Electricity Trade and Capacity Expansion Options in West ...purdue.edu/discoverypark/energy/assets/pdfs/centers/wapp-yr4-prop… · The User-Friendly Interface for the West Africa

Electricity Trade and Capacity Expansion Options

in West Africa

Proposal for February 15, 2003 to February 14, 2004

PURDUE UNIVERSITY F.T. Sparrow

William Masters Brian H. Bowen

December, 2002

1Electricity Trade and Capacity Expansion Options in West Africa, 2003 to 2004

F.T. Sparrow et al November 2002

Summary

The User-Friendly Interface for the West Africa Power Pool long-term planning model was restructured and improved for wide general use in 2002. It is proposed, for 2003, that further output improvements be made to this interface. ECOWAS recommendations for the interface and WAPP model are listed and supported by the Purdue team in this proposal. As well as interface improvements it is proposed by ECOWAS colleagues that more financial dimensions be added to the model output reports and to the model coding to improve the representation of the private sector in West Africa’s power supply industry. In 2003, following the in-depth specialized training of 2002, it is expected that, through the effective design and transfer of the model interface to the region, that there will be a significant increase in use of the model. The illustration below shows the output screen facility demonstrating the lines that are built in the WAPP Zone B, for one of the demonstration models.

The 2003 WAPP modeling work and interface enhancement will assist the ECOWAS planners in their regional planning for generation capacity expansion and in determining the increased role of the private sector in the power supply business of West Africa and the effects of changing fuel costs and contracting agreements. In the next 10 years it is predicted, from the region and from the current demonstration WAPP model, that about 9,000MW of new generation capacity is needed to supply essential needs of the region. With the completion of regional data validation in 2003 these generation forecast plans can be more reliably assessed. Further training of key ECOWAS and WAPP staff, in the use of the WAPP planning model and the interpretation of the output results, is being scheduled.


WAPP Training and Modeling in 2002 and What Next for 2003? The 2003 Purdue modeling and planning activities, with the WAPP, will build upon the modeling work and training that was achieved in 2002. Training took place at Purdue in 2002 for WAPP policy analysts at two, 2-week long training sessions (Appendix 1). These were for the model operators in WAPP’s Zone A and Zone B from August 12 to August 23, 2002 and for the ECOWAS model operator from September 9 to September 20, 2002. In September 2001 there was consultation in the region on the WAPP modeling and data validation needs in Cotonou, Benin. The summer training periods of 2002 marked a turning point in the ECOWAS electricity policy analysis work following the creation of the vastly improved WAPP model interface. The colleagues from ECOWAS were able to use the model for easy data input and output analysis exercises. These colleagues then took the latest WAPP model and interface back to the region for further application and data sensitivity work. From the number of emails received, from West Africa, since their return it is clearly demonstrated that the model is now being used in the region. (Appendix 2). The major technical development in 2002 was the improvement and restructuring of the user-friendly interface for general users of the WAPP planning model. This interface was used extensively on a daily basis during the 4 weeks of training in the summer of 2002. For 2003 it is recommended, by the ECOWAS model operators, that extra facilities be added to the interface especially to provide increased financial outputs, the role of independent power producers, and the collective plans for Zone A and Zone B. These recommendations are supported by the Purdue team and are also detailed in a later section of this proposal. The following section illustrates three of the most used input screens of the interface also three output result screens. The in-depth training of model operators for WAPP Zone A and Zone B, and the ECOWAS Secretariat has created a structure for a much deeper level of cooperation between the Purdue modelers and the ECOWAS Community. These model operators and policy analysts will take primary responsibility for training others within ECOWAS on how to use this planning tool. The Purdue staff, in 2003, will supply the necessary technical and policy analysis support, and expertise to assist in the “training of the trainers”.


WAPP Interface Development The main technical achievement for the Purdue modeling team was the improvement to the earlier version of the user-friendly interface. The additions of pull-down menus and total restructuring of the interface has produced a much superior interface to that produced under the SAPP Project. This latest version of the interface has also the potential for meeting more sophisticated demands from the ECOWAS such as the need to create more nodes in each country which will provide a better picture to reflect the independent and national facilities as well as distinguishing between urban and rural communities. The newly created data screens for the WAPP are shown in Figure 1. During 2002 the Purdue java programmers created several new graphical output screens which provide an immediate pictorial analysis of regional and national potential costs and capacity expansion options. Figure 2 shows examples of these screens capable of providing the rapid illustrative output results. In 2003 there are plans for further improvement to these screens to give a more complete financial accounting of planning options and analysis from the perspective of Zone A and Zone B respectively. ECOWAS Data and Modeling Results Data modeling in 2003 will assist the ECOWAS planners in their planning of generation expansion. Over the past 10 years the ECOWAS has studied and promoted international transmission line options and now in the coming years it is necessary that more emphasis is to be given to generation expansion plans. The Purdue WAPP model is designed to provide economic generation expansion plans through its’ least cost optimization analysis. The present demonstration WAPP model (based on ECOWAS Electricity Data Set # 5, September 2001) indicates that the West Africa region will require in the range of $8 to $10 billion to meet the regions’ growing electricity needs in the next 10 years (Table 1). Table1. Total Costs in WAPP for 2002 to 2012 with Reliability & Free Trade Thermal & Hydro Reserve Margins

