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# Pattern usage questions.

I'm having a tough time wrapping my head around Pattern usage.  It seems there are at least 3 different ways that patterns can be applied: 1) Demand Alternatives, 2) Customer Meters, and 3) Calculation options.

My model has all the customer meters in it, with each meter assigned to its appropriate junction.  The "Demand (Base) (gpm)" column is populated with each meter's ADF (in gpm).  What I want to do is apply a Peaking Factor to the customer demand.  I have created a pattern called "Max Day".  It seems more logical (to me, anyway) that if I want to apply a multiplier to all customer usage, the best place to do that would be in the "Customer Meter" Flex table.

I have a diurnal curve set up as a pattern, as well as having Simple Controls for my pumps and am using the "EPS-Snapshot" feature (in order to use patterns and controls).

Can anyone shed some light on the rationale for having multiple places where patterns can be applied, and under what circumstances to use each place?  Is there a preferred or suggested way to apply patterns to customer meter demand?  With having so many options regarding where and how to apply patterns, it can get confusing pretty quickly.  I would like to keep it simple and as intuitive as possible.

Parents
• I've struggled with this in the past and the most intuitive approach (in my opinion) that we applied was this:

Base Demand (customer meter/junction): Demand based on the latest billing data (in m3/h, so for example yearly demand/(365/24)). This value signifies the usage difference per customer (small/large households for example)

Hourly pattern values: Diurnal pattern of usage per customer type (households/small businesses/industry etc.). This signifies the variance of hourly consumption.

Daily pattern values: Used for adjusting one type of demand (usualy household demand) so that the mass-balance equation between the base demand + hourly pattern value + monthly pattern value and DMA measured consumption is closed.

Monthly pattern values: Used for lifting/lowering seasonal types of demand (Hotel/campsite etc.) which have a large variance between seasons

Demand adjustment factor (Calculation Options/Scada Simulator): Used in forecasting models which contain scenario's which span multiple years. Used to gradually increase/decrease types of demand over multiple scenario's. This way, the base demand remains what it is, a base demand. When updating billing data, this prevents having to manually change every forecast demand alternative.

We don't use the daily pattern values for the purpose they were intended (variance between weekdays) because the variance in our case is not so much in daily demand increase/decrease but rather in the form of the diurnal curve (weekdays typically have high morning peaks while weekend days tend to have high evening peaks in our case)

• I've struggled with this in the past and the most intuitive approach (in my opinion) that we applied was this:

Base Demand (customer meter/junction): Demand based on the latest billing data (in m3/h, so for example yearly demand/(365/24)). This value signifies the usage difference per customer (small/large households for example)

Hourly pattern values: Diurnal pattern of usage per customer type (households/small businesses/industry etc.). This signifies the variance of hourly consumption.

Daily pattern values: Used for adjusting one type of demand (usualy household demand) so that the mass-balance equation between the base demand + hourly pattern value + monthly pattern value and DMA measured consumption is closed.

Monthly pattern values: Used for lifting/lowering seasonal types of demand (Hotel/campsite etc.) which have a large variance between seasons

Demand adjustment factor (Calculation Options/Scada Simulator): Used in forecasting models which contain scenario's which span multiple years. Used to gradually increase/decrease types of demand over multiple scenario's. This way, the base demand remains what it is, a base demand. When updating billing data, this prevents having to manually change every forecast demand alternative.

We don't use the daily pattern values for the purpose they were intended (variance between weekdays) because the variance in our case is not so much in daily demand increase/decrease but rather in the form of the diurnal curve (weekdays typically have high morning peaks while weekend days tend to have high evening peaks in our case)

Children