Merge pull request #39 from GenXProject/Dev

Version Upgrade of GenX for running on Julia 1.5.x and 1.6.x

Author: sambuddhac

.travis.yml

@@ -4,8 +4,10 @@ notifications:
   email: false
 julia:
   #- 1.0
-  - 1.3
-  #- nightly
+  #- 1.3
+  - 1.5
+  - 1.6
+  - nightly
 coveralls: true
 branches:
   only:

Example_Systems/RealSystemExample/ISONE_Singlezone/Settings/gurobi_settings.yml

@@ -4,13 +4,13 @@ Feasib_Tol: 1.0e-06           # Constraint (primal) feasibility tolerances.
 Optimal_Tol: 1e-6             # Dual feasibility tolerances.
 TimeLimit: 110000             # Limits total time solver.
 Pre_Solve: 1                  # Controls presolve level.
-Method: 4                     # Algorithm used to solve continuous models (including MIP root relaxation).
+Method: 2                  # Algorithm used to solve continuous models (including MIP root relaxation).
 
 #Gurobi-specific solver settings
 MIPGap: 1e-4                  # Relative (p.u. of optimal) mixed integer optimality tolerance for MIP problems (ignored otherwise).
 BarConvTol: 1.0e-08           # Barrier convergence tolerance (determines when barrier terminates).
 NumericFocus: 0               # Numerical precision emphasis.
-Crossover: -1                 # Barrier crossver strategy.
+Crossover: 0                # Barrier crossver strategy.
 BarObjRng: 1e+75              # Sets the maximum absolute value of the objective function
 PreDual: 0                    # Decides whether presolve should pass the primal or dual linear programming problem to the LP optimization algorithm.
 AggFill: 10                   # Allowed fill during presolve aggregation.

Example_Systems/RealSystemExample/ISONE_Trizone/Settings/genx_settings.yml

@@ -3,7 +3,7 @@ OverwriteResults: 0 # Overwrite existing results in output folder or create a ne
 PrintModel: 0 # Write the model formulation as an output; 0 = active; 1 = not active
 NetworkExpansion: 1 # Transmission network expansionl; 0 = not active; 1 = active systemwide
 Trans_Loss_Segments: 1 # Number of segments used in piecewise linear approximation of transmission losses; 1 = linear, >2 = piecewise quadratic
-Reserves: 0 # Regulation (primary) and operating (secondary) reserves; 0 = not active, 1 = active systemwide
+Reserves: 1 # Regulation (primary) and operating (secondary) reserves; 0 = not active, 1 = active systemwide
 EnergyShareRequirement: 1 # Minimum qualifying renewables penetration; 0 = not active; 1 = active systemwide
 CapacityReserveMargin: 1 # Number of capacity reserve margin constraints; 0 = not active; 1 = active systemwide
 CO2Cap: 1 # CO2 emissions cap; 0 = not active (no CO2 emission limit); 1 = mass-based emission limit constraint; 2 = load + rate-based emission limit constraint; 3 = generation + rate-based emission limit constraint
@@ -12,7 +12,7 @@ MinCapReq: 1  # Activate minimum technology carveout constraints; 0 = not active
 Solver: Clp # Available solvers: Gurobi, CPLEX, CLP, CBC
 ParameterScale: 1 # Turn on parameter scaling wherein load, capacity and power variables are defined in GW rather than MW. 0 = not active; 1 = active systemwide
 WriteShadowPrices: 1 # Write shadow prices of LP or relaxed MILP; 0 = not active; 1 = active
-UCommit: 0 # Unit committment of thermal power plants; 0 = not active; 1 = active using integer clestering; 2 = active using linearized clustering
+UCommit: 2 # Unit committment of thermal power plants; 0 = not active; 1 = active using integer clestering; 2 = active using linearized clustering
 OperationWrapping: 1 # Sets temporal resolution of the model; 0 = single period to represent the full year, with first-last time step linked; 1 = multiple representative periods
 LongDurationStorage: 0 # Inter-period energy exchange for storage technologies; 0 = not active; 1 = active systemwide
 TimeDomainReductionFolder: "TDR_Results" # Directory name where results from time domain reduction will be saved. If results already exist here, these will be used without running time domain reduction script again.