WAPP Total CostFree Trade ($ million)

WAPP Total Cost& Independence ($ million)

Percentage Cost Savingswith Free Trade

5% 7924 9394 15.6% 20% 8060 9990 19.3% Difference 5% - 20%

1.7% 6.3%

Source [1] There is only a1.7% increase in the investment value to guarantee a 20% reserve margin in the free trade scenario as opposed to a 6.3% increase in investment to guarantee the same reserve margin the independent scenario (Table 1). There is a great cost savings in the free trade scenario ranging from $1.47 billion to $1.93 billion, with corresponding reserve margins ranging from 5% to 20%. The costs savings


between free trade and no reserve margins and total independence (self sufficiency) with no reserve margins pays for more than seven times the increase in the investment necessary to guarantee a 20% reserve margin in a free trade scenario. The data collection process within WAPP requires more validation in 2003 in order for the model to be used in the planning activities of ECOWAS. The most significant need is the data sub-set for Nigeria. Table 2 shows the generation capacity expansion requirements over the 10 year horizon with reserves set at 5% and 20%, and with and without free trade.

Table 2. WAPP Generation Capacity Expansions with Reliability & Free Trade Thermal & Hydro Reserve Margins

WAPP Total Capacity Expansions

with Free Trade (MW)

WAPP Total Capacity Expansions with Independence

(MW)

5% Total 8395 Thermal 7096 Hydro 1299

Total 8064 Thermal 7004 Hydro 1060

20%



Source [1] As would be expected, Table 2 shows that the reserve margins require more capacity. The results in Table 1, which shows a shift to energy independence, decreases regional capacity expansion rather than increases it, needs an explanation. What happens when trade is eliminated is that countries, by themselves, are unable to meet their energy and capacity demands from the reduced set of generation option available within their countries. This results in a dramatic increase in unserved demand and unmet reserve requirements, as the countries are forced to rely on very expensive backup generators to satisfy their demands. Thus the decrease in central generation expenditures associated with energy independence is uniformly bad news for WAPP members. It means that many countries will be forced to turn to more expensive supply options within their boarders. The paradoxical side effect of all this is a decrease in cheap generation investment as shown in Table 2. When free trade planning takes place with a strong reliability margin of 20% then the maximum capacity expansion is 8,914MW (Table 2). The largest generation capacity expansion, in any one time period, takes place during 2005 to 2006 with about 3,400MW (Table 3).


Figure 1. The New WAPP User-Friendly Interface & Screen Options


Figure 2 The New WAPP User-Friendly Interface Illustrating the Output Screens


Table 3. Thermal & Hydropower Generation Expansions for 2002 to 2012 & Free Trade Reserve Margins

Period 1 2003-4

Period 2 2005-6

Period 3 2007-8

Period 4 2009-10

Period 5 2011-12

TOTALS

5% Thermal (MW) 1758 3001 655 746 936 7096 Hydro (MW) 263 391 248 235 162 1299 TOTAL (MW) 2021 3392 903 981 1098 8395 20% Thermal (MW) 1771 3002 670 738 1260 7441 Hydro (MW) 412 446 181 241 193 1473 TOTAL (MW) 2183 3448 851 979 1453 8914

Source [1] It can be seen in Table 4 that, based on the demonstrated output results, that the country with the greatest amount of generation capacity expansion will be in Nigeria. From the 8,395MW generation capacity expansion needs in the next 10 years 83% of this is forecast to be in Nigeria. In 2003, with a dependable updated Nigeria data sub-set being supplied to WAPP planners, then dependable regional expansion plans can be expected. Table 4. WAPP Generation Capacity Expansions (thermal & hydropower)

with 5% Reserve Margins & Free Trade Country Period 1

2003-4 Period 22005-6

Period 32007-8

Period 42009-10

Period 52011-12

TOTALS

Benin 4 4 Burkina Faso 0 Cote D’Ivoire 247 247 Gambia 0 Ghana 115 115 Guinea 106 388 134 101 2 731 Guinea Bissau 15 15 Liberia 32 3 39 10 84 Mali 95 95 Niger 114 5 119 Nigeria 1736 3001 616 736 840 6929 Senegal 18 19 37 Sierra Leone 0 Togo 19 19 TOTALS 2021 3392 903 981 1098 8395 Source [1]


