Power Generation Capacity and Its Investment Requirements in Pakistan for Twenty Years ( )

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1 Chapter 117 Power Generation Capacity and Its Investment Requirements in Pakistan for Twenty Years ( ) Nadeem A. Syed, Akbar Saeed and Asif Kamran Abstract Pakistan is facing an unprecedented power crunch. Despite sufficient generating capacity, there is extreme shortage of output, and load shedding for long hours has become the norm. This paper develops a forecasting model for estimating the least possible generating capacity of electric power, required in Pakistan during the 20 years ( ). The estimation is based on demographic and macroeconomic factors. Data from 1950 to 2010 has been analyzed. After developing the model, forecast has been made over the 20 years for the least possible generating capacity in mega watts (MW) which needs to be in place. The investment requirements have been identified for each of the years in the forecasted period. It may be noted that forecasting electric power demand is not the objective of this study. Keywords National Transmission and Dispatch Company Limited (NTDC) Gross Domestic Product (GDP) Mega watts (MW) Independent Power Producers (IPP) Introduction The first energy (oil) crisis in the world occurred in early 1970s. After the crisis, demand forecasting for energy in general, and demand forecasting for electricity in particular has vastly gained researchers interest. As per kumar Policy makers and planners need reliable demand forecast for electricity and energy to formulate N. Syed Management Science Department, National University (Fast), Karachi , Pakistan A. Saeed Management Science Department, Bahria University, Karachi , Pakistan A. Kamran (B) School of Management & Economics, University of Electronic Science & Technology of China, Chengdu , P. R. China asifkamrankhan@hotmail.com J. Xu et al. (eds.), Proceedings of the Seventh International Conference on Management Science and Engineering Management (Volume 2), Lecture Notes in Electrical Engineering 242, DOI: / _117, Ó Springer-Verlag Berlin Heidelberg

2 1372 N. Syed & A. Saeed & A. Kamran strategies [8]. The task is especially challenging for developing countries because necessary data and institutional framework are lacking. Developing countries such as Pakistan, although having sufficient generating capacity, also experience supply shortages of electricity, which arise because of inappropriate policies as well as investment decisions in power generation. The concept of unfulfilled or suppressed demand inhibits analysis. Demand Side Management (DSM), which is considered an internationally accepted technique, is applied extensively to bridge the demand supply gap. The current per capita consumption is one of the lowest in the world at 640 KWH compared to 13,000 for USA. The objective of this study is to forecast the bare minimum power generating capacity that should be continuously enhanced to meet the least possible power requirements of the country, keeping in view the population growth and economic growth. The period covered is twenty years ( ). The study also computes the forecast for investment requirements in power generation over the same 20 year period. It is emphasized that the objective of this study is not to forecast the demand for electricity Literature Review The World Bank has come up with several publications in context of energy demand forecasting and management. Energy Demand Models for Policy Formulation A Comparative Study of Energy Demand Models concludes its investigation that two types of approaches are used in the world. The first one is econometric in nature and the other one is accounting. Forecasting Investment Needs in South Africa s Electricity and Telecom Sectors is another World Bank publication of The study has estimated required investment in electricity and telephone lines for for South Africa using panel data on 52 countries for the period The study has predicted that the required average annual investment in electricity over the period are of the order of $ 0.52 billion which is about 0.2% of GDP. Using the Granger Causality approach, Aqeel investigated the relationship between energy consumption and economic growth, and energy consumption and employment in Pakistan [3]. The study applied techniques of co-integration and Hsiao s version of Granger causality. The study reveals that economic growth causes total energy consumption. As per Bhattacharyya Economic growth also causes increase in usage of petroleum products, no particular relationship was found between economic growth and gas consumption. Electricity consumption was found to affect economic growth [1]. Chaudhry has been estimated the electricity demand on firm-level and economy-wide level in Pakistan. The research paper concludes that consumption of electricity per capita will increase at a rate of 0.65% for every 1% increase in per capita income. The research estimates that higher prices will significantly reduce the demand for electricity in the manufacturing sector [4]. National Transmission and Despatch Company Limited (NTDC) is an organization under the Ministry of Water and Power, Government of Pakistan. NTDC has prepared the Electricity Demand Forecast for the period 2011 to NTDC has computed the

