another example, plot  310  may illustrate a histogram of lengths of links of a respective class or group of classes of link objects (e.g., conductive line objects). Plot  310  illustrates normalized lengths of link object on the x-axis, where the longest length is normalized to 1 and the shortest length is 0. The lengths are grouped into ranges. On the y-axis, plot  310  provides frequency (e.g., number of link objects corresponding to each range of lengths). For example, in the illustrative example of plot  310 , there are 1,250 link objects (or 50%) of the link objects that have a length shorter than 0.05 unit. Similarly, 2,120 link objects (or 84%) of the conductive line objects are shorter than 0.10 unit. The remaining 16% of the link objects are relatively long, for example, between 0.10 to 1.00 unit. 
     Plot  320  illustrates an example line graph of accumulated length of topology of the distribution feeder model versus accumulated number of link objects of the distribution feed model for two example selection methods. The double dotted line  322  illustrates a random selection method, whereby link objects are selected randomly from all link objects. The solid line  324  illustrates a second selection method in accordance with the example implementations disclosed herein, for example, selection of link objects based on relative length of the link objects. In some implementations, plot  320  may be all link objects, a class of links objects, or a plurality of classes. For example, as shown in plot  320 , the link objects considered are conductive line objects. 
     With the random selection method plotted as line  322 , 10% of accumulated number of link objects represent approximately 10% of accumulated length of the topology (e.g., represents 10% of the entire length of the distribution feeder model). As another example point, 60% of accumulated number of objects represent approximately 60% of accumulated length of the feeder. 
     With the second selection method plotted as line  324 , where selection of link objects is based on relative length, a smaller percentage of accumulated number of link objects may represent a greater percentage of the accumulated length (e.g., fewer link objects are needed to represent a greater percentage of the topology of the distribution feeder model). In this selection method, link objects of relatively longer lengths are selected prior to link objects of shorter length. For example, 10% of accumulated number of objects represent approximately 30% of accumulated length of the feeder and 60% of accumulated number of objects represent approximately 90% of accumulated length of the feeder. Additional number of objects provide less additional information. 
     By leveraging a selection method according to the implementations disclosed herein, such as selection based on the relative length, a small number of objects can be utilized to represent a majority of the feeder topology. 
       FIG.  4    illustrates an example visualization  400  of a child map view, in accordance with example implementations disclosed herein. The visualization  400  generates a graphical representation of a parent object  410  and corresponding children objects  420 - 470 . The visualization  400  may be generated separate from a main map view (e.g., main map views  210  and/or  220 ) to reduce the utilization of the limited resource of the system. Similarly, the visualization  400  may be generated separately from the visualization  100  of  FIG.  1   . 
     In the example visualization  400 , a parent object  410  (e.g., triplex meter) is displayed with six behind-the-meter objects (e.g., children objects  420 - 470 ) of the distribution feeder model from  FIG.  1    that share the same geographic information as the parent object  410 . The example visualization  400  is a child map view of a single house object  420  connected to a triplex meter object  410 . The house object  420  contains an inverter object  430 , a water heater object  440 , and other load objects  450  (e.g., one or more additional loads on the feeder model). Inverter  430  may be connected to a PV-DG (Photovoltaic Distribution Generation) object  460  and a battery storage object  470 . While house object  420  is a child object of the triplex meter object  410 , the house object  420  is also a parent object of the inverter object  430 , the water heater object  440 , and the other load objects  450 . In various implementations, only node objects may have children objects. 
     In various example implementations, on a main map view, the system may display only an upper most parent object (e.g., the triplex meter object  410  in the illustrative example of  FIG.  4   ) that is connected directly to other objects of the distribution feeder model as shown in the main map view  210  of  FIG.  2   . For example, based on the example distribution feeder model in  FIG.  1   , only 12,000 objects may be displayed in the main map view instead of all 27,000 objects of the distribution feeder model. 
     In some implementations, visualization  400  may be displayed as a separate child map view (e.g., a separate window or pane of the GUI either adjacent to or overlaid) when a user requests to visualize information of children object(s) of a selected parent object. For example, as described below in greater detail, a user may select a parent object from the tree diagram  105  of  FIG.  1    and/or the main map view, and in response to the selection a child map view may open in a second window pane or viewport. The GUI may provide an interface through which the user can switch between the main map view and the child map view. The child map view may be closed at any time. 
     Separation of child map view from the main map view may reduce redundancy and cluttering that may result from showing multiple objects sharing the same geographical information in the main map view. This method reduces utilization of the resource of the system significantly. 
       FIG.  5    illustrates a portion  500  of tree diagram  105  of the example visualization of the distribution feeder model of  FIG.  1   , in accordance with example implementations disclosed herein.  FIG.  5    also illustrates examples of graphical indicators  510 - 530  indicating child relationship properties of objects of the tree diagram  105 . 
     In the illustrative example of  FIG.  5   , portion  500  is a portion of the tree diagram  105  including a class of node objects. In this example, the top level node object in the portion  500  is a house object class. The house class may be displayed underneath the residential class of node objects in the child objects tree  110  portion of the tree diagram  500 . For example, as shown in  FIG.  1   , child objects tree  110  includes residential class of nodes and underneath the residential class includes, among other possible nodes, the house class node objects shown as the top level of  FIG.  5   . Further underneath the house class of node objects are distinct node objects, such as house1 and house2 in the illustrative example of  FIG.  5   . While two house objects are shown in  FIG.  5   , it will be appreciated that the number of distinct node objects underneath the house class of  FIG.  5    may be more than two. For example, as represented by the “(500)” in  FIG.  5   , there may be 500 distinct house objects underneath the house class. 
