pglib_case5_sad.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MathOptInterface"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using PowerModels, Gurobi, Ipopt, JuMP, COSMO, Mosek, MosekTools, MathOptInterface\n",
    "const MOI = MathOptInterface"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"../pglib-opf/sad/pglib_opf_case5_pjm__sad.m\""
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "file = \"../pglib-opf/sad/pglib_opf_case5_pjm__sad.m\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m[info | PowerModels]: extending matpower format with data: areas 1x3\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 4: [4000.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 1: [1400.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 5: [1000.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 2: [1500.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 3: [3000.0, 0.0]\u001b[39m\n",
      "\n",
      "******************************************************************************\n",
      "This program contains Ipopt, a library for large-scale nonlinear optimization.\n",
      " Ipopt is released as open source code under the Eclipse Public License (EPL).\n",
      "         For more information visit http://projects.coin-or.org/Ipopt\n",
      "******************************************************************************\n",
      "\n",
      "This is Ipopt version 3.13.2, running with linear solver mumps.\n",
      "NOTE: Other linear solvers might be more efficient (see Ipopt documentation).\n",
      "\n",
      "Number of nonzeros in equality constraint Jacobian...:      299\n",
      "Number of nonzeros in inequality constraint Jacobian.:      140\n",
      "Number of nonzeros in Lagrangian Hessian.............:      236\n",
      "\n",
      "Total number of variables............................:       44\n",
      "                     variables with only lower bounds:        0\n",
      "                variables with lower and upper bounds:       44\n",
      "                     variables with only upper bounds:        0\n",
      "Total number of equality constraints.................:       35\n",
      "Total number of inequality constraints...............:       34\n",
      "        inequality constraints with only lower bounds:       11\n",
      "   inequality constraints with lower and upper bounds:        0\n",
      "        inequality constraints with only upper bounds:       23\n",
      "\n",
      "iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls\n",
      "   0  1.0059989e+02 3.99e+00 2.88e+01  -1.0 0.00e+00    -  0.00e+00 0.00e+00   0\n",
      "   1  6.4873444e+03 2.80e+00 8.17e+01  -1.0 2.78e+00    -  4.11e-03 2.97e-01h  1\n",
      "   2  6.4129814e+03 2.80e+00 8.13e+01  -1.0 1.57e+01    -  8.38e-02 2.56e-03f  1\n",
      "   3  5.8153521e+03 2.69e+00 1.78e+02  -1.0 1.32e+01    -  8.80e-02 3.90e-02f  1\n",
      "   4  6.8645446e+03 2.48e+00 6.08e+02  -1.0 4.46e+00    -  2.67e-01 7.85e-02h  1\n",
      "   5  9.2729004e+03 2.11e+00 8.22e+02  -1.0 4.11e+00    -  2.77e-01 1.49e-01h  1\n",
      "   6  1.1140991e+04 1.86e+00 1.11e+03  -1.0 4.35e+00    -  1.85e-01 1.18e-01h  1\n",
      "   7  2.3770874e+04 2.79e-01 2.45e+02  -1.0 3.25e+00    -  5.46e-01 8.50e-01h  1\n",
      "   8  2.3949873e+04 2.55e-01 4.51e+02  -1.0 2.90e+00    -  5.32e-01 8.88e-02h  1\n",
      "   9  2.4151016e+04 2.24e-01 8.91e+02  -1.0 5.54e+00    -  2.46e-01 1.21e-01h  2\n",
      "iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls\n",
      "  10  2.5455034e+04 1.02e-01 1.67e+02  -1.0 5.08e+00    -  2.96e-01 7.12e-01H  1\n",
      "  11  2.5685317e+04 4.23e-02 2.89e+02  -1.0 2.22e+00    -  8.21e-01 3.45e-01h  1\n",
