BB Installation Guide

SAP HANA 1.0 June 2015 English

Configuration for Transformer Load Analytics (EZ8) Building Block Configuration Guide

SAP SE Dietmar-Hopp-Allee 16 69190 Walldorf Germany SAP Best Practices Transformer Load Analytics Configuration (EZ8): Configuration Guide

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Revision Change Date Description 0 June 6,2015 Initial

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Content

Configuration for Transformer Load Analytics...... 6 1 Purpose...... 6 2 Preparation...... 6 2.1 Prerequisites...... 6 2.2 Assumptions...... 6 3 Deploying Business Delivery Units...... 8 3.1 Configuring Transformer Load Analytics...... 8 3.1.1 Deploy the foundation delivery unit...... 8 3.1.2 Execute the AFL seeding procedure...... 9 3.1.3 Deploy the business layer delivery unit...... 9 4 Configuring SAP HANA...... 11 4.1 Assign SAP HANA roles for Transformer Load Analytics...... 11 4.1.1 Assign role with Viewer rights...... 11 4.1.2 Assign role with Admin rights...... 12 4.2 Configuring Transformer Load Analytics...... 12 4.2.1 Application Configuration Settings...... 12 4.2.2 Set Transformer Characteristics for Loss of Life Calculation...... 14 5 Loading Data...... 15 5.1 Sample Data...... 15 5.1.1 Load Sample Data...... 15 5.1.2 Unload sample data...... 15 5.2 Load your own data...... 16 5.2.1 Load Transformer Master Data...... 16 5.2.2 Load Transformer Load Data...... 17 5.2.3 Load Weather Station Master Data...... 17 5.2.4 Load Weather Data...... 17 5.3 Generate Weather Data...... 18 6 Additional Resources...... 20 6.1.1 SAP HANA Guides...... 20 6.1.2 Important SAP HANA Security Notes...... 20

Configuration for Transformer Load Analytics

1 Purpose The purpose of this document is to describe the general configuration steps required to manually set up the transformer load analytics scope item configuration for SAP HANA® Big Data Intelligence rapid-deployment solution. The configuration steps are within the system landscape you have already installed using the corresponding installation or configuration guides for installation.

2 Preparation 2.1 Prerequisites Before you start installing this scenario, your system landscape must meet the prerequisites for the scope item. For more information about prerequisites, see the SAP Note 1956985 and the Configuration Guide: Getting Started attached to that note. The SAP Note is available on the SAP Service Marketplace for rapid-deployment solutions, http://service.sap.com/rds-bdi → SAP HANA Big Data Intelligence rapid-deployment solution → Find Out More → Latest Information

2.2 Assumptions The following assumptions are made about the configuration of the technical components for this solution: 1. SAP HANA platform is installed and configured. The installation and configuration of SAP HANA is not in scope for this solution. An installed and configured SAP HANA environment is a prerequisite for this rapid- deployment solution. For more information about the installation and configuration of the SAP HANA platform, see the SAP Help Portal http://help.sap.com/hana_platform

2. SAP HANA Predictive Analytics Library (PAL) functions are installed. To confirm that the PAL functions were installed successfully, you can check the following three public views: •sys.afl_areas •sys.afl_packages •sys.afl_functions

These views are granted to the PUBLIC role and can be accessed by anyone.

To check the views, run the SQL statements:

SELECT * FROM "SYS"."AFL_AREAS" WHERE AREA_NAME = 'AFLPAL'; SELECT * FROM "SYS"."AFL_PACKAGES" WHERE AREA_NAME = 'AFLPAL'; SELECT * FROM "SYS"."AFL_FUNCTIONS" WHERE AREA_NAME = 'AFLPAL';

The result alerts you to whether the PAL functions were successfully installed on your system In addition, ensure that the following permissions are in place: _SYS_REPO user has been assigned EXECUTE rights for the following procedures:  "SYSTEM"."AFL_WRAPPER_GENERATOR"  "SYSTEM"."AFL_WRAPPER_ERASER" If those rights have not been applied, then modify _SYS_REPO user to grant those rights. For more information about SAP HANA Predictive Analysis Library (PAL) functions, see the SAP Help Portal http://help.sap.com/hana_platform → Reference Information → SAP HANA Library References → SAP HANA Predictive Analysis Library

3 Deploying Business Delivery Units Setting up SAP HANA technical components for the solution require the following high-level processes: 1. Configure SAP HANA Big Data Intelligence 2. Configure Transformer Load Analytics 3. Define user accounts 4. Loading data to solution space.

The following subsections describe detail steps required and performed using SAP HANA studio.