Transmission planning in 2003 will need to give focus on WAPP’s Zone B. Shown in Table 5 are the optimal line expansions within Zones A and B and how they are significantly expanded in Zone B when a free trade option is taken. Transmission capacities in Zone B need to double when there are no constraints on regional electricity trade. Transmission plans in Zone A are at an advanced stage. Major expansions on the existing Zone A “coastal spine” are predicted for 2005/6 (Table 6). These line expansion are justifiable in conjunction with generation expansions taking place at the same time in Nigeria. The transmission expansions in Zone A are also expected to receive more attention from international investors in 2003. Line expansions can be more reliably planned therefore in 2003 when the Nigeria data sub-set is validated. Table 5 Total Transmission and Generation Capacity Expansions in Zones A and B,

2002–2012, under Free Trade (Scenario 1) and Limited Reserve Trading (Scenario 2, AF=90%, ENAF=50%)

Scenario 1 Free Trade

MW Expansions

Scenario 2 Limited Trade

MW Expansions Increment

Transmission 1,739 1,627 7% Thermal Generation 7,378 7,408

Zone A

Hydropower 415 592 3%

Transmission 613 298 105% Thermal Generation 85 231

Zone B

Hydropower 1,191 932 10%

Source [2] Table 6 Scenario 1, Free Trade & Zone A,

~ Transmission Capacity Expansions for 2002 to 2012

Line name Initial design

capacity MW & kV

Period 1 2003-2004

( MW)

Period 2 2005-2006

(MW)

Period 3 2007-2008

(MW)

Period 4 2009-2010

(MW)

Period 5 2011-2012

(MW)

Total Expansion

(MW)

Ben-Nga 560 / 330 686 3 689 Bfa-Gha 30 / 225 21 17 38 Ico-Gui 150 / 225 102 101 203 Ico-Lib 100 / 225 42 12 54 Ben-Tog 150 / 161 450 5 455 Gha-Tog 256 / 161 300 300 Total 1,739

Source [2]


ECOWAS Electricity Planning Infrastructures Since the legal establishment of the WAPP in 2000 the modeling group at Purdue has given technical support and training to members of the WAPP Technical Working Group. For 2003 it is proposed that Purdue provide further “training to WAPP trainers”. The three WAPP model operators, trained at Purdue in summer 2002, are the core members of this regional training and planning team. WAPP Modeling & Interface Recommendations Recommendations for the modeling in 2003 are outlined in the three WAPP reports [1,2,3], prepared while at Purdue in summer 2002. The recommendations listed below are from [1]. Initial model changes are also outlined in the preliminary emails listed in Appendix 2. The recommendations for the WAPP model can be divide into four categories: 1. A Financial Module

2. The modeling parameters [1] 3. The model interface [1] 4. WAPP Capacity Planning Group [1]

1. A Financial Module

The ECOWAS attendees in the summer 2002 workshops, at Purdue, suggested that a separate expanded revenue/expenditure projection be made for each country. Such a financial module would have as an input the prices the utility would charge domestically for it’s electricity, which then could be converted into a revenue stream by multiplying these prices by the levels of domestic demands in the model. These revenues, along with any revenues from export sales the model now calculates, would form the basis of the country’s electric revenues.

On the cost side, in addition to energy and capacity costs now in the model, there would be added the fixed costs of existing capacity. (This is now left out of the optimization model, being a sunk cost).

The result of the module would be a much improved projection of the revenue and expenses streams each country could expect under the differing scenarios examined by the model.

2. Modeling Parameters

(a) A better model of the region will result from the provision of more nodes for each country within the region in order to represent the roles of IPPs and national utility urban and rural electricity generation and supplies. (b) Allow for certain regional parameters to vary by country, site, year and wet and dry season (Wcost, water cost; fdrought, drought factor ; Resthm, reserve margin for thermal generation; ResHyd, reserve margin for hydropower generation ; UMcost, cost of unmet reserve ; UEcost, cost of unserved energy). (c) Allow for the impact of various contracts with third parties providers of


electricity services to WAPP (IPPs take or pay contracts, independent transmission providers). (d) AF, UMcost and UEcost will have to be worked out to reflect the true situation in each country. (e) The importance of data validation and update must be re-emphasized, as the more accurate and recent the information is the accurate and precise the model predicts results, (f) Wheeling charges must be agreed to in such a way that all parties involved benefit from the energy trade, of course this will be reflected in the total cost for the region.

