Energy AnalytiX Dashboard

Energy AnalytiX is an analytics data-driven application for Energy Management. It operates by collecting data from various data sources (real time, historical, Web services-based, external, etc.) and then utilizes the collected data in evaluating user-defined energy calculations.

Introduction

This topic provides an introduction on how to utilize the sample energy dashboard. The key idea of the sample energy dashboard is to provide a quick start and an example of how to create energy visualization using a data model and HTML5 based visualization.

Note: This help page is intended to be a guide primarily for planning purposes and to give you an understanding of the recommended sequence of steps for efficiently deploying your Energy AnalytiX application. For more details about any step mentioned herein please consult the help documentation as well as other available help pages.

Energy AnalytiX Architecture

Energy AnalytiX integrates a number of ICONICS key technologies in order to provide an energy management solution, including:

Energy AnalytiX is deployed using the AssetWorX infrastructure and the Asset AnalytiX support for mapping equipment properties to Hyper Historian tags and calculations. Thus, an end user can add energy functionality to any asset using the Energy AnalytiX extension in the Workbench.

The newly updated energy dashboard is quite compatible with the previous releases with the following differences:

The updated Workbench Desktop package will overwrite any existing energy data models and energy dashboards.

If the user has manually modified a prior released energy data models and energy dashboards, he should not install the updated Workbench Desktop package on the same project, but rather create a new project temporarily and review updates for the latest release.

Sample Energy Dashboard

Energy AnalytiX product installation will install an energy dashboard for the end user to utilize as a starting point for providing visualization for the energy application.

The energy dashboard is developed to be a general-purpose energy application visualization tool and it will require customization from the end user to make it specific to the end user’s application. For example, if the target energy application does not involve say Carbon-based analysis, then the default energy dashboard will need to be customized to exclude carbon-based visualization.

Both the energy data model and the energy dashboard are developed in a generic way and they accommodate all possible data that an energy application may include. They are also developed in a way to automatically update with newer data, on different periodic intervals, based on the estimated frequency of changes in the underlying data.

Before You Start

Energy data can include data spanning significant time intervals or a high volume of energy calculations. Therefore, prior to deploying the energy data models or using them, it is advised that the end user sets the data load timeout interval to a high value in the AnalytiX-BI point manager, like 3600 seconds.

Energy Dashboard Deployment

This refers to the process of deployment of the AnalytiX-BI Energy data model and related energy dashboard implemented in KPIWorX. The energy dashboard requires three areas to be available so that it can work.

For the new Energy AnalytiX there will be a new Workbench project pack file, which the end user will have to un-pack manually. This pack file can be located under Program Files > ICONICS > GENESIS64 > AnalytiX Dashboards and is called EnergyDashboard_Pack_version.pkgx.

If you have unpacked a previous version of the pack file containing the energy dashboard and data model, the newer version will overwrite any previously existing energy dashboards and data models.

The end user will have to unpack this file. While unpacking, the user should check all the related KPIWorX files.

After the energy dashboard is successfully unpacked, the end user should perform the following actions:

o If any errors are displayed under the Rename Column step, delete the step, click Apply and then manually re-add the step

o This issue may appear when for certain asset structures which are much different than the sample one used for creating the energy data model

Troubleshooting missing data in dashboards

The sample energy dashboard was developed on a sample energy application used as a showcase of the product functionality. The end user energy application maybe different than the one utilized in developing the sample energy dashboard and as a result in some cases no data maybe displayed at the energy dashboards. First of all, if no corresponding energy functions are configured, then the related energy dashboard visuals will display no data.

For example, if no carbon calculations are defined, then the related carbon visuals will display no data.

To troubleshoot the scenario where no data are displayed in the energy dashboard, when all related energy calculations and functionality are defined,, a few troubleshooting steps can be utilized.

Energy data are not displayed due to differences in filter possible values

The sample energy dashboards store within the dashboard file the current data filter selection. It is quite possible that the related data filters in an end user’s application may have different values than the target application filters. In this case, choosing a different data filter selection in the dashboard should display the existing energy data.

EnergyAssetsDim Dataflows errors, missing data in dashboards

If I examine my data models in AnalytiX-BI, the EnergyAssetsDimBi table under the any of the three energy data models is showing with an "error" status.