Example_Systems/RealSystemExample/ISONE_Trizone/Settings/gurobi_settings.yml

@@ -4,13 +4,13 @@ Feasib_Tol: 1.0e-06           # Constraint (primal) feasibility tolerances.
 Optimal_Tol: 1e-6             # Dual feasibility tolerances.
 TimeLimit: 110000             # Limits total time solver.
 Pre_Solve: 1                  # Controls presolve level.
-Method: 4                     # Algorithm used to solve continuous models (including MIP root relaxation).
+Method: 2                     # Algorithm used to solve continuous models (including MIP root relaxation).
 
 #Gurobi-specific solver settings
 MIPGap: 1e-4                  # Relative (p.u. of optimal) mixed integer optimality tolerance for MIP problems (ignored otherwise).
 BarConvTol: 1.0e-08           # Barrier convergence tolerance (determines when barrier terminates).
 NumericFocus: 0               # Numerical precision emphasis.
-Crossover: -1                 # Barrier crossver strategy.
+Crossover: 0               # Barrier crossver strategy.
 BarObjRng: 1e+75              # Sets the maximum absolute value of the objective function
 PreDual: 0                    # Decides whether presolve should pass the primal or dual linear programming problem to the LP optimization algorithm.
 AggFill: 10                   # Allowed fill during presolve aggregation.

Example_Systems/RealSystemExample/ISONE_Trizone_FullTimeseries/Settings/genx_settings.yml

@@ -9,7 +9,7 @@ CapacityReserveMargin: 1 # Number of capacity reserve margin constraints; 0 = no
 CO2Cap: 1 # CO2 emissions cap; 0 = not active (no CO2 emission limit); 1 = mass-based emission limit constraint; 2 = load + rate-based emission limit constraint; 3 = generation + rate-based emission limit constraint
 StorageLosses: 1 # Energy Share Requirement and CO2 constraints account for energy lost; 0 = not active (DO NOT account for energy lost); 1 = active systemwide (DO account for energy lost)
 MinCapReq: 1  # Activate minimum technology carveout constraints; 0 = not active; 1 = active
-Solver: Gurobi # Available solvers: Gurobi, CPLEX, CLPs
+Solver: Clp # Available solvers: Gurobi, CPLEX, CLPs
 ParameterScale: 1 # Turn on parameter scaling wherein load, capacity and power variables are defined in GW rather than MW. 0 = not active; 1 = active systemwide
 WriteShadowPrices: 1 # Write shadow prices of LP or relaxed MILP; 0 = not active; 1 = active
 UCommit: 0 # Unit committment of thermal power plants; 0 = not active; 1 = active using integer clestering; 2 = active using linearized clustering

Example_Systems/RealSystemExample/MGA_ISONE_Trizone_FullTimeseries/Run.jl

@@ -73,5 +73,12 @@ outpath = "$inpath/Results"
 write_outputs(EP, outpath, mysetup, myinputs)
 if mysetup["ModelingToGenerateAlternatives"] == 1
     println("Starting Model to Generate Alternatives (MGA) Iterations")
-    mga(EP,inpath,mysetup,myinputs,outpath)
+    if Sys.isunix()
+		sep = "/"
+    elseif Sys.iswindows()
+		sep = "\U005c"
+    else
+        sep = "/"
+	end
+    mga(EP,inpath,mysetup,myinputs,outpath, sep)
 end

Example_Systems/RealSystemExample/MGA_ISONE_Trizone_FullTimeseries/Settings/gurobi_settings.yml

@@ -4,13 +4,13 @@ Feasib_Tol: 1.0e-06           # Constraint (primal) feasibility tolerances.
 Optimal_Tol: 1e-6             # Dual feasibility tolerances.
 TimeLimit: 110000             # Limits total time solver.
 Pre_Solve: 1                  # Controls presolve level.
-Method: 4                     # Algorithm used to solve continuous models (including MIP root relaxation).
+Method: 2                   # Algorithm used to solve continuous models (including MIP root relaxation).
 
 #Gurobi-specific solver settings
 MIPGap: 1e-4                  # Relative (p.u. of optimal) mixed integer optimality tolerance for MIP problems (ignored otherwise).
 BarConvTol: 1.0e-08           # Barrier convergence tolerance (determines when barrier terminates).
 NumericFocus: 0               # Numerical precision emphasis.
-Crossover: -1                 # Barrier crossver strategy.
+Crossover: 0                 # Barrier crossver strategy.
 BarObjRng: 1e+75              # Sets the maximum absolute value of the objective function
 PreDual: 0                    # Decides whether presolve should pass the primal or dual linear programming problem to the LP optimization algorithm.
 AggFill: 10                   # Allowed fill during presolve aggregation.

