OSemosys user manual
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1. The parameter InputActivityRatio r t f m y gives the rate of input use of fuel for a technology as a ratio to the rate of activity Commonly it is advisable to define the InputActivityRatio as the inverse efficiency n of the technology and set the OutputActivityRatio described later in this document equal to one Like this the rate of activity of a technology equals the output of a technology E g if a power plant is active at 87 MW it produces 87 MWh per hour while consuming 87 MWh n tof input fuel per hour Further all cost parameters which are related to the rate of activity of a technology then refer to the output of the technology This makes sense for all power plants as e g capacity costs are commonly given per unit of output However the capacity of refineries may be measured in terms of barrels of crude oil processed per day i e per fuel input In such cases it is preferable to set the InputActivityRatio equal to one and enter the efficiency in the OutputActivityRatio Like this the activity of the refinery equals the input to this technology E g if the oil refinery is active at a certain level this level corresponds to the amount of input fuel processed to produce this level times n of output fuel e g gasoline Further all cost parameters are then related to this fuel input i e the barrels of crude oil processed using the units of energy chosen upfront for all technologies by the analyst e g PJ2. Output When glpsol runs successfully it prints a status line Each line will look similar to the following 4 objval 1 563750000e 002 infeas 0 000000000e 000 0 means that a basic feasible solution has been found 4 means that there have been 4 iterations to find a solution so far objval shows the current objective value and infeas shows the amount of infeasibility When a feasible solution has been found its value will be either O or a very small number For more information on this please read this the documentation on GNU Linear Programming from Rodrigo Ceron Ferreira de Castro here http www osemosys org uploads 1 8 5 0 18504136 ceron 2006 the gnu linear programming kit part 1 introduction to linear optimization pdf Solution To see the full solution use a text editor to open results txt For example Notepad or Notepad see Section 3 6 on Supportive Programmer and Documentation Recall that the solution file will be found in the directory GnuWin32 bin The summary solution file for OSeMOSYS is a comma separated file called SelectedResults csv A csv file is conveniently opened in a spreadsheet and by using the comma option when asked how data is delineated The selected results file produces tables of the following outputs The units indicated are specific to the UTOPIA example Other units may be defined by the user when setting up a new data file Total emissions by type and reg
3. Alternatively LEAP has also proven useful to write an OSeMOSYS data file HOW TO USE LEAP TO OPTIMISE THE ELECTRICITY SYSTEM LEAP the Long range Energy Alternatives Planning System is a widely used medium to long term modelling tool for integrated resource planning It is applied to assess climate change mitigation strategies and analyse energy policies by investigating yearly capacity expansions The underlying dispatch of technologies is calculated for each user define time slice within a year LEAP is a simulation tool but uses OSeMOSYS for the optimisation of power system investments It is well documented free for developing countries and online support is provided by Stockholm Environment Institute www energycommunity org In LEAP it is possible to optimise the LEAP branch Transformation Electric Generation using OSeMOSYS To do this follow the exercise 6 5 in the LEAP Training Exercises found here http www energycommunity org documents LEAPTrainingExerciseEnglish2014 pdf HOW TO USE LEAP TO WRITE A DATA FILE WHICH CAN THEN BE MODIFIED IN NOTEPAD When developing the model according to exercise 6 5 and run the optimisation in LEAP the data file that is used for the OSeMOSYS optimisation within LEAP will be saved in your LEAP folder under the name OpData L Debug Text Document 4KB nxtrans cfg CFG File 1KB OpData13 Text Document 49 KB OpDatal5 ext Document 49 KB L OpResults13 ext Docum
4. The InputActivityRatio is defined by year as the efficiency of the technology could degrade technology fuel produced the mode of operation and region Care needs to be taken to enter this matrix correctly because of its multi dimensional form It is suggested that for each fuel and mode of operation a two dimensional matrix with years in the columns and technologies in the rows be constructed EXAMPLE INPUTACTIVITYRATIO param InputActivityRatio default O UTOPIA DSL 1 1990 1991 1992 1993 1994 E70 3 4 3 4 3 4 3 4 3 4 RHO 1 428571429 1 428571429 1 428571429 1 428571429 1 428571429 TXD 1 1 1 1 1 UTOPIA ELC 1 1990 1991 1992 1993 1994 RHE 1 1 1 1 1 RL1 1 1 1 1 1 14 TXE 1 1 1 1 1 The parameter OutputActivityRatioly t f m r gives the rate of output of fuel as a ratio to the rate of activity in which a technology is operating Please bear in mind that the InputActivityRatio and OutputActivityRatio are connected and it is preferable to place the inverse efficiency n at the InputActivityRatio and keep the OutputActivityRatio at 1 for power production It is defined by year as the efficiency of the technology could degrade technology fuel produced technology mode of operation as well as by region Care needs to be taken to enter this matrix correctly because of its multi dimensional form It is suggested that for each fuel and mode of operation a two dimensional matrix with years in the columns and technolo
5. so that the limit is effectively not enforced The unit of the parameter is the unit that is used to measure 18 the respective technologies capacity in the model The parameter is a matrix with the years as the columns and technologies in the rows EXAMPLE OF TOTALANNUALMINCAPACITYINVESTMENT param TotalAnnualMinCapacitylnvestment default 0 4 6 3 ACTIVITY LIMITS It may be the case that there is an annual limit to the rate of activity summed up over all modes of operation i e the total amount a technology could produce each year If that is the case the TotalTechnologyAnnualActivityUpperLimit r t y parameter should be used The default value of this parameter is high so that it is usually not enforced The unit of the parameter is the unit that is used to measure the respective technology s rate of activity in the model The parameter is a matrix with the years as the columns and technologies in the rows EXAMPLE OF TOTALTECHNOLOGYANNUALACTIVITYUPPERLIMIT param TotalTechnologyAnnualActivityUpperLimit default 99999 It may be the case that there is minimum rate of activity that a technology considering the sum of all modes of operation must produce each year If that is the case the TotalTechnologyAnnualActivityLowerLimit r t y parameter should be invoked The default value of this parameter is zero so that it is effectively not enforced The unit of the parameter is the unit that is used to measure the respective
6. 1 EO1 E21 E31 E51 E70 RHE RHO UTOPIA 40 40 100 100 40 30 The actual output of a technology in OSeMOSYS is calculated as the capacity factor in each time slice summed up over a year with is then multiplied by the availability factor E g if a technology has a capacity factor which is zero in five timeslices and one in five other timeslices and an availability factor of 0 9 it could only produce 5096 times 0 9 4596 of its total capacity throughout the year Yet if the availability factor would represent maintenance work one would schedule this maintenance work rather in those timeslices where the technology is not producing resulting in a yearly output of 5096 instead of 4596 17 4 6 2 CAPACITY LIMITS If the sum of all technology investments are allowed up to a maximum total residual i e historic and total new capacity each year of the modelling period the limiting capacity level is included in the TotalAnnualMaxCapacity r t y parameter The default value for all technologies is a high number so that the limit is usually not enforced The unit of the parameter is the unit that is used to measure the respective technologies capacity in the model The parameter is a matrix with the years as the columns and technologies as the rows index EXAMPLE OF TOTALANNUALMAXCAPACITY param TotalAnnualMaxCapacity default 99999 UTOPIA 1990 1991 1992 1993 1994 E31 0 1301 0 1401 0 1401 0 1501 0 1501 E51 3 3 3 3 3 If a
7. It should however not be used for modelling an electricity demand as electricity has to be supplied instantly when a demand occurs Demands for energy carriers i e fuels such as electricity should rather be modelled as a specified annual demand which has a specific demand profile during the year that must be satisfied The units are set by the user However note that these should be consistent for all demands A suggested unit for a national model is PJ a The AccumulatedAnnualDemand r f y parameter is entered as a matrix which can be specified for any fuel A default demand is set to zero so no annual demand is given to fuels not listed in the matrix Model YEARs are in the column index and FUELs in the rows This matrix is repeated for each REGION modelled EXAMPLE ACCUMULATEDANNUALDEMAND param AccumulatedAnnualDemand default 0 UTOPIA 1990 1991 1992 1993 1994 TX 5 2 5 46 5 72 5 98 6 24 There are demands for which time of use is necessarily specified during the year These are included in the SpecifiedAnnualDemandlr f y parameter As the name implies this parameter contains the total specified demand for the year This is distributed by timeslice with the next parameter The parameter is entered as a matrix which can be specified for each fuel energy service demand A default demand is set to zero so no specified demand is given to fuels not listed in the matrix Model YEARS are in the row index and FUELs in the colum