This issue can happen if the AssetWorX hierarchy is not set up in a way consistent with the data model. To resolve this, make the following changes to the AssetWorX configuration:

Once your AssetWorX configuration meets the above requirements, follow these steps:

Energy Data Model

The energy data models, implemented in AnalytiX-BI, include all the reference data (dimension data) as well as all the energy data (fact data) and data relationships to model the energy application and to facilitate advanced energy data analysis and visualization.

o Relationships between energy data (fact data) and reference data (dimension data)

Regarding the time span that we collect the data for, the energy data model consists of:

o Require daily data aggregates option enabled in Energy AnalytiX General Options\Data Aggregate Options

We have just adjusted the default data time range interval for the energy data model to reflect an integral rolling interval of say, 1 week, 1 year or 3 years. This rolling time interval takes into account full calendar months as well.

Consider the yearly model. By default, if say today's date is 1/26/2022 (today's date), the default time range for data in the yearly interval will be from 1/1/2021 to 1/26/2022 (today's date) to reflect an integral number of calendar months.

Energy Data Model Architecture

The energy data model has support for parameterized views, which allow for a parameterized API that clients like GridWorX64 can utilize

In more details, new parameterized views were added at all data models to process data based on the time and data resolution of each energy data model.

All parameterized views are commented and they do include comments regarding their parameters

In addition, the Long term analysis energy data model includes newly added parameterized views for calculating the CuSum consumption, Cost or Carbon data of an energy asset. Specifically, we have added support in the Long term Analysis data model in the form of parameterized views which will produce yearly and monthly CuSum totals fort consumption, cost and carbon.

The newly added parameterized views will return both the daily values as well as the CuSum values:

The accuracy of the energy data in the parameterized views strongly depends on the energy data model’s trigger-based data update mechanism and the caching of data in AnalytiX-BI

As an example, consider the Long term energy data model. On say September 12th latest data will be from September 11th 12:00 AM - September 12th 12:00 AM. The end user can make the related energy data model update triggers to update with new data say every 1 hour, however this could increase the load on AssetWorX, Hyper Historian and AnalytiX-BI servers.

Energy Data Model Editing

The Energy Analysis Data Model is a generic data model and most likely end users will have to customize it. Editing the default energy data model needs to be planned carefully and with an understanding of the required steps.

Note: It is recommended that prior to any modification of the Energy Data Model, the related configuration database is backed up.

Next, the type of editing in the data model has to be reviewed with respect to data model entities relationship and parent child hierarchies. It is best if we provide a few examples of how to accomplish this.

Deleting an Existing Entity from the Data Model

Prior to deleting any entity, the user will need to review if other energy data model entities depend or reference the entity to be deleted. More specifically:

If the entity to be deleted is a data flow, all related tables, views and associated relationships must be deleted first. If the entity to be deleted is a data table or data view, all related data views and relationships need to be deleted first.

As a use case scenario, let’s say that we would like to remove any carbon-related entities from the weekly data model. The required steps would be:

Step 1: Expand the Weekly Energy Data Model and identify carbon-related entities and identify the carbon-related entities.

Step 2: Open the Weekly Energy Data Model in the Workbench, and for each carbon- related entity, delete associated relationships and save the Data Model.

Another use case scenario would be to add or remove fields from existing data flows, data tables or views. The required steps would be:

If adding a new column to a data flow, in order to propagate it to the related data table, the user must first refresh the schema of the related data table.

In general, any change in the data model’s entities will most likely impact the energy visualization dashboard. As such, it is recommended that users once they complete changes in the Energy Analysis data model that they do review all visuals in the related dashboards and verify that they operate properly. In some cases, users may need to remove visuals for which no data are available in the energy data model while in some cases, pending on the changes committed, all that it is required to add or to remove data model entity field from the related visual’s fields.

Multiple Time Zone Support

Energy assets can be geographically distributed and they can be allocated to different time zones. An Energy dashboard user would like to visualize energy data across same time intervals related to different time zones.

For example, let’s assume that we have defined two time zones in our asset structure.

Now, let’s say we would like to look at data for a calendar day 12:00 AM (today) to 12:00 AM (next day) in local time on 11/17/2020. The corresponding Hyper Historian data request would be in UTC times.

All energy data model data tables and data views will propagate the energy asset’s Timezone information to the energy data model queries and all energy dashboard filters will operate on the local time of the user visualizing energy data.