3. User Interface

(a) The cost summary screen for the WAPP interface should be checked to update data directly from the GAMS output files and possibly a proper financial report included. (b) Provision can be made for zonal output report for zones A and B. (c) The print screen facility for the output graphs to be worked on to print properly. (d) Allow the number of WAPP nodes to be changed through the interface. (e) Complete the online library documentation users. (f) Include an interactive tutorial for general users.

4. A WAPP “Capacity Planning Group” (CPG) to work with Purdue University on the following tasks:

(a) Preparation of WAPP policy papers. (b) Data collection. (c) Regional training needs. (d) Planning of meetings for coordination and collaboration with WAPP-CDG

Purdue University Power Pool Development Group (PPDG) staff. The team of the Capacity Planning Group should include Sidy KANE (Zone A), Alpha SYLLA (Zone B), Olumuyiwa SHOKUNBI (ECOWAS secretariat), plus 2 or 3 other resource people.

Independent Power Producer, IPP, Contracts in ECOWAS In 2(c) above, it is proposed to introduce IPP contracts into the WAPP model in 2003. So far, ECOWAS IPP contracts share the following characteristics and costs; (1) A "take or pay" contract which requires the purchaser to pay a fixed yearly fee over the life of the contract for access to a certain fixed yearly amount of electricity; (2) an additional cost/kWh to be paid for any part of the fixed amount of electricity actually delivered during a year; (3) An option to purchase additional electricity over the fixed amount at a specified cost per kWh up to some maximum amount. Cost (1) represents the guaranteed return on the IPP's investment in the plant; it assures that the IPP will get back over the life of the contract their investment in the plant, plus a fair return, plus money to cover the fixed O&M necessary to maintain the plant in


working order. While this contract is stated in terms of a fixed amount of electricity (MWH)that must be purchased per year, it can also be thought of an an access charge to a fixed amount of generating capacity (MW) per year. Cost (2) is the cost/MWh paid to the IPP or another third party to cover the variable cost/MWh of generating any electricity actually delivered to the purchaser each year, up to the fixed MWh amount specified in the contract. Cost (3) is the charge/MWh for any electricity delivered to the purchaser each year over and above the fixed contractual amount. It has two parts; (a) a cost/MWh paid to the IPP to allow them an additional return on their investment; (b) a cost/MWh paid to the IPP or another third party to cover the variable cost/MWh. Sometimes, Cost (3) is broken down into segments, each segment having its own cost/MWh. The CIPREL contract, in Cote D’Ivoire, is an example of such a three part contract. Cost (1) requires the purchaser to take a minimum of 1,410,000 kWh per year (160.958 MW of capacity) over the life of the contract at a fixed cost of $24.273 million per year; Cost (2), the fuel cost of electricity delivered to the purchaser, is set at $32.626/MWh; Cost (3) is in two segments. The first segment allows the purchaser to purchase an additional 50,000 kWh of electricity (5.708 MW of capacity) over the fixed amount at a cost of $1.335/MWh to be paid to the IPP, (cost (a) above) plus a fuel cost of $32.626/MWh (cost (b) above). The second segment allows the purchase of additional electricity at a cost of $6.317/MWh to be paid to the IPP, plus the same fuel cost of $32.626/MWh. While the maximum amount of electricity available at this price was not specified, it is assumed be the capacity of the CIPREL plant, 210 MW, less the minimum amount, 160.958, less the 5.708 MW for the first segment, or 43.334 MW (379,000 MWh). To introduce this type of contract as an option in the model, a binary decision variable "YIPP( ty,z,IPPi)" must be added to the set of decision variables now in the model. The variable will be set at 1 in the year "ty" the contract is to start, and 0 both before and after that year. Starting in the year "ty" the model chooses to start the contract, the model then charges the objective function each year over the life of the contract the fixed yearly cost of the contract. Also starting in year "ty" is access to the fixed amount of energy per year made available by the take or pay portion of the contract, at a fuel cost as specified in the agreement. A new generation variable, "PG(ty,ts,td,th, z,IPPi)" represents the electricity actually delivered during the year, at the fuel cost as specified. The rate at which this is delivered must not exceed the amount of capacity made available under the take or pay provisions of the contract, and the total MWh/year limit in the take or pay contract cannot be exceeded. Thus, the take or pay portion of the contract is modeled exactly as the construction of a new hydro generation facility with a fixed charge is now handled in the model. The annual charge is entered each year into the objective function just as the annualized equipment charge for a new hydro plant is entered; the rate of generation of electricity each year cannot exceed the capacity of the plant, and the fuel cost is charged for each kWh of power delivered during the year as is the case of the