      "  12  2.5910880e+04 2.03e-02 1.92e+02  -1.0 2.60e+00    -  3.60e-01 5.20e-01h  1\n",
      "  13  2.6149536e+04 9.08e-04 3.41e-01  -1.0 8.67e-01    -  1.00e+00 1.00e+00h  1\n",
      "  14  2.6120398e+04 3.28e-05 5.17e-02  -1.7 1.65e-01    -  1.00e+00 1.00e+00f  1\n",
      "  15  2.6115912e+04 6.72e-06 1.54e-02  -2.5 5.51e-02    -  1.00e+00 1.00e+00h  1\n",
      "  16  2.6115237e+04 3.22e-07 3.98e-04  -3.8 1.22e-02    -  1.00e+00 1.00e+00h  1\n",
      "  17  2.6115195e+04 7.91e-09 1.10e-06  -5.7 1.87e-03    -  1.00e+00 1.00e+00h  1\n",
      "  18  2.6115194e+04 3.16e-13 8.68e-11  -8.6 1.16e-05    -  1.00e+00 1.00e+00h  1\n",
      "\n",
      "Number of Iterations....: 18\n",
      "\n",
      "                                   (scaled)                 (unscaled)\n",
      "Objective...............:   6.5287985091102314e+02    2.6115194036440924e+04\n",
      "Dual infeasibility......:   8.6759714214943860e-11    3.4703885685977544e-09\n",
      "Constraint violation....:   3.1582375603633750e-13    3.1582375603633750e-13\n",
      "Complementarity.........:   2.5408966381950159e-09    1.0163586552780063e-07\n",
      "Overall NLP error.......:   2.5408966381950159e-09    1.0163586552780063e-07\n",
      "\n",
      "\n",
      "Number of objective function evaluations             = 23\n",
      "Number of objective gradient evaluations             = 19\n",
      "Number of equality constraint evaluations            = 23\n",
      "Number of inequality constraint evaluations          = 23\n",
      "Number of equality constraint Jacobian evaluations   = 19\n",
      "Number of inequality constraint Jacobian evaluations = 19\n",
      "Number of Lagrangian Hessian evaluations             = 18\n",
      "Total CPU secs in IPOPT (w/o function evaluations)   =      1.817\n",
      "Total CPU secs in NLP function evaluations           =      0.653\n",
      "\n",
      "EXIT: Optimal Solution Found.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Dict{String,Any} with 8 entries:\n",
       "  \"solve_time\"         => 2.87869\n",
       "  \"optimizer\"          => \"Ipopt\"\n",
       "  \"termination_status\" => LOCALLY_SOLVED\n",
       "  \"dual_status\"        => FEASIBLE_POINT\n",
       "  \"primal_status\"      => FEASIBLE_POINT\n",
       "  \"objective\"          => 26115.2\n",
       "  \"solution\"           => Dict{String,Any}(\"baseMVA\"=>100.0,\"branch\"=>Dict{Stri…\n",
       "  \"objective_lb\"       => -Inf"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ipopt_rec = run_opf(file, ACRPowerModel, Ipopt.Optimizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m[info | PowerModels]: extending matpower format with data: areas 1x3\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 4: [4000.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 1: [1400.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 5: [1000.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 2: [1500.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 3: [3000.0, 0.0]\u001b[39m\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Warning: MathOptInterface.VariablePrimalStart() is not supported by MathOptInterface.Bridges.LazyBridgeOptimizer{MosekModel}. This information will be discarded.\n",
      "└ @ MathOptInterface.Utilities /home/weiqizhang/.julia/packages/MathOptInterface/RmalA/src/Utilities/copy.jl:140\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Problem\n",
      "  Name                   :                 \n",
      "  Objective sense        : min             \n",
      "  Type                   : CONIC (conic optimization problem)\n",
      "  Constraints            : 196             \n",
      "  Cones                  : 12              \n",
      "  Scalar variables       : 115             \n",