3.1 Configuring Transformer Load Analytics To implement the transformer load analytics scope item of SAP HANA Big Data Intelligence, you perform the following steps. 1. Deploy the foundation delivery unit 2. Execute the seeding procedure 3. Deploy the business layer delivery unit

3.1.1 Deploy the foundation delivery unit The following steps are used to load the transformer load analytics foundation delivery unit.

The transformer load analytics foundation delivery unit can be imported using either Server or Client as source of delivery unit file location. If an import from the server is required, contact your system administrator for the server path. This step must be executed using SYSTEM account.

1. Ensure the transformer load analytics foundation delivery unit (HCO_RDS_BDI_UTL_TA_FND) is downloaded into desired location. If it is not available, contact your system administrator.

Instructions for acquiring the configuration delivery unit are provided in the Configuration Guide: Getting Started, attached to SAP Note 1956985.

2. Choose the Quick Launch window and select the SAP HANA deployment instance (SYSTEM) and select Import Option. 3. Choose Delivery Unit and select Next. 4. In the Select file section, choose the import location (Server or Client) and specify the location of HCO_RDS_BDI_UTL_TA_FND.tgz 5. Choose Finish to import the content of the delivery unit.

Result The HCO_RDS_BDI_UTL_TA_FND should have been successfully deployed. The Job Log shows the status of the package as it loads. If the load is successful, then the status displays Completed successfully. If the deployment fails, then Error appears. Navigate in

the SAP HANA studio to the Catalog section of the system where the delivery unit is imported.

3.1.2 Execute the AFL seeding procedure After deploying the transformer load analytics foundation delivery unit, you must run the AFL seeding procedure to prepare for deploying the business layer delivery unit. Procedure

1. Grant the required privileges to execute the seeding procedure CALL "_SYS_REPO"."GRANT_SCHEMA_PRIVILEGE_ON_ACTIVATED_CONTENT"('EXEC UTE', 'SAP_RDS_BDI_UTL_TRANSFORMER','SYSTEM'); CALL "_SYS_REPO"."GRANT_SCHEMA_PRIVILEGE_ON_ACTIVATED_CONTENT"('SELE CT','SAP_RDS_BDI_UTL_TRANSFORMER','SYSTEM'); 2. Execute the seeding procedure. CALL "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.prep::GENERATE_FORECASTSMOOTH_PROC" (); Result The TRANSFORMER_FSMOOTH_PROC procedure is created and is available in the _SYS_AFL. Verify that this procedure appears in the catalog.

3.1.3 Deploy the business layer delivery unit The transformer load analytics business layer delivery unit deploys the SAP HANA views, procedures, and roles. Perform the following steps to load the transformer load analytics business layer delivery unit for the solution.

The transformer load analytics business layer delivery unit can be imported using either Server or Client as source of delivery unit file location. If an import from the server is required, contact your system administrator for the server path. This step must be executed using SYSTEM account.

1. Ensure that the transformer load analytics business layer delivery unit (HCO_RDS_BDI_UTL_TA) is downloaded into desired location. If it is not available, contact your system administrator.

Instructions for acquiring the configuration delivery unit are provided in the Quick Guide, attached to SAP Note 1956985.

2. Choose the Quick Launch window and select the SAP HANA deployment instance (for SYSTEM user) and select Import Option. 3. Choose Delivery Unit and select next. 4. In the Select file section, choose the import location (Server or Client) and specify the location of HCO_RDS_BDI_UTL_TA.tgz 5. Choose Finish to import the content of the delivery unit. Result The transformer load analytics business layer delivery unit (HCO_RDS_BDI_UTL_TA) successfully deploys. The Job Log shows the status of the package as it loads. If the load is successful, then the status displays Completed successfully. If the deployment fails,

then Error appears. Navigate in the SAP HANA studio to the Catalog section of the system where the delivery unit is imported. Ensure that the required views, procedures, and roles are available.

This completes your deployment of transformer load analytics delivery units. To use the solution, you must create the required administrative and operational users. You also must modify the configuration settings as required for your business needs.

4 Configuring SAP HANA The following section describes the SAP HANA configuration settings for transformer load analytics.

4.1 Assign SAP HANA roles for Transformer Load Analytics Assign SAP HANA viewer and administrator roles with granted privileges for Transformer Load Analytics. For more information, see the SAP HANA Administration Guide section User Provisioning.

To access the latest version of the SAP HANA Administration Guide, see the SAP Help Portal http://help.sap.com/hana_appliance → System Administration and Maintenance Information. 4.1.1 Assign role with Viewer rights This section must be performed using SYSTEM user account. The solution user has permission to view this solution within SAP HANA. The following roles are required to perform business operations for this solution:  sap.rds-bdi.utl.transformer.access::transformerViewer

Procedure To configure a user to be able to perform all business operations related to this solution, follow these steps.