Project.toml

@@ -18,7 +18,6 @@ Distances = "b4f34e82-e78d-54a5-968a-f98e89d6e8f7"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
 DocumenterTools = "35a29f4d-8980-5a13-9543-d66fff28ecb8"
 GLPK = "60bf3e95-4087-53dc-ae20-288a0d20c6a6"
-Gurobi = "2e9cd046-0924-5485-92f1-d5272153d98b"
 Ipopt = "b6b21f68-93f8-5de0-b562-5493be1d77c9"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
@@ -30,27 +29,26 @@ StatsBase = "2913bbd2-ae8a-5f71-8c99-4fb6c76f3a91"
 YAML = "ddb6d928-2868-570f-bddf-ab3f9cf99eb6"
 
 [compat]
-CSV = "0.6.0, 0.8"
-BenchmarkTools = "1.0.0"
+BenchmarkTools = "1.1.1"
+CSV = "0.8.5"
 Cbc = "0.8.0"
-Clp = "0.8.1"
+Clp = "0.8.4"
 Clustering = "0.14.2"
 Combinatorics = "1.0.2"
-DataStructures = "0.17.20, 0.18"
-DataFrames = "0.20.2, 1"
-DiffEqSensitivity = "6.33.0"
-Distances = "0.10.2"
-Documenter = "0.24.7, 0.27"
-DocumenterTools = "0.1.9"
-GLPK = "0.14.8"
-Ipopt = "0.6.0, 0.7"
-Gurobi = "0.7.6, 0.9"
-JuMP = "0.21.3"
+DataFrames = "1.0.0"
+DataStructures = "0.18.9"
+DiffEqSensitivity = "6.52.1"
+Distances = "0.10.3"
+Documenter = "0.27.3"
+DocumenterTools = "0.1.13"
+GLPK = "0.14.12"
+Ipopt = "0.7.0"
+JuMP = "0.21.8"
 MathProgBase = "0.7.8"
-OrdinaryDiffEq = "5.42.3"
+OrdinaryDiffEq = "5.60.1"
 QuasiMonteCarlo = "0.2.3"
-StatsBase = "0.33.0"
-YAML = "0.4.3"
+StatsBase = "0.33.8"
+YAML = "0.4.7"
 julia = "1"
 
 [extras]

README.md

@@ -23,12 +23,10 @@ The 'main' branch is the current master branch of GenX. The various subdirectori
 
 ## Requirements
 
-GenX.jl runs on Julia v1.3.x series, where x>=0 and a minimum version of JuMP v0.21.3, and is currently setup to use one of the following open-source freely available solvers: A) [Clp](https://github.com/jump-dev/Clp.jl) for linear programming (LP) problems and (B) [Cbc](https://github.com/jump-dev/Cbc.jl) for mixed integer linear programming (MILP) problems. We also provide the option to use one of these two commercial solvers: C) [Gurobi](https://www.gurobi.com), and D) [CPLEX](https://www.ibm.com/analytics/cplex-optimizer). Note that using Gurobi and CPLEX requires a valid license on the host machine. There are two ways to run GenX with either type of solver options (open-source free or, licensed commercial) as detailed in the section, `Running an Instance of GenX`.
+GenX currently exists in version 0.1.0 and runs only on Julia v1.6.x and v1.5.x series, where x>=0 and a minimum version of JuMP v0.21.x. There is also an older version of GenX, which is also currently maintained and runs on Julia 1.3.x and 1.4.x series (For those users who has previously cloned GenX, and has been running it successfully so far, and therefore might be unwilling to run it on the latest version of Julia: please look into the GitHub branch, [old_version](https://github.com/GenXProject/GenX/tree/old_version)). It is currently setup to use one of the following open-source freely available solvers: A) [Clp](https://github.com/jump-dev/Clp.jl) for linear programming (LP) problems and (B) [Cbc](https://github.com/jump-dev/Cbc.jl) for mixed integer linear programming (MILP) problems. We also provide the option to use one of these two commercial solvers: C) [Gurobi](https://www.gurobi.com), and D) [CPLEX](https://www.ibm.com/analytics/cplex-optimizer). Note that using Gurobi and CPLEX requires a valid license on the host machine. There are two ways to run GenX with either type of solver options (open-source free or, licensed commercial) as detailed in the section, `Running an Instance of GenX`.
 
 The file `julenv.jl` in the parent directory lists all of the packages and their versions needed to run GenX. You can see all of the packages installed in your Julia environment and their version numbers by running `pkg> status` on the package manager command line in the Jula REPL.
 