      "  Matrix variables       : 3               \n",
      "  Integer variables      : 0               \n",
      "\n",
      "Optimizer started.\n",
      "Presolve started.\n",
      "Linear dependency checker started.\n",
      "Linear dependency checker terminated.\n",
      "Eliminator started.\n",
      "Freed constraints in eliminator : 17\n",
      "Eliminator terminated.\n",
      "Eliminator - tries                  : 1                 time                   : 0.00            \n",
      "Lin. dep.  - tries                  : 1                 time                   : 0.00            \n",
      "Lin. dep.  - number                 : 9               \n",
      "Presolve terminated. Time: 0.00    \n",
      "Problem\n",
      "  Name                   :                 \n",
      "  Objective sense        : min             \n",
      "  Type                   : CONIC (conic optimization problem)\n",
      "  Constraints            : 196             \n",
      "  Cones                  : 12              \n",
      "  Scalar variables       : 115             \n",
      "  Matrix variables       : 3               \n",
      "  Integer variables      : 0               \n",
      "\n",
      "Optimizer  - threads                : 4               \n",
      "Optimizer  - solved problem         : the primal      \n",
      "Optimizer  - Constraints            : 121\n",
      "Optimizer  - Cones                  : 13\n",
      "Optimizer  - Scalar variables       : 89                conic                  : 39              \n",
      "Optimizer  - Semi-definite variables: 3                 scalarized             : 63              \n",
      "Factor     - setup time             : 0.00              dense det. time        : 0.00            \n",
      "Factor     - ML order time          : 0.00              GP order time          : 0.00            \n",
      "Factor     - nonzeros before factor : 1540              after factor           : 2188            \n",
      "Factor     - dense dim.             : 0                 flops                  : 5.39e+04        \n",
      "ITE PFEAS    DFEAS    GFEAS    PRSTATUS   POBJ              DOBJ              MU       TIME  \n",
      "0   5.0e+00  4.0e+03  4.8e+01  0.00e+00   2.500000000e+04   2.495312000e+04   1.0e+00  0.02  \n",
      "1   5.8e-01  4.7e+02  1.6e+01  -1.00e+00  2.319650836e+04   2.315725846e+04   1.2e-01  0.02  \n",
      "2   2.7e-01  2.2e+02  1.1e+01  -9.74e-01  2.116196436e+04   2.113316948e+04   5.4e-02  0.02  \n",
      "3   1.2e-01  9.5e+01  5.7e+00  -7.62e-01  1.886983218e+04   1.885882706e+04   2.4e-02  0.02  \n",
      "4   5.1e-02  4.1e+01  2.3e+00  -2.87e-01  1.559110153e+04   1.559068565e+04   1.0e-02  0.02  \n",
      "5   2.9e-02  2.4e+01  1.2e+00  2.05e-01   1.398547774e+04   1.398689521e+04   5.9e-03  0.02  \n",
      "6   1.4e-02  1.2e+01  5.4e-01  2.96e-01   1.288654581e+04   1.289080560e+04   2.9e-03  0.02  \n",
      "7   6.2e-03  5.0e+00  1.6e-01  6.05e-01   1.177600100e+04   1.177786283e+04   1.2e-03  0.02  \n",
      "8   3.1e-03  2.5e+00  7.6e-02  5.20e-01   1.153847056e+04   1.154150756e+04   6.2e-04  0.02  \n",
      "9   1.2e-03  9.9e-01  6.1e-02  -4.91e-01  1.238339230e+04   1.240427479e+04   2.5e-04  0.02  \n",
      "10  4.5e-04  3.6e-01  2.9e-02  -5.14e-01  1.373538482e+04   1.377600645e+04   9.0e-05  0.02  \n",
      "11  2.7e-04  2.2e-01  1.5e-02  4.59e-02   1.489298852e+04   1.492370164e+04   5.4e-05  0.03  \n",
      "12  2.0e-04  1.6e-01  1.3e-02  -1.32e-01  1.519451394e+04   1.523386580e+04   4.1e-05  0.03  \n",
      "13  1.4e-04  1.1e-01  8.3e-03  9.49e-02   1.652356113e+04   1.656224148e+04   2.7e-05  0.03  \n",
      "14  6.7e-05  5.4e-02  3.4e-03  2.93e-01   1.846962479e+04   1.849630479e+04   1.3e-05  0.03  \n",