     As shown in  FIG.  5   , one or more graphical indicators  510 - 530  maybe be generated and displayed adjacent to each respective object of the tree diagram. Each graphical indicator may be indicative of a respective visualization property (also referred to as a visualization characteristic) of an associated object. Graphical indicators  510 - 530  may be generated in the form of distinct icons indicative of a given property or characteristic. 
     For example, as shown in  FIG.  5   , graphical indicators  510 - 530  are displayed adjacent to each house object. Graphical indicator  510  may indicate that the associated object contains one or more children objects. For example, a house object may contain inverter, water heater, and other loads, for example, as described above in connection to  FIG.  4   . While graphical indicator  510  is shown for both house1 and house2, if an object does not contain any children objects the graphical indicator  510  may not be displayed or an alternative indicator may be displayed (e.g., graphical indicator  510  with a line or “X” through it). Graphical indicator  520  may indicate that the associated object is not displayed in a main map view (e.g., the main map view of  FIG.  2   ). This may be the case if the object is not displayed due to the limit of objects being exceeded (as described herein) and/or that the object itself is a child. In some implementations, the object may be shown in a child map view, as shown in  FIG.  4   . Graphical indicator  530  may indicate that the associated object is a child object associated with a parent node. For example, as shown in  FIG.  5   , each house object may be a child of a triplex meter object, as shown in  FIG.  4   . 
       FIG.  6    illustrates an example topology of an example distribution feeder model displayed in a main map view  600  with example graphical indicator(s) indicative of child relationship properties of displayed objects, in accordance with example implementations disclosed herein. In the illustrative example, main map view  600  includes visualizations of a plurality of objects  610 - 690 . Objects  610 - 650  are examples of node objects connected by link objects  660 - 690 . The main map view  600  may be an illustrative portion of a larger main map view (e.g., the main map views of  FIG.  2   ). 
     As described above, one or more of the node objects may be associated with one or more children objects. The characteristic or property of containing children objects may be indicated in the main map view  600  by displaying each object using a graphical indicator (or icon) indicative of the characteristics and/or property. For example, objects  610 ,  620 , and  630  may be example node objects that are not associated with any children objects, while objects  640  and  650  may be examples of objects that contain one or more children objects. To indicate that the objects do not contain any children objects, objects  610 - 630  may be displayed using an icon that does not include an edge or outline (e.g., a solid icon). To indicate that the objects do contain one or more children objects, the objects  640  and  650  may be displayed using an icon having an edge or outline, as illustrated in  FIG.  6   . 
     As another example, objects having one or more children objects may be displayed without an edge or outline, while objects not having children objects may be displayed with an edge or outlined (e.g., the reverse of what is shown in  FIG.  6   ). In another example, differently shaped icons (e.g., circular, ovular, square, etc.) may be used in the main map view to indicate respective properties. In some implementations, a first icon may be indicative of no children objects, a second icon indicative of one child object, and a third indicative of a plurality of child objects. 
     As noted above, the concept of icons described in connection to  FIG.  6    may be applied to the various node objects shown in visualization  210  of  FIG.  2   . 
       FIG.  7    is a flow diagram illustrating an example distribution system visualization process  700 , in accordance with example implementations disclosed herein. The process  700  may provide an improved user experience and information visualization for use during distribution planning process, for example, via a distribution planning simulation platform. For example, process  700  may provide for limiting the number of objects of a distribution feeder model that are displayed on a main map view of the system, while providing optimal geographic information representation of a feeder model (e.g., as described in connection to  FIG.  3   ). By reducing the number of objects to be displayed, the computation resources are efficiently utilized in displaying the feeder model, without slowdown and/or failure. According to various example implementations, the process  700  may be executed, for example, in a computing environment, such as the computing environment  1500  described in connection with  FIG.  15   . 
     Process  700  provides improvements over related art implementations in various ways. For example, with regards to related art implementations utilizing the display of picture tiles, a user may not be able to locate the actual location of an object on the map view. As another example, with regards to related art implementations relying on clustering objects together and displaying as a number, a user may not know the exact location or topology of a distribution feeder model. Both of these above noted approaches are not suitable to a distribution feeder model including grid assets. 
     Implementations herein are not limited to the particular examples provided and may be extended to other types of objects. For instance, the total number of OH objects may extend to cover other classes of object such as underground line, transmission lines, etc. As noted above, the term conductive lines may be used to refer to one or more classes of link objects, such as but not limited to, OH line objects, underground line objects, transmission line objects, etc. In some implementations, conductive lines may refer to OH line object class only, while in others conductive lines may refer to OH lines and other link object classes based on the various objects included in a respective distribution feeder model to be displayed according to the implementations disclosed herein. 
     While the following description and reference to the number of objects is based on an example of the distribution feeder model in  FIG.  1   , it will be appreciated that this reference is for illustrative purposes only. Process  700  may be applied to a distribution feeder model of any number of objects. While the implementations herein are particularly well suited for distribution feeder models having a large number of objects (e.g., 25,000 or more) so to reduce adverse impact on computation resource utilization, the process and methods herein may be applied to any distribution feeder model. 
     The process  700  starts at step  705 , where a limit for number of objects to display on a main map view is set. For example, the limit may be set to 1,250 objects permissible to be displayed on the main map view (e.g., main map described in connection with  FIG.  2   ). The limit may be set based on consideration of computation resources of the system so to minimize performance problems and slowdowns resulting from generating and displaying a significant number of objects. In some implementations, the limit may be set based on consideration of sharing computing resources of a system with other programs and/or browser open and running at the same time as the implementations disclosed herein. For example, sharing of computation resource amongst multiple programs may result in slow downs, necessitating a lower limit. 