8. defined by year technology emission as well as by the technologies mode of operation Care needs to be taken to enter this matrix correctly due to its multi dimensional form The units are the units of the emissions per unit of energy e g kton per PJ As this value is multiplied by the rate of activity it is important to be aware if the rate of activity equals the input fuel consumed or the output fuel consumes i e which of these values has been set to one when defining the InputActivityRatio and OutputActivityRatio EXAMPLE OF EMISSIONACTIVITYRATIO param EmissionActivityRatio default O UTOPIA CO2 1 1990 1991 1992 1993 1994 IMPDSL1 0 075 0 075 0 075 0 075 0 075 IMPGSL1 0 075 0 075 0 075 0 075 0 075 An EmissionsPenalty r e y is defined for each region emission and year It is represented as a matrix with model years as the columns and emissions as rows It is measures in the units of costs per unit of activity e g Million EUR PJ EXAMPLE OF EMISSIONSPENALTY param EmissionsPenalty UTOPIA 1990 1991 1992 1993 1994 CO2 0 0 0 0 0 If there are emissions that need to be accounted for but are not calculated by the model on an annual basis they can be included as annual exogenous emissions for each year and region in the parameter AnnualExogenousEmission r e y The parameter is entered as a matrix with model years as columns and emissions in emissions units in the rows EXAMPLE OF ANNUALEXOGENOUSEMIS
9. file is structured to compile an energy model in OSeMOSYS For easy reference it is set out in the same structure and order as the inputs are specified in the OSeMOSYS code It is also written in an informal style with comments aimed at helping the new user to become more familiar with the system It is up to the analyst to use a consistent set of units as pointed out in Section 3 5 4 1 SETS First off the model sets need to be defined These are the elements that will be modelled Mathematically they represent the indices within the equations of the model constraints l e the constraints are formulated for all combinations of all or a selection of the sets outlined below These include e The EMISSION to be accounted for These are indexed in the mathematical formulations by the letter e e The TECHNOLOGYs modelled Note that this includes any element of the energy system which generates a fuel e g a coal mine or a wind farm converts one energy form into another e g a coal fired power plant or consumes a fuel e g an air conditioner Technologies are indexed by the letter t e The FUELS used Energy carriers fuels required in the model have to be produced by a technology Energy carriers fuels are only produced if they are going to be consumed or if they feed a final demand Also demands for energy services are defined as fuels in OSeMOSYS e g a heating demand would be defined as a fuel All fuels are indexed by
10. for each REGION FUEL YEAR By default it is defined to be zero l e if an accumulated annual demand would not be listed for a fuel in the matrix below it would be zero for this fuel The first is in the position of the set FUEL which is therefore defined in the row of the matrix TX stands for transport fuel The second is in the position of the set YEAR which are therefore listed in the columns The region entered is UTOPIA which is the only region in this case If there were several regions simply one region would be defined after another in several such matrices Only the last data entry of the last matrix will be followed by the which is always required to indicate the end of a parameter definition param AccumulatedAnnualDemand default 0 UTOPIA 1990 1991 1992 1993 1994 TX 5 2 5 46 5 72 5 98 6 24 Please note that in the two background papers by Howells M et al 2011 and Welsch M et al 2012 the parameters are indexed differently to the current version of the OSeMOSYS input file Please refer to the Change log on www osemosys org for further background on this switch of indices 4 4 GLOBAL PARAMETERS The first type of parameters are Global in that they define the global aspects of the model framework The parameter YearSplit l y is a matrix which measures the duration of a modelled time slice as a fraction of the year Model years defined in the SETs are in columns and timeslices defi
11. technologies activity in the model The parameter is a matrix with the years as columns and technologies in the rows EXAMPLE OF TOTALTECHNOLOGYANNUALACTIVITYLOWERLIMIT param TotalTechnologyAnnualActivityLowerLimit default 0 z Should there be a maximum level of activity by a technology summed over all modes of activity over the whole model period the parameter TotalTechnologyModelPeriodActivityUpperLimit r t y should be used The default value of this parameter is high so that it is usually not enforced The unit of the parameter is the unit that is used to measure the respective technologies activity in the model EXAMPLE OF TOTALTECHNOLOGYMODELPERIODACTIVITYUPPERLIMIT param TotalTechnologyModelPeriodActivityUpperLimit default 99999 Should there be a minimum level of activity summed over all modes of activity to be enforced by a technology over the whole model period the parameter TotalTechnologyModelPeriodActivityLowerLimit r t should be used The default value of this parameter is zero so that it is effectively not enforced The unit of the parameter is the unit that is used to measure the respective technologies activity in the model EXAMPLE OF TOTALTECHNOLOGYMODELPERIODACTIVITYLOWERLIMIT param TotalTechnologyModelPeriodActivityLowerLimit default 0 2 19 4 7 EMISSIONS The parameter EmissionActivityRatio r t e m y gives the emission levels per quantity fuel of a particular mode of activity for a technology It is
12. Ctrl F and take a step by step approach both in the 26 input file and OSeMOSYS code to identify if the issue is in one of these constraints to get a feasible solution One option is for example to write a hash before one or several of these constraints thus commenting them out If the model then solves successfully it is clear that these constraints potentially in combination with others where the reason for the previous infeasibility and adjustments in the data file are necessary These could involve correcting incorrectly entered input data or raising the maximum limits defined in the data file Of course the commented out constraints would have to be activated again in the corrected model by removing the hash sign 6 ADVANCED USES OF OSEMOSYS 6 1 USING OSEMOSYS WITH CPLEX CPLEX is a commercial solver that is more powerful than the freely available GLPK solver It is freely available for use by universities and in non commercial projects Especially when models get very complex GLPK might solve very slowly In these cases other solvers such as CPLEX or GUROBI might be valuable alternatives Below there is a quick summary of how to run OSeMOSYS using CPLEX 1 Inorder to use CPLEX the OSeMOSYS model and data files first need to be combined into a single lp file To do this open the command prompt and use the following command glpsol m OSeMOSYS model file d Data file wlp Input Filename lp 2 After the lp f
13. ISSION CO2 NOX TECHNOLOGY E01 E21 E31 E51 E70 IMPDSL1 IMPGSL1 IMPHCO1 IMPOIL1 IMPURN1 RHE RHO RL1 SRE TXD TXE TXG RIV RHu RLu TXu FUEL CSV DSL ELC GSL HCO HYD LTH OIL URN RH RL TX YEAR 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 TIMESLICE ID IN SD SN WD WN MODE OF OPERATION 1 2 REGION UTOPIA SEASON 1 2 3 set DAYTYPE 1 set DAILYTIMEBRACKET 1 2 set STORAGE DAM 4 2 PARAMETERS The parameters are entered next They are the input values defined for certain combinations of sets as outlined before All parameters must be defined to be able to calculate the resulting variables Variables constitute the output values from the model run 4 3 SYNTAX FOR THE PARAMETERS All parameters are entered in the form of a matrix some of which have several dimensions One default value can be defined for all elements of one specific parameter If an element is explicitly assigned a diverging value in the matrix defining a parameter this diverging value will replace the default value When specifying a matrix ax with more than two dimensions using a instead of an element of a set will indicate which set is listed in the column first when listing the sets and which set is listed in the row second when listing the sets For example the parameter AccumulatedAnnualDemandlr f y listed below is defined by the sets r f y i e