      "15  4.8e-05  3.8e-02  2.5e-03  1.19e-01   1.936193267e+04   1.939208008e+04   9.5e-06  0.03  \n",
      "16  3.3e-05  2.6e-02  1.9e-03  1.61e-01   1.990280402e+04   1.993721837e+04   6.6e-06  0.03  \n",
      "17  2.2e-05  1.8e-02  8.6e-04  4.32e-01   2.199214743e+04   2.200742660e+04   4.5e-06  0.03  \n",
      "18  1.3e-05  1.1e-02  4.5e-04  6.29e-01   2.307933353e+04   2.309151776e+04   2.6e-06  0.03  \n",
      "19  6.1e-06  4.9e-03  1.8e-04  5.49e-01   2.437430741e+04   2.438333530e+04   1.2e-06  0.03  \n",
      "20  2.6e-06  2.1e-03  5.7e-05  7.84e-01   2.524696306e+04   2.525227344e+04   5.1e-07  0.03  \n",
      "21  7.3e-07  5.8e-04  9.5e-06  8.89e-01   2.584254930e+04   2.584437977e+04   1.5e-07  0.03  \n",
      "22  2.5e-07  2.0e-04  2.0e-06  9.32e-01   2.601335319e+04   2.601407057e+04   5.0e-08  0.03  \n",
      "23  3.3e-08  2.6e-05  1.1e-07  9.75e-01   2.610063067e+04   2.610074424e+04   6.6e-09  0.03  \n",
      "24  1.9e-08  5.5e-06  1.1e-08  1.00e+00   2.611198604e+04   2.611201187e+04   1.4e-09  0.04  \n",
      "25  5.0e-09  9.0e-07  7.1e-10  1.00e+00   2.611466863e+04   2.611467287e+04   2.3e-10  0.04  \n",
      "26  5.0e-09  9.0e-07  7.1e-10  1.00e+00   2.611466863e+04   2.611467287e+04   2.3e-10  0.04  \n",
      "27  5.0e-09  9.0e-07  7.1e-10  1.00e+00   2.611466877e+04   2.611467301e+04   2.3e-10  0.04  \n",
      "28  5.0e-09  9.0e-07  7.1e-10  1.00e+00   2.611466877e+04   2.611467301e+04   2.3e-10  0.04  \n",
      "Optimizer terminated. Time: 0.06    \n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Dict{String,Any} with 8 entries:\n",
       "  \"solve_time\"         => 0.0566931\n",
       "  \"optimizer\"          => \"Mosek\"\n",
       "  \"termination_status\" => SLOW_PROGRESS\n",
       "  \"dual_status\"        => FEASIBLE_POINT\n",
       "  \"primal_status\"      => FEASIBLE_POINT\n",
       "  \"objective\"          => 26114.7\n",
       "  \"solution\"           => Dict{String,Any}(\"baseMVA\"=>100.0,\"branch\"=>Dict{Stri…\n",
       "  \"objective_lb\"       => 0.0"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mosek_sdp = run_opf(file, SparseSDPWRMPowerModel, Mosek.Optimizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m[info | PowerModels]: extending matpower format with data: areas 1x3\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 4: [4000.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 1: [1400.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 5: [1000.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 2: [1500.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 3: [3000.0, 0.0]\u001b[39m\n",
      "Academic license - for non-commercial use only\n",
      "Academic license - for non-commercial use only\n",
      "Gurobi Optimizer version 9.0.2 build v9.0.2rc0 (linux64)\n",
      "Optimize a model with 58 rows, 51 columns and 190 nonzeros\n",
      "Model fingerprint: 0xf7cfeb27\n",
      "Model has 18 quadratic constraints\n",
      "Coefficient statistics:\n",
      "  Matrix range     [2e-02, 2e+02]\n",
      "  QMatrix range    [1e+00, 1e+00]\n",
      "  Objective range  [1e+03, 4e+03]\n",
      "  Bounds range     [3e-02, 6e+00]\n",
      "  RHS range        [3e-01, 4e+00]\n",
      "  QRHS range       [6e+00, 2e+01]\n",
      "Presolve removed 0 rows and 1 columns\n",
      "Presolve time: 0.00s\n",
      "Presolved: 154 rows, 74 columns, 309 nonzeros\n",
      "Presolved model has 18 second-order cone constraints\n",
      "Ordering time: 0.00s\n",
      "\n",
      "Barrier statistics:\n",
      " AA' NZ     : 1.283e+03\n",
      " Factor NZ  : 2.010e+03\n",
      " Factor Ops : 3.034e+04 (less than 1 second per iteration)\n",
      " Threads    : 1\n",
      "\n",
