diff --git a/README.md b/README.md index a308b72..6feed3e 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,16 @@ -# mpcpy +mpcpy +===== A group of classes to run model predictive control (MPC) simulations using python and Dymola. +# Installation +requires: +* `numpy` + +To install download the latest [release](https://github.com/BrechtBa/mpcpy/releases), unpack, cd to the unpacked folder and run: +``` +python setup.py install +``` # Workflow In a model predictive control simulation we need several components. diff --git a/examples/example.ipynb b/examples/example.ipynb index 577ffd6..e69a496 100644 --- a/examples/example.ipynb +++ b/examples/example.ipynb @@ -24,7 +24,7 @@ "output_type": "stream", "text": [ "{'p_el': 0.20647047612756303, 'Q_flow_hp_max': 5000.0, 'Q_flow_sol': 564.7047612756302, 'T_em_max': 303.15, 'time': 1800.0, 'T_amb': 278.4088190451025, 'T_in_min': 293.15}\n", - "{'p_el': 0.20647047612756303, 'Q_flow_hp_max': 5000.0, 'Q_flow_sol': 564.7047612756303, 'T_em_max': 303.15, 'time': 88200.0, 'T_amb': 278.4088190451025, 'T_in_min': 293.15}\n" + "{'p_el': 0.20000000000000004, 'Q_flow_hp_max': 5000.0, 'Q_flow_sol': 500.00000000000034, 'T_em_max': 303.15, 'time': 88200.0, 'T_amb': 278.15, 'T_in_min': 293.15}\n" ] } ], @@ -37,7 +37,7 @@ " 'Q_flow_hp_max': 5000*np.ones_like(time),\n", " 'T_in_min': 20*np.ones_like(time)+273.15,\n", " 'T_em_max': 30*np.ones_like(time)+273.15}\n", - "boundaryconditions = mpcpy.Boundaryconditions(bcs)\n", + "boundaryconditions = mpcpy.Boundaryconditions(bcs,periodic=False)\n", "print( boundaryconditions(1800) )\n", "print( boundaryconditions(24.5*3600) )" ] @@ -150,7 +150,13 @@ "output_type": "stream", "text": [ "0\n", - "{'Q_flow_hp': [5000.0, 999.3126333371038, 0.0, 0.0, 218.44463971606456, 1577.4258599164896, 1653.2408964233473, 1786.76116650342, 1968.887484403327, 2187.2082425359986, 2426.8452420273097, 2671.467617380433, 2904.4047579726903, 3109.782382619567, 3273.604345604079, 3384.7064508771873, 3435.517273569538, 3422.574140083452, 3346.759103576769, 3213.2388334967545, 5000.0, 2560.774159460445, 1019.5922750795144, 0.0, 0.0], 'time': array([ 0., 3600., 7200., 10800., 14400., 18000., 21600.,\n", + "{'Q_flow_hp': array([ 5000. , 999.31263334, 0. , 0. ,\n", + " 218.44463972, 1577.42585992, 1653.24089642, 1786.7611665 ,\n", + " 1968.8874844 , 2187.20824254, 2426.84524203, 2671.46761738,\n", + " 2904.40475797, 3109.78238262, 3273.6043456 , 3384.70645088,\n", + " 3435.51727357, 3422.57414008, 3346.75910358, 3213.2388335 ,\n", + " 5000. , 2560.77415946, 1019.59227508, 0. ,\n", + " 0. ]), 'time': array([ 0., 3600., 7200., 10800., 14400., 18000., 21600.,\n", " 25200., 28800., 32400., 36000., 39600., 43200., 46800.,\n", " 50400., 54000., 57600., 61200., 64800., 68400., 72000.,\n", " 75600., 79200., 82800., 86400.])}\n" @@ -249,7 +255,7 @@ " # return the contol inputs\n", " sol = {}\n", " sol['time'] = pre['time']\n", - " sol['Q_flow_hp'] = ocp.solution.get_values(['Q_flow_hp[%s]'%(i) for i in range(N)])\n", + " sol['Q_flow_hp'] = np.array( ocp.solution.get_values(['Q_flow_hp[%s]'%(i) for i in range(N)]) )\n", "\n", " return sol\n", "\n", @@ -280,34 +286,49 @@ "text": [ "Run MPC |\n", "-------------------------------------------------------------------------------- done\n", - "[ 4549.58984375 4233.67577054 3917.76147461 3601.84716797 3285.93290418\n", - " 2970.01851184 2008.07348633 1673.39457194 1338.71565755 1004.03674316\n", - " 669.35782878 334.67892456 24.52283287 101.03502909 177.54718444\n", - " 254.05943298 330.57165609 407.08378011 563.29986572 663.09927696\n", - " 762.89852577 862.69793701 962.49732791 1062.29653602 1004.52294922\n", - " 1065.93598709 1127.34892502 1188.76196289 1250.17500814 1311.58809408\n", - " 1274.8984375 1317.34517415 1359.79187012 1402.23864746 