water cost in the hydro facilities. The limit on the total energy delivered each year is set just as the kWh volume of water in the reservoir sets a limit on yearly generation in the hydro case. Since the delivery of electricity is presumed to be guaranteed by the IPP, both the forced and unforced outage rates are set to zero. The option to purchase additional electricity at a set price up to some maximum amount is modeled as a separate contract similar in form to the way the model now models generation from an existing hydro facility. There is no capital charge, only a fuel cost, generation cannot exceed some prescribed capacity, and the total amount of electricity generated over the year cannot exceed some prescribed amount. The only difference is that the electricity cannot be drawn upon until the take or pay portion of the contract has been accepted by the model. If there is more than one segment in the option, each is modeled as a separate contract. The following example, based on what we know about the CIPREL contract, illustrates how such contracts are modeled. Consider first the take or pay portion of the CIPREL contract. The binary decision variable, "YIPP(ty,z,CIPREL) is set to 1 in the year "ty" the contract is signed; otherwise, it is 0. The fixed cost of $24.273 million/year is entered into the objective function the year the contract is signed and each year thereafter by adding to the objective function the following term:

[sum t=1 to ty of YIPP(t,z,CIPREL)]*$24.273e6 Note that if the contract has been signed prior to the current period "ty", (e.g., if the year in question "ty" is year three, and the contract was signed in year two), then the bracketed total is 1, and $24.273e6 is entered in the objective function for the year "ty". If the contract was not in force prior to year "ty", then the bracketed sum is 0, and no fixed charge is entered in the objective function in year "ty". The capacity constraint of the take or pay contract is not specified in the material provided. Lacking this information, it is assumed to be the capacity of the CIPREL plant, 210 MW. This maximum rate of power generation is entered by first defining a new generation variable, "PGIPP(ty, ts,td,th,z,CIPREL)" which is the instantaneous power generated within the IPP take or pay portion of the contract. This variable is limited to 0 until the year when the contract is signed, and 210 MW after the contract is signed. The capacity constraint is then:

PGIPP(ty,ts,td,th,z,CIPREL)<= [sum t=1 to ti of YCC(t,z,CIPREL)]*210 Again, the bracketed amount is 1 if the contract has been signed prior to or including year "ty",and 0 if the contract has not been signed.


The yearly energy limit is entered in the model in the same way an energy limit is entered in the modeling of a hydro generation facility:

Sum[Mseason, Mday, Mhour,PGIPP(ty,ts,td,th,z,CIPREL)]<=1,410,000 MWh Note that there is no need to limit the right hand side of the constraint to be zero Until the contract is signed; that has already been taken care of in the capacity constraint. The variable cost of the power delivered under the terms of the take of pay portion of the contract is entered into the objective function by multiplying PGIPP(..) by the fuel cost of $32.626/MWh, using the appropriate weights for the seasons, days, and hours. The two segments of the options to purchase additional electricity over and above the contracted amount are modeled as separate projects which are linked to the signing of the take or pay contract in the following way. Letting PGIPP(ty,ts,td,th,z,CIPREL1) be the extra power purchased under the first segment's terms, and PGIPP(ty,ts,td,z,CIPREL2) be the extra power purchased under the second segment's terms, and again assuming the maximum rate of power to be the capacity of the CIPREL plant, then the capacity constraints for the two segments can be written as;

PGIPP(ty,ts,td,th,z,CIPREL1)<=[sumt=1 to ti of YIPP(ty,z,CIPREL]*210 MW

PGIPP(ty,ts,td,th,z,CIPREL2),=[sum t=1 to ti of YIPP(ty,z,CIPREL]*210 MW Thus, until the take or pay contract is signed(until the bracketed term is 1) no power can be purchased from either segment; once the contract is signed (the bracketed term is 1), the rates are limited by the contracted capacities. The energy limits of the two segments aare entered in the same way as in the take or pay portion of the contract. Eg:

Sum [Mseason, Mday, Mhour PGIPP( ty,ts,td,th,z,CIPREL1)]<= 50,000 MWh Sum [Mseason, Mday,Mhour, PGIPP(ty,ts,td,th,z, CIPREL2)]<=(43.334)(8760) = 379,000 MWh

The variable costs of the two segments, $33.961/MWh and $38.943/MWh, are entered into the objective function in the same way as in the take or pay portion of the contract. Note that in this instance, there is no need to require the purchaser to purchase the full 50,000 kWh( utilize the full capacity of 5.708MW) before moving to the second segment, since the second segment's variable cost ($38.943) is higher than the first segment cost,($33.961) and the optimization itself will guarantee that the second, more expensive segment is never used until the first, cheaper segment is fully utilized. The three data forms for CIPREL, CIPREL1, and CIPREL2 are attached in Appendix 3.


