Oracle 1Z0-1091-22 Exam Dumps

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.

A dynamic option is an option that is assigned to an entity at run time based on a characteristic value. Dynamic options are used to provide flexibility and customization for different scenarios. According to the Oracle Utilities Meter Solution Cloud Service Business User Guide, some examples of dynamic options are:

The utility has a program where customers can optionally participate in demand response (DR) programs. A dynamic option is specified on a usage subscription to allow different DR programs to be applied depending on a characteristic value such as customer class or rate schedule.

An option is specified on a service point to allow Validation, Estimation, and Editing (VEE) processing to dynamically invoke a group of VEE rules depending on a characteristic. For example, if the service point has a characteristic indicating that it is part of a net metering program, then a different set of VEE rules may be applied than for a regular service point.

The utility has a program that credits customers for conservation during critical peak periods. A dynamic option is specified on a usage subscription to allow different credit calculations to be applied depending on a characteristic value such as customer class or rate schedule.

Initial measurement data (IMD) are raw measurement data that are imported into Oracle Utilities Meter Data Management from various sources, such as head-end systems, meter reading systems, or manual entry. IMD can be viewed through the Measuring Component portal, but they are not ready for export or further processing until they pass validation, estimation, and editing (VEE) processing. VEE processing is a set of rules and algorithms that check and correct measurement data for any gaps, errors, or anomalies. According to the Oracle Utilities Meter Data Management Business User Guide, one type of VEE rule that IMD must pass in order to become final measurement data is:

Critical validation: This is a rule that checks whether IMD meet certain minimum criteria for quality and completeness. Critical validation can be used to filter out IMD that are missing, duplicated, corrupted, or invalid.

Some of the best practices for measurement retention are:

Derive time-of-use (TOU) values with interval data to prevent storing extra data: Time-of-use (TOU) values are scalar values that are calculated from interval data based on different TOU periods. Interval data is measurement data that is recorded at regular intervals, such as every 15 minutes or every hour. To prevent storing extra data, you can derive TOU values with interval data instead of storing them separately.

Derive demand from interval data to prevent storing extra data: Demand is a value that indicates the maximum power or load that is consumed or generated during a certain period. Demand can be calculated from interval data by using certain methods, such as block demand or rolling demand. To prevent storing extra data, you can derive demand from interval data instead of storing them separately.

Use Information Lifecycle Management (ILM) processes to help archive data: Information Lifecycle Management (ILM) processes are features that enable MDM to manage the lifecycle of measurement data based on certain policies or rules. ILM processes can help archive data that is no longer needed or used by moving them to different storage tiers or deleting them.

You do not need to keep scalar measurements in the customer read tables to stay consistent, which are tables that store measurement data that is entered by customers or meter readers. Scalar measurements are measurement data that are recorded at certain events, such as billing cycle end or meter exchange. You can store scalar measurements in different tables based on their source or status.

You do not need to keep initial measurement data (IMD) for the same period of time as final measurements for cancel rebill purposes, which are records that store the raw measurement data that is received from smart meter systems or other sources. Final measurements are records that store the measurement data that has been validated, edited, and estimated. You can keep IMD for a shorter period of time than final measurements based on your business needs or requirements.

To configure the derived values that are relevant for a device, you should configure them on the measuring component type for the measuring components to be defined on the device. A measuring component type defines the type of measurement that a device can record, such as scalar, interval, or event. A measuring component type can also define the derived values that are calculated from raw measurements based on certain rules or factors. A measuring component is an instance of a measuring component type that is associated with a device.

You do not need to configure the derived values on the final measurement type, which defines how measurements are stored and processed in Oracle Utilities Meter Data Management. Final measurement types do not define derived values.

You do not need to configure the derived values on the device type, which defines the physical characteristics and attributes of a device, such as manufacturer, model, or serial number. Device types do not define derived values.

You do not need to configure the derived values on the measuring component, which is an instance of a measuring component type that is associated with a device. Measuring components inherit derived values from their measuring component types.