Free Oracle 1Z0-1091-22 Exam Practice Questions & Explanations
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If a project is setting up meter commands with a head-end system (HES), which TWO components should you configure to support the inbound responses from HES?
Smart Grid Gateway (SGG) is a product that provides integration between Oracle Utilities Meter Data Management and various head-end systems that communicate with smart meters. SGG supports inbound and outbound communication between the two systems using web services and message queues. According to the Oracle Utilities Smart Grid Gateway User Guide, if a project is setting up meter commands with a head-end system (HES), two components that should be configured to support the inbound responses from HES are:
Inbound web services: These are web services that are exposed by SGG to receive messages from HES. Inbound web services can be used to receive responses from HES for commands that were sent by SGG or other systems.
Message sender: This is a component that sends messages from SGG to other systems using message queues. Message sender can be used to send responses from HES to Oracle Utilities Meter Data Management or other systems.
The Vector and Service Quantity Math usage rule facilitates the configuration of complex vector calculations. It is based on a series of underlying services with vectors configured as input to the calculations.
What are THREE typical uses of the usage rule?
The Vector and Service Quantity Math usage rule facilitates the configuration of complex vector calculations. It is based on a series of underlying services with vectors configured as input to the calculations. Some typical uses of the usage rule are:
Finding coincident peaks: This is a calculation that finds the highest demand value for each interval across multiple service points or devices.
Performing Array math: This is a calculation that performs arithmetic operations on arrays of interval data, such as addition, subtraction, multiplication, or division.
Performing math formulas on interval data: This is a calculation that performs mathematical functions on interval data, such as logarithm, exponentiation, square root, or trigonometry.
Finding max values is not a typical use of the Vector and Service Quantity Math usage rule. Finding max values is a simple calculation that finds the highest demand value for each service point or device.
Converting interval data to scalar reads is not a typical use of the Vector and Service Quantity Math usage rule. Converting interval data to scalar reads is done by using other usage rules, such as Interval Data Scalar Read Rule.
You want to create Smart Grid Gateway (SGG) Payload Processing extendable lookup values. Which Groovy Library Method would you configure in the User Exit Interceptors section?
To create Smart Grid Gateway Payload Processing extendable lookup values, you should configure the Events Set Parser and Set Transformer methods in the User Exit Interceptors section. These methods are used to parse and transform event data from payload files into a common format that can be processed by Oracle Utilities Meter Data Management.
You do not need to configure Get Parser and Get Transformer methods, which are used to parse and transform measurement data from payload files. You do not need to configure SOAPSNDR and RTHTTPSNDR methods, which are used to send SOAP or HTTP messages to external systems. You do not need to configure Initial Measurements and Device methods, which are used to initialize measurement data and device information from payload files.
You need to set up a configuration that allows service points to be used with various meters. This configuration should support interval, time of use, and scalar devices.
How would you meet this requirement?
A service point is a record that represents a physical location where a utility provides service to a customer. A service point can have one or more devices associated with it to measure the usage of the service. A device is a record that represents a physical meter or other equipment that records usage data. A device can have one or more measuring components associated with it to represent different types of usage data, such as interval, time of use, or scalar. According to the Oracle Utilities Meter Data Management Business User Guide, to set up a configuration that allows service points to be used with various meters and support interval, time of use, and scalar devices, one way to meet this requirement is:
Configure one service point, one device, and three measuring components to be related to the service point as required by the data scenarios. This can be done by creating a service point record and associating it with a device record that represents the meter. Then, creating three measuring component records that represent different types of usage data (interval, time of use, and scalar) and associating them with the device record. Depending on the data scenarios, different measuring components can be used to collect and process usage data for the service point.
Which THREE statements are true about the Subtractive Interval Data functionality?
The Subtractive Interval Data functionality is a feature that enables Meter Data Management (MDM) to process interval data from devices that do not provide interval readings, but only cumulative readings. The Subtractive Interval Data functionality performs the following actions:
The IMD load processes calculate consumption in engineering units: The IMD load processes are batch processes that load initial measurement data (IMD) records from smart meter systems or other sources into MDM. The IMD load processes calculate consumption in engineering units by subtracting consecutive cumulative readings and applying conversion factors.
A new reading condition field ensures that you do not lose the reading quality when a meter's consumption is estimated: A reading condition field is an attribute that indicates the quality or status of a measurement, such as valid, invalid, estimated, or substituted. A new reading condition field called Original Reading Condition is added to store the original reading condition of a cumulative reading when its consumption is estimated by using VEE rules.
You can optionally validate for rollover exceptions and negative consumption calculations: You can configure VEE rules to check for rollover exceptions and negative consumption calculations when processing subtractive interval data. A rollover exception occurs when a cumulative reading reaches its maximum value and resets to zero. A negative consumption calculation occurs when a cumulative reading decreases instead of increasing.
It is not true that it validates consumption in initial measurement data (IMD), which are records that store the raw measurement data that is received from smart meter systems or other sources. Subtractive Interval Data functionality does not validate consumption in IMD, but calculates consumption from cumulative readings.
It is not true that it converts engineering units into reads, which are values that are recorded by devices at certain intervals or events. Subtractive Interval Data functionality does not convert engineering units into reads, but calculates consumption in engineering units from cumulative readings.