     At step  710 , the process  700  determines whether the total number of objects in the distribution feeder model exceeds the limit set at step  705 . For example, at step  710  the number of objects contained in the distribution feeder model may be retrieved and/or identified from a database storing the distribution feeder model and the total number of objects may be compared against the set limit. If the total number of objects is less than or equal to the limit set at step  705 , the process  700  proceeds to step  715 , where all objects are generated and displayed on a main map view (e.g., as described in connection with visualization  210  of  FIG.  2   ). Otherwise, in the case where the total number of objects exceeds the limit set at step  705 , the process  700  proceeds to step  720 . 
     At step  720 , the process  700  determines whether the total number of link objects contained in the distribution feeder model exceeds the limit set at step  705 . For example, at step  720  the total number of link objects is identified and compared against the set limit. If the total number of link objects is less than or equal to the limit set at step  705 , the process  700  proceeds to step  725 , where all link objects are generated and displayed on a main map view. In some implementations, the main map view displayed following step  725  may not display any node objects, such that only link objects are displayed. In another implementation, the main map view following step  725  may include a number of node objects, such that the total number of objects displayed does not exceed (e.g., less than or equal to) the limit. For example, children objects may not be displayed and a random selection method may be used to select node objects to be displayed. As another example, the nodes objects to be displayed may be customizable. For example, a user may set a priority of node object types, such that higher prioritized node objects are displayed first until the limit is reached (e.g., a user may set load node objects to have a higher priority than capacitor node objects and the process  700  will display load node objects first and then, if the limit is not yet reached, display capacitor objects). In the case where the total number of link objects exceeds the limit set at step  705 , the process  700  proceeds to step  730 . 
     At step  730 , the process  700  determines whether the total number of conductive line objects exceeds the limit set at step  705 . For example, at step  730  the total number of conductive line objects is identified and compared against the set limit. In some implementations, as noted above, conductive line objects may refer to only OH line objects, while in other implementations conductive line objects may refer to a plurality of classes of link objects (e.g., one or more of OH line objects, transmission lines, underground lines, etc.) as desired based on the respective distribution feeder model and the link object classes included therein. In a case where the total number of conductive line objects is less than or equal to the limit set at step  705 , the process  700  proceeds to step  735  where all conductive line objects are generated and displayed on a main map view. 
     If the total number of conductive line objects exceeds the limit set at step  705 , the process  700  selects one or more subsets of the conductive line objects identified at step  730  based on one or more conditions related to the conductive lines, and generates the main map view displaying a visualization of the distribution feeder model topology using the one or more subsets of the conductive lines. For example, the one or more conditions may be a plurality of conditions, each condition different from each other and configured to select one or more subsets of conductive line objects that are representative of the overall topology of the distribution feed model (e.g., as described in connection to  FIG.  3   ). 
     For example, where the process determines the number of conductive line objects exceeds the limit at step  735 , the process  700  proceeds to step  740 . At step  740 , the process  700  selects a first subset (also referred to as a first portion) of the conductive line objects identified at step  730  based on a first condition related to the conductive lines. For example, the distribution feeder model under consideration in process  700  may contain main conductive line objects with longer sections as a backbone of the system and lateral conductive line objects with shorter sections to cover wider area toward the end of the feeder model. At step  740 , according to some examples, the process  700  may select a small portion (e.g., subset) of conductive line objects that represent the most of the overall topology of the distribution feeder model, for example, an amount of the accumulated length of the distribution feeder model that is representative of the overall topology. For example, the first condition may be set to select the top 10% longest length conductive line objects relative to the remaining conductive lines, such that the first subset of conductive line objects selected at step  740  are only those top 10%. That is, the conductive line objects may be ordered according to their respective lengths (e.g., as shown by plot  310  of  FIG.  3   ) and the top 10% of the conductive line objects may be selected at step  740 . 
     For example, the distribution feeder model from  FIG.  1    contains a total of 2,500 Oil objects. The process  700  may select the top 10% (e.g., top 250 OH objects) with the longest length relative to the remaining 01 lines at step  740 . As shown in  FIG.  3   , plot  320  shows that this 10% of OH objects represents 30% of accumulated length of all OH objects. 
     While 10% of conductive line objects having the longest relative length is used herein as an example, other criteria may be utilized. For example, the first condition may be to select the top 20%, 30%, etc., of conductive line objects that may be used. As another example, the first condition may be based on selecting all of a first phase conductive line objects before second phase conductive line objects (e.g., selecting all of 3 phases conductive line objects before single phase conductive line objects). As yet another example, the first condition may be based on selecting all of conductive line objects corresponding to a first voltage level before conductive line objects corresponding to a second voltage level (e.g., selecting all conductive line objects corresponding to 25 kV before conductive line objects corresponding to 12 kV). 
     The process  700  may then proceed to step  745 , where the process selects a second subset (e.g., second portion) of the remaining conductive line objects. Step  745  may be configured to select a portion of the remaining conductive line objects to cover wider area toward the end of the feeders (e.g., a portion of the conductive lines having smaller lengths which tend to be located toward the end of the distribution feeder model). At step  745 , the process  700  may select a number of the remaining conductive line objects up to the limit set at step  705  object. 
     Selection at step  745  from the remaining conductive line objects may be based on a second condition. The second condition may be different from the first condition. For example, the second condition may be a random selection method, whereby the conductive line objects for the second portion are randomly selected from the remaining conductive line objects. Additional examples for the second condition are described in connection with  FIG.  8   . 
     As an illustrative example with reference to the example distribution feeder model of  FIG.  1   , the distribution feeder model contains a total of 2,500 OH objects. From step  740 , 10% of the 2,500 OH objects is 250 OH objects (e.g., an example of a first subset of the conductive line objects). At step  745 , the process selects 1.000 objects from remaining OH objects (e.g., an example of a second subset of conductive line objects), based on the limit of 1250 objects set at step  705  and the 250 OH objects selected step  740 . At step  745 , the 1,000 objects may be selected by, but not limited to, the random selection method. 