14. Royal Institute of Technology din of rx E KTH Division of EER i Ende Energy Systems Analysis x Working Paper Series DESA 15 11 2015 OSeMOSYS User Manual November 2015 Nandi Moksnes Manuel Welsch Francesco Gardumi Abhishek Shivakumar Oliver Broad Mark Howells Constantinos Taliotis Vignesh Sridharan Please send all comments and feedback you may have regarding this manual through www osemosys org or to osemosys gmail com This will help us update and improve it 1 KTH Royal Institute of Technology Stockholm Sweden Politecnico di Milano Milan Italy KTH Royal Institute of Technology Stockholm Sweden Table of content 1 2 3 7 PUrpOS6Q 2 2 22 5 22 2 EE EE ORE EE EE OE OE EE EE RE 1 Introd ction to OSEMOSYS ER EE EE RR br De eU ee RE De EE ED ee RR GER Ge Ee 1 Getting started With OSEM O S G sis or e rere rU eer e ee Eg Senses REIR de Reg Pe eds ee 2 3 1 Aifirst mode Fn ia Sees chase AE ER EE e EOM E ER OER ee ER OE RE EE 2 3 2 Use of the full or the short version of OSeMOSYS esse ee ee ee ee ee ee ee Re Age ee enne enne en nnne en 4 3 3 Mapping the reference energy SYSteM iese se se ee ee Ge Ge ER AA Ge Ge RR ee AG Ee ee ee nins ee natia ee ee ee ee 4 3 4 Creatine TETTE RTT SE EG Ee Be Eie a Ee ee ee ee n see ee GE ee ee Re ee GER 5 3 5 Dataafid Choice Of Ullts o ER GER cents rr EI GE EE rne EE Ee ged eke EE Ee Pe Gee ge Pe ke oen Eer ep Ee 6 3 6 Su
15. SION param AnnualExogenousEmission default 0 z The sum of all emissions from the energy system being modelled plus any annual exogenous emissions can be limited using the AnnualEmissionLimit r e y parameter It is entered as a matrix with model years as the columns and emissions in emissions units in the rows EXAMPLE OF ANNUALEMISSIONLIMIT param AnnualEmissionLimit default 9999 20 If there are emissions that need to be accounted for but are not calculated by the model over the entire model period they can be included as annual exogenous emissions for each year and region in the parameter ModelPeriodExogenousEmission r e The parameter is entered as a matrix with exogenous emissions as the columns and regions in the rows EXAMPLE OF MODELPERIODEXOGENOUSEMISSION param ModelPeriodExogenousEmission default 0 z The sum of emissions from the energy system modelled over the model period plus any annual or model period exogenous emissions may be limited using the parameter ModelPeriodEmissionLimit r e The parameter is entered as a matrix with emissions in emissions units as the columns and regions in the rows EXAMPLE OF MODELPERIODEMISSIONLIMIT param ModelPeriodEmissionLimit default 9999 E 4 8 RESERVE MARGIN Fuel s that require a reserve margin are given a value of 1 in the ReserveMarginTagFuellr f y parameter The default otherwise is zero The parameter is a matrix with the years in the columns and fuel
16. SYS For illustrative purposes the demonstrations in this paper refer to a consistent sample dataset called UTOPIA The version referred to in this manual is OSeMOSYS 2013 05 10 The paper describes how to get started with OSeMOSYS using LEAP for modelling with OSeMOSYS mapping the reference system choice of units and data collection and parameter descriptions with examples from UTOPIA There is also some tips for debugging the model if there is no feasible solution to the model Quite some of the descriptions have been compiled from the following two publications which are therefore not referenced throughout this document whenever language is taken from them e OSeMOSYS The Open Source Energy Modeling System An introduction to its ethos structure and development by M Howells et al in 2011 e Modelling elements of Smart Grids Enhancing the OSeMOSYS Open Source Energy Modelling System code by Welsch M et al in 2012 2 INTRODUCTION TO OSEMOSYS At present there exists a useful but limited set of accessible energy system models These tools often require significant investment in terms of human resources training and software purchases in order to apply or further develop them Unlike long established energy systems partial equilibrium models OSeMOSYS potentially requires a less significant learning curve and time commitment to build and operate Additionally by not using proprietary software or commercial programmin
17. and several other modelling frameworks it is not calculated automatically based on historical investments and a lifetime associated with those investments Therefore this needs to be calculated outside of OSeMOSYS manually and added to the ResidualCapacity parameter l e the value for a technology should decrease over time as historic capacity is retired Model years are given in the column index and the technologies in the rows The units are in capacity EXAMPLE OF RESIDUALCAPACITY param ResidualCapacity default 0 UTOPIA i 1990 1991 1992 1993 1994 EO1 0 5 0 5 0 5 0 4 0 4 E21 0 0 0 0 0 The AvailabilityFactor r t y parameter is defined for each model region technology and year It is often used to simulate planned outages and indicates the maximum time a technology may run for the whole year The model will then decide by itself in which timeslices the output will be reduced if the value given is lower than 1 which constitutes its default value E g if there would be ten timeslices a constant capacity factor and an 16 availability factor of 0 9 the model may choose to operate the technology up to is capacity factor in all but one timeslice in which the technology will not produce anything Alternatively it may choose to operate it in all but two timeslices in which the technology only produces half of what the capacity factor would allow It is not recommended to combine an availability factor smaller then 1 with capacity
18. are to ensure that this is consistent with the discount rate used 15 Not all technologies as represented in OSeMOSYS may incur a capacity cost E g a technology may represent the sun and its availability which is then used by other technologies like solar panels The default value is therefore zero It is suggested that data is entered two dimensional matrix with model years in the columns and technologies in the rows The units are in currency per unit of installed capacity EXAMPLE CAPITALCOST param CapitalCost default O UTOPIA 1990 1991 1992 1993 1994 E01 1400 1390 1380 1370 1360 E21 5000 5000 5000 5000 5000 The VariableCost r t m y is defined for each year technology mode of operation and region It is the cost per unit of activity for a given mode of operation of that technology As not all technologies as represented in OSeMOSYS incur a variable cost this is set to zero by default It is suggested that the data be entered as a two dimensional matrix for each mode of operation that the technology has In this form model years are the column index and the technologies in the rows EXAMPLE OF VARIABLECOST param VariableCost default O UTOPIA 1 1990 1991 1992 1993 1994 E01 0 3 0 3 0 3 0 3 0 3 E21 1 5 1 5 1 5 1 5 1 5 ResidualCapacity r t y is entered for each model year technology and each region It is the capacity left over from a period prior to the modelling period Unlike MESSAGE LEAP
19. arginTagTechnology default 0 z UTOPIA 1990 1991 1992 1993 1994 EO1 1 1 1 1 1 E21 1 1 1 1 1 4 9 STORAGE How to model storage in OSeMOSYS is best described in Welsch M et al in 2012 The following just provides a brief outline how to provide unlimited storage in the model which corresponds to the UTOPIA case applied in this illustration If there is no need to consider storage simply do not link any technology to the storage site by setting the TechnologyToStorage and TechnologyFromStorage equal to zero Unlike in a more basic data file set up chronological information is required when modelling storage levels If storage is used then each time slice needs to be assigned to a season day type and daily time bracket as defined in the following three parameters The parameter Conversionls l Is is set equal to 1 to assign a particular time slice to a season Set it equal to 0 in order not to assign a particular time slice to a season The parameter is a matrix with the season as columns and timeslice in the rows In the example below for example the third and fourth timeslices SD Summer Day and SN Summer Night are combined in one season called 3 EXAMPLE CONVERSIONLS param Conversionls default 0 1 2 3 ID 0 1 0 IN 0 1 0 SD 0 0 1 SN 0 0 1 WD 1 0 0 WN 1 0 0 The parameter Conversionld I Id s set equal to 1 to assign a particular time slice to a day type Set it equal to 0 in order not to assig
20. at certain default constraint levels e g the total max capacity are set to values such as 999999 This limits can be violated if the choice of unit is too small like kW for a large system for which GW are recommendable Possible choice of unit Energy GWh MWh PJ GJ etc Power GW MW etc Cost Million Million Million Euro etc Emissions Mton There is no unit conversion in OSeMOSYS the modelling system assumes that all units are consistent For example the unit for capital costs needs to be coherent with the choice of units from the above table and is applied for all parameters relating to costs E g when choosing GW and as power and monetary units respectively the Capital cost has to be defined in GW Similarly if the energy unit is PJ for the demand then it also needs to be chosen for all other parameters activity generation output related parameters This is particularly important for the parameter CapacityToActivityUnit see p 11 2 3 3 6 SUPPORTIVE PROGRAMMES AND DOCUMENTATION The installation of Notepad is recommended to work with and edit the model and data files It can be downloaded here 5 The following three files are recommended if more background on the basics of GnuMathProg and the linear optimisation logic applied in OSeMOSYS are of interest 1 http www osemosys org uploads 1 8 5 0 18504136 ceron 2006 the gnu linear programming kit part 1 introduction to li
