Oracle 1Z0-1091-22 Exam Dumps

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 different types of commands that can be sent to smart meters to perform various actions, such as reading, pinging, connecting, or disconnecting. According to the Oracle Utilities Smart Grid Gateway User Guide, some examples of commands that are supported by the SGG adapters are:

On-demand reading: This is a command that requests a smart meter to send its current or historical usage data to the head-end system. On-demand reading can be used for billing purposes or for verifying meter readings.

Ping meter: This is a command that tests the communication between the head-end system and the smart meter. Ping meter can be used for troubleshooting purposes or for checking meter status.

Connect: This is a command that enables the service at a smart meter. Connect can be used for activating service for a new customer or for restoring service after a payment.

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.

To build a new Service Order process that includes meter commands, you need to configure the following options:

Measuring component type: This defines the type of measurement that a device can record, such as scalar, interval, or event.You can associate meter commands with measuring component types to perform actions on devices that have those types1.

Activity type: This defines the type of work that needs to be performed on a service point or device, such as installation, removal, or inspection.You can associate meter commands with activity types to trigger actions on devices when an activity is completed1.

Communication type Message sender: This defines the communication channel and protocol that is used to send meter commands to devices.You can configure message senders for different communication types, such as AMI, AMR, or manual1.

You do not need to configure device configuration type, which defines the physical characteristics and attributes of a device, such as manufacturer, model, or serial number1. Device configuration type does not affect meter commands.

Consumption synchronization is a process that ensures that the usage data from different measuring components (such as interval and scalar) are consistent and aligned. Consumption synchronization can be performed using various methods, such as adjustment, estimation, or derivation. According to the Oracle Utilities Meter Data Management Business User Guide, two types of VEE rules that are typically configured on a project for consumption synchronization processes are:

Interval adjustment from scalar: This is a rule that adjusts the interval curve to match the register consumption. Interval adjustment from scalar can be used to correct any discrepancies between interval and scalar usage data due to factors such as clock drift or multiplier errors.

Sum check: This is a rule that ensures that the usage data from two measuring components are in sync. Sum check can be used to compare the usage data from different measuring components (such as import and export) and flag any differences or errors.

Derived values are values that are calculated from raw measurements based on certain rules or factors. Derived values can be used for different purposes, such as billing, analysis, or reporting. Some examples of derived values are:

Value with a factor such as line loss applied: This is a value that is adjusted by applying a factor that accounts for the loss of energy or water during transmission or distribution. For example, a line loss factor can be applied to a meter reading to calculate the actual amount of energy or water that was delivered to a customer.

Value converted from one unit of measurement to another: This is a value that is converted from one unit of measurement (UOM) to another based on a conversion factor. For example, a volume reading in cubic feet can be converted to a volume reading in gallons by multiplying it by a conversion factor.

Interval data values created by ''intervalizing'' a scalar reading by applying a profile to it: This is a value that is created by dividing a scalar reading into smaller time intervals based on a profile that represents the usage pattern of a customer. For example, a daily scalar reading can be intervalized into hourly readings by applying a load profile that reflects the customer's hourly usage.

Estimated value if the final measurement is too low or high is not a derived value, but an estimated value. Estimated values are values that are generated when raw measurements are missing or invalid based on certain criteria. Estimated values can be based on historical data, statistical methods, or other sources.

Comparison of normal versus actual usage is not a derived value, but an analysis result. Analysis results are values that are calculated by comparing or aggregating measurements or derived values for different purposes, such as revenue protection, load research, or customer engagement.