1444.6854248\n", - " 1487.13212077 1478.22753906 1515.42944336 1552.63134766 1589.83337402\n", - " 1627.03527832 1664.23718262 1675.1541748 1713.29085286 1751.42765299\n", - " 1789.56433105 1827.70113118 1865.83780924 1890.53625488 1931.35493978\n", - " 1972.17366536 2012.99243164 2053.81103516 2094.62988281 2128.67553711\n", - " 2171.55296686 2214.43059438 2257.30786133 2300.18529108 2343.0629186\n", - " 2382.79833984 2425.91087648 2469.02361249 2512.13598633 2555.24852297\n", - " 2598.36109617 2640.37036133 2681.28759024 2722.2048414 2763.12207031\n", - " 2804.03905508 2844.95655039 2886.05786133 2922.26066363 2958.4637016\n", - " 2994.66650391 3030.86938755 3067.07250698 3104.31811523 3133.4683612\n", - " 3162.61904114 3191.76928711 3220.91977722 3250.07029435 3280.87939453\n", - " 3301.05301614 3321.22676902 3341.40039062 3361.57401223 3381.74768378\n", - " 3403.87353516 3413.73524877 3423.59727076 3433.45898438 3443.32069799\n", - " 3453.18255718 3465.22119141 3464.10123941 3462.98136146 3461.86157227\n", - " 3460.74162027 3459.62190512 3460.67016602 3717.22462222 3973.78074887\n", - " 4230.33496094 4486.88941715 4743.44554379 5000. 5000. 5000.\n", - " 5000. 5000. 5000. 5000. 5000. 5000.\n", - " 5000. 5000. 5000. 5000. 5000. 5000.\n", - " 5000. 5000. 5000. 5000. 5000. 5000.\n", - " 5000. 5000. 5000. 5000. 5000. 5000.\n", - " 5000. 5000. 5000. 5000. 4180.39746094\n", - " 3360.79500326 2541.19238281 1721.59000651 901.98746745 82.38495636]\n" + "[ 4.54958984e+03 4.54958984e+03 4.54958984e+03 4.54958984e+03\n", + " 4.54958984e+03 4.54958984e+03 2.65426245e+03 1.73182080e+03\n", + " 1.73182080e+03 1.73182080e+03 1.73182080e+03 1.73182080e+03\n", + " 1.73182080e+03 1.44314485e-01 0.00000000e+00 0.00000000e+00\n", + " 0.00000000e+00 0.00000000e+00 0.00000000e+00 0.00000000e+00\n", + " 0.00000000e+00 1.14616814e+02 1.14616814e+02 1.14616814e+02\n", + " 1.14616814e+02 1.14616814e+02 1.14616814e+02 8.49753127e+02\n", + " 7.69080078e+02 7.69080078e+02 7.69080078e+02 7.69080078e+02\n", + " 7.69080078e+02 7.69080078e+02 1.34828278e+03 1.20817261e+03\n", + " 1.20817261e+03 1.20817261e+03 1.20817261e+03 1.20817261e+03\n", + " 1.20817261e+03 1.56455965e+03 1.48443311e+03 1.48443311e+03\n", + " 1.48443311e+03 1.48443311e+03 1.48443311e+03 1.48443311e+03\n", + " 1.74003009e+03 1.70538147e+03 1.70538147e+03 1.70538147e+03\n", + " 1.70538147e+03 1.70538147e+03 1.70538147e+03 1.93924369e+03\n", + " 1.92783472e+03 1.92783472e+03 1.92783472e+03 1.92783472e+03\n", + " 1.92783472e+03 1.92783472e+03 2.16992367e+03 2.16899609e+03\n", + " 2.16899609e+03 2.16899609e+03 2.16899609e+03 2.16899609e+03\n", + " 2.16899609e+03 2.42186369e+03 2.42547778e+03 2.42547778e+03\n", + " 2.42547778e+03 2.42547778e+03 2.42547778e+03 2.42547778e+03\n", + " 2.67905260e+03 2.68453931e+03 2.68453931e+03 2.68453931e+03\n", + " 2.68453931e+03 2.68453931e+03 2.68453931e+03 2.92404449e+03\n", + " 2.93020801e+03 2.93020801e+03 2.93020801e+03 2.93020801e+03\n", + " 2.93020801e+03 2.93020801e+03 3.14026008e+03 3.14629126e+03\n", + " 3.14629126e+03 3.14629126e+03 3.14629126e+03 3.14629126e+03\n", + " 3.14629126e+03 3.31281058e+03 3.31830688e+03 3.31830688e+03\n", + " 3.31830688e+03 3.31830688e+03 3.31830688e+03 3.31830688e+03\n", + " 3.43004342e+03 3.43448511e+03 3.43448511e+03 3.43448511e+03\n", + " 3.43448511e+03 3.43448511e+03 3.43448511e+03 3.48387577e+03\n", + " 3.48698901e+03 3.48698901e+03 3.48698901e+03 3.48698901e+03\n", + " 3.48698901e+03 3.48698901e+03 3.47063588e+03 3.47224878e+03\n", + " 3.47224878e+03 3.47224878e+03 3.47224878e+03 3.47224878e+03\n", + " 3.47224878e+03 3.39126505e+03 3.39125098e+03 3.39125098e+03\n", + " 3.39125098e+03 3.39125098e+03 3.39125098e+03 3.39125098e+03\n", + " 3.24853777e+03 3.25168042e+03 3.25168042e+03 3.25168042e+03\n", + " 3.25168042e+03 3.