     In some implementations, step  745  may utilize a second condition related to the conductive line objects to select the subset of the remaining conductive line objects. For example, second condition may be a percentage of the remaining conductive line objects having relatively longer lengths. In some implementations, step  745  may include one or more steps of selecting from the remaining conductive line objects based on one or more conditions related to the conductive line objects followed by a random selection method step to meet the limit. In another example, the second condition may be based on phase of the conductive line objects or voltage levels. 
     In another example, the first condition may be based on a phase of the conductive line objects and the second condition may be based on length or voltage level. Similarly, the first condition may be based on voltage level and the second condition based on length or phase. 
     Once the one or more subsets of conductive line objects are selected at steps  740  and/or  745 , the process  700  proceeds to step  750  where only the selected subsets of conductive line objects are displayed in a main map view. From the above example referring to  FIG.  1   , the total number of OH objects (e.g., 2,500 OH objects) exceeds the limit set at step  705 , which is set at 1,250 objects in this example. At step  740 , the process  700  selects 250 OH objects based on the first condition and, at step  745 , the process  700  selects 1,000 OH objects based on the second condition. Thus, the one or more subsets of OH objects selected by the process  700  is at the limit set at step  705 . The process  700  then displays the 1,250 OH objects in a main map view at step  750 , which is representative of the topology of the distribution feeder model (e.g., 30% from the first subset plus topology represented by the second subset). 
     The combination of the subsets selected at steps  740  and  745  allows a system with limited resources to display both (1) information in terms of accumulated length aspects and (2) wide area location aspects of a feeder model on a main map view optimally, without slowdown or system failure. 
     Following steps  715 ,  725 ,  735 , or  750 , the visualization of the distribution feeder model topology in the main map view may represent the whole (e.g., entirety) feeder view. This view may be representative of the entire geographic service area corresponding to the distribution feeder model. 
     In some example implementations, the process  700  may include optional step  755 , where the process is configured to stand-by for further input action from a user of the computing environment on which process  700  is executed. During step  755 , the computing environment may generate and display the visualization of the main map view based, for example, on steps  710 - 750 . That is, for example, where the limit is not exceeded at step  720 , the main map view may display all link objects; where the limit is not exceeded at step  730 , the main map view displays all conductive line objects, and otherwise the main map view displays the distribution feeder model based on the one or more subsets of conductive line objects from steps  740  and  745 . The whole service area of the distribution feeder model may also be displayed, either in combination or separately. 
     The process  700  may also include optional step  760 , where process  700  dynamically displays additional objects based on a selection of an object. For example, user input may select one or more objects from a visualization, separate from the main map view (e.g., the tree diagram of  FIG.  1   ). The selected object(s) may not be currently displayed on the main map view. Based on receiving the object selection, process  700  may dynamically update the main map view to display the selected object(s). In some implementations, the last one or more link objects added to the subset at step  745  may be removed from the main map view in response to adding the selected object(s), such that the total number of objects displayed in the main map view is maintained at the limit set at step  705 . In another example, the selected object(s) may be added while continuing to display all objects displayed in the main map view prior to adding the selected object(s). In some implementations, the selected object(s) may be displayed and highlighted in the main map view to assist pinpoint location of the selected object(s) on the main map view. In another implementation, either alone or in combination, the selected object(s) may be hidden on the main map view after a certain time period (e.g., 5 minutes or other desired time period), so as to limit the resource utilization required to display the selected object. The time period may be set by the user in a setting menu. 
     The process  700  may also include optional step  765 , where the process  700  dynamically displays additional objects up to the limit set in step  705  in response to changes in zoom level. For example, user input may request a zoom-in operation to view a portion of the geographical area of the distribution feeder model topology. At step  765 , the process  700  may unload (e.g., unselect and remove from generation and display) one or more objects that are not in a current viewing area (e.g., viewport or window) of the main map view, such that the unloaded objects are no longer necessary for the visualization that is generated. Additionally, in some implementations, the process  700  may dynamically display additional objects not previously displayed in the whole feeder view level from step  725 ,  735 , or  750 . The total number of objects in the zoomed in visualization is limited by the limit set in step  705 , such that for any zoom-in operation the number of objects viewed does not exceed the limit. Additional details of the zoom-in operation are described below in connection to  FIG.  12   . 
       FIG.  8    illustrates example methods of selecting a subset of conductive line objects, in accordance with example implementations disclosed herein. For example,  FIG.  8    may illustrate examples of approaches for implementing in step  745 . As noted above, step  745  may include selecting a second subset of conductive line objects based on a second condition.  FIG.  8    illustrates example conditions, illustratively shown as schematics  820 - 840 , that may be used as the second condition for selecting conductive line objects at step  745 . 
     For example, schematic  810  illustrates an example of 20 conductive line objects. For illustrative purposes, the 20 conductive line objects may be considered the remaining conductive line objects following step  740 . Schematic  820  illustrates an example condition where every other conductive line object is selected, resulting in a selection of 10 conductive line objects. Schematic  830  illustrates an example of selecting every other two conductive line objects, resulting in selection of ten conductive line objects. Schematic  840  illustrates an example of selection of 10 conductive line objects using a random selection method. 
       FIG.  9    illustrates example visualizations  915  and  925  of the topology of the distribution feeder model of  FIG.  1    in main map views  910  and  920  displaying link objects, in accordance with example implementations disclosed herein.  FIG.  9    is an example for a system with limited resources that may not respond efficiently when displaying all objects of an example of the distribution feeder model in  FIG.  1   , as shown in visualization  210  of  FIG.  2   . 