21. dualCapacity eese ResidualStorageCapacity esesssss EE TUS NE tereti nte otro ERI E Eee Pee RETagTechnology eene SpecifiedAnnualDemand ee ee SpecifiedDemandProfile ee se se ee Ee ee StoragelevelStart iss sees esse se StorageMaxChargeRate StorageMaxDischargeRate TechnologyFromstorage ees ss see ee ee ee ee TechnologyToStorage ees se se ee ee TechWithCapacityNeededToMeetPeakTS 13 TotalAnnualMaxCapacity iese sesse se ee ee 17 TotalAnnualMaxCapacityInvestment 18 TotalAnnualMinCapacity eeeeeseess 18 TotalAnnualMinCapacitylnvestment 18 TotalTechnologyAnnualActivityLowerLimit 19 TotalTechnologyAnnualActivityUpperLimit 18 TotalTechnologyModelPeriodActivityLowerLimit 19 TotalTechnologyModelPeriodActivityUpperLimit 19 VariableCost Mel RR ert eee Res 1 PURPOSE The purpose of this paper is to help new OSeMOSYS users to understand how to set up an OSeMOSYS model from scratch defining the model parameters in text files However this manual is also useful for users applying one of the OSeMOSYS interfaces that are currently being developed This is because of its description of how to set up and debug an OSeMOSYS model and the definition of the various input parameters used in OSeMO
22. e advantage that only one region has to be defined and thus all equations are only defined for one region Defining e g two regions would roughly double the amount of equations in the model and thus also the computational burden Regions are indexed by the letter r The STORAGE set contains the storage facilities This is indexed by the letter s The SEASONS are indexed as Is DAYTYPEs as Id and DAILYTIMEBRACKETs as Ih and are all connected to the TIMESLICE I They are only required if storage will be used in the model Note that these three sets need to be defined as numerical consecutive values e g 1 2 3 Conversion factors are used when modelling storage to attribute each time slice to a specific season day type and daily time bracket refer to Section 4 9 Seasons occur within a year and day types within a week e g weekdays and weekends Daily time brackets define the number of brackets that the days is divided in e g one hour or mornings afternoons and evenings If no storage is modelled it is sufficient to define each of these three sets with one numerical element e g 1 EXAMPLE SETS FROM UTOPIA Below are the sets defined in the sample file UTOPIA Note that abbreviations are used e g for emissions technologies and fuels However any other name could be used to describe those as long as they are consistently used throughout the model set set set set set set set set EM
23. e ee ee ER ee AA GE Ge airaa siis inni tensa asses satira daas ee ee ee 27 6 2 Modifications enhancements additions to the main code ee ee ee ee ee ee ee ee ee nennen 28 ide ASE EE N EE EE EE EE OO R ERE 28 Index for parameters AccumulatedAnnualDemand AnnualEmissionLimit esee AnnualExogenousEmission ssesss AvailabilityFactor eeeeeeseeeeeenee enne CapacityFactor ss ss se ee eene eene enne ee CapacityToActivityUnit eee CapitalCOoSt oie roh ri Ere eh CapitalCostStorage see ees ee se ee ee ee ee ee ConVversionld Re EE erdt Conversionlh Conversionls DayslInDayType DaySpllt LS ere eti dr ehe Een e ie des DiscountRate iss ses koes se ee nennen DiscountRateStOrage ees ese ee ee RR Re ke Re Re ke EmissionActivityRatio ee ee ke ke Ne Re ke EmissionsPenalty sesse ees se Ee ee ee ee ek dele RE EE EE aii InputActivityRatio iese ee ee ee ee Re ee Ne ke Ne Re ee MinStorageCharge se se ee ee ee ModelPeriodEmissionLimit esse ee se ee ee ModelPeriodExogenousEmission OperationalLite ees OperationalLifeStorage OutputActivityRatio REMinProductionTarget ReserveMargin eee ReserveMarginTagFuel ReserveMarginTagTechnology Resi
24. e rows index It is repeated for each region EXAMPLE OF RETAGTECHNOLOGY param RETagTechnology default 0 z Similarly the fuels in each region for which there is a renewable target are tagged using the RETagFuel r f y parameter EXAMPLE OF RETAGFUEL param RETagFuel default 0 2 The REMinProductionTarget r y parameter indicates how much of the fuels tagged in the RETagFuel parameter must come from RE technologies that were tagged with the RETechnologyly tr parameter A value of 0 indicates that there is no RE target The target is specified for each year in the units of energy EXAMPLE OF REMINPRODUCTIONTARGET param REMinProductionTarget default 0 25 5 DEBUGGING THE MODEL 5 1 ADDING A DUMMY TECHNOLOGY There can be several reasons why a model has no feasible solution One way of finding where the errors might be located is to add a dummy technology which is not originally part of the model that has high capacity and or a very high variable cost and to make things simple no input fuel This ensures that the model only uses the dummy technology when no other option remains To debug a model therefore define a single dummy technology and run the model to see if there is now a solution and start as close to the demand as possible referred to as 1 in the below figure If the model now runs successfully check the results file and check when the dummy technology is used e g only in certain time slices On
25. ent 16 KB L OpResults15 ext Document 16 KB E OSEMOSYS Windows Batch File 1KB 4 E D t Lj OSeMOSYS ext Document 37 KB Documents _ packedok ext Document 1KB d Anpassade Office mallar report Configuration sett 19 KB d Bluetooth Folder Resultsindex ext Document 6 KB d C ROADS v3 Results S2R1 VLC media file bi 25 KB a M LEAP2011 Areas Results S4R1 VLC media file bi 25KB amp Results S6R1 VLC media file bi 25 KB Backup ELLE EE s amp Results S9R1 VLC media file bi 25 KB x Results S13R1 VLC media file bi 27 KB Jo LEAP Settings A Pictures 4 Results S15R1 VLC media file bi 27 KB Scripts L SelectedResults13 Text Document 407 KB SelectedResults15 17 14 11 Text Document 407 KB 4 Work pum i LJ sysinfo 2015 08 20 09 15 Text Document 2 KB di Area 1 Figure 2 LEAP model file in Area 1 The OpData OSeMOSYS data file can then be opened in NotePad edited and used further within OSeMOSYS Using LEAP to set up an OSeMOSYS data file ensures that the OSeMOSYS data file is set up correctly thus making it easier to build the remaining RES for further optimisation in OSeMOSYS This may for example be useful to optimise other non electricity sectors such as transport or heat as this is currently not possible within LEAP Further if new equations should be added to an updated OSeMOSYS version that is therefore not supported by LEAP it may as well be useful to take the LEAP data file as a sta
26. factors varying over the year Model years are given in the columns and technologies in the rows EXAMPLE OF AVAILABILITYFACTOR param AvailabilityFactor default 1 UTOPIA 1990 1991 1992 1993 1994 RHE 1 1 1 1 1 RHO 1 1 1 1 1 The CapacityFactorlr t l y is defined for each region technology timeslice and year It is used to convert annual capacity to the capacity available for each timeslice i e the actual energy output vs the potential energy output at the maximum capacity of a technology By default it is given the value 1 meaning that all of the capacity is available for each timeslice Model years are given in columns and the timeslice in the rows This is repeated for each technology Only technologies for which there is a capacity factor to mimic forced outage or to de rate them e g to model wind availabilities in different times of the year need explicitly be included If a PV panel should be modelled then the daytime capacity factor could be 0 4 during the day and 0 during the night time with an average of 0 2 over the year EXAMPLE OF CAPACITYFACTOR param CapacityFactor default 1 5 UTOPIA E01 1990 1991 1992 1993 1994 ID 0 8 0 8 0 8 0 8 0 8 IN 0 8 0 8 0 8 0 8 0 8 Each technology is given a limited operational lifespan This is included in the OperationalLife r t presented as a matrix with technologies in columns and regions in rows EXAMPLE OF OPERATIONALLIFE param OperationalLife default
27. g languages and solvers OSeMOSYS requires no upfront financial investment OSeMOSYS is designed as a tool to inform the development of local national and multi regional energy strategies It covers all or individual energy sectors including heat electricity and transport It is a deterministic linear optimisation model and minimises the total discounted costs Mixed integer programming may be applied for certain functions like the optimisation of discrete power plant capacity expansions The model is driven by exogenously defined demands for energy services These can be met through a range of technologies which draw on a set of resources defined by their potentials and costs On top of this policy scenarios may impose certain technical constraints economic realities or environmental targets As in most long term optimisation models OSeMOSYS in its standard configuration assumes perfect foresight and perfect competition on energy markets The model is characterised by a wide and flexible technology definition A technology comprises any fuel use and conversion from resource extraction and processing to generation transmission and distribution and appliances It could therefore refer to for example an oil refinery a hydropower plant or a heating system A technology can be defined to consume and produce any combination of fuels Each technology is characterised by numerous economic technical and environmental parameters for example invest