3 117 Power Generation Capacity and its Investment Requirements in Pakistan peak demand as 20,223 MW, 2020 peak demand as 45,398 MW and 2035 peak demand as 134,814 MW. NTDC has projected that the present transmission losses of 3% will reduce to 2.5% in 2015 and would remain at that level thereafter. The present distribution losses of 14.6% have been assumed to reduce to 8% by 2019 and then remain at the same level thereafter. NTDC study also found that industrial share in the electricity sales in the years 1980, 1990, 2000 and 2010 has been recorded as 42%, 40%, 36% and 35% respectively, which shows that industrial share is continuously decreasing. On the other hand domestic share for the same years was 21%, 30%, 43%, and 42% respectively. This is considered alarming by NTDC and warrants facilitation to the industrial sector by the Government [5] (The Electricity Demand Forecast for the period 2011 to 2035, Feb 2011). A detailed review of the NTDC study reveals lack of data pertaining to the role of private sector. The Independent Power Producers that is the IPPs such as the Hub Power Company with a capacity of 1300 MW and more than twenty other private sector producers with varying capacities have a definite role in this regard. But their contribution appears to have been missed out in this elaborate study. The investment requirements have also not been identified in the NTDC research. As can be seen, most of the studies have focused on estimation of demand Past Data - Capacity & Output in Pakistan The electricity generation capacity in Pakistan has progressively increased from a total of 106 MW in 1950 to 20,728 MW in The decade wise breakup of the generation capacity into its constituents, that is, hydro, thermal and nuclear is presented in the following table along with the total output (in GWH). Population, GDP, and generating capacity installed are shown in Table ,000 12,000 10,000 8,000 6,000 4,000 2, H N T Fig Electricity generation capacity As can be seen from the above Table and Fig , the reliance on thermal sources of power generation has proportionally increased since 1980s.

4 1374 N. Syed & A. Saeed & A. Kamran Table Population, GDP, and generating capacity installed Years Population GDP MW Prod. GWH Source: SBP Hand Book of Pakistan s Statistics 2010.

5 117 Power Generation Capacity and its Investment Requirements in Pakistan 1375 Table Electricity generation capacity Year Hydro (MW) Thermal (MW) Nuclear (MW) Total (MW) Generation (GWH) Source: Hand Book of Pakistan s Statistics 2010, State Bank of Pakistan The Gap between Capacity and Output The thermal sources include generation plants based on fuels derived from imported crude oil and the indigenous natural gas. The international prices of crude oil have nearly tripled since 1980s thereby putting a great deal of pressure on generating costs which cannot be matched with selling prices of electrical units of output because of policy constraints [2]. Hence there is no other alternative other than to produce less electricity because the Government simply cannot pay the bill of fuel. Another reason for the gap is the capacity factor, which is significantly different for each of the method of generation. Because of constraints of the water level in dams, 50% capacity factor for hydroelectric plants is quite common in the world. Power capacity factor for nuclear plants in USA is 90%, wind farms 20-40%, and solar 20%. Geothermal plants, based on Earth s heat have a higher capacity factor. The current world-wide geothermal installed capacity is 10,715 MW. The largest is in USA (3,000 MW) followed by Philippines and Indonesia Forecasting Electricity Generating Needs ( ) Forecast of the increasing electric generating requirements for the next 20 years can be undertaken on several criteria such as increasing population, increasing economic factors such as GDP. Table contains the data from 1950 to 2010 regarding Pakistan s Population, GDP and the installed capacity of electricity generation measured in MW. In the following sections, forecasting model is first developed on the basis of population, then GDP, and then finally on the basis of both population and GDP taken together.

6 1376 N. Syed & A. Saeed & A. Kamran Regression Model-I: Installed Capacity (MW) and Population The regression model for forecasting installed capacity of electricity as a function of population is presented in the following graph, which also shows the regression equation. In terms of this regression model, the required generating capacities for 2010, 2020, and 2030 are 20,667 MW, 28,147 MW and 34,977 MW respectively. The model is statistically acceptable. The forecast of population is described in the later sections. Fig The regression model for forecasting installed capacity of electricity as a function of population Fig shows the regression equation. In terms of this regression model, the required generating capacities for 2010, 2020, and 2030 are 20,667 MW, 28,147 MW and 34,977 MW respectively Regression Model-II: Installed Capacity (MW) and GDP Regression model for GDP and Electricity generating capacity is presented in the following figure. The graph also shows the regression equation. It may be noted that the GDP has been measured in terms of constant factor cost of If this model is applied, then the required generation capacities in 2010, 2020, and 2030 are 22,967 MW, 32,637 MW and 44,018 MW respectively. This regression equation is also statistically acceptable. Forecasting of GDP is undertaken in the later sections.