Replace {TRANSFORMER_VIEWER} and {Password} with your values.

CREATE USER {TRANSFORMER_VIEWER} PASSWORD {Password}; CALL "_SYS_REPO"."GRANT_ACTIVATED_ROLE" ('sap.rds-bdi.utl.transformer.access::transformerViewer','{TRANSFORMER_VIEWER}');

The output window of the SQL Editor notifies when the command is successfully run.

The initial password established for this data scientist user has a change password requirement at first logon.

Verify the creation by opening a SQL Window using your transformer admin account created previously.  SAP_RDS_BDI_UTL_TRANSFORMER schema is visible in the catalog area of the transformer solution user name Result The Viewer role is assigned to the specified user. The user granted with this role is allowed to logon into the transformer load analytics to view the data and conduct analyses.

4.1.2 Assign role with Admin rights This section must be performed using SYSTEM user account.

The Solution Admin user has permission to manage this solution, and can perform all administrative tasks for this solution within SAP HANA. The following roles are required to perform all administrative tasks for this solution:  sap.rds-bdi.utl.transformer.access::transformerAdmin

Procedure To configure a user to be able to perform all administrative tasks related to this solution, follow these steps.

Replace {TRANSFORMER_ADMIN} and {Password} with your values.

CREATE USER {TRANSFORMER_ADMIN} PASSWORD {Password}; CALL "_SYS_REPO"."GRANT_ACTIVATED_ROLE" ('sap.rds- bdi.utl.transformer.access::transformerAdmin','{TRANSFORMER_ADMI N}');

The output window of the SQL Editor notifies when the command is successfully run.

The initial password established for this data scientist user has a change password requirement at first logon.

Verify the creation by opening a SQL Window using your transformer admin account created previously.  SAP_RDS_BDI_UTL_TRANSFORMER schema is visible in the catalog area of the transformer admin user name Result The Admin role is assigned to the specified user.

4.2 Configuring Transformer Load Analytics The application includes configurable tables, which can be modified to customize the solution based on your specific business requirements. The following tables include listings of all configurable settings. Modifying the default values is described in the sections.

4.2.1 Application Configuration Settings Use The following table lists all of the customizable configuration settings available within your implementation.

Procedure To modify these settings, execute the following SQL update command:

UPDATE "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.config::BDI_CONFIG_PARAMETERS" SET VALUE='{KEY_VALUE}' WHERE BUSINESS_AREA='Transformer' AND NAME='{KEY_NAME}'

Functional Key Name Description and default key value Area General MEASUREMENT_IN Interval length between to consecutive TERVAL measurements of the equidistant load time series. This is valid and fixed for the whole application. Default value is 10 [minutes]. When using your own data and the interval between two consecutive measurements is different from the ten-minute period, you have to modify your period as previously described.

Non-equidistant time series are not supported in this version.

DEFAULT_OVERLO Default setting for showing transformers as AD_LIMIT overloaded in this application. Map markers have a yellow color at this value. Default value is 80 [%]. Map DAYS_TO_CONSID Number of past days that are used as input for the Overview ER triple exponential smoothing algorithm for calculating the forecast of the next day as well as the number of days used to calculate the performance indicators displayed on the start page information tiles. In the latter case considered period ends at the day of the last available transformer load measurement and begins with the selected amount of days. Default is 42 [days]. DEFAULT_OVERLO Default threshold for showing transformers with a AD_UPPER_THRES dark red color on the map in this application. Default HOLD is 130 [%]. Spike DEAFULT_SPIKE_LI Default percentage point setting for the spike Inspector MIT inspector to show transformers on the map. Default is 25 [pp]. Loss of Life DEFAULT_AMBIENT Default ambient temperature to be used for loss of _TEMP life calculation in case that no temperature measurements are available for a transformer,for example, the table "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.data::tables.WEATHER_DATA" does not contain ambient temperature values for the weather station assigned to the considered transformer for the considered time. Default value is 10 [°C].