     Main map view  910  illustrates an example visualization  915  displaying all 5,000 link objects of the distribution feeder model of  FIG.  1   . In this case, the limit set by a user at step  705  of  FIG.  7    for visualization  915  is 5,000 objects. The total number of objects displayed in visualization  915  is a combination of 2,500 overhead line objects and 2,500 of other link objects such as regulator, switch, transformer, and triplex line objects. Thus, in this example, visualization  915  displays only link objects. 
     Main map view  920  illustrates an example visualization  925  displaying 2,500 link objects of the distribution feeder model of  FIG.  1   . In this case, the limit at step  705  may have been set to 2,500 objects. Thus, the total number of objects may be 2,500 overhead line objects. 
     In main map views  910  and  920 , the information displayed by both visualization  915  and visualization  925  are quite similar; however, the system resource utilization for visualization  925  is much smaller than that of visualization  915  since visualization  925  contains half the number of objects to be generated and displayed as compared to visualization  915 . 
     At a whole feeder view (e.g., entirety of the topology), both visualization  915  and visualization  925  may function as good representations of the entire feeder topology as compared to the visualizations of  FIG.  2   . 
       FIG.  10    illustrates example visualizations  1015  and  1025  of the topology of the distribution feeder model of  FIG.  1    in main map views  1010  and  1020  displaying 50% of conductive line objects, in accordance with implementations disclosed herein. The example visualizations of  FIG.  10    are examples that utilize fewer system resources than the example visualizations of  FIG.  9   . For example, the limit set at step  705  for generating the visualizations  1015  and  1025  of  FIG.  10    may be 1,250 objects. 
     Main map view  1010  illustrates an example visualization  1015  of the distribution feeder model of  FIG.  1    displaying 50% of conductive line objects using a random selection method to select the displayed objects. 
     Main map view  1020  illustrates an example visualization  1025  of the distribution feeder model of  FIG.  1    displaying 50% of conductive line objects according to implementations disclosed herein. For example, visualization  1025  illustrates a combination of step  740  (e.g., the top 10% of the longest length conductive line objects as the first condition) and step  745 , where the second condition is a random selection method of the remaining conductive line objects. 
     Both visualization  1015  and visualization  1025  contain 1,250 conductive line objects, but visualization  1025  clearly provides more detailed information of accumulated length of the distribution feeder model than that of visualization  1015 . 
       FIG.  11    illustrates example visualizations  1115  and  1125  of the topology of the distribution feeder model of  FIG.  1    in main map views  1110  and  1120  displaying 25% of overhead line, in accordance with example implementations disclosed herein. The example visualizations of  FIG.  11    are examples that utilize fewer system resources than the example visualizations of  FIGS.  9  and  10   . For example, the limit set at step  705  for generating the visualizations of  FIG.  11    may be 625 objects. 
     Main map view  1110  illustrates an example visualization  1115  of the distribution feeder model of  FIG.  1    displaying 25% of conductive line objects using a random selection method to select displayed objects. 
     Main map view  1120  illustrates an example visualization  1125  of the distribution feeder model of  FIG.  1    displaying 25% of conductive line objects according to implementations disclosed herein. For example, visualization  1120  illustrates a combination of step  740  (e.g., the top 10% of the longest length conductive line objects as the first condition) and step  745 , where the second condition is a random selection method of the remaining conductive line objects. 
     Both visualization  1115  and visualization  1125  contain 625 conductive line objects, but visualization  1125  clearly provides more detailed information of accumulated length of the distribution feeder model than that of visualization  1115 . 
       FIG.  12    illustrates visualizations  1215 ,  1225 ,  1235 , and  1245  of example main map views  1210 ,  1220 ,  1230 , and  1240  at different zoom levels, in accordance with example implementations disclosed herein. For example,  FIG.  12    illustrates example visualizations at different zoom levels of the main map displayed according to step  765  of  FIG.  7   . 
     For illustrative purposes only, the visualization  1215  is similar to visualization  1125  of  FIG.  11   . Visualization  1215  illustrates the example distribution feeder model topology displayed using 25% of the conductive line objects with the method according to the implementations disclosed herein. That is, visualization  1215  illustrates a combination of step  740  (e.g., the top 10% of the longest length conductive line objects as the first condition) and step  745 , where the second condition is a random selection method of the remaining conductive line objects. A dotted rectangle  1217  is shown in main map view  1210  indicating an area of the topology to be zoomed into, thus defining a zoom-in level. The zoom-in operation may be in response to a user input, for example, following the stand-by step  755  of  FIG.  7   . Visualization  1225  illustrates the resulting visualization following the zoom-in operation defined by box  1217 . 
     Visualization  1225  illustrates a portion of the topology of visualization  1215  following the zoom-in action, where the topology displayed by visualization  1225  corresponds to the portion defined by box  1217 . The computing environment dynamically updates the main map view  1220  by unloading unnecessary objects and adding new objects to be displayed. Thus, the visualization  1225  displays additional objects up to the limit, while unloading objects displayed in visualization  1210  that are now outside of the zoomed-in visualization  1225  displayed in main map view  1220 . In an illustrative example, the additional objects added to the visualization  1225  may be link objects, such that link objects that were not included in visualization  1215  are now added, while previously selected link objects are removed. In an example, objects to be added may be selected by the method described in connection to  FIG.  8   . As another example, objects to be added may be selected according to length as described herein (e.g., step  740  of  FIG.  7   ). The link objects added to the displayed visualization provide additional details of the zoomed-in topology, while avoiding adverse impact to system performance and resource utilization. 