7 117 Power Generation Capacity and its Investment Requirements in Pakistan 1377 Fig Regression model for GDP and Electricity generating capacity Fig shows the regression equation. It may be noted that the GDP has been measured in terms of constant factor cost of If this model is applied, then the required generation capacities in 2010, 2020, and 2030 are 22,967 MW, 32,637 MW and 44,018 MW respectively Regression Model-III: Installed Capacity (MW), Population and GDP Finally, the dependent variable (installed capacity in MW) is estimated together with two independent variables that is population and the GDP. The 3-D graph of the three variables is depicted in Fig Fig Egression Model: Installed Capacity(MW), Population & GDP

8 1378 N. Syed & A. Saeed & A. Kamran Analysis of Multiple Regression (see Table 117.3): Installed Capacity (MW), Population, and GDP. Table Analysis of multiple regression Predictor Coef SE Coef T P Constant Population GDP S= 1194, R-Sq= 97.1%, R-Sq(adj)= 97.0%. The regression equation is: Installed Capacity(MW) = Population GDP. Analysis of Variance (see Table 117.4) Table Analysis of variance Source DF SS MS F P Seq SS Regression Residual Error Total Population GDP The above regression model (Fig ), estimates of population and estimates of GDP are required to be made for the years 2011 to Forecasting of Population and GDP Till 2030 In order to estimate the electric power generating capacity requirements with the help of the above regression model, estimates of population and estimates of GDP are required to be made for the years 2011 to 2030.

9 117 Power Generation Capacity and its Investment Requirements in Pakistan Population The trend of population increase can be statistically forecasted with help of following three techniques: Linear Quadratic Exponential Figs depict the above three trends for the increase in the population. Fig Linear trends for the increase in the population Based on the above three models, the population growth has been forecasted for the period 2010 to 2030 in Table Considering all aspects, the quadratic growth forecast for population increase appears to be suitable. Hence the quadratic forecast for population increase has been adopted for determining the future requirements of electricity generation in Pakistan Gross Domestic Product (GDP) As stated earlier, the forecast of GDP for the next 20 years is also required for determining the electricity generation requirements for the next 20 years. The GDP growth can also be forecasted on the following three basis: Linear Quadratic Exponential

10 1380 N. Syed & A. Saeed & A. Kamran Fig Quadratic trends for the increase in the population Fig Exponential trends for the increase in the population Figs depict the above three techniques for determining the increase in the size of Gross Domestic Product for the next 20 years. Based on the above three models, the GDP has been forecasted for the period 2010 to 2030 in Table Considering all aspects, the exponential forecast appears to be more ambitious and improbable. Therefore, for the regression analysis, the quadratic forecast for

11 117 Power Generation Capacity and its Investment Requirements in Pakistan 1381 Table Population forecast (millions) Years Linear Quadratic Exponential Fig Linear techniques for determining the increase in the size of Gross Domestic Product GDP increase has been adopted for determining the future requirements of electricity generation in Pakistan.

12 1382 N. Syed & A. Saeed & A. Kamran Fig Quadratic techniques for determining the increase in the size of Gross Domestic Product Fig Exponential techniques for determining the increase in the size of Gross Domestic Product Estimation of Power Generation Requirements The regression model to forecast the power generation requirements which was developed in the earlier section is reproduced below: Installed Capacity (MW) = Population GDP. (117.1)

13 117 Power Generation Capacity and its Investment Requirements in Pakistan 1383 Table GDP growth (millions of rupees) Years Linear Quadratic Exponential Based on the above equation, and also based on the forecasted values of population and GDP, the requirements for capacity of power generation in Pakistan for the next 20 years have been computed. The same is shown in Table Forecasting Investment Requirement in Power Generation for the Next 20 Years The present power generating assets would gradually get depreciated and would need to be replaced at some point in time in the future. For example the KANNUP with 137 MW capacity has outlived its life. Sooner or later it would be shut down and retired and 137 MW from the existing capacity would be eliminated. Therefore, for estimating the investment requirements, it is assumed that physical wear and tear (annual depreciation) would result in elimination of 2% generating capacity every year and would thus need yearly replenishment. Investment requirements in US Dollars per one MW varies from $1.00 million to $1.50 million, depending on the type of the power generation envisaged. The lower limit is for hydel and the upper limit is for off shore wind mill. The conventional thermal power units planned in and around 2010 and which are likely to become operational by 2015 are expected to cost around $1.25 million per 1.0 MW. Based on the foregoing capital cost, the