4.2.2 Set Transformer Characteristics for Loss of Life Calculation In this step, you set transformer characteristics values, which are used for calculating transformer loss of life according to IEC 60076-7:2005 "Power transformers - Part 7: Loading guide for oil-immersed power transformers". If you use the sample data, a default entry (id=0) is provided (medium-/high-power transformer, ONAF cooling). The comprised transformer characteristics are used for loss of life calculation of a transformer, when this transformer provides no individual entry (for example, no entry with an id matching the transformer's id in "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds-bdi.utl.transformer.data::tables.ASSETS"). Each entry comprises 10 parameters. See IEC 60076-7:2005 for detailed descriptions and recommendations:

Parameter Default value Description DTtor 45 top-oil rise over ambient temperature at rated load on tap position to be studied [K] DThr 35 winding hottest-spot rise over top-oil temperature at rated load on tap position to be studied [K] x 0.8 oil exponent y 1.3 winding exponent R 8 ratio of load to non-load losses C 150 oil time constant (tau_to) / thermal capacity of transformer [min] k11 0.5 heat model constant k21 2 heat model constant k22 2 heat model constant tau_w 7 winding time constant [min] If you do not use the sample data you provide an own default entry (id=0) or provide for each of your transformers an individual entry (id=) according to the transformer's thermal characteristics and recommended parameters. It is also possible to provide individual entries only for a subset of your transformers as long as a default entry (id=0) is present. For adding individual entries, follow these procedures.

Procedure 1. Open SQL console in SAP HANA studio with a user having transformerAdmin rights. 2. Execute

INSERT INTO "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.data::lol.IECCharacteristics" VALUES (, , , , , , , , ,,);

In case that a value already exists, conduct an update.

5 Loading Data You have two options when implementing this solution for data. You can load your own data or load the sample data provided with the solution. Loading sample data is optional. If you load your own data, you can skip Section 5.1

5.1 Sample Data Loading sample data is optional. Skip this section if you load your own data. 5.1.1 Load Sample Data The following steps are used to load the sample data for this solution delivery unit.

The transformer load analytics sample delivery unit can be imported using either Server or Client as source of delivery unit file location. If an import from the server is required, contact your system administrator for the server path. This step must be executed using SYSTEM account. Instructions for locating and downloading the delivery unit is provided in the Quick Guide for Transformer Load Analytics attached to the SAP Note 1956985.

1. Ensure the transformer load analytics foundation delivery unit (of HCO_RDS_BDI_UTL_TA_SAMPLE) is downloaded into desired location. If it is not available, contact your system administrator. 2. Choose the Quick Launch window and select the SAP HANA deployment instance (SYSTEM) and select Import Option. 3. Choose Delivery Unit and select Next. 4. In the Select file section, choose the import location (Server or Client) and specify the location of HCO_RDS_BDI_UTL_TA_SAMPLE.tgz 5. Choose Finish to import the content of the delivery unit.

Result The HCO_RDS_BDI_UTL_TA_SAMPLE should have been successfully deployed. The Job Log shows the status of the package as it loads. If the load is successful, then the status displays Success. Once the sample data is successfully loaded, navigate to following the link: Replace the {SERVER} and replace XX with your SAP HANA implementation instance number. http://{SERVER}:80XX/sap/rds-bdi/utl/transformer using either the Solution administrator user or business solution user.

5.1.2 Unload sample data The following script is provided to purge all data from the solution space. When initially using the sample data set, this procedure is used to erase that data before the introduction of your production data set.

This step must be executed using either SYSTEM or solution administrator account.

Using the purge script erases the entire solution space of any data, so apply just before introducing productive data to solution. y delete from "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.data::tables.ASSETS"; delete from "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.data::tables.MEASUREMENTS"; delete from "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.data::tables.SETTINGS"; delete from "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.data::tables.WEATHER_DATA"; delete from "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.data::tables.WEATHER_STATION";

This step purges all data from the solution.

5.2 Load your own data If instead of the provided sample data you want to use your own data, there are four tables to be filled. 1. Master Data 2. Load Data 3. Weather Station Master Data 4. Weather Data Loading your own data is not part of the solution scope. For more information about importing, loading, or replicating your existing data into the respective tables in SAP HANA, see the SAP Help Portal, http://help.sap.com/hana_platform

5.2.1 Load Transformer Master Data The master data table for the transformers comprises eight columns. The table name is "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds-bdi.utl.transformer.data::tables.ASSETS". Column name Type Description ID Integer The unique identifier of the transformer VALIDITY_START Date Time Validity start date for this record. VALIDITY_END Date Time Validity end date for this record. Null if still valid. LAT Double Geo-location of this transformer (latitude). LONG Double Geo-location of this transformer (longitude). NAME String Readable name of the transformer. TYPE String Type of transformer, for example MVLV. WEATHER_ Integer Identifier of the weather station that collects STATION ambient temperature information for this

transformer.