     Visualization  1235  illustrates another zoom-in action where the geographic area displayed corresponds to box  1227  of main map view  1220 . In this illustrative example, the main map view  1230  is dynamically updated by adding additional objects to the visualization  1235  while removing objects from visualization  1225  that are outside of the main map view  1230 . In this case, link objects and/or node objects are added, up to the limit, and unneeded link objects outside of the main map view  1230  are unloaded. Thus, the system displays additional link and/or node objects on the main map view, while avoiding adverse impact to system performance and resource utilization. As noted above, any of the methodologies disclosed herein may be utilized to add additional objects to the main map view. 
     Visualization  1245  illustrates a zoom-in action, where the geographic area displayed corresponds to box  1237  of main map view  1230 . In this illustrative example, additional objects are not added because the previous visualization (e.g., in this case visualization  1235 ) may have already displayed all link and node objects of the distribution feeder model. 
       FIG.  13    illustrates example visualizations  1310 ,  1320 , and  1330  of the distribution feeder model of  FIG.  1    in the form of tree diagrams  1315 ,  1325 , and  1335  including example graphical indications indicative of display status of object classes in a main map view, in accordance with example implementations disclosed herein. For example,  FIG.  13    illustrates highlight boxes generated for one or more object classes, where each box is indicative of a display status, with respect to the separately displayed main map view, of the respective object class. 
     For example, each box may indicate that not all objects of an associated object class are displayed in a main map view. In this scenario, tree diagram  1315  illustrates status of objects for main map view  1210 , where 25% (e.g., 625 conductive line objects) are displayed in the visualization  1215 . Tree diagram  1325  illustrates status of objects for main map view  1220 , where all link objects are dynamically displayed by the visualization  1225 . However, none of the node objects are shown since inclusion of such would be over the limit. Tree diagram  1335  illustrates status of objects for main map view  1240 , where all link and node objects are dynamically displayed by the visualization  1245 . 
     While highlighted boxes as illustratively shown in  FIG.  13   , it will be appreciated that any graphical indicator may be generated and used to indicate object class display status/properties. For example, the graphical indicators may be circular, ovular, etc. As another example, the text of the object class may be displayed in a contrasting manner relative to other text, such as, but not limited to, bold type, italic type, differing fonts, larger or smaller fonts, etc. As yet another example, an icon may be provided adjacent to the object class text indicating the status. 
     System Environment 
       FIG.  14    illustrates a system involving one or more node objects and one or more link objects of a distribution feeder model, and distribution planning simulation platform utilizing a power distribution network visualization system configured to manage and generate visualizations of the distribution feeder model, in accordance with an example implementation. In some implementations, link objects  1401 - 1 , node objects  1401 - 2 , and children objects  1401 - 3  are communicatively coupled to a network  1400  which is connected to the distribution planning simulation platform  1402 , which comprises or is otherwise communicatively coupled (e.g., via wired or wireless communication) to the power distribution network visualization system  1404 . In another implementation, the system stores link objects  1401 - 1 , node objects  1401 - 2 , children objects  1401 - 3 , and geographical information in database  1403 . To upload data to the database  1403 , the data may be uploaded for storage in the database  1403  via network  1400  through a power distribution network visualization system  1404  of the system  1402  and store in database  1403 . The distribution planning simulation platform  1402  may be utilized for distribution planning process, which may utilize the visualizations and methodologies disclosed herein performed by the power distribution network visualization system  1404 . 
     The power distribution network visualization system  1404  and distribution planning simulation platform  1402  access a database  1403 , which contains historical data, geographical information, and children relationship information collected from the distribution feeder model in the network  1400 . In alternate example implementations, the data for the objects  1401 - 1 ,  1401 - 2 , and  1401 - 3  can be stored to a central repository or central database such as proprietary databases such that power distribution network visualization system  1404  and/or distribution planning simulation platform  1402  can access or retrieve the data from the central repository or central database. As described herein, each of the objects may be associated with a geographic location, wherein the power distribution network visualization system  1404  maintains information managing and visualizing the one or more objects of the power distribution feeder model by the power distribution network visualization system  1404  according to associated geographical locations. 
     Computing Environment 
       FIG.  15    illustrates an example computing environment with an example computer device suitable for use in some example implementations, such as a power distribution network visualization system  1404  and/or the distribution planning simulation platform  1402  of  FIG.  14   . Computer device  1505  in computing environment  1500  can include one or more processing units, cores, or processors  1510 , memory  1515  (e.g., RAM, ROM, and/or the like), internal storage  1520  (e.g., magnetic, optical, solid-state storage, and/or organic), and/or L/O interface  1525 , any of which can be coupled on a communication mechanism or bus  1530  for communicating information or embedded in the computer device  1505 . I/O interface  1525  is also configured to receive images from cameras or provide images to projectors or displays, depending on the desired implementation. For example, I/O interface  1525  may be configured to provide image data to a projector and/or display to generate and display the visualizations disclosed herein (e.g., the visualizations as described in connection with  FIGS.  1 ,  2 ,  4 - 6  and  8 - 12   ). 
     Computer device  1505  can be communicatively coupled to input/user interface  1535  and output device/interface  1540 . Either one or both of the input/user interface  1535  and output device/interface  1540  can be a wired or wireless interface and can be detachable. Input/user interface  1535  may include any device, component, sensor, or interface, physical or virtual, that can be used to provide input (e.g., buttons, touch-screen interface, keyboard, a pointing/cursor control, microphone, camera, braille, motion sensor, optical reader, and/or the like). For example, the input/user interface  1535  may provide an interface and a means for receiving inputs from users, for example, such as user inputs for performing steps  755  and/or  760  of  FIG.  7   . The input/user interface  1535 , according to some embodiments, may be a means for receiving a limit of objects to be displayed on a main map view, according to some implementations. Output device/interface  1540  may include a display, television, monitor, printer, speaker, braille, or the like. In some example implementations, input/user interface  1535  and output device/interface  1540  can be embedded with or physically coupled to the computer device  1505 . In other example implementations, other computer devices may function as or provide the functions of input/user interface  1535  and output device/interface  1540  for a computer device  1505 . Output device/interface  1540  may be configured to receive image data, for example, from I/O interface  1525  and display images based on the image data to display the visualizations disclosed herein (e.g., the visualizations as described in connection with  FIGS.  1 ,  2 ,  4 - 6 , and  8 - 12   ). According to some implementations, the I/O interface  1525  may be a means for generating one or more of the visualizations disclosed herein (e.g., in connection with any one or more of  FIGS.  1 ,  2 ,  4 - 6 , and  8 - 12   ) and a display and/or projector may be a means for displaying the visualizations. 