      "                  Objective                Residual\n",
      "Iter       Primal          Dual         Primal    Dual     Compl     Time\n",
      "   0   5.75675093e+04 -7.81345187e+03  4.05e+00 1.21e+03  3.34e+03     0s\n",
      "   1   2.41445365e+04 -2.48519581e+04  1.19e-01 1.69e+02  4.79e+02     0s\n",
      "   2   2.12651001e+04  1.96084396e+03  6.92e-02 4.38e+01  1.63e+02     0s\n",
      "   3   2.16442127e+04  1.27690198e+04  4.59e-02 1.79e+01  8.15e+01     0s\n",
      "   4   2.15660629e+04  1.76831874e+04  3.40e-02 1.04e+01  4.97e+01     0s\n",
      "   5   2.19180262e+04  1.96739158e+04  2.19e-02 7.59e+00  3.56e+01     0s\n",
      "   6   2.53777157e+04  2.24517553e+04  3.66e-03 1.24e+00  1.99e+01     0s\n",
      "   7   2.52831318e+04  2.49738334e+04  8.03e-04 3.02e-02  2.55e+00     0s\n",
      "   8   2.51772362e+04  2.51551518e+04  7.13e-05 1.24e-03  1.99e-01     0s\n",
      "   9   2.51715394e+04  2.51708443e+04  1.94e-06 4.20e-06  5.85e-03     0s\n",
      "  10   2.51711598e+04  2.51710570e+04  2.44e-07 1.24e-07  8.14e-04     0s\n",
      "  11   2.51711024e+04  2.51710906e+04  3.12e-08 3.57e-09  9.69e-05     0s\n",
      "  12   2.51710967e+04  2.51710936e+04  1.00e-08 1.79e-09  2.76e-05     0s\n",
      "  13   2.51710950e+04  2.51710943e+04  2.47e-09 1.75e-09  6.54e-06     0s\n",
      "  14   2.51710946e+04  2.51710945e+04  6.59e-10 1.40e-08  1.62e-06     0s\n",
      "  15   2.51710946e+04  2.51710946e+04  1.06e-10 7.04e-07  3.61e-07     0s\n",
      "\n",
      "Barrier solved model in 15 iterations and 0.01 seconds\n",
      "Optimal objective 2.51710946e+04\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Dict{String,Any} with 8 entries:\n",
       "  \"solve_time\"         => 0.00769997\n",
       "  \"optimizer\"          => \"Gurobi\"\n",
       "  \"termination_status\" => OPTIMAL\n",
       "  \"dual_status\"        => NO_SOLUTION\n",
       "  \"primal_status\"      => FEASIBLE_POINT\n",
       "  \"objective\"          => 25171.1\n",
       "  \"solution\"           => Dict{String,Any}(\"baseMVA\"=>100.0,\"branch\"=>Dict{Stri…\n",
       "  \"objective_lb\"       => -Inf"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grb_soc = run_opf(file, SOCWRPowerModel, Gurobi.Optimizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[32m[info | PowerModels]: extending matpower format with data: areas 1x3\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 4: [4000.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 1: [1400.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 5: [1000.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 2: [1500.0, 0.0]\u001b[39m\n",
      "\u001b[32m[info | PowerModels]: removing 1 cost terms from generator 3: [3000.0, 0.0]\u001b[39m\n",
      "Min 4000 0_pg[4] + 1500 0_pg[2] + 3000 0_pg[3] + 1000 0_pg[5] + 1400 0_pg[1]\n",
      "Subject to\n",
      " 0_vi[4] = 0.0\n",
      " 0_p[(6, 4, 5)] + 0_p[(2, 4, 1)] + 0_p[(5, 4, 3)] - 0_pg[4] = -10.748800000000001\n",
      " 0_q[(6, 4, 5)] + 0_q[(2, 4, 1)] + 0_q[(5, 4, 3)] - 0_qg[4] = -1.3147\n",
      " 0_p[(4, 2, 3)] + 0_p[(1, 2, 1)] = -8.0616\n",
      " 0_q[(4, 2, 3)] + 0_q[(1, 2, 1)] = -0.9861\n",
      " 0_p[(5, 3, 4)] + 0_p[(4, 3, 2)] - 0_pg[3] = -8.0616\n",
      " 0_q[(5, 3, 4)] + 0_q[(4, 3, 2)] - 0_qg[3] = -0.9861\n",
      " 0_p[(3, 5, 1)] + 0_p[(6, 5, 4)] - 0_pg[5] = 0.0\n",
      " 0_q[(3, 5, 1)] + 0_q[(6, 5, 4)] - 0_qg[5] = 0.0\n",
      " 0_p[(2, 1, 4)] + 0_p[(3, 1, 5)] + 0_p[(1, 1, 2)] - 0_pg[2] - 0_pg[1] = 0.0\n",
      " 0_q[(2, 1, 4)] + 0_q[(3, 1, 5)] + 0_q[(1, 1, 2)] - 0_qg[2] - 0_qg[1] = 0.0\n",
      " -9.167583425009166 0_vr[2]² - 9.167583425009166 0_vi[2]² + 9.167583425009166 0_vr[2]*0_vr[3] + 9.167583425009166 0_vi[2]*0_vi[3] - 91.67583425009167 0_vi[2]*0_vr[3] + 91.67583425009167 0_vi[3]*0_vr[2] + 0_p[(4, 2, 3)] = 0.0\n",
