Abu Dhabi Water And Electricity Company’ Demand Forecasting

Abu Dhabi Water and Electricity Company’ Demand Forecasting Case Study

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In the current previous, it has turn out to be crucial for electrical energy suppliers all over the world to estimate their future demand. In the previous twenty years, analysts have developed varied tools to assist in forecasting demand for electrical energy utilities. In the 1970s and early Eighties, it was attainable to estimate how much electrical energy might be required sooner or later by simple extrapolation of previous vitality consumption information. The power utility corporations used demand for energy that was recorded prior to now to determine future demand for the commodity. However, numerous components in modern world market have made it essential to adjust the modeling methods utilized by power utility corporations.

The factors necessitating the change in the mindset of the demand analysts include, amongst others, the rising price of gas, new applied sciences of manufacturing electrical energy, high inflation rates (both in the developing and developed economies), and alter in lifestyle and institutional constructions. As a result of these elements, the ability utility firms discover it necessary to take into consideration prices, population dynamics, revenue, know-how, as well as different demographic, economic, technological, and policy variables (Industry Forecast Scenario, 2011).

According to Energy Report (2011a), precision is an important side in the means of forecasting demand. In the past, all through the world, every time the demand of electricity was underestimated, it was corrected by organising generator vegetation that ran on fuel or oil. The organising of such crops required solely a small funding and it was possible to complete the setup within a comparatively brief period of time. Likewise, overestimations have been corrected because the demand for electrical energy increased with time.

Demand forecasting was made simple given that the majority countries didn’t have the environmental issues that exist today. What this meant was that regulation was extra predictable then than it’s right now. Today, underestimates will ultimately end in under-capability, which can lead to brownouts and blackouts. Overestimation, then again, would lead to creation of plants that can remain unused or underutilized for a few years. Such a development will be very expensive for the utility (Energy Report, 2011a). Furthermore, in mild of the increasing function of players from the private sector (as well as the ongoing reforms in the UAE that require demand to be assessed realistically), electricity demand forecasting makes lots of sense. The present paper goals at outlining how the Abu Dhabi Water and Electricity Company (herein known as ADWEC) forecast the demand for its services.

Company Background

The Abu Dhabi Water and Electricity Company is among the 5 subsidiaries of the Abu Dhabi Water and Electricity Authority. Abu Dhabi Water and Electricity Company is the only organization that buys and sells water and electrical energy in Abu Dhabi. The main function of the corporate is to be sure that all electricity and water customers in Abu Dhabi have fixed supply of the commodities. According to Adwec.ae (2012a), “this function (of offering a constant supply of water and electrical energy to customers) is fulfilled via a careful brief– time period and long– term balancing (act) of supply and demand (Demand Forecast and Generation Expansion Planning)” (par. 5). Adwec.ae (2012a) continues to state that the balancing is achieved by way of “long– term Power and Water Purchase Agreements (herein referred to as PWPAs) with the Power & Water Producers, by way of the Bulk Supply Tariff (herein referred to as BST) sales agreements with the Distribution Companies (DISCOs) and Fuel Supply Agreements (herein referred to as FSA) with Fuel Supplies” (par. 5). The firm is licensed beneath OHSAS 18001:2007, ISO 9001:2008, and ISO 14001:2004 (Adwec.ae, 2012b).

On July, 2012, the corporate managed to generate energy beyond the ten,000 MW mark. Eighty % of the power so generated was utilized in Abu Dhabi, whereas the remaining was offered to other Emirates. What this means is that the company had the capacity to generate electricity that satisfied the wants of the native shoppers, exporting the remaining to other areas. In the GCC area, only Kuwait and Saudi Arabia have managed to generate more than 10,000 MW of electrical power. According to economic estimates, the corporate is predicted to proceed producing power at this stage for the remaining part of the 2012. The major reason why that is so is due to the growing stage of export to the Federal Electricity & Water Authority (herein referred to as FEWA) and the Sharjah Electricity & Water (herein known as SEWA) within the north. The company is headed by Abdulla Saif Al Nuaimi, who acts as the Chairman. Al Nuami is assisted by three board members (Adwec.ae, 2012a). Figure 1 under is an illustration of the organizational construction at ADWEC:

Results and Discussion

Today, power corporations everywhere in the world have realized the necessity to determine the demand for his or her merchandise sooner or later. To this end, there are various methods that power companies use to estimate the demand of electrical power. Companies select between the totally different strategies relying on the info they have and the element and nature of the forecasts to be made. ADWEC have realized the necessity to make accurate predictions of demand for electricity and water in Abu Dhabi and the other emirates it exports to. To attain these accurate predictions, ADWEC makes use of numerous strategies and compares the different findings made. The approach of using different strategies has turn out to be useful for ADWEC, particularly for the needs of setting tariffs and designing demand administration packages (Industry Forecast Scenario, 2011).

Trend Method

It is one of the varied strategies utilized in predicting demand for electrical energy. In this method, the variables which are needed are expressed as features of time. The variables used usually are not associated to technological, coverage, demographic, or financial components. The time operate provides enough info to explain out there knowledge, which helps in making quick- term projections (Energy Report, 2011b).

ADWEC makes use of the development method to predict the demand for energy by most consumers, aside from high temperature industries. The firm makes necessary changes to the strategy to detail unmet calls for that arise from power cuts (Industry Forecast Scenario, 2011). According to Adwec.ae (2012c), the development methodology is simple and simple to make use of. However, it has one major shortcoming that negatively impacts its effectiveness. The method does not take into account the correlation between the variable underneath focus and exterior economic components.