28. gies in the rows be constructed Note also that if the variable and capacity cost parameters are being entered in terms of the technology s output then the OutputActivityRatio should be given the value 1 The latter representation is useful for power stations who s capacity is reported in terms of electricity power output EXAMPLE OUTPUTACTIVITYRATIO param OutputActivityRatio default 0 UTOPIA RH 1 1990 1991 1992 1993 1994 RHE 1 1 1 1 1 RHO 1 1 1 1 1 RHu 1 1 1 1 1 UTOPIA RL 1 1990 1991 1992 1993 1994 RL1 1 1 1 1 1 RLu 1 1 1 1 1 The fixed cost parameter FixedCost r t y is defined for each year each technology and each region It is the cost per unit of capacity of that technology As not all technologies as represented in OSEMOSYS incur a fixed cost this is left as zero by default It is represented as a matrix with model years as the column index and the technologies as row index The unit is currency per unit of capacity EXAMPLE OF FIXEDCOST param FixedCost default 0 z UTOPIA 1990 1991 1992 1993 1994 EO1 40 40 40 40 40 E21 500 500 500 500 500 The CapitalCost r t y of each technology is given as a function of the technology as well as the year in which the technology is invested in Note that OSeMOSYS does not include a construction time period Any interest occurred during the construction time therefore needs to be accounted for externally when entering this value The user should take c
29. ilable http www e3mlab ntua gr manuals PRIMsd pdf 29
30. ile generation is done close the command prompt window Open CPLEX Type read and press enter The name of the file to read is C Input_Filepath Input_Filename p 3 After the file is read type optimize and press enter 4 After the optimization is done type write and press enter The name of file to write is C Output_Filepath Output_Filename sol 5 Now that the solution file is written close the CPLEX window and open the command prompt again The solution file will need to be sorted and reordered For this download the python sorting script that was developed for this function and copy it in to the Python 3 5 0 installation folder C Python35 is the default installation directory This script can be downloaded from the OSeMOSYS website Go to the directory C Python35 Type python transform_31072013 py Output_Filename sol Output_Filename txt For this step you will need to have Python 3 5 0 installed Python 3 5 0 can be downloaded from here Click on the link Download Python 3 5 0 and follow the installation instructions The steps described here assume that the Python installation directory is C Python35 6 After the python script is done type sort 1 lt C Python33 Output_Filepath Output_Filename txt gt C Python33 Output_Filename_so rted txt The file produced through the above process contains the results of the model run in a format that is easy to analyse either directly
31. ion TECHNOLOGY is given in columns and REGION in rows The parameter effectively relates the energy in the chosen energy units that would be produced were one unit of capacity in the chosen capacity unit fully used for one year Thus if capacity is measured in GW and energy in PJ for a given technology then this parameter would have a value of 31 536 EXAMPLE OF CAPACITYTOACTIVITYUNIT param CapacityToActivityUnit default 1 E01 E21 E31 E51 E7 UTOPIA 31 536 31 536 31 536 31 536 31 536 In the parameter TechWithCapacityNeededToMeetPeakTS r t unlike the name suggests all technologies which operate timeslice dependent need to be tagged i e set equal to 1 E g all power plants like a coal fired power plant need to be tagged with this parameter A coal mine however will not need to be tagged with this parameter as it may mine coal constantly throughout the year independently of the actual timeslice dependent demand of the coal fired power plant This is because storage for coal is cheap and available 13 If the value of this parameter is 1 equations are looked at on a timeslice bases such as for power plants If the value 0 or any number different to 1 then the equations are just calculated on yearly bases such as for a coal mine TECHNOLOGY is given in columns and REGION in rows EXAMPLE FOR TECHWITHCAPACITYNEEDEDTOMEETPEAKTS param TechWithCapacityNeededToMeetPeakTS default 0 E01 E21 E31 E51 E70 UTOPIA 1 1 1 1 1
32. ion emissions units Mton Total costs by region currency units m The time independent demand for each energy carrier this is zero if no demand was entered region and year energy units PJ The time dependent demand for each energy carrier this is zero if no demand was entered time slice region and year energy units PJ The time dependent production for each energy carrier timeslice region and year energy units PJ The total annual capacity of each technology by region capacity units GW The new investment in capacity for each technology for each year by region capacity units GW The annual production by each technology of each energy source by region energy units GW The annual use by each technology of each energy source by region energy units PJ Annual emissions by species and region emissions units Mton Annual emissions by technology species and region emissions units Mton 1 If you have problems with running the files from the GnuWin32 bin directory due to administration rights redirect the txt you open and results file in a different directory Remember that you then need to write the complete path e g C Users user001 Documents OSeMOSYS_201 txt in the Command Prompt or change to the new folder before running the model 3 2 USE OF THE FULL OR THE SHORT VERSION OF OSEMOSYS When downloading OSeMOSYS a full version and a short version are available The l
33. lt 0 UTOPIA 2 DAM E51 1 23 The parameter TechnologyFromStorage r t s m links a technology to a storage facility for discharging the storage by assigning a value of 1 E g a pumped storage hydro power plant may be linked in the mode of operation turbine 1 to a reservoir called dam The storage is given in the columns and technology in the rows for each mode of operation EXAMPLE TECHNOLOGYFROMSTORAGE param TechnologyFromStorage default 0 i UTOPIA 1 DAM E51 1 The parameter StorageLevelStart sets the storage level at the beginning of first year in the units of energy available in the storage Note if it is zero OSeMOSYS will use the first time slices in the entire first day type in the entire first season to fill the storage To avoid OSeMOSYS taking a whole part of a season to fill up the storage and to avoid having to define shorter seasons set it to zero run the model and check the StorageLevelYearStart variable of the following year and use a similar value for StorageLevelStart Alternatively model a few years before your first year interest EXAMPLE STORAGELEVELSTART param StorageLevelStart default 0 2 The parameter StorageMaxChargeRate r s states the maximum charge that the storage can store in units of power EXAMPLE STORAGEMAXCHARGERATE param StorageMaxChargeRate default 99 The parameter StorageMaxDischargeRate r s is the rate that the storage can be discharged at in units
34. ly in certain years and also check which other technologies are not used to the extent one would expect This may give some clues where the error in the model is situated After trying to find and fix the error rerun the model and remove the dummy technology if it is not used any longer alternatively check every single time you run the model that the dummy technology is not used again potentially for another reason if the model was modified in the meantime In more complex models the model might solve after adding a dummy technology yet it may still be unclear where the mistake in the model file might be In these cases revert back to the original model and add a dummy technology in 2 in the RES as seen in Figure 1 and subsequently if necessary in 3 This method will help to identify more clearly in which part of the Reference Energy System to mistake might be Electricty Diesel Ei Ughting Heating Passenger km s I BEEBB 7 pre Figure 1 Strategy to add dummy technology in the RES 5 2 UPPERLIMIT AND MAXLIMIT INCREASE If the optimisation has no feasible solution then one issue can be that certain upper limits or maximum limits have become binding and prevent the solver from finding a feasible solution There are upper limits defined by the user but also default upper limits on parameters that are embedded in the code for OSeMOSYS To find these upperlimit and maxlimit search in the code
