JuMP Updates (#40)

* update debug models to use two sided constraints
* update packages to latest versions
* update jump models to new NL interface, update jump version lower bound in compat
* update to latest ipopt and moi versions

Project.toml

@@ -16,11 +16,11 @@ Symbolics = "0c5d862f-8b57-4792-8d23-62f2024744c7"
 [compat]
 ADNLPModels = "0.7"
 Ipopt = "1"
-JuMP = "1"
+JuMP = "1.15"
 Nonconvex = "2"
 NonconvexIpopt = "0.4"
 Optim = "1"
 Optimization = "3"
-OptimizationMOI = "0.1"
-PowerModels = "0.19"
+OptimizationMOI = "0.3"
+PowerModels = "0.20"
 Symbolics = "5"

debug/nlpmodels-jump.jl

@@ -94,8 +94,6 @@ for (i,branch) in ref[:branch]
 
     # Voltage angle difference limit
     @constraint(model, branch["angmin"] <= va_fr - va_to <= branch["angmax"])
-    #@constraint(model, va_fr - va_to <= branch["angmax"])
-    #@constraint(model, va_fr - va_to >= branch["angmin"])
 
     # Apparent power limit, from side and to side
     @constraint(model, p_fr^2 + q_fr^2 <= branch["rate_a"]^2)

debug/nonconvex-jump.jl

@@ -102,8 +102,6 @@ for (i,branch) in ref[:branch]
 
     # Voltage angle difference limit
     @constraint(model, branch["angmin"] <= va_fr - va_to <= branch["angmax"])
-    #@constraint(model, va_fr - va_to <= branch["angmax"])
-    #@constraint(model, va_fr - va_to >= branch["angmin"])
 
     # Apparent power limit, from side and to side
     @constraint(model, p_fr^2 + q_fr^2 <= branch["rate_a"]^2)

jump.jl

@@ -83,12 +83,12 @@ function solve_opf(file_name)
         b_to = branch["b_to"]
 
         # From side of the branch flow
-        JuMP.@NLconstraint(model, p_fr ==  (g+g_fr)/ttm*vm_fr^2 + (-g*tr+b*ti)/ttm*(vm_fr*vm_to*cos(va_fr-va_to)) + (-b*tr-g*ti)/ttm*(vm_fr*vm_to*sin(va_fr-va_to)) )
-        JuMP.@NLconstraint(model, q_fr == -(b+b_fr)/ttm*vm_fr^2 - (-b*tr-g*ti)/ttm*(vm_fr*vm_to*cos(va_fr-va_to)) + (-g*tr+b*ti)/ttm*(vm_fr*vm_to*sin(va_fr-va_to)) )
+        JuMP.@constraint(model, p_fr ==  (g+g_fr)/ttm*vm_fr^2 + (-g*tr+b*ti)/ttm*(vm_fr*vm_to*cos(va_fr-va_to)) + (-b*tr-g*ti)/ttm*(vm_fr*vm_to*sin(va_fr-va_to)) )
+        JuMP.@constraint(model, q_fr == -(b+b_fr)/ttm*vm_fr^2 - (-b*tr-g*ti)/ttm*(vm_fr*vm_to*cos(va_fr-va_to)) + (-g*tr+b*ti)/ttm*(vm_fr*vm_to*sin(va_fr-va_to)) )
 
         # To side of the branch flow
-        JuMP.@NLconstraint(model, p_to ==  (g+g_to)*vm_to^2 + (-g*tr-b*ti)/ttm*(vm_to*vm_fr*cos(va_to-va_fr)) + (-b*tr+g*ti)/ttm*(vm_to*vm_fr*sin(va_to-va_fr)) )
-        JuMP.@NLconstraint(model, q_to == -(b+b_to)*vm_to^2 - (-b*tr+g*ti)/ttm*(vm_to*vm_fr*cos(va_to-va_fr)) + (-g*tr-b*ti)/ttm*(vm_to*vm_fr*sin(va_to-va_fr)) )
+        JuMP.@constraint(model, p_to ==  (g+g_to)*vm_to^2 + (-g*tr-b*ti)/ttm*(vm_to*vm_fr*cos(va_to-va_fr)) + (-b*tr+g*ti)/ttm*(vm_to*vm_fr*sin(va_to-va_fr)) )
+        JuMP.@constraint(model, q_to == -(b+b_to)*vm_to^2 - (-b*tr+g*ti)/ttm*(vm_to*vm_fr*cos(va_to-va_fr)) + (-g*tr-b*ti)/ttm*(vm_to*vm_fr*sin(va_to-va_fr)) )
 
         # Voltage angle difference limit
         JuMP.@constraint(model, branch["angmin"] <= va_fr - va_to <= branch["angmax"])
@@ -116,7 +116,7 @@ function solve_opf(file_name)
     solve_time = time() - time_solve_start
     total_time = time() - time_data_start
 
-    nlp_block = JuMP.MOI.get(model, JuMP.MOI.NLPBlock())
+    nlp_block = JuMP.MOI.get(JuMP.unsafe_backend(model), JuMP.MOI.NLPBlock())
     total_callback_time =
         nlp_block.evaluator.eval_objective_timer +
         nlp_block.evaluator.eval_objective_gradient_timer +