Personnel and Workplan The Purdue modeling team consists of: F.T. Sparrow William Masters Brian H. Bowen Frank J. Smardo (consultant) Tarik Aouom The Purdue User Friendly Interface team consists of: Brian H. Bowen

Geoff Granum Deepesh Mohnani Shimon Modi January 2003 Confirmation of 2003 Workplan for WAPP modeling and interface will take place at the ECOWAS Benin meeting. As of time of writing the venue is Cotonou, the capital city of Benue, but from drawing upon past experience it is possible that an alternative West Africa venue will be used. Travel funds for this meeting will come from the 2001 – 2002 budget and it is planned that only Dr. Bowen will be attending to represent the Purdue team. WAPP Year 4, Phase 1

• Testing of the WAPP2003 model, based on ECOWAS Data Set #6, January 2003).

• Development of new financial module for the WAPP model. • Achieve compilation of ECOWAS Data Set #7 with the inclusion of Nigeria data

validation. The testing of the January2003 WAPP model and policy analysis work for 2003 will be the responsibility of Brian Bowen, PhD student Tarik Aouam, and under-graduate student Geoff Granum (Appendix 4 [a]). The new financial module will require gams modeling and detailed attention to the core code of the model. This new modeling module work will be undertaken by Consultant Frank Smardo with guidance from Professor Tom Sparrow (Appendix 4 [b]). Communications with regional modeling operators, in Nigeria, Cote D’Ivoire and Guinea, will be the responsibility of Brian Bowen. The expected compilation of the Data Set # 7, will also be the responsibility of Dr. Bowen (Appendix 4[c]). Advise on the economic needs of the region and the most suitable planning strategies will be provided by Professor William Masters.


WAPP Year 4, Phase 2

• Enhancement to the Interface and beta testing. • Training at technical workshop at Purdue (2 weeks duration). • Create and test the WAPP model using Data Set #7. • Develop WAPP generation capacity expansion plan.

The improvements to the WAPP user-friendly interface will be supervised by Dr. Bowen while the actual java programming will be completed by students Geoff Granum, Shimon Modi, and Deepesh Mohnani (Appendix 4 [d]). The planning and organization of the summer 2003 technical workshop will be a job for Dr. Bowen, in consultation with Prof.. Sparrow. Teaching and instruction at this workshop will also be the responsibility of Prof. Sparrow and Dr. Bowen. Substantial work on the interface, in preparation for this training session, will take place during the summer months by the java programming team. Supervision of the java programmers will be for Dr. Bowen (Appendix 4 [e]). Development of the WAPP expansion plan will be demonstrated using the ECOWAS Data Set # 6. For an effective plan to be made it is expected that once the Data Set # 7 is validated in 2003 then this will be possible. The collection of the new data set and developing the plan will be the main responsibility of Dr. Bowen. Prof. Sparrow will provide expertise in the final stages of this work activity (Appendix 4 [f]). WAPP Year 4, Phase 3

• Sensitivity analysis tests, using the Data Set #7 model. • Collaboration with ECOWAS operators on the analysis of Data Set #7 results.

Employment of the Data Set # 7 will depend on the speed of collection of new data in the first half of 2003. The sensitivity analysis tests will be determined by regional colleagues in consultation with Prof. Sparrow and Dr. Bowen. Testing will be completed by Dr. Bowen and Tarik Aouam. Translation into French will also be provided by Tarik Aouam (Appendix 4 [g]). All communications, emails and phone calls to West African colleagues is a responsibility of Dr. Bowen. The preparation of reports and workshop materials is also to be done by him. (Appendix 4 [h]). January 2004 Provision of training at a regional meeting in West Africa with the updated version of the interface, with several computer users involved, depending on the number of PCs and solver software purchased for the ECOWAS. It is planned that Dr. Bowen will be the main regional technical trainer. It is possible that training will take place at the end of Phase 3, later in 2003. The budget allows for two Purdue staff to travel during the year.


Alternatively it might mean that Dr. Bowen will travel by himself to the region on two occasions. These travel plans are flexible although a limited budget is provided for travel (Appendix 4 [j]). The preparation for presentation of the WAPP generation capacity expansion plan will take place if an adequate validation of the Nigerian and other regional data has been satisfactorily completed by late 2003. At Purdue technical support will be provided by Barbara Gotham throughout the WAPP Year 4 proposal. References [1] Olumuyiwa O. Shokunbi et al, “Reliability and Free Trading in the ECOWAS Electricity Generation Capacity Expansions Plans for 2002 to2012”, ECOWAS Secretariat, Abuja, Nigeria, September 12, 2002. [2] Sidy Kané et al, Thermal Generation & Transmission Capacity Expansion Plans for Zone A of the West Africa Power Pool, WAPP, Société d’Opération Ivoirienne d’Electricité, Abidjan, Côte d’Ivoire, August 23, 2002

