MODELING ELECTRICITY TRADE in SOUTHERN AFRICA Second Year Final Report to the Southern African Power Pool
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March 23, 1999 USAID Co-operative Agreement on Equity and Growth through Economic Research Trade Regimes and Growth (EAGER/Trade) MODELING ELECTRICITY TRADE IN SOUTHERN AFRICA Second Year Final Report to the Southern African Power Pool F.T. Sparrow, William A. Masters, Zuwei Yu, Brian H. Bowen PURDUE UNIVERSITY Peter B. Robinson, Zimconsult David Madzikanda SAPP-PSC Jean-Louis Pabot SAPP-GPWG Arnot Hepburn Eskom, South Africa B.R.F. Moore BPC, Botswana M. Badirwang BPC, Botswana Fatima Arthur EDM, Mozambique Bongani Mashwama SEB, Swaziland Roland Lwiindi ZESCO, Zambia Edward Tsikirayi, ZESA, Zimbabwe K.R. Abdulla TANESCO, Tanzania Jose A. Salguerio Energy Sector, TAU, SADC Swaziland SAPP Management Meeting February 23-25, 1999 2 ACKNOWLEDGEMENTS Each of the members of Purdue UniversityÕs State Utility Forecasting Group and graduate staff have made significant contributions during the second year of SAPP modeling. These include Doug Gotham, David G. Nderitu, Frank Smardo, James Wang, Kevin Stamber, Basak Aluca, and Pedro Gonzales-Orbago. The administrative assistance from Chandra Allen and Barbara Beaver has been a great help throughout. Thanks is given to each one for contributing so much. Colleagues from the Southern African Power Pool (SAPP) and researchers at Purdue University highly value the funding and support of the USAID/EAGER in making the Purdue/SAPP joint research project all possible. CONTENTS Page Acknowledgements.............................................................................................................. 2 Section 1 Overview of The SAPP Modeling............................................................... 4 Section 2 Formulation ................................................................................................. 6 Section 3 Data Collection............................................................................................ 8 Section 4 Computation.............................................................................................. 15 Section 5 Introduction to the Long-Term Model Runs............................................. 16 Section 6 Demonstration Model Runs...................................................................... 18 6.1 Run One......................................................................................................... 19 6.1.1 Costs.............................................................................................. 19 6.1.2 MW ............................................................................................... 20 6.2 Run Two........................................................................................................ 22 6.2.1 Costs.............................................................................................. 22 6.2.2 MW ............................................................................................... 24 6.3 Run Three ...................................................................................................... 25 6.3.1 Costs.............................................................................................. 25 6.4 Run Four........................................................................................................ 27 Section 7 Further Work & Model Implementation................................................... 29 FIGURES Figure 3.1 ............................................................................................................. 13 3 Figure 3.2 ............................................................................................................. 14 Figure 5.1 ............................................................................................................. 17 Figure 5.2 ............................................................................................................. 17 Figure 6.1 ............................................................................................................. 21 Figure 6.2 ............................................................................................................. 23 Figure 6.3 ............................................................................................................. 26 TABLES Table 3.1 ............................................................................................................... 9 Table 3.2 ............................................................................................................. 11 Table 3.3 ............................................................................................................. 10 Table 3.4 ............................................................................................................. 11 Table 3.5 ............................................................................................................. 12 Table 3.6 ............................................................................................................. 12 Table 6.1 ............................................................................................................. 28 Table 6.2 ............................................................................................................. 28 Table 6.3 ............................................................................................................. 29 BIBLIOGRAPHY............................................................................................................. 30 4 1. Overview of The SAPP Modeling The past two years have seen substantial progress in the modeling of electricity trade in the southern region of Africa. The first year researched the short-term benefits of alternative trading procedures. The second year has seen the construction of a comprehensive (generation and transmission) and transparent long-term planning model which provides insights into the optimal lowest cost construction scenarios for the region over a twenty year horizon. It is hoped that a further year of joint modeling work between the SAPP and Purdue University will see the long- term model effectively implemented and running in at least three or four centers of Southern Africa. • The first year had studied the short-term benefits of alternative electricity trade contracts within the SAPP. It showed that 80 to 100 million USD could be saved annually from the reduction in production costs as a result of a centralized dispatch method of trading. • Year two of the modeling of electricity trade in Southern Africa has built upon the earlier work that was completed in year one. The second year is working on the SAPP long-term (LT) model. It is showing that an average regional high growth (5.7%) in electricity demand will cost (for new capacity and operations) the region 23.4 billion USD over the next twenty years. If a regional average low growth (2.0%) in demand in electricity is used then the total cost will be 5.8 billion USD. Expansion in transmission is shown to be very important for the earlier years in the model. • The second year of modeling has produced a workable and sophisticated LT model that will operate on a personal computer. The data will need sensitive detailed double checking by the SAPP colleagues in the third year of implementation. Changes in data for demand growth, project costing, levels of national independence of electricity supply, capital recovery factors (CRF) and several other variables will significantly alter the outcome from this fascinating and powerful LT model. A halving of the CRF for example in the major hydropower countries of SAPP creates savings of over 1.5 billion USD. The long-term modeling is largely based on the assumption of a medium or SADC average weighted demand growth rate in electricity (3.8%) over the next 20 years. Regional costs for 20 years amount to $11.4 billion USD with a free trade scenario. With a great concerted effort the costs and technical data in this LT model have been updated in a relatively short period of about six months. This has been achieved through excellent collaboration between the SAPP Generation Planning Working Group (GPWP) and the staff at Purdue University. No commercial software is yet available to achieve the level of integration in utility planning and electricity trading for the long-term which this model provides. 5 The medium demand growth figures (Table 3.5) and many other inputs to the model will require further reassessment over the next several months before the LT model can be used for decision analysis in prioritizing construction projects. Numerous runs of the LT model have been made since the Cape Town modeling workshop (July 1998). Improved constraints and equations have since been added. A superior, working model is now available for SAPP to thoroughly test and use within the region. In some countries a low electricity demand growth rate could be considered as being more appropriate. This decision together with other economic and financial data inputs must be decided upon. A closer scrutiny of all the data has yet to be completed in the region. This second year of modeling has established the working LT model and has shown that it is possible to run such a complex model on a personal computer. The PC platform had been an objective specified by the SAPP management in March 1998. This year two final report needs to be read in conjunction with two other SAPP modeling documents that are dated January/February 1999. These are: • The SAPP Long-Term Modeling USER MANUAL (Second Edition) [6], • Modeling Electricity Trade in Southern Africa 1999/2000