Demand

Demand

WRMP
1. Micro-Component Model
  1. Splits
    1. Unmeasured / Measured
      1. No Switchers
        View that customers will become more efficient and then switch
        Will lead to lower PCC in long run
      2. Measured split further
        Different occupancy
        Creates different PCC
        Same O F V
        Proportionally combined to get Measured PCC
        Split into ...
        New Properties
        Yearly total
        Meter Optants
        5000 until 2024/25
        % of unmeasured base from 2025/26 onwards
        Compulsory
        Not used
        Change of Occupier
        Not Used
        Selective
        Not used
        Other
        New properties total from previous years
        As they have nowhere else to go
        Need to be separate as will have different occupancy to meter optants
    2. Occupancy
      1. 1 to 6
        Proportioned to add up to total of each split
      2. Measured taken from survey
        Remaining is unmeasured
        Split calculated using model
  2. O F V Methodology
    1. Ownership
      1. From customer survey
        Different ages
    2. Frequency
      1. From customer survey
    3. Volume
      1. Outdoor from customer survey
      2. Rest from literature and assumptions
        Linked to ownership of different ages
    4. Replacement rates
      1. Literature and assumptions
      2. Used to predict future PCC
  3. Categories
    1. Toilet Flushing
    2. Personal Washing
      1. Bath and shower combined
      2. Wash Basin
    3. Clothes Washing
      1. Washing Machine
      2. Hand Washing
    4. Dish Washing
      1. Dish Washer
      2. Hand Washing
    5. Outdoor Use
      1. Garden Washing
        Hose
        Sprinkler
        Watering Can
        Drip Irrigation
      2. Car Washing
        Bucket
        Hose
        Pressure Washer
    6. Other
      1. Misc Indoor Use
      2. Misc Outdoor Use
  4. Scenarios
    1. Main Model
      1. Normal Year
      2. Dry Year
        ADO
        Use 'Dry Factors' from WRc Compendium
        PDO
        Use 'Summer Factors' from WRc Compendium
        MDO
        Use 'Winter Ractors' from WRc Compendium
        1 in 20
    2. Other
      1. 1 in 10 - 1 in 200
  5. Improvements
    1. Using @Risk
      1. Understand consequence of assumptions
      2. Generate PCC ranges
    2. Add Switchers
      1. % less than unmeasured
      2. Used by many company MC Model
      3. Different way at looking at meter optants
        May produce different results
    3. Use ACORN
      1. Expensive
        But more extensive results
      2. RV not good indicator
    4. Integrate more into Main Model
      1. Prop and Pop Model
      2. 'Other' scenarios
      3. Sensitivity Analysis
2. Non-Household
  1. Flat Properties
    1. Small number assumed to switch from unmeasured to measured each year
      1. 4.38% of unmeasured
      2. Based on change in 2012/13
  2. Forecast
    1. Based on regression model
      1. Total consumption
      2. Strongest relationship is GDP and Rainfall
        Statistically significant
        As GDP increases, demand decreases
        Move from secondary to public services
        Public services use less water
        Rainfall explains variance
    2. SIC Code Analysis
      1. Regression analysis for each SIC category
        Varied results
        Therefore fitted into total consumption model
        Leads to fall in agriculture
        Queried by stakeholders
        Different from Southern and South East
        Not deciding factor in forecast
        Very difficult to predict at SIC level
        Especially for small company
3. Properties and Population
  1. Experian
    1. Trend
      1. National statistics
    2. Plan
      1. Local councils
    3. Most Likely
      1. Experian view using both Trend and Plan
        Used in WRMP
4. Leakage
  1. Falling forecast
    1. No increase with new properties
      1. Assumed to be cancelled out by efficiencies in leakage detection
    2. Due to increase in meter optants
      1. Have lower supply pipe leakage
5. Sensitivity
  1. Properties and Population
    1. Trend + 0.53 Ml/d
    2. Plan - 5.20 Ml/d
  2. Climate Change
    1. Double climate change impact + 1.99 Ml/d
    2. No climate change - 1.99 Ml/d
  3. Water Efficiency
    1. 5% increase - 6.10 Ml/d
    2. 5% decrease + 9.06 Ml/d
  4. Meter Optants
    1. 1500 a year + 4.67 Ml/d
    2. 8500 a year - 3.83 Ml/d
  5. Micro - Components
    1. 5% increase in assumptions + 9.66 Ml/d
    2. 5% decrease in assumptions - 9.45 Ml/d
Yearly
1. Consumption Monitor
  1. What do we have?
    1. Unmeasured
      1. Read 6 monthly
        March and September
        Separate walks for meter readers
        Data with IT
      2. Currently roughly 800
        Ongoing work to increase this
        Prize Draw
        Roughly 300 being added in March/April
        Project by Dani and Danie
        Aided by Tony Bird
        Recently resurveyed
        400 responded
        Prize Draw
        Project by Dani and Danie
    2. Measured
      1. Uses yearly meter reads for billing
      2. Takes occupancy from billing system
        Collected from customer survey
        Collected in phone calls
  2. Process
    1. RAW data from IT
    2. Data placed into consumption monitor
      1. MUR added
      2. Sense Checked
    3. Analysed by occupancy
      1. Outliers removed
        Uses Analyse-It
      2. Occupancy is weighted
    4. Results calculated
      1. Used in water balance
      2. Used to check micro-component model
      3. Used to assess trends
        Needs further work
        Possible future project
2. Historical Demand Analysis
  1. Normalised to current base year
  2. Used to determine demand in different years
    1. Normal to 1 in 50
  3. Used as check against...
    1. Micro-component Model
    2. Consumption Monitor
      1. Helps to determine profile of current year

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	Created by j.jones9013 about 10 years ago