GOC3 scopf implementation

.github/workflows/ci.yml

@@ -34,9 +34,10 @@ jobs:
           key: compiled-${{ runner.os }}-${{ hashFiles('**/Project.toml') }}-${{ hashFiles('**/Manifest.toml') }}
           restore-keys: compiled-${{ runner.os }}-
 
+
       - name: Install package dependencies
         run: |
-          julia --project=. -e 'using Pkg; Pkg.instantiate(); Pkg.precompile()'
+          julia --project=. -e 'using Pkg; Pkg.add(PackageSpec(url="https://github.com/lanl-ansi/GOC3Benchmark.jl")); Pkg.instantiate(); Pkg.precompile()'
 
       - name: Check for CUDA availability
         id: check-cuda

.github/workflows/docs.yml

@@ -17,7 +17,7 @@ jobs:
         with:
           version: '1'
       - name: Install dependencies
-        run: julia --project=docs/ -e 'using Pkg; Pkg.Registry.update(); Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'
+        run: julia --project=docs/ -e 'using Pkg; Pkg.add(PackageSpec(url="https://github.com/lanl-ansi/GOC3Benchmark.jl")); Pkg.Registry.update(); Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate(); Pkg.precompile()'
       - name: Build and deploy
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # If authenticating with GitHub Actions token

Project.toml

@@ -9,6 +9,9 @@ PGLib = "07a8691f-3d11-4330-951b-3c50f98338be"
 PowerModels = "c36e90e8-916a-50a6-bd94-075b64ef4655"
 ExaModels = "1037b233-b668-4ce9-9b63-f9f681f55dd2"
 JLD2 = "033835bb-8acc-5ee8-8aae-3f567f8a3819"
+JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
+GOC3Benchmark = "3a45b339-860d-44d0-a64b-5f943cdd120b"
+Downloads = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
 
 [compat]
 ExaModels = "~0.8"

README.md

@@ -9,7 +9,8 @@ ExaModelsPower.jl is an optimal power flow models using ExaModels.jl
 ## Usage
 ### Static optimal power flow
 ```julia
-using ExaModelsPower, MadNLP, MadNLPGPU, CUDA
+using ExaModelsPower, MadNLP, MadNLPGPU, CUDA, ExaModels, GOC3Benchmark, JSON
+
 
 model, vars, cons = opf_model(
     "pglib_opf_case118_ieee.m";
@@ -21,11 +22,32 @@ result = madnlp(model; tol=1e-6)
 
 ### Security-constrained optimal power flow
 ```julia
-model, vars, cons = scopf_model(
-    "pglib_opf_case118_ieee.m"; contingencies = [1,2],
+#This model is based on the GOC3 formulation of the SCOPF problem
+#https://www.pnnl.gov/publications/grid-optimization-competition-challenge-3-problem-formulation
+
+#The current implementation requires a UC solution to be provided, which is then parsed with
+#the other input data to generate a structure of named tuples which can then interface with 
+#ExaModels to generate the full model. We do not make any relaxations or decompositions for this problem
+
+model, sc_data, vars, lengths = scopf_model(
+    "data/C3E4N00073D1_scenario_303.json", "data/C3E4N00073D1_scenario_303_solution.json"; 
     backend = CUDABackend()
 )
-result = madnlp(model; tol=1e-6) # currently failing
+result = madnlp(model; tol=1e-4)
+
+#Solution from GPU can be used to warm start a CPU solution or vice versa
+model_cpu, sc_data, vars, lengths = scopf_model(
+    "data/C3E4N00073D1_scenario_303.json", "data/C3E4N00073D1_scenario_303_solution.json"; 
+    result_set = [result, vars]
+)
+result_cpu = ipopt(model_cpu; tol=1e-8)
+
+#Additionally, the SC problem can be evaluated without contingencies
+model, sc_data, vars, lengths = scopf_model(
+    "data/C3E4N00073D1_scenario_303.json", "data/C3E4N00073D1_scenario_303_solution.json"; 
+    backend = CUDABackend(), include_ctg = false
+)
+result = madnlp(model; tol=1e-4)
 ```
 
 ### Multi-period optimal power flow
@@ -59,7 +81,7 @@ result = madnlp(model; tol=1e-6)
 
 #Alternatively, provide a smooth function for the charge/discharge efficiency to remove complementarity constraint
 function example_func(d, srating)
-    return d + .2/srating*d^2
+    return -((s_rating/2)^d)+1
 end
 
 model, vars, cons = mpopf_model(

src/ExaModelsPower.jl

@@ -1,15 +1,18 @@
 module ExaModelsPower
 
 import JLD2
+import Downloads
+import ExaModels: ExaCore, variable, constraint, ExaModel, objective, constraint!, convert_array, solution
 import PGLib
-import ExaModels: ExaCore, variable, constraint, ExaModel, objective, constraint!, convert_array
 import PowerModels
 
+
 include("parser.jl")
 include("opf.jl")
 include("scopf.jl")
 include("mpopf.jl")
 include("constraint.jl")
+include("sc_parser.jl")
 
 const NAMES = filter(names(@__MODULE__; all = true)) do x
     str = string(x)