In AnalytiX-BI, energy data model all energy dimensions will propagate the time zone information (or emptry string if not defined). The energy data model data flows are modified to use the new time zone support function in AnalytiX-BI (totimezonetime) and to parameterize the data request from Hyper Historian to the appropriate UTC time interval based on the asset’s timezone. Once the data are retrieved in UTC time for Hyper Historian, they will be converted to a LocalTimeZone time using as parameter the timezone of the related asset and then all added columns such as year, month, day, etc will be applied. In the energy dashboard, based on KPIWorX-BI, all date-based filters will work using the newly added LocalTimeZone column and all date-based data filtering will be based on the local time of the energy dashboard user.

As an example, let us look at hourly data inside Energy AnalytiX' overview dashboard page.

Without any asset selected, we can see data up to 8:00 PM although the screenshot was taken at 2:05 PM at Foxboro on 11/17/2020. This makes sense since NY is in Athens, where the time now is 9:05 PM and the consumption chart rolls up everything at the 10962 Enterprise level.

Now, let’s use CT as our selection. Data are displayed until 2:00 PM, since this is our local time and CT is in Eastern (Foxboro) time.

Next, let’s use NY as our selection. Data are displayed until 9:00 PM, since this is our local time and NY is in EET (Athens, Greece) time and there the local time is 9:05 PM.

Finally, let’s look at the total consumption at the 10962 Enterprise level. 10962 Enterprise level consumption = CT consumption + NY consumption.

We have added also support for time zones in related Energy AnalytiX service tasks. In more details:

If time zones exist, then the internal trigger in the Energy AnalytiX Workbench Desktop must be delayed “enough” so all the time zones have a full set of data for a given day when it is running periodically

Energy Dashboard

The energy dashboard is implemented as a set of dashboard pages developed within KPIWorX (under \ProgramData\ICONICS\KPIXStorage\Public). It is supplied as a sample energy dashboard with a general-purpose approach to provide a sample and a starting point for the end user to customize energy visualization to fulfill application requirements. Typically, it will need to be modified by the end user to be made more applicable to the individual energy visualization needs of the end user’s application.

The energy dashboard is structured to have a home page (Energy Analysis Overview) and a number of related dashboard pages within dedicated virtual folders. In general, the following dashboard sections are supplied as a starting point.

Energy Analysis (overview) page
- Overview page displays energy data for the current day
Energy Weekly Analysis
- Energy data analysis for the last 7 calendar days
- Utilizes base summary data aggregated by hour
Energy Yearly Analysis
- Energy data analysis for 1 year
- Utilizes base summary data aggregated by calendar day
Energy Long Term Analysis
- Energy data analysis for 3 years
- Utilizes raw daily aggregates calculated by the historian
Reports
- Tabular report (grid) displays
- Utilizes raw daily aggregates calculated by the historian

Before You Start

Before starting to use the Energy Dashboard, please verify the following:

IIS is restarted
Your energy application is set as the active configuration in Workbench
Hyper Historian Logger service is running
AnalytiX-BI point manager service is running (restart if needed)

An energy dashboard page in general is developed using energy data from the energy data model along with filters to allow the end user to easily analyze energy data based on the current filter context selection.

Energy Analysis Overview page

Note: The dashboard filters which are used in single selection mode may have pre-selected values which are based on the source energy sample data that the sample energy dashboard was developed. As such, once the user goes to display runtime mode and selects an existing filter value, the new filter value will take affect and the saved pre-selected filter value will reflect existing values from the user’s energy application.

In the following sections, we will describe with more details each energy dashboard area.

Energy Weekly Analysis

The Energy Weekly Analysis dashboard pages are intended to present a quick summary of energy data for the last 7 calendar days.

Energy Weekly Analysis Folder

Energy Yearly Analysis

The Energy Analysis dashboard pages are intended to present analysis of energy data for the last 12 calendar months (1 rolling year) using daily resolution for the data.

Energy Yearly Analysis Folder

Energy Long Term Analysis

The Energy Long Term Data Analysis dashboard pages are intended to present analysis of energy data for the last 36 calendar months (3 rolling years) using daily resolution for the data.

Energy Long Term Analysis Folder

Reports

The Reports dashboard pages are intended to present tabular analysis of energy data for the last 36 calendar months (3 rolling years) using daily resolution for the data.

Reports Folder