35. m Environment Institute SEI and North Carolina State University Several user interfaces are currently available or under development For example OSeMOSYS is well integrated into LEAP which applies a limited set of OSeMOSYS optimisation features for power plant capacity expansion planning Two alternative interfaces are currently being developed by KTH One is a simplified Excel based interface for teaching purposes while the other will fully support the complete functionality of OSeMOSYS However at this stage if the full scope of OSeMOSYS is required or if adjustments are necessary OSeMOSYS is best set up as text files This manual provides an introduction on how to do so While the development of OSeMOSYS initiated in 2008 its first detailed description was published by Howells et al in 2011 and a subset of the expansions described in Welsch M et al in 2012 led to its current version This version is available for download at www osemosys org 3 GETTING STARTED WITH OSEMOSYS OSeMOSYS models comprise a model file and a data file This manual explains how to set up the data text file The Command Prompt is then used to call the solver to optimise the model described in the model file given the data provided in the data file This produces a results text file and a Comma Separated Values csv file which can easily be opened in Excel and presents the main outputs of the model 3 1 A FIRST MODEL RUN To do a first model run star
36. ment and operating costs efficiencies availabilities and emission profiles t Models such as MARKAL TIMES 8 MESSAGE 9 PRIMES 10 EFOM 6 and POLES 7 The OSeMOSYS model code is written in GNU MathProg a high level mathematical programming language The open source solver GLPK may be used for the mathematical optimisation of the model Both the OSeMOSYS model and the GLPK solver do not require any upfront financial expenditure GLPK can as well produce an MPS file for use with a more powerful solver Diverging from commonly applied programming conventions rather long parameter and variable names are used in OSeMOSYS This ensures that formulas can be read in a rather self explanatory manner and simplifies the familiarisation with the OSeMOSYS code for those new to this modelling tool In its extended version OSeMOSYS comprises just above 400 lines code In 2013 a parallel shortened version of OSeMOSYS have been released The merging of equations significantly improved the performance without affecting the model s data requirements or results at the price of a reduced readability of the code OSeMOSYS is developed in collaboration with a range of institutions including the International Atomic Energy Agency IAEA the United Nations Industrial Development Organisation UNIDO KTH Royal Institute of Technology Stanford University University College London UCL University of Cape Town UCT Paul Scherrer Institute PSI Stockhol
37. n a particular time slice to a day type The set DAYTYPE is in the column index and TIMESLICE in the row index In the following example there is only one day type in a season e g there could be a differentiation between weekdays and weekends to which all timeslices are assigned to 22 EXAMPLE CONVERSIONLD param Conversionld default 0 1 ID 1 IN 1 SD 1 SN 1 WD 1 WN 1 The parameter Conversionlh l Ih is set equal to 1 to assign a particular time slice to a daily time bracket Set it equal to 0 in order not to assign a particular time slice to a daily time bracket The DAILYTIMEBRACKET is in the column index and TIMESLICE in the row index In the following example there are two DAILYTIMEBRACKETS in a given day type in a given season E g SD and SN was assigned to one season before and first comes the day SD which has the value 1 and then comes the night SN which has the value 2 EXAMPLE CONVERSIONLH param Conversionlh default 0 1 2 ID 1 0 IN 0 1 SD 1 0 SN 0 1 WD 1 0 WN 0 1 The parameter TechnologyToStorage r t s m links a technology to a storage facility for charging the storage by assigning a value of 1 E g a pumped storage hydro power plant may be linked in the mode of operation pump 2 to a reservoir called dam The storage is given in the columns and technology in the rows for each mode of operation EXAMPLE OF TECHNOLOGYTOSTORAGE param TechnologyToStorage defau
38. near optimization pdf 2 http www osemosys org uploads 1 8 5 0 18504136 ceron 2006 the gnu linear programming kit part 2 intermediate problems in linear programming pdf 3 http www osemosys org uploads 1 8 5 0 18504136 ceron 2006 the gnu linear programming kit part 3 advanced problems and elegant solutions pdf Further as mentioned before the most comprehensive description of how OSeMOSYS works is provided in OSeMOSYS The Open Source Energy Modeling System An introduction to its ethos structure and development by M Howells et al in 2011 and Modelling elements of Smart Grids Enhancing the OSeMOSYS Open Source Energy Modelling System code by Welsch M et al in 2012 It should be noted that the salvage value as described in Howells M et al 2011 is not applicable anymore please see the changelog provided at www osemosys org for latest changes Further the description of storage in Howells M et al 2011 is not applicable any longer Instead refer to the current way of modelling storage or variability as described in Welsch M et al 2012 4 PARAMETER DESCRIPTION In this chapter the sets and parameters in OSeMOSYS are described Illustrative examples taken from UTOPIA are also added to illustrate how the resulting input file could look like It is therefore recommendable to read this section while comparing the text with the UTOPIA file opened in Notepad This note sets out how the data
39. ned in the SETs in the rows The same values are used for all regions The sum of each entry over the year should equal 1 Consider for 10 example a model constructed with a year that has two TIMESLICES Summer and Winter and those are the same length Then the YearSplit parameter for each TIMESLICE in that year will be 0 5 If you want to summarise all weekday mornings in summer you would for example name it SWM in the set TIMESLICE be consistent and attribute a year share of Summer months June July August SUM Days per month 30 31 31 Weekdays 22 23 21 222423421 66 days Hours in the morning 6 6 6 66 6 396 hours Hours per year 8760 hours YearSplit for SWM 396 8760 0 045 This would be reflected in the YearSplit parameter as follows EXAMPLE FROM UTOPIA YEARSPLIT param YearSplit 1990 1991 1992 ID 0 1667 0 1667 0 1667 IN 0 0833 0 0833 0 0833 SWM 0 045 0 045 0 045 SD 0 205 0 205 0 205 WD 0 3333 0 3333 0 3333 WN 0 1667 0 1667 0 1667 Make sure that the sum for each year equals 1 The parameter DaySplit lh y is the length of one DailyTimeBracket in one specific day as a fraction of the year e g when distinguishing between days and night 12h 24h 365d EXAMPLE DAYSPLIT param DaySplit default 0 00137 The parameter DayslnDayTypells ld y represents the number of days for each day type within a week i e out of 7 EXAMPLE DAYSINDAYTYPE param DayslnDayType default 7 The Discou
40. ngton S Kypreos A Hughes S Silveira J DeCarolis M Bazillian and A Roehrl OSeMOSYS The Open Source Energy Modeling System An introduction to its ethos structure and development Energy Policy vol 39 p 5850 5870 2011 3 M Welsch M Howells M Bazilian J DeCarolis S Hermann and H Rogner Modelling elements of Smart Grids Enhancing the OSeMOSYS Open Source Energy Modelling System code Energy vol Volume 46 no Issue 1 p Pages 337 350 October 2012 4 A Gupta A Kartavtseva and G Avgerinopoulos Training Manual ANSWER OSeMOSYS KTH Stockholm 2013 5 OSeMOSYS Development team OSEeMOSYS Getting started 06 07 2015 Online Available http osemosysmain yolasite com getting started php Accessed 06 07 2015 6 E Van der Voort The EFOM 12C energy supply model within the EC Omega vol 10 no 5 p 507 523 1982 7 Enerdata POLES Prospective Outlook on Long Term Energy Systems 2015 Online Available http www enerdata net enerdatauk solutions energy models poles model php 28 8 ETSAP Energy Technology Systems Analysis Program Software and Tools 2015 Online Available http www etsap org Tools asp 9 IAEA International Atomic Energy Agency PESS Energy Models 2015 Online Available https www iaea org OurWork ST NE Pess PESSenergymodels html 10 NTUA National Technical University of Athens The PRIMES Energy 2015 Online Ava
41. ns The matrix is repeated for each REGION modelled EXAMPLE OF SPECIFIEDANNUALDEMAND param SpecifiedAnnualDemand default 0 UTOPIA 1990 1991 1992 1993 1994 RH 25 2 26 46 27 72 28 98 30 24 12 For each energy service or fuel which has a SpecifiedAnnualDemand a demand profile should be assigned This is included in the SpecifiedDemandProfile r f y parameter If this is left blank then no specified demand is calculated The SpecifiedDemandProfile parameter indicates the annual fraction of energy service or fuel demand that is required in each time slice For each year these should sum up to one EXAMPLE OF SPECIFIEDDEMANDPROFILE param SpecifiedDemandProfile default 0 UTOPIA RH 1990 1991 1992 1993 1994 ID 0 12 0 12 0 12 0 12 0 12 IN 0 06 0 06 0 06 0 06 0 06 SD 0 0 0 0 0 SN 0 0 0 0 0 WD 0 5467 0 5467 0 5467 0 5467 0 5467 WN 0 2733 0 2733 0 2733 0 2733 0 2733 Make sure that the sum for each year equals 1 4 6 TECHNOLOGY In a departure from several existing modelling frameworks all energy system components are set up as a technology in OSeMOSYS For example a resource is represented as a technology with no input fuel but producing an output fuel with limits on its activity to represent the resource availability 4 6 1 PERFORMANCE CHARACTERISTICS As the capacity may be measured in one unit and energy in another the parameter CapacityToActivityUnit r t is specified for each technology and for each reg