      " -91.66657425009167 0_vr[2]² - 91.66657425009167 0_vi[2]² + 91.67583425009167 0_vr[2]*0_vr[3] + 91.67583425009167 0_vi[2]*0_vi[3] + 9.167583425009166 0_vi[2]*0_vr[3] - 9.167583425009166 0_vi[3]*0_vr[2] + 0_q[(4, 2, 3)] = 0.0\n",
      " -9.167583425009166 0_vr[3]² - 9.167583425009166 0_vi[3]² + 9.167583425009166 0_vr[2]*0_vr[3] + 9.167583425009166 0_vi[2]*0_vi[3] + 91.67583425009167 0_vi[2]*0_vr[3] - 91.67583425009167 0_vr[2]*0_vi[3] + 0_p[(4, 3, 2)] = 0.0\n",
      " -91.66657425009167 0_vr[3]² - 91.66657425009167 0_vi[3]² + 91.67583425009167 0_vr[2]*0_vr[3] + 91.67583425009167 0_vi[2]*0_vi[3] - 9.167583425009166 0_vi[2]*0_vr[3] + 9.167583425009166 0_vr[2]*0_vi[3] + 0_q[(4, 3, 2)] = 0.0\n",
      " -3.2569046378322044 0_vr[1]² - 3.2569046378322044 0_vi[1]² + 3.2569046378322044 0_vr[1]*0_vr[4] + 3.2569046378322044 0_vi[1]*0_vi[4] - 32.56904637832204 0_vi[1]*0_vr[4] + 32.56904637832204 0_vi[4]*0_vr[1] + 0_p[(2, 1, 4)] = 0.0\n",
      " -32.56575637832204 0_vr[1]² - 32.56575637832204 0_vi[1]² + 32.56904637832204 0_vr[1]*0_vr[4] + 32.56904637832204 0_vi[1]*0_vi[4] + 3.2569046378322044 0_vi[1]*0_vr[4] - 3.2569046378322044 0_vi[4]*0_vr[1] + 0_q[(2, 1, 4)] = 0.0\n",
      " -3.2569046378322044 0_vr[4]² - 3.2569046378322044 0_vi[4]² + 3.2569046378322044 0_vr[1]*0_vr[4] + 3.2569046378322044 0_vi[1]*0_vi[4] + 32.56904637832204 0_vi[1]*0_vr[4] - 32.56904637832204 0_vr[1]*0_vi[4] + 0_p[(2, 4, 1)] = 0.0\n",
      " -32.56575637832204 0_vr[4]² - 32.56575637832204 0_vi[4]² + 32.56904637832204 0_vr[1]*0_vr[4] + 32.56904637832204 0_vi[1]*0_vi[4] - 3.2569046378322044 0_vi[1]*0_vr[4] + 3.2569046378322044 0_vr[1]*0_vi[4] + 0_q[(2, 4, 1)] = 0.0\n",
      " -15.470297029702971 0_vr[1]² - 15.470297029702971 0_vi[1]² + 15.470297029702971 0_vr[1]*0_vr[5] + 15.470297029702971 0_vi[1]*0_vi[5] - 154.7029702970297 0_vi[1]*0_vr[5] + 154.7029702970297 0_vi[5]*0_vr[1] + 0_p[(3, 1, 5)] = 0.0\n",
      " -154.68734029702972 0_vr[1]² - 154.68734029702972 0_vi[1]² + 154.7029702970297 0_vr[1]*0_vr[5] + 154.7029702970297 0_vi[1]*0_vi[5] + 15.470297029702971 0_vi[1]*0_vr[5] - 15.470297029702971 0_vi[5]*0_vr[1] + 0_q[(3, 1, 5)] = 0.0\n",
      " -15.470297029702971 0_vr[5]² - 15.470297029702971 0_vi[5]² + 15.470297029702971 0_vr[1]*0_vr[5] + 15.470297029702971 0_vi[1]*0_vi[5] + 154.7029702970297 0_vi[1]*0_vr[5] - 154.7029702970297 0_vr[1]*0_vi[5] + 0_p[(3, 5, 1)] = 0.0\n",
      " -154.68734029702972 0_vr[5]² - 154.68734029702972 0_vi[5]² + 154.7029702970297 0_vr[1]*0_vr[5] + 154.7029702970297 0_vi[1]*0_vi[5] - 15.470297029702971 0_vi[1]*0_vr[5] + 15.470297029702971 0_vr[1]*0_vi[5] + 0_q[(3, 5, 1)] = 0.0\n",
      " -3.3336667000033335 0_vr[3]² - 3.3336667000033335 0_vi[3]² + 3.3336667000033335 0_vr[3]*0_vr[4] + 3.3336667000033335 0_vi[3]*0_vi[4] - 33.33666700003334 0_vi[3]*0_vr[4] + 33.33666700003334 0_vi[4]*0_vr[3] + 0_p[(5, 3, 4)] = 0.0\n",
      " -33.33329700003334 0_vr[3]² - 33.33329700003334 0_vi[3]² + 33.33666700003334 0_vr[3]*0_vr[4] + 33.33666700003334 0_vi[3]*0_vi[4] + 3.3336667000033335 0_vi[3]*0_vr[4] - 3.3336667000033335 0_vi[4]*0_vr[3] + 0_q[(5, 3, 4)] = 0.0\n",
      " -3.3336667000033335 0_vr[4]² - 3.3336667000033335 0_vi[4]² + 3.3336667000033335 0_vr[3]*0_vr[4] + 3.3336667000033335 0_vi[3]*0_vi[4] + 33.33666700003334 0_vi[3]*0_vr[4] - 33.33666700003334 0_vr[3]*0_vi[4] + 0_p[(5, 4, 3)] = 0.0\n",
      " -33.33329700003334 0_vr[4]² - 33.33329700003334 0_vi[4]² + 33.33666700003334 0_vr[3]*0_vr[4] + 33.33666700003334 0_vi[3]*0_vi[4] - 3.3336667000033335 0_vi[3]*0_vr[4] + 3.3336667000033335 0_vr[3]*0_vi[4] + 0_q[(5, 4, 3)] = 0.0\n",