14 1384 N. Syed & A. Saeed & A. Kamran Table Forcasted population, GDP, and power generation capacity requirements Years Population (millions) GDP (million Rs.) Power generation capacity (MW) ,344 22, ,733 23, ,284 23, ,997 24, ,870 25, ,904 26, ,100 27, ,457 28, ,975 29, ,653 29, ,494 30, ,495 31, ,657 32, ,981 33, ,465 34, ,111 35, ,918 36, ,886 37, ,015 38, ,306 39, ,757 40,880 investment requirement in US Dollars is estimated for the next 20 years in Table Conclusion Pakistan s population is projected to increase to 263 million and the GDP is projected to increase to Rs. 430 billion by the year The minimum electricity generating capacity required to support the present living standards is projected at 40,000 MW for the year The 2010 installed capacity is around 20,000 MW. Assuming a 2% wear and tear of the installed capacity every year, continuous replenishment of the existing installed capacity together with additional required to support the increasing population and consequent increasing economic activity (GDP) would increase from 1,350 MW in 2010 to 26,750 MW in As per Cichanowicz the capital cost of new investment in power plants ranges from US Dollars 1.0 million to 1.5 million per one MW [6]. The lower limit is for hydel and the upper limit is for off shore wind mill. The conventional thermal power units planned in and around 2010 and which are likely to become operational by 2015 are expected to cost around $1.25 million per 1.0 MW. Based on the foregoing cost, the investment requirement in US Dollars is estimated as $4.6 billion for The

15 117 Power Generation Capacity and its Investment Requirements in Pakistan 1385 Table The investment requirement in US Dollars Years Power capacity required (MW) Actual capacity installed (MW) Additional capacity required (MW) Required investment ($ in millions) ,269 20,921 1,348 1, ,068 20,728 2,340 2, ,881 20,313 3,568 4, ,708 19,907 4,801 6, ,549 19,509 6,040 7, ,404 19,119 7,285 9, ,272 18,736 8,536 10, ,154 18,362 9,793 12, ,050 17,995 11,056 13, ,960 17,635 12,326 15, ,884 17,282 13,602 17, ,821 16,936 14,885 18, ,773 16,598 16,175 20, ,738 16,266 17,472 21, ,717 15,940 18,776 23, ,709 15,621 20,088 25, ,716 15,309 21,407 26, ,736 15,003 22,733 28, ,770 14,703 24,067 30, ,818 14,409 25,409 31, ,880 14,121 26,759 33,449 investment requirement in each year after 2012 will gradually increase. In the year 2015 it would be $9 billion, in 2020 it would be $17 billion. In 2025 the investment requirement is estimated at $25 billion and for 2030 it is estimated at $33 billion. The investment requirements may be lowered if the investment is made in plants based on hydroelectric sources. It is re-emphasized that the foregoing estimates of investment cost are not based on estimates of future demand of electric power. The estimates are based on the minimum possible power requirements of the growing population and the consequent growing economic activity. The other studies referred have estimated the demand rather ambitiously, which is unlikely to be met. This study has attempted to determine the bare minimum capacity of power generation needed in the years 2011 to The optimum mix of hydoelectric, thermal, nuclear, wind, and solar needs to be determined. Capacity building is needed to undertake research and development in area of renewable sources. The need to build consensus on the major issues and concerns amongst the stakeholders is paramount. Delays are going to cause greater efforts to recover from the slide.

16 1386 N. Syed & A. Saeed & A. Kamran References 1. Bhattacharyya SC (2009) Energy demand models for policy formulation A comparative study of energy demand models. World Bank Policy Research Working Paper Fedderke J (2006) Forecasting investment needs in South Africa s Electricity & Telecom Sectors. World Bank Policy Research Working Paper Aqeel A (2001) The relationship between energy consumption and economic growth in Pakistan. Asia-Pacific Development Journal 8(2): Chaudhry A (2010) A panel data analysis of electricity demand in Pakistan. The Lahore Journal of Economics 15: Electricity Demand forecast for Pakistan 2011 to National Transmission and Despatch Company Limited February Cichanowicz E (2010) Current capital cost and cost effectiveness of power plant emission control technologies 7. Electricity Generation Cost (2011) Department of energy and climate change, UK 8. Kumar A (2010) Electricity sector in India SSRN,

Energy Consumption Profile

Energy Consumption Profile Presentation to BY Objectives Availability of energy on sustainable basis to achieve planned GDP targets Reliance on indigenous resources shift of energy mix towards local resources Construction of new