ADWEC 2008 Statement of Future Capacity Requirements 2008 ...

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RSB Approved Version – 4 th August 2008 ADWEC Base Electricity Methodology for Residential / Commercial Mega Projects Mega Projects’ Developers Connected Load Forecasts ADWEC Demand / Diversity Factors Developers’ Connected Load x ADWEC Demand / Diversity Factors = Unadjusted Developers’ Mega Projects Peak Demand Forecast Peak Demand Forecast Adjustment Factors for 2013 / 2020 / 2030 UPC’s Total Population Forecasts versus Mega Projects Developers’ Total Population Forecasts Mega Projects’ Population Curve Pro-rated to obtain Intermediate Years ADWEC Base Electricity Demand Forecast Mega Projects Forecasting Uncertainties 1) Timing / Size of Mega Projects. • Implementation needs to be synchronized with the development of utility capacity and vice versa. • Shortage of contractors / labour could result in delays. • Mega Projects’ Developers timing estimates are usually optimistic, actual timing is likely to be delayed by at least 1 – 2 years. 2) Population • Population / Number of new expatriates living in Mega Projects. 3) Developers’ Demand Forecasts provided to ADWEC. • Relationship between Electricity Peak Demand and Electricity Connected Load depends on Demand & Diversity Factors. • Peak Demand will likely lag Connected Load because of lag associated with moving in etc. 4) Unannounced Mega Projects - less important now that UPC in place. 5) District Cooling: use in place of Conventional Air Conditioning. 6) Waste Water: Desalinated water use in Irrigation / District Cooling etc. 7) Industry: Zonescorp (Special Economic Zones / clusters /worker cities), Khalifa Port Industrial Zone (KPIZ), ADBIC and ADNOC etc. Source: ADWEC Electricity Demand Forecast 2008 – 2030 presentation, www.adwec.ae. Statement of Future Capacity Requirements 2008 – 2030 46
RSB Approved Version – 4 th August 2008 Stochastic Demand Factors A number of stochastic (random) demand factors can result in the demand forecast deviating from the actual value. Apart from unexpected delays etc, the main stochastic factor is temperature. For example, during June 2008 the daily peak load declined from 5100 – 5300 MW at the start of the month, when the temperature was 35 – 37 degrees Celsius, to around 4500 MW when the temperature fell to 32 degrees Celsius (excluding Fridays / Saturdays). An analysis of all of the hourly data between the 4 th June 2008 and the start of 17 th June 2008 suggested that each 1 degree Celsius change in the temperature changes the hourly load by around 100 MW. 6000 Hourly Demand v Temperature 5000 4000 Gross MW 3000 2000 Hourly Demand =1337.56 + 95.21 * Temperature 1000 0 25 26 28 29 29 30 30 31 31 32 33 34 34 35 36 Temperature Degrees Celsius It can be seen that in June 2008 variations in temperature resulted in the hourly gross MW demand varying by up to 10%. This estimate is obviously based on the composition of demand in June 2008. In future this response to temperature may alter as a result of industrialisation and the use of district cooling. During the August peak month the variation in temperature is also likely to be smaller than observed in June, however this reduced variation in temperature makes accurate regression analysis very difficult because of the limited unique information in the existing August data set. This is why June 2008 data has been used to estimate the relationship, since the drop in temperature was most unusual and provides a rare opportunity to estimate the relationship between hourly demand and temperature in a summer month. In summary, ADWEC’s electricity annual peak demand forecasts can be expected to lie within a range of + / - 10% around the peak forecast due to temperature variations. ADWEC Annual Peak Forecast + / - 10% ADWEC will be undertaking further analysis to improve upon the above multiple regression to include other explanatory variables. Statement of Future Capacity Requirements 2008 – 2030 47
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