42. ntRatelr t parameter is a matrix that gives the discount rate for each technology in each region Technologies are given in columns and regions in rows The parameter is used to calculate a discount factor for the start of each year That is used when discounting new capacity investments and any other costs such as operating costs It is also used together with the lifetime of a technology to calculate the salvage value of each technology invested in during the model period but whose life extends beyond the final model year 11 In the example files provided a default and common discount rate is used Having separate discount rates can be useful when trying to simulate specific hurdle rates that differ from sector to sector However this is not possible in the version OSeMOSYS 2013 05 10 or OSeMOSYS 2013 05 10 short Therefore only use a single default value as of now and check the change log for updated functionality EXAMPLE OF DISCOUNTRATE UTOPIA param DiscountRate default 0 05 4 5 DEMANDS Next the user enters the demands Note that these demands are commonly defined for energy services or fuels There are two different kinds of demands One is an accumulated annual demand This type of demand can be satisfied at any time of the year as long as the total is met This is a simplification that is useful when storage is not a constraint e g to enter a demand for oil when there are enough reserves available within a country
43. of power EXAMPLE STORAGEMAXDISCHARGERATE param StorageMaxDischargeRate default 99 The parameter MinStorageChargelr s y is given as a fraction of the maximum available storage level i e between 0 00 and 0 99 The storage facility cannot be empties below this level EXAMPLE MINSTORAGECHARGE param MinStorageCharge default O 24 The parameter OperationalLifeStoragelr s y is the storage s operational lifetime in years param OperationalLifeStorage default 99 The CapitalCostStorage r s y is the cost to invest in new storage facilities defined per region storage type and year It is given in units of costs per units of energy e g Million EUR PJ param CapitalCostStorage default O The parameter DiscountRateStorage r s is the applied discount rate for the chosen storage per region entered as a fraction e g 1 05 param DiscountRateStorage default Os The parameter ResidualStorageCapacity r s y is the storage capacity which is available from before the modelling period or which is known to become available in a specific year It is given in the units of energy EXAMPLE RESIDUALSTORAGECAPACITY param ResidualStorageCapacity default 999 4 10 RENEWABLE ENERGY TARGETS Each renewable technology may be tagged using the RETagTechnologylr ty parameter The tag value is either 1 for a renewable technology or 0 otherwise The parameter is a matrix with the years as the columns and technologies in th
44. ogram files you need to go to C Program Files GnuWin32 bin Open the command prompt and 1 return to the root by typing cd then 2 navigate to the folder that the files are stored in by typing cd C GnuWin32 bin then hit the return key if you need help on command prompt type help and possible command options will be listed Running the UTOPIA example in OSeMOSYS using glpsol Now that you are in the VGnuWin32Vbin directory in the command prompt and you have OSeMOSYS 201 txt and UTOPIA txt pasted in the same directory you can run the UTOPIA example in OSeMOSYS To do this type glpsol m OSeMOSYS 201 txt d UTOPIA 201 dat o results txt All characters are important including space This invokes a command glpsol to take the model file OSeMOSYS 201 txt and associated data input file UTOPIA txt to produce an output file with a full set of results result txt The results file is particularly large even for a simple problem To make life easier therefore OSeMOSYS is programmed to produce a summary results file called SelectedResults csv This as well as the full results file will appear in the GnuWin32 bin directory after a model run A list of other possible command options can be found in the command prompt by typing glpsol help Errors Glpsol will display an error message if it does not understand the input files and it will also tell you in which line number there is a conflict
45. ong version is easier to read and understand as it includes more simple user friendly equations The shorter version was developed by merging equations from the full version This eliminates the need to calculate and store intermediate values and results in faster calculation times While it produces the same key outputs it is harder to understand the individual equations The full version computes more variables which help the user in understanding what the model actually does The full version is therefore as well particularly helpful to test modifications and enhancements to the main code Therefore the use of the full version is recommended unless the calculation times get prohibitively long Problems which cannot be solved with the full code due to time or RAM constraints can be solved with the short code It is easy to check if the RAM is a limiting constraint during the computation it is sufficient to open the system task manager Ctrl Alt Delete and check if the RAM use is close to saturation The RAM and time constraint may become binding when the model gets too complex This may happen e g when a multi regional model with many technologies and time slices is set up In such cases the shorter version is recommended The reduction in the number of equations in the shorter version translates into the generation of a smaller matrix to be solved This significantly reduces the memory usage 10x and the processing time 5x The sho
46. or after being copied into another software platform such as MS Excel 27 6 2 MODIFICATIONS ENHANCEMENTS ADDITIONS TO THE MAIN CODE If a user develops model code extensions it is very much appreciated if these are communicated to the OSeMOSYS team refer to the contacts given at www osemosys org Code extensions are in general kept separate from the main code published on the website When some enhancement or addition is proposed it is advised to create an independent txt or doc file where the new parameters variables and constraints are written in a format compatible with the main code Any modification to existing constraints should be properly indicated Further a second file describing the modifications should be attached in line with the concept of OSeMOSYS this file should describe the modifications on four levels 1 a conceptual description 2 a mathematical formulation 3 a formulation in GNU MathProg language ready to be copied and pasted directly in the main code 4 Further a sample file should be provided to test the model runs For an example of such modifications and their description please refer to http onlinelibrary wiley com doi 10 1002 er 3250 abstract 7 REFERENCE LIST 1 OSeMOSYS Development team OSeMOSYS Start up guide 06 07 2015 Online Available http www energycommunity org documents OSeMOSYS readme pdf Accessed 06 07 2015 2 M Howells H Rogner N Strachan C Heaps H Hunti
47. pportive Programmes and Documentation ese se ee ee ee Ee RR ER ee AA GR ER ee ee AA Ge ee ke ee ee ee 7 Parameter description iuit ree Ge ee eee ee dae Ee ee Ge ko one Ge ee Ge Ge Ee ee weed 8 4 1 SOUS areca P 8 4 2 li EE EE RE EO EE 10 4 3 Syntaxtortlie parameteps de etre tenta tes eer ere eol te d EE eee e epe ree uua eR Ere ERR ERE R ERE P EE 10 4 4 Global paramieters EE Teo tene eee te o EGO GE Ie teatros dk 10 4 5 Demands Em 12 4 6 Technology ieu rete asian bak eere EE RE EE EA OER 13 4 6 1 Performance Characteristics enne enne nne en nnne nnnm nnne nnne ee nnne enne 13 4 62 v Gapacity limits e eem e toe Do Mes e o ar e dv d edt deus RR VEE ED AER 18 4 6 3 zACEIVIty IR RE AR Eee uoo ER eee a qe EE EE RE EE cre NEW E TETTE Toe 19 4 7 dIe EE E EE OE N OE EQ 20 4 8 Reserve margini 2 5 neret EE EK OE OE EK EE RRRAR 21 4 9 kil Ee De EG ee SE A E E ous ee dues N Se ee ee Seg 22 4 10 Renewable energy targets ccna se Ee ee eriei rea AA GE ee ee ee AA enne RA ee ee teda ee AA ee ke ee ee ee ee 25 Deb gsgirig the model io to teer ee eg DE Ge poe e i dui ee SE EE 26 5 1 Adding a Dummy technology rea AE Ge Ee ee AA Ge Ee ee ener Ge ninh nnns ee Ge Ee tesa nasi sient raga snas sn ee 26 5 2 Upperlimit and maxlimit increase sees se Ee ee ee ER ee AA ee Ee RA ee ee Ee Re ee ee ee ke ee ee 26 Advanced uses of OSeMOSYS i e EE SEE AA eGGSA EG Fo aet er dee Ett kl eke ge Re a na kiai ienis 27 6 1 Using OSeMOSYS with CPLEX ees esse se se ee e