For occasion, it overlooks the impacts of such factors as level of earnings, progress of cities, inhabitants dynamics, in addition to costs on the demand for energy. The main assumption of the method is that point determines the value hooked up to the variable beneath examination. In different phrases, the method assumes that the variable will maintain the pattern recorded up to now. In spite of those weaknesses, the strategy is still extensively used in predicting the demand for electricity. The major cause why it’s nonetheless used is the fact that it helps the corporate to generate an estimate of the value that’s predicted (Industry Forecast Scenario, 2011).

End-Use Method

In addition to the development method analyzed above, ADWEC uses the tip-use technique predict demand. The method takes into consideration the effects of the patterns that end result from utilizing electrical energy on completely different systems and units. The technique is used to estimate demand in agricultural, business, industrial, and residential sectors. Like the pattern method, this method makes several assumptions in predicting demand for energy. The major assumption made in this method is that electrical power isn’t wanted as the final good. On the contrary, the power is needed for service delivery (Industry Forecast Scenario, 2011).

The equation below exhibits how vitality is consumed in several sectors:



The summation of E for various end-makes use of in the sector offers an estimate of how a lot electrical vitality is used within the sector. The P worth within the equation accounts for power use efficiency, inter-gas substitution, and rates of utilization. In this manner, the tactic implicitly components in earnings, costs, as well as other policy and economic effects.

At instances, ADWEC combines the end-use method and the pattern method to estimate the quantity of vitality that’s wanted in various sectors in the future (Energy Report, 2011a). The approach is essential in cases the place new fuels and applied sciences are introduced into the market. The method can be useful within the absence of time series data on consumption trends. The technique is, nonetheless, termed as a mechanical method, which does not issue within the behaviors of customers. In addition, it ignores the modifications in consumption that are attributable to cultural, socio-financial, and demographic factors.

Econometric Method

It is another technique utilized in predicting demand. It brings collectively statistical approaches and economic conceptualizations to give you prediction equations. ADWEC makes use of the equations so generated to forecast the demand for electrical power out there. The method is efficient in establishing causal relationships between the demand of energy and financial variables. The approach achieves this by using ‘pooled’ cross-sectional information or time-collection (Energy Report, 2011b). The demand for electricity is conceptualized as a facet of different elements. The elements on this case embrace, among others, inhabitants, price of energy, and the value of different gas. By placing into consideration all these elements, the method generates an equation for predicting the demand for electrical energy. The equation generated is given beneath:

ED = f (T, POP, Pj, Pi, Y)


The company makes use of a variant of the econometric method, where it applies a four.2% annual population progress rate to estimate the demand for power for a interval of fifteen years. The methodology requires constant data collected over a protracted period of time to find out how variables relate to each other within the quick time period and the long term. However, the method is criticized for assuming that the speed of growth for explanatory variables will stay constant. Moreover, the method does not consider economic shocks and coverage measures which will change how the variable in focus will behave in the future.

Time Series

Time sequence strategies are econometric methods that use the variable’s lagged values as explanatory variables. The major assumption of the method is that sooner or later, variables will behave in a manner associated to their predicted and actual values prior to now (Industry Forecast Scenario, 2011). The method puts into consideration changes that consider how past realizations deviated from what was expected. In this regard, for a time sequence method to be successfully used in predicting future demand for electricity, the data for twenty to thirty time intervals is needed. Various characteristics set aside econometric methods and time collection strategies. For instance, the previous depends on time series knowledge. Another character setting them aside is the nature of explanatory variables taken into consideration. In the former, such explanatory variables as revenue, population development, and prices are used to determine the causal relationship. However, within the case of time collection strategies, only the variable’s lagged or previous values are used to make predictions (Energy Report, 2011a).

ADWEC makes use of time series methods to estimate the demand for electrical energy within the short-term period. For example, the corporate has a time collection model that is used to find out the monthly demand for energy for a interval of three years. On the opposite hand, the corporate uses econometric methods to determine the demand for electricity in the long run (Energy Report, 2011b). Time series techniques have the benefit of structural simplicity compared to the other techniques used in predicting demand for electrical energy. Furthermore, in collection methods, there isn’t a need to gather the information of multiple variables.

All that is required to use the approach is the flexibility to come up with correct observations of the particular variable that is under examination. However, the strategies have numerous shortcomings that negatively affect their effectiveness in predicting the demand for electrical energy. The main weakness of those models is that they fail to ascertain the character of the trigger and impact link between the varied variables. In the case of ADWEC, the model does not provide information as to why there were modifications in the demand for electricity, which is the variable under examine (Industry Forecast Scenario, 2011).


ADWEC has grown to turn into one of many leading mills and suppliers of electricity within the United Arab Emirates and in the larger GCC area. The primary purpose for the success of the corporate is the ability to forecast how demand for electricity modifications with time. The company uses different methods to forecast demand, relying on whether the forecast is short time period or long run. It additionally takes into consideration the needs of every sector of the economic system.


Adwec.ae. (2012). ADWEC organizational construction. Web.

Adwec.ae. (2012). ADWEC’s position. Web.

Adwec.ae. (2012). ADWEA’s peak electricity technology exceeds 10,000 MW. Web.

Energy Report. (2011). Energy industry report. UAE Energy Industry Report, three(1), 6-12.

Energy Report. (2011). Energy business report. UAE Energy Industry Report, three(2), 3-9.

Industry Forecast Scenario. (2011). Energy prediction in UAE. UAE Oil & Gas Report, 2(2), 39-forty seven.





Type Case Study Pages eight Words 2172 Subjects

Company Analysis
Language 🇺🇸 English

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