[3] Mamadou Alpha Sylla et al, Hydropower Generation & Transmission Capacity Expansion Plans for Zone B of the West Africa Power Pool, WAPP, Electricite de Guinee, Conakry, Guinea, August 23, 2002


Appendix 1

West Africa Power Pool WAPP Workshop

Purdue University

August 12 - August 23, 2002

The Seven WAPP Training Models ~ Summary & Notes

The first week of training involves using the WAPP interface with seven demonstration training models. An outline and description of the models is documented below. In order to understand the output consequences, from making data changes with the user-friendly interface, it is important that the notes below are used in conjunction with the daily computer exercises. Models 1-4, Static Models - Single Period Without Capacity Expansions Model 1 1 period with 1 year in period (Yper =1, n =1) Includes: Existing (old) thermal generation only. Excludes: Trade, reserve margin, new capacity expansion. Vary data values: Upeak, PGOinit, UEcost Output interpretation before & after data changes: Thermal capacity, demand/supply, costs, Model 2 1 period with 1 year in period (Yper =1, n =1) Includes: Existing (old) thermal generation and existing (old) hydropower only. Excludes: Trade, reserve margin, new capacity expansion. Vary data values: Hoinit, HOLF, Wcost, fdrought. Output interpretation before & after data changes: Generation capacity, demand/supply, costs, Model 3 1 period with 1 year in period (Yper =1, n =1) Includes: Existing thermal & existing hydro generation, & reliability constraints. Excludes: Trade, new capacity expansion Vary data values: Resthm, Reshyd, Umcost Output interpretation before & after data changes: Demand/supply, costs.


Model 4 1 period with 1 year in period (Yper =1, n =1) Includes: Trade in both energy and reserves & all above Excludes: Capacity expansion Vary data values: PFOloss, PFOinit Output interpretation before & after data changes: Trade quantities, demand/supply, costs. Models 5-7, Dynamic Models - Multiple Periods With Capacity Expansions Model 5 5 periods with 2 years in period (Yper =5, n =2) Includes: Dynamic modeling with only existing capacity expansion for thermal, hydro & lines. Excludes: Expansion of new capacity expansion, autonomy factors. Vary data values: PGOmax, PFOmax. Output interpretation before & after data changes: Trade quantities, demand/supply, costs. Model 6 5 periods with 2 years in period (Yper =5, n =2) Includes: Construction of new generation and transmission projects. Excludes: Autonomy factors. Vary data values: Addition and/or deletion of new power stations and new lines. Output interpretation before & after data changes: Trade quantities, demand/supply, costs. Model 7 5 periods with 2 years in period (Yper =5, n =2) Includes: Dynamic modeling with autonomy control. Vary data values: AF, ENAF, addition and/or deletion of new power stations and new lines. Output interpretation before & after data changes: Trade quantities, demand/supply, costs. The workshop exercises will be conducted in conjunction with the following WAPP related documents:

• WAPP Data Set #5 (ECOWAS, September 2001) • General Training Manual (Purdue, October 2000) • HV Transmission Networks (World Bank, October 2001) • User Manual for the Long-Term Model, 7th Edition (Purdue,

November 2000)


Appendix 2 Economic and technical data feedback emails from WAPP, in Fall 2002

At 03:28 PM 11/18/2002 +0000, KANE Sidy wrote: Dear Brian, The modeling of CIPREL in three parts looks quite very good and interesting! I just think that the variable fuel costs must not change in my point of view. What do you think about that? Can you please explain me why it must change. I think it must be $32.626/MWh in part 1 as in part 2 and part 3. I'm waiting for your answer. Exciting! And what about Azito? A bientôt, Sidy At 01:34 PM 11/14/2002 +0000, KANE Sidy wrote: Dear Brian, The take or pay contract with CIPREL does not include the fuel cost. It is the same thing with the Azito contract. The contracts with the IPP's are to service their capital costs, their O&M costs, their benefits and every thing but not the fuel costs. The state of Ivory Coast give the fuel (natural Gas) to the IPP to pruduce energy we pay only for this energy. The state of Ivory Coast also have three differents take or pay contracts with three independant natural gas suppliers. And each of these gas suppliers is connected with CIPREL and Azito. So i don't think we must represent the gas suppliers in the model. I suggest that we consider the fuel costs as a variable cost depending on the level of MWh we actually take and it is 32.626 /MWh for CIPREL and $29.080/MWh for Azito at this time. For the IPP's there is no O&M costs because it is include in their remuneration. I am ready to give you any further information. Sincerely, Sidy ------------------------------------------------------------------------------------------------------------ At 11:34 AM 10/28/2002 +0000, you wrote: Dear Brian, As i said during my stay in Purdue, we pay fuel for our IPPs and we also pay for energy delivered by this IPPs: CIPREL and Azito. So we must update the fuel cost like below: Fuel cost == real fuel Cost + Cost of energy delivered - OMO OMO = 1.2 $/MWh for Ciprel; OMO = 9.2 $/MWh for Azito. At the end of september, we have for: Ciprel real fuel Cost: 32.46 $/MWh, Cost of energy delivered: 15.36 $/MWh