     Examples of computer device  1505  may include, but am not limited to, highly mobile devices (e.g., smartphones, devices in vehicles and other machines, devices carried by humans and animals, and the like), mobile devices (e.g., tablets, notebooks, laptops, personal computers, portable televisions, radios, and the like), and devices not designed for mobility (e.g., desktop computers, other computers, information kiosks, televisions with one or more processors embedded therein and/or coupled thereto, radios, and the like). 
     Computer device  1505  can be communicatively coupled (e.g., via I/O interface  1525 ) to external storage  1545  and network  1550  for communicating with any number of networked components, devices, and systems, including one or more computer devices of the same or different configuration. Computer device  1505  or any connected computer device can be functioning as, providing services of, or referred to as a server, client, thin server, general machine, special-purpose machine, or another label. 
     I/O interface  1525  can include but is not limited to, wired and/or wireless interfaces using any communication or I/O protocols or standards (e.g., Ethernet, 802.11x, Universal System Bus, WiMax, modem, a cellular network protocol, and the like) for communicating information to and/or from at least all the connected components, devices, and networks in computing environment  1500 . Network  1550  can be any network or combination of networks (e.g., the Internet, local area network, wide area network, a telephonic network, a cellular network, satellite network, and the like). 
     Computer device  1505  can use and/or communicate using computer-usable or computer readable media, including transitory media and non-transitory media. Transitory media includes transmission media (e.g., metal cables, fiber optics), signals, carrier waves, and the like. Non-transitory media includes magnetic media (e.g., disks and tapes), optical media (e.g., CD ROM, digital video disks, Blu-ray disks), solid-state media (e.g., RAM, ROM, flash memory, solid-state storage), and other non-volatile storage or memory. 
     Computer device  1505  can be used to implement techniques, methods, applications, processes, or computer-executable instructions in some example computing environments. Computer-executable instructions can be retrieved from transitory media, and stored on and retrieved from non-transitory media. The executable instructions can originate from one or more of any programming, scripting, and machine languages (e.g., C, C++, C#, Java, Visual Basic, Python, Perl, JavaScript, and others). 
     Memory  1515  can be configured to store one or more programs, such as Operating System (OS), Hypervisor, and applications. Memory  1515  may be configured to store instructions for executing a power distribution network visualization process, such as process  700  of  FIG.  7   . One or more of internal storage  1520  and external storage (if applicable) may be configured to store information of the power distribution feeder model of  FIG.  1   , including information pertaining to the objects contained therein. 
     Processor(s)  1510  can execute under any operating system (OS) (not shown), in a native or virtual environment. One or more applications can be deployed that include logic unit  1560 , application programming interface (API) unit  1565 , input unit  1570 , output unit  1575 , and inter-unit communication mechanism  1595  for the different units to communicate with each other, with the OS, and with other applications (not shown). The described units and elements can be varied in design, function, configuration, or implementation and are not limited to the descriptions provided. Processor(s)  1510  can be in the form of hardware processors such as central processing units (CPUs) or in a combination of hardware and software units. 
     Processor(s)  1510  can be in the form of physical hardware processors (e.g., Central Processing Units (CPUs), field-programmable gate array (FPGA), application-specific integrated circuit (ASIC)) or a combination of software and hardware processors. 
     Processor(s)  1510  can be configured to fetch and execute programs stored in memory  1515 . When processor(s)  1510  execute programs, processor(s)  1510  fetch instructions of the programs from memory  1515  and execute them, such as programs for performing process  700  illustrated in  FIG.  7   . When processor(s)  1510  execute programs, processor can load and unload information such as information defining the power distribution feeder model and the objects therein, as in  FIGS.  1   , from memory. Processor(s)  1510  can pre-fetch and cache instruction of programs and information to improve performance. 
     In some example implementations, when information or an execution instruction is received by API unit  1565 , it may be communicated to one or more other units (e.g., logic unit  1560 , input unit  1570 , output unit  1575 ). In some instances, logic unit  1560  may be configured to control the information flow among the units and direct the services provided by API unit  1565 , the input unit  1570 , the output unit  1575 , in some example implementations described above. For example, the flow of one or more processes or implementations may be controlled by logic unit  1560  alone or in conjunction with API unit  1565 . The input unit  1570  may be configured to obtain input for the calculations described in the example implementations, and the output unit  1575  may be configured to provide an output based on the calculations described in example implementations. 
     Processor(s)  1510  can be configured to set a limit of objects of a power distribution network to be displayed on a map, the objects comprising at least nodes and links between the nodes, the links comprising at least conductive lines; and when the total number of the objects exceeds a limit, select one or more subsets of the conductive lines based on one or more conditions related to the conductive lines, and generating a first visualization displaying the map comprising a subset of the objects including the one or more subsets of the conductive lines. Where a number of displayed objects is less than or equal to the limit, as illustrated in  FIG.  7   . In some examples, the one or more events may be stored in a storage device, such as internal storage  1520 , memory  1514 , external storage  1545 , etc. In various example implementations, the processor(s)  1510  (or the components therein) may be an example of means for setting a limit of objects to be displayed on a main map view, for example, based on user input via the input/user interface  1535 . The processor(s)  1510  (or the components therein) may also be an example means for, when the total number of objects exceeds a limit, selecting one or more subsets of conductive lines based on one or more conditions related to the conductive lines. Furthermore, the processor(s)  1510  (or the components therein) may also be an example means for generating visualizations of the power distribution network, for example, by generating information to be provided by the I/O interface  1525  to a display and/or projector that displays the visualization. 