-You can see all of the packages installed in your Julia environment and their version numbers by running pkg> status on the package manager command line.
-
 ## Documentation
 
 Detailed documentation for GenX can be found [here](https://genxproject.github.io/GenX/dev). It includes details of each of GenX's methods, required and optional input files, and outputs. Interested users may also want to browse through prior publications that have used GenX to understand the various features of the tool. Full publication list is available [here](https://energy.mit.edu/genx/#publications).
@@ -56,28 +54,28 @@ Here are step-by-step instructions for running Run.jl, following the two slightl
 
 Execution of the entire sequence of the four steps above should look like the figure below:
 
-![Creating the Julia environment and installing dependencies from Project.toml file from inside the GenX folder: Steps 1-4](docs/src/assets/Method1_Julia_Kernel_from_inside_GenX_Step1.png)
+![Creating the Julia environment and installing dependencies from Project.toml file from inside the GenX folder: Steps 1-4](docs/src/assets/Method1_Julia_Kernel_from_inside_GenX_Step1_Updated.png)
 *Figure.Creating the Julia environment and installing dependencies from Project.toml file from inside the GenX folder: Steps 1-4*
 
 5. Type the back key to come back to the `julia>` prompt.
 6. Run the script by executing the command `julia> include(“<path to your case>/Run.jl”)`. For example, in order to run the ISONE_Singlezone case within the Example_Systems/RealSystemExample/, type `include("Example_Systems/RealSystemExample/ISONE_Singlezone/Run.jl")` from the `julia>` prompt (while being still in the GenX i.e. the root level in the folder hierarchy)
 
 Execution of the steps 5 and 6 above should look like the figure below:
 
-![Creating the Julia environment and installing dependencies from Project.toml file from inside the GenX folder: Steps 5-6](docs/src/assets/Method1_Julia_Kernel_from_inside_GenX_Step2.png)
+![Creating the Julia environment and installing dependencies from Project.toml file from inside the GenX folder: Steps 5-6](docs/src/assets/Method1_Julia_Kernel_from_inside_GenX_Step2_Updated.png)
 *Figure.Creating the Julia environment and installing dependencies from Project.toml file from inside the GenX folder: Steps 5-6*
 
 7. After the script runs to completion, results will be written to a folder called “Results”, also located in the same directory as `Run.jl`.
 
 If however, the user opens a julia kernel, while not yet inside the GenX folder, it's still possible to reach to the GenX folder while being inside the Julia REPL by executing the `pwd()` command first to check where on the directory structure the user is currently, and then by executing the `cd(<path to GenX>)` command. Afterwards, the steps are the same as above. This is shown in the three figures below:
 
-![Creating the Julia environment and installing dependencies from Project.toml file from outside the GenX folder: Changing path to GenX](docs/src/assets/Method1_Julia_Kernel_from_outside_GenX_Step1.png)
+![Creating the Julia environment and installing dependencies from Project.toml file from outside the GenX folder: Changing path to GenX](docs/src/assets/Method1_Julia_Kernel_from_outside_GenX_Step1_Updated.png)
 *Figure.Creating the Julia environment and installing dependencies from Project.toml file from inside the GenX folder: Changing path to GenX*
 
-![Creating the Julia environment and installing dependencies from Project.toml file from outside the GenX folder: Steps 1-4](docs/src/assets/Method1_Julia_Kernel_from_outside_GenX_Step2.png)
+![Creating the Julia environment and installing dependencies from Project.toml file from outside the GenX folder: Steps 1-4](docs/src/assets/Method1_Julia_Kernel_from_outside_GenX_Step2_Updated.png)
 *Figure.Creating the Julia environment and installing dependencies from Project.toml file from inside the GenX folder: Steps 1-4*
 
-![Creating the Julia environment and installing dependencies from Project.toml file from outside the GenX folder: Steps 5-6](docs/src/assets/Method1_Julia_Kernel_from_outside_GenX_Step3.png)
+![Creating the Julia environment and installing dependencies from Project.toml file from outside the GenX folder: Steps 5-6](docs/src/assets/Method1_Julia_Kernel_from_outside_GenX_Step3_Updated.png)
 *Figure.Creating the Julia environment and installing dependencies from Project.toml file from inside the GenX folder: Steps 5-6*
 
 ### Method 2: Creating the Julia environment and installing the dependencies by building the Project.toml files by running activation script