So Fuel Cost of CIPREL: 46.62 $/MWh Azito real fuel Cost: 28.93 $/MWh, Cost of energy delivered: 20.69 $/MWh So Fuel Cost of Azito: 40.42 $/MWh Can you tell me which are the countries where the need of updated values of data is necessary at this time? Best wishes Sidy At 09:35 AM 10/29/2002 +0000, you wrote: Dear Brian, Good morning. It seems the questions have started pouring over here, so here’s another one. In the Training Manual (Oct 30, Data Set#5 CD), there is a sub heading under Section 6: titled: Implications of Model Structure on Data: 1.Fixed O&M ($/kW/yr) should be considered only for new plants; they are sunk costs for existing plants (unless plants mothballed). Q.Why should O&M not be considered for old plants as the expenditure keeps going on throughout the life of the plant? Or does the sunk cost take into account the ongoing O&M costs on old plants. 2. Demands (D(z,t,y)) should be sent out demands, not received demands. Q. By received demands does that mean demand served at the consumer end? In that case sent out demand will then be what it is sent out as in the preceding bullet of the same document. On the model I was just wondering what would happen if there was an inclusion of entirely new projects not in the database already. I will let you know when I’ll be trying out these new projects in the model (gather all the data I’ll be assuming concerning the project), then we can compare the results, I guess I will take your advice and hold on till I get the NEPA data. Incidentally I have a meeting set up for tomorrow with one of the planning managers. Thanks for the help Brian, Take care, Muyiwa


At 03:55 PM 11/18/2002 +0000, you wrote: Hi Brian, I couldn't go to NEPA anymore, instead had a discussion with the guy in charge of data collection for this project, and he say's that some of the guys in the other departments that were supposed to get the data for him were not ready so I should wait till Wednesday that He's sure to have quite an amount for me then. So we wait. I also want to ask you this; In the MODEL while changing some country parameters I discovered that the autonomy factors can be changed per period ( this I think is good for sensitivity analysis), but does this reflect in the model or is this one of the user interface questions that we've got to resolve? If not, then how does the model compute this considering that the autonomy factors can be changed in periodic intervals of 1yr while the model works with 2yr intervals. Thanks expect your reply later. Muyiwa


Appendix 3a

Electricity -Thermal IPP Contract

Country: Cote D’Ivoire Station Name: CIPREL Contract – Take or Pay Station Type: …………………………… Operating Status: ……………………….. Number of Units: ………………. Load type: ……………………………….

Parameter Description Value Parameter

Fixed costs per year of contract ($) 24.273 e6 FGIPP Maximum rate of delivery (MW) 210.0 PGNIPP

Forced/ unplanned outage rate (%) 0 FORNIPP

Unforced / planned outage rate (%) 0 UFORNIPP

Capital recovery factor for IPP contract (fraction/year) 1 crfIPP

Variable O&M cost ($/MWh) 0 OMIPP

Fixed O&M cost ($/MW/year) 0 FixOMIPP

Heat rate 106 BTU’s/MWh 1 HRNIPP

Fuel cost of new combined cycle station ($/MWh) 32.626 FpNIPP

This contract will start AT period ty 0 AtIPP

This contract WILL start BEFORE or AT period ty 0 BefIPP

This contract will start AFTER period ty 0 AftIPP

Fixed MWh of Take or Pay (MWh/Year) 1.41 e6 FixMWhIPP

Expected length of contract (years) 20

Starting year of contract 2002


Appendix 3b


Country: Cote D’Ivoire Station Name: CIPREL Contract – Variable Cost, Segment 1 Station Type: …………………………… Operating Status: ……………………….. Number of Units: ………………. Load type: ……………………………….

Parameter Description Value Parameter

Fixed costs per year of contract ($) 0 FGIPP Maximum rate of delivery (MW) 210.0 PGNIPP















Appendix 3c


Country: Cote D’Ivoire Station Name: CIPREL Contract – Extra MWh, Segment 2 Station Type: …………………………… Operating Status: ……………………….. Number of Units: ………………. Load type: ……………………………….

Parameter Description

Value Parameter

Fixed costs per year of contract ($) 0 FGIPP Maximum rate of delivery (MW) 210.0 PGNIPP














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