     In example implementations, processor(s)  1510  may be configured to select a plurality of subsets of the conductive lines based on a plurality of conditions related to the conductive lines; and display only the plurality of subsets of the conductive lines. For example, processor(s)  1510  may be configured to select a first subset of the conductive lines based on a first condition related to the conductive lines; select a subset of the remaining conductive lines based on a second condition; and display at least the first and second subsets. In some implementations, the first condition is different than the second condition, and may be based on relative lengths of the conductive lines. In some implementations, the second condition is a random selection algorithm. 
     In some example implementations, processor(s)  1510  may also be configured to dynamically display remaining objects such that the number of displayed objects is less than or equal to the limit. 
     In some example implementations, processor(s)  1510  may also be configured to generate a second visualization for a parent node, the second visualization displaying the parent node and one or more child nodes associated with the parent node, where the second visualization is displayed separately from the first visualization, for example, as described in connection with  FIG.  4   . The processor(s)  1510  may also be configured to display, in the first visualization displaying the map, one or mom parent nodes with the one or more subsets of conductive lines; and, when a respective parent node is associated with one or more child nodes, display a graphical indicator associated with the respective parent node indicative that the respective parent node is associated with the one or more child nodes, for example, as described in connection with  FIG.  6   . 
     In some example implementations, processor(s)  1510  may also be configured to generate a third visualization for displaying a tree diagram of the objects of the power distribution network, where the tree diagram comprises a first branch graphically displaying the nodes and a second branch graphically displaying the links, for example, as shown in  FIGS.  1  and  13   . In some implementations, the processor(s)  1510  may be configured to, at least one of: display, in the third visualization, a first icon adjacent to a first node in the tree diagram, the first icon indicative that the first node is a parent node associated with one or more child nodes; display, in the third visualization, a second icon adjacent to a second node in the tree diagram, the second icon indicative that the second node is not displayed in the map; and displaying, in the third visualization, a third icon adjacent to a third node in the tree diagram, the third icon indicative that the third node is a child node associated with a parent node, for example, as shown in  FIG.  5   . 
     Additionally, according to some implementations, the processor(s)  1510  may be configured to display, in the tree diagram of the third visualization, objects displayed in the map differently than the objects that are not displayed in the map, for example, with a highlighted box surrounding the objects not displayed in the map, for example, as shown in  FIG.  13   . 
     Some portions of the detailed description are presented in terms of algorithms and symbolic representations of operations within a computer. These algorithmic descriptions and symbolic representations are the means used by those skilled in the data processing arts to convey the essence of their innovations to others skilled in the art. An algorithm is a series of defined steps leading to a desired end state or result. In example implementations, the steps carried out require physical manipulations of tangible quantities for achieving a tangible result. 
     Unless specifically stated otherwise, as apparent from the discussion, it is appreciated that throughout the description, discussions utilizing terms such as “processing,” “computing,” “calculating,” “determining,” “displaying,” or the like, can include the actions and processes of a computer system or other information processing device that manipulates and transforms data represented as physical (electronic) quantities within the computer system&#39;s registers and memories into other data similarly represented as physical quantities within the computer system&#39;s memories or registers or other information storage, transmission or display devices. 
     Example implementations may also relate to an apparatus for performing the operations herein. This apparatus may be specially constructed for the required purposes, or it may include one or more general-purpose computers selectively activated or reconfigured by one or more computer programs. Such computer programs may be stored in a computer readable medium, such as a computer readable storage medium or a computer readable signal medium. A computer readable storage medium may involve tangible mediums such as, but not limited to, optical disks, magnetic disks, read-only memories, random access memories, solid-state devices, and drives, or any other types of tangible or non-transitory media suitable for storing electronic information. A computer readable signal medium may include mediums such as carrier waves. The algorithms and displays presented herein are not inherently related to any particular computer or other apparatus. Computer programs can involve pure software implementations that involve instructions that perform the operations of the desired implementation. 
     Various general-purpose systems may be used with programs and modules in accordance with the examples herein, or it may prove convenient to construct a more specialized apparatus to perform desired method steps. In addition, the example implementations are not described with reference to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the example implementations as described herein. The instructions of the programming language(s) may be executed by one or more processing devices, e.g., central processing units (CPUs), processors, or controllers. 
     As is known in the art, the operations described above can be performed by hardware, software, or some combination of software and hardware. Various aspects of the example implementations may be implemented using circuits and logic devices (hardware), while other aspects may be implemented using instructions stored on a machine-readable medium (software), which if executed by a processor, would cause the processor to perform a method to carry out implementations of the present application. Further, some example implementations of the present application may be performed solely in hardware, whereas other example implementations may be performed solely in software. Moreover, the various functions described can be performed in a single unit, or can be spread across a number of components in any number of ways. When performed by software, the methods may be executed by a processor, such as a general-purpose computer, based on instructions stored on a computer readable medium. If desired, the instructions can be stored on the medium in a compressed and/or encrypted format. 
     Moreover, other implementations of the present application will be apparent to those skilled in the art from consideration of the specification and practice of the teachings of the present application. Various aspects and/or components of the described example implementations may be used singly or in any combination. It is intended that the specification and example implementations be considered as examples only, with the true scope and spirit of the present application being indicated by the following claims.