      " -3.3336667000033335 0_vr[4]² - 3.3336667000033335 0_vi[4]² + 3.3336667000033335 0_vr[4]*0_vr[5] + 3.3336667000033335 0_vi[4]*0_vi[5] - 33.33666700003334 0_vi[4]*0_vr[5] + 33.33666700003334 0_vi[5]*0_vr[4] + 0_p[(6, 4, 5)] = 0.0\n",
      " -33.33329700003334 0_vr[4]² - 33.33329700003334 0_vi[4]² + 33.33666700003334 0_vr[4]*0_vr[5] + 33.33666700003334 0_vi[4]*0_vi[5] + 3.3336667000033335 0_vi[4]*0_vr[5] - 3.3336667000033335 0_vi[5]*0_vr[4] + 0_q[(6, 4, 5)] = 0.0\n",
      " -3.3336667000033335 0_vr[5]² - 3.3336667000033335 0_vi[5]² + 3.3336667000033335 0_vr[4]*0_vr[5] + 3.3336667000033335 0_vi[4]*0_vi[5] + 33.33666700003334 0_vi[4]*0_vr[5] - 33.33666700003334 0_vr[4]*0_vi[5] + 0_p[(6, 5, 4)] = 0.0\n",
      " -33.33329700003334 0_vr[5]² - 33.33329700003334 0_vi[5]² + 33.33666700003334 0_vr[4]*0_vr[5] + 33.33666700003334 0_vi[4]*0_vi[5] - 3.3336667000033335 0_vi[4]*0_vr[5] + 3.3336667000033335 0_vr[4]*0_vi[5] + 0_q[(6, 5, 4)] = 0.0\n",
      " -3.5234840209999647 0_vr[1]² - 3.5234840209999647 0_vi[1]² + 3.5234840209999647 0_vr[1]*0_vr[2] + 3.5234840209999647 0_vi[1]*0_vi[2] - 35.234840209999646 0_vi[1]*0_vr[2] + 35.234840209999646 0_vi[2]*0_vr[1] + 0_p[(1, 1, 2)] = 0.0\n",
      " -35.231280209999646 0_vr[1]² - 35.231280209999646 0_vi[1]² + 35.234840209999646 0_vr[1]*0_vr[2] + 35.234840209999646 0_vi[1]*0_vi[2] + 3.5234840209999647 0_vi[1]*0_vr[2] - 3.5234840209999647 0_vi[2]*0_vr[1] + 0_q[(1, 1, 2)] = 0.0\n",
      " -3.5234840209999647 0_vr[2]² - 3.5234840209999647 0_vi[2]² + 3.5234840209999647 0_vr[1]*0_vr[2] + 3.5234840209999647 0_vi[1]*0_vi[2] + 35.234840209999646 0_vi[1]*0_vr[2] - 35.234840209999646 0_vr[1]*0_vi[2] + 0_p[(1, 2, 1)] = 0.0\n",
      " -35.231280209999646 0_vr[2]² - 35.231280209999646 0_vi[2]² + 35.234840209999646 0_vr[1]*0_vr[2] + 35.234840209999646 0_vi[1]*0_vi[2] - 3.5234840209999647 0_vi[1]*0_vr[2] + 3.5234840209999647 0_vr[1]*0_vi[2] + 0_q[(1, 2, 1)] = 0.0\n",
      " -0_vr[4]² - 0_vi[4]² ≥ -1.2100000000000002\n",
      " -0_vr[2]² - 0_vi[2]² ≥ -1.2100000000000002\n",
      " -0_vr[3]² - 0_vi[3]² ≥ -1.2100000000000002\n",
      " -0_vr[5]² - 0_vi[5]² ≥ -1.2100000000000002\n",
      " -0_vr[1]² - 0_vi[1]² ≥ -1.2100000000000002\n",
      " 0_vi[2]*0_vr[3] - 0_vi[3]*0_vr[2] + 0.5773502691896257 0_vr[2]*0_vr[3] + 0.5773502691896257 0_vi[2]*0_vi[3] ≥ 0.0\n",
      " 0_vi[1]*0_vr[4] - 0_vi[4]*0_vr[1] + 0.5773502691896257 0_vr[1]*0_vr[4] + 0.5773502691896257 0_vi[1]*0_vi[4] ≥ 0.0\n",
      " 0_vi[1]*0_vr[5] - 0_vi[5]*0_vr[1] + 0.5773502691896257 0_vr[1]*0_vr[5] + 0.5773502691896257 0_vi[1]*0_vi[5] ≥ 0.0\n",
      " 0_vi[3]*0_vr[4] - 0_vi[4]*0_vr[3] + 0.5773502691896257 0_vr[3]*0_vr[4] + 0.5773502691896257 0_vi[3]*0_vi[4] ≥ 0.0\n",
      " 0_vi[4]*0_vr[5] - 0_vi[5]*0_vr[4] + 0.5773502691896257 0_vr[4]*0_vr[5] + 0.5773502691896257 0_vi[4]*0_vi[5] ≥ 0.0\n",
      " 0_vi[1]*0_vr[2] - 0_vi[2]*0_vr[1] + 0.5773502691896257 0_vr[1]*0_vr[2] + 0.5773502691896257 0_vi[1]*0_vi[2] ≥ 0.0\n",
      " -0_vr[4]² - 0_vi[4]² ≤ -0.81\n",
      " -0_vr[2]² - 0_vi[2]² ≤ -0.81\n",
      " -0_vr[3]² - 0_vi[3]² ≤ -0.81\n",
      " -0_vr[5]² - 0_vi[5]² ≤ -0.81\n",
      " -0_vr[1]² - 0_vi[1]² ≤ -0.81\n",
      " 0_vi[2]*0_vr[3] - 0_vi[3]*0_vr[2] - 0.5773502691896257 0_vr[2]*0_vr[3] - 0.5773502691896257 0_vi[2]*0_vi[3] ≤ 0.0\n",
      " 0_p[(4, 2, 3)]² + 0_q[(4, 2, 3)]² ≤ 18.147599999999997\n",
      " 0_p[(4, 3, 2)]² + 0_q[(4, 3, 2)]² ≤ 18.147599999999997\n",
      " 0_vi[1]*0_vr[4] - 0_vi[4]*0_vr[1] - 0.5773502691896257 0_vr[1]*0_vr[4] - 0.5773502691896257 0_vi[1]*0_vi[4] ≤ 0.0\n",
      " 0_p[(2, 1, 4)]² + 0_q[(2, 1, 4)]² ≤ 18.147599999999997\n",
      " 0_p[(2, 4, 1)]² + 0_q[(2, 4, 1)]² ≤ 18.147599999999997\n",
      " 0_vi[1]*0_vr[5] - 0_vi[5]*0_vr[1] - 0.5773502691896257 0_vr[1]*0_vr[5] - 0.5773502691896257 0_vi[1]*0_vi[5] ≤ 0.0\n",
      " 0_p[(3, 1, 5)]² + 0_q[(3, 1, 5)]² ≤ 18.147599999999997\n",