5.2.2 Load Transformer Load Data The time series table for the transformer load measurements comprises three columns. The table name is "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.data::tables.MEASUREMENTS". Column name Type Description M_TIMESTAMP Date Time The timestamp of the measurement, for example, 2014-31-12 14:10:00. To be mapped the timestamps in this table have to be the same as in the weather data table. Only equidistant time series are supported. ASSET_ID Integer The unique identifier of the respective transformer. M_LOAD Double The captured relative load value of the transformer for this timestamp. In percent, for example a relative load of 56.67% is saved as 56.67.

5.2.3 Load Weather Station Master Data The master data table for the weather stations comprises four columns. The table name is "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.data::tables.WEATHER_STATION". Column name Type Description ID Integer The unique identifier of the respective weather station. NAME String Readable name of the weather station. LAT Double Geo-location of the weather station (latitude). LONG Double Geo-location of the weather station (longitude).

5.2.4 Load Weather Data The time series table for the ambient temperature measurements comprises three columns. The table name is "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.data::tables.WEATHER_DATA". Column name Type Description M_TIMESTAMP Date Time The timestamp of the measurement, for example, 2014-31-12 14:10:00. To be mapped the timestamps in this table have to be the same as in the load data table. Only equidistant time series are supported. STATION_ID Integer The unique identifier of the respective weather station. M_TEMPERATURE Double The ambient / outside temperature value captured by the weather station for this timestamp. In °C, meaning that a temperature of 18.1°C is saved as 18.1.

5.3 Generate Weather Data When no weather data is available and the usage of a single default ambient temperature value is not adequate for loss of life calculation, weather data can also be generated. Use the "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.procedures.helper::GENERATE_WEATHER_DATA" procedure. It can be called by any user granted the viewer role ( sap.rds- bdi.utl.transformer.access::transformerViewer role). The "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.procedures.helper::GENERATE_WEATHER_DATA" procedure generates weather data based on two sine functions. It allows the user to generate the data in a selectable time interval. The minimum interval length is 1 minute.

Parameter Type Description name startDateTime TIMESTAMP The first timestamp for which to generate the ambient temperature time series endDateTime TIMESTAMP The final timestamp for which to generate the ambient temperature time series weatherStationID INTEGER The identifier of the weather station for which to generate the weather data yearlyAvg DOUBLE The yearly average of the data that the procedure generates. yearlyDiff DOUBLE The average difference between summer/winter temperature values and the yearly average (see Image 1: green arrow). dailyDiff DOUBLE The daily difference between day/night temperatures and the average day temperature based on the yearly curve (see Image 1: blue arrow).

Consider an example of generating weather data for a weather station, with a weatherStationID value of 2, with start and end dates of ‘2014-01-01’ and ‘2014-12-31’. YearlyAvg is 10°C, yearlyDiff 20°C and dailyDiff 10°C. The following procedure call example generates weather data for weatherStationID 2 based on the example values:

CALL "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.procedures.helper::GENERATE_WEATHER_DATA" ('2014-01-01 00:00:00', '2014-12-31 23:59:59', 2, 10, 20, 10);

The generated weather data displays visually with curves dependent upon calculations derived from two sine functions. The first sine function gives the periodically temperature rise and fall over the common year. The function is:

is the current minute in the year.

The second overlying sine function gives the day and night temperature rise and fall:

is the current minute in the day.

The sum of both sine functions is the generated temperature time series that the procedure inserts into the table "SAP_RDS_BDI_UTL_TRANSFORMER"."sap.rds- bdi.utl.transformer.data::tables.WEATHER_DATA".

1 Additional Resources The following reference manuals support the core product stack and are available on the SAP Help Portal http://help.sap.com 1.1.1 SAP HANA Guides For information about SAP HANA landscape, deployment, installation, administration, and security, see the resources listed in the table: Topic Guide/Tool Quick Link SAP HANA SAP Help http://help.sap.com/hana Landscape, Portal SAP HANA Master Guide Deployment &  Installation SAP HANA Overall Installation Guide SAP HANA Automated Update Guide SAP HANA SAP Help http://help.sap.com/hana_platform Security Portal SAP HANA Security Guide SAP HANA SAP Help http://help.sap.com/hana_platform Installation and Portal SAP HANA Technical Operations Manual Administration SAP HANA database Studio Installation SAP HANA Trigger-based Replication (SLT) Installation Guide SAP HANA Sizing SAP Service http://service.sap.com/quicksizer Marketplace

1.1.2 Important SAP HANA Security Notes The most important SAP Notes that apply to SAP HANA appliance software and SAP HANA database security are shown in the table:

SAP Note Title 1598623 SAP HANA appliance - Security 1514967 SAP HANA appliance – Central Note