48. rt version of the OSeMOSYS code contains only the essential equations required for running the model However all the previous equations have been left as before and commented out to better understand the methodology followed to shorten the code It is important to note that the shortening of the code does not change any aspect of the functionality of OSeMOSYS Further there are no special formatting requirements for the data file required to run the short version instead of the full version Both the regular and the short versions of OSeMOSYS are developed and released as parallel versions simultaneously 3 3 MAPPING THE REFERENCE ENERGY SYSTEM When developing a model in an optimisation tool like OSeMOSYS the energy system needs to be mapped to identify all the relevant technologies that will be involved To the left in the model the technologies categorised as primary energy resources are mapped shown in boxes in Figure 1 The lines represent energy carriers e g 4 crude oil coal etc Moving from the left to right the energy carriers are transformed through different technologies to ultimately meed a final demand for energy services presented by the technologies at the very right hand side of Figure 1 The Reference Energy System RES can be seen as a table of content for the energy model Error Reference source not found Figure 1 illustrates the RES for a demonstration case referred to as TOPIA The chosen acronyms are freely chosen b
49. rting point 3 5 DATA AND CHOICE OF UNITS The cornerstone of a legitimate model is the data Using accurate data relevant model designs and a consistent choice of assumptions will ultimately offer better and more representative insights into the system Typical data requirements include Energy demand for the activities that are considered in the model and an annual load curve for electricity heating and cooling Efficiencies the capacity and the capacity availability factor of the power production technologies Corresponding costs for technologies Constraints like import constraints resource levels etc Emissions and others Useful technology briefs containing such data have been developed by ETSAP http www etsap org The World Energy Outlook from IEA http www worldenergyoutlook org IEA Cost of Generating Electricity look for latest publication at www iea org and IRENA s Renewable energy publications can further be used to obtain the required data for modelling a country s energy sector The fossil fuel reserves in every country can be obtained from EIA U S Energy Information Administration 4 Also the World Bank database is a useful source of data for energy demand Note that these publications provide generic values and national studies and strategy documents are usually preferable over generic more global values For OSeMOSYS there are 4 units that needs to be chosen carefully Bear in mind th
50. s included in the rows EXAMPLE OF RESERVEMARGINTAGFUEL param ReserveMarginTagFuel default O UTOPIA 1990 1991 1992 1993 1994 ELC 1 1 1 1 1 The ReserveMargin r y parameter is given per year and indicates the reserve level of installed capacity required over the peak demand as modelled for the corresponding fuel Note that only technologies that are tagged are included in this reserve margin It is entered as a matrix with the years as the columns and regions included in the rows The reserve margin is given as a unitless fraction In the following case 18 more total installed capacities are required then the actual peak load Note that the capacity factor is not applied to calculate the reserve requirements i e the full installed capacity is taken EXAMPLE OF RESERVEMARGIN param ReserveMargin 1990 1991 1992 1993 1994 UTOPIA 1 18 1 18 1 18 1 18 1 18 Each technology in each region that is allowed to contribute to the reserve margin is tagged using the ReserveMarginTagTechnology r t y If the tag value is 1 then 100 of the installed capacity of that technology contributes to the reserve If the tag value is 2 then only 20 This representation is useful as e g some variable renewable technologies contribute to the capacity reserve in a limited manner The parameter is a matrix with the years as the columns and technologies included in the rows 21 EXAMPLE OF RESERVEMARGINTAGTECHNOLOGY param ReserveM
51. t by downloading the OSeMOSYS files from osemosys org which consists of two OSeMOSYS files one short and one long version both of which produce the same results see next section and one example file called UTOPIA The main steps to perform a model run are outlined in the following 1 Getting started with the UTOPIA example in OSeMOSYS a Download GLPK GLPK is free and open source software http sourceforge net projects gnuwin32 files glpk 4 34 glpk 4 34 setup exe download b Once you have downloaded the setup exe execute the file All this does is to extract files in a folder of your choice referred to as in the following 2 The OSeMOSYS model file and the UTOPIA data file For example GUROBI offers free academic licenses 3 a 5 6 7 Cut and paste the OSeMOSYS 201 txt and UTOPIA txt file into the GnuWin32 bin directory Remember that you set which directory this is after executing the glpk setup exe file Open the command prompt The command prompt can be opened by clicking in Windows on Start Run and then typing cmd There are other ways of doing this but the latter is one of the easiest The command prompt will have some text to indicate the current directory to which you can send prompts If you are not in the same directory as the one where GLPK stored then you need to change the directory that contains glpsol exe NGnuWin32 bin If you extracted it to the default pr
52. technology should be invested in to reach a minimum total residual and new capacity each year the limiting capacity level is included in the TotalAnnualMinCapacity r t y parameter The default for all technologies is zero so that the limit is effectively not enforced The unit of the parameter is the unit that is used to measure the respective technologies capacity in the model The parameter is a matrix with the years as the columns and technologies in the rows EXAMPLE OF TOTALANNUALMINCAPACITY param TotalAnnualMinCapacity default 0 UTOPIA 1990 1991 1992 1993 1994 E31 0 13 0 14 0 14 0 15 0 15 SRE 0 1 0 1 0 1 0 1 0 1 If annual investments in new capacities for a given technology are limited to a given level each year this upper limit is included in the TotalAnnualMaxCapacitylnvestmentlr t y parameter The default for all technologies is a high number so that the limit is usually not enforced The unit of the parameter is the unit that is used to measure the respective technologies capacity in the model The parameter is a matrix with the years as the rows and technologies included in the columns EXAMPLE OF TOTALANNUALMAXCAPACITYINVESTMENT param TotalAnnualMaxCapacitylnvestment default 99999 If annual investments in new capacities for a given technology are limited to a given level each year this lower limit is included in the TotalAnnualMinCapacitylnvestmentlr t y parameter The default for all technologies is zero
53. the letter f e The YEARs modelled indexed by the letter y e The TIMESLICEs each of which combines a fraction of the year with specific load and supply characteristics One time slice could for example represent all the weekend evenings in summer another one the weekday evenings in winter As such time slices do not have an inherent chronology The time slices are indexed by the letter I e Thenumber of MODES OF OPERATION that a technology can have assuming that the technology can switch between a linear combination of these Modes of operation are usually defined if a technology can use various input or output fuels and can choose the mix of these input or output fuels For example a CHP plant may vary between producing heat in one mode of operation and 3 Note that all indexes are lower case electricity in another The capacity remains constant simply because the same piece of machinery produces both outputs The modes of operation are indexed by the letter m The REGIONS that are to be modelled Commonly one country is modelled as one region and it may be efficient from a computational point of view to even multiple countries within a single region e g by defining different fuels and technologies for each country In this case countries could be linked to one another by setting up technologies which link one country to another by converting the fuels used in one country to the fuels used in another This has th
54. y the user and can therefore differ from one model to the next In the UTOPIA RES for example EO1 is a coal fired power plant and RHE is Residential Heating Electricity 2 3 t 25 P I eee 23 23 E ziji EF d Figure 1 The reference system in UTOPIA 2 KEY TO THE REFERENCES SYSTEM IN UTOPIA E01 is a power plant which consumes coal IMPHCOL E21 is a nuclear power plant that consumes uranium IMPURN1 E31 is a hydro power plant E51 consumes electricity and generates electricity E70 is a power plant that consumes diesel IMPDSL1 RHE is residential electricity heating that consumes electricity RHO is residential heating that consumes diesel IMPLDSL1 RHL is residential lighting that consumed electricity TXG is transport in passenger km consuming gasoline IMPGSL1 TXD is transport in passenger km consuming diesel IMPDSL1 TXE is transport in passenger km consuming Electricity 2 3 4 CREATING AN INPUT FILE To create the input data for an optimisation run you can set up the model directly in a text editor like Notepad It is advisable to start with a small model and build it up step wise This will simplify the debugging see Section 5 Debugging the model It is further advisable to back up working versions of model data files by saving them in a folder of your choice The Utopia input file provided with the downloaded model code might serve as a useful starting point to see how data needs to be correctly formatted
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