      " 0_p[(3, 5, 1)]² + 0_q[(3, 5, 1)]² ≤ 18.147599999999997\n",
      " 0_vi[3]*0_vr[4] - 0_vi[4]*0_vr[3] - 0.5773502691896257 0_vr[3]*0_vr[4] - 0.5773502691896257 0_vi[3]*0_vi[4] ≤ 0.0\n",
      " 0_p[(5, 3, 4)]² + 0_q[(5, 3, 4)]² ≤ 18.147599999999997\n",
      " 0_p[(5, 4, 3)]² + 0_q[(5, 4, 3)]² ≤ 18.147599999999997\n",
      " 0_vi[4]*0_vr[5] - 0_vi[5]*0_vr[4] - 0.5773502691896257 0_vr[4]*0_vr[5] - 0.5773502691896257 0_vi[4]*0_vi[5] ≤ 0.0\n",
      " 0_p[(6, 4, 5)]² + 0_q[(6, 4, 5)]² ≤ 5.76\n",
      " 0_p[(6, 5, 4)]² + 0_q[(6, 5, 4)]² ≤ 5.76\n",
      " 0_vi[1]*0_vr[2] - 0_vi[2]*0_vr[1] - 0.5773502691896257 0_vr[1]*0_vr[2] - 0.5773502691896257 0_vi[1]*0_vi[2] ≤ 0.0\n",
      " 0_p[(1, 1, 2)]² + 0_q[(1, 1, 2)]² ≤ 16.0\n",
      " 0_p[(1, 2, 1)]² + 0_q[(1, 2, 1)]² ≤ 16.0\n",
      " 0_vr[4] ≥ -1.1\n",
      " 0_vr[2] ≥ -1.1\n",
      " 0_vr[3] ≥ -1.1\n",
      " 0_vr[5] ≥ -1.1\n",
      " 0_vr[1] ≥ -1.1\n",
      " 0_vi[4] ≥ -1.1\n",
      " 0_vi[2] ≥ -1.1\n",
      " 0_vi[3] ≥ -1.1\n",
      " 0_vi[5] ≥ -1.1\n",
      " 0_vi[1] ≥ -1.1\n",
      " 0_pg[4] ≥ 0.0\n",
      " 0_pg[2] ≥ 0.0\n",
      " 0_pg[3] ≥ 0.0\n",
      " 0_pg[5] ≥ 0.0\n",
      " 0_pg[1] ≥ 0.0\n",
      " 0_qg[4] ≥ -5.86\n",
      " 0_qg[2] ≥ -1.776\n",
      " 0_qg[3] ≥ -5.75\n",
      " 0_qg[5] ≥ -4.5\n",
      " 0_qg[1] ≥ -1.776\n",
      " 0_p[(4, 2, 3)] ≥ -4.26\n",
      " 0_p[(2, 1, 4)] ≥ -4.26\n",
      " 0_p[(3, 1, 5)] ≥ -4.26\n",
      " 0_p[(5, 3, 4)] ≥ -4.26\n",
      " 0_p[(6, 4, 5)] ≥ -2.4\n",
      " 0_p[(1, 1, 2)] ≥ -4.0\n",
      " 0_p[(4, 3, 2)] ≥ -4.26\n",
      " 0_p[(2, 4, 1)] ≥ -4.26\n",
      " 0_p[(3, 5, 1)] ≥ -4.26\n",
      " 0_p[(5, 4, 3)] ≥ -4.26\n",
      " 0_p[(6, 5, 4)] ≥ -2.4\n",
      " 0_p[(1, 2, 1)] ≥ -4.0\n",
      " 0_q[(4, 2, 3)] ≥ -4.26\n",
      " 0_q[(2, 1, 4)] ≥ -4.26\n",
      " 0_q[(3, 1, 5)] ≥ -4.26\n",
      " 0_q[(5, 3, 4)] ≥ -4.26\n",
      " 0_q[(6, 4, 5)] ≥ -2.4\n",
      " 0_q[(1, 1, 2)] ≥ -4.0\n",
      " 0_q[(4, 3, 2)] ≥ -4.26\n",
      " 0_q[(2, 4, 1)] ≥ -4.26\n",
      " 0_q[(3, 5, 1)] ≥ -4.26\n",
      " 0_q[(5, 4, 3)] ≥ -4.26\n",
      " 0_q[(6, 5, 4)] ≥ -2.4\n",
      " 0_q[(1, 2, 1)] ≥ -4.0\n",
      " 0_vr[4] ≤ 1.1\n",
      " 0_vr[2] ≤ 1.1\n",
      " 0_vr[3] ≤ 1.1\n",
      " 0_vr[5] ≤ 1.1\n",
      " 0_vr[1] ≤ 1.1\n",
      " 0_vi[4] ≤ 1.1\n",
      " 0_vi[2] ≤ 1.1\n",
      " 0_vi[3] ≤ 1.1\n",
      " 0_vi[5] ≤ 1.1\n",
      " 0_vi[1] ≤ 1.1\n",
      " 0_pg[4] ≤ 11.72\n",
      " 0_pg[2] ≤ 3.41\n",
      " 0_pg[3] ≤ 11.5\n",
      " 0_pg[5] ≤ 2.92\n",
      " 0_pg[1] ≤ 2.22\n",
      " 0_qg[4] ≤ 5.86\n",
      " 0_qg[2] ≤ 1.776\n",
      " 0_qg[3] ≤ 5.75\n",
      " 0_qg[5] ≤ 4.5\n",
      " 0_qg[1] ≤ 1.776\n",
      " 0_p[(4, 2, 3)] ≤ 4.26\n",
      " 0_p[(2, 1, 4)] ≤ 4.26\n",
      " 0_p[(3, 1, 5)] ≤ 4.26\n",
      " 0_p[(5, 3, 4)] ≤ 4.26\n",
      " 0_p[(6, 4, 5)] ≤ 2.4\n",
      " 0_p[(1, 1, 2)] ≤ 4.0\n",
      " 0_p[(4, 3, 2)] ≤ 4.26\n",
      " 0_p[(2, 4, 1)] ≤ 4.26\n",
      " 0_p[(3, 5, 1)] ≤ 4.26\n",
      " 0_p[(5, 4, 3)] ≤ 4.26\n",
      " 0_p[(6, 5, 4)] ≤ 2.4\n",
      " 0_p[(1, 2, 1)] ≤ 4.0\n",
      " 0_q[(4, 2, 3)] ≤ 4.26\n",
      " 0_q[(2, 1, 4)] ≤ 4.26\n",
      " 0_q[(3, 1, 5)] ≤ 4.26\n",
      " 0_q[(5, 3, 4)] ≤ 4.26\n",
      " 0_q[(6, 4, 5)] ≤ 2.4\n",
      " 0_q[(1, 1, 2)] ≤ 4.0\n",
      " 0_q[(4, 3, 2)] ≤ 4.26\n",
      " 0_q[(2, 4, 1)] ≤ 4.26\n",
      " 0_q[(3, 5, 1)] ≤ 4.26\n",
      " 0_q[(5, 4, 3)] ≤ 4.26\n",
      " 0_q[(6, 5, 4)] ≤ 2.4\n",
      " 0_q[(1, 2, 1)] ≤ 4.0\n"
     ]
    }
   ],
   "source": [
    "pm = instantiate_model(file, ACRPowerModel, PowerModels.build_opf)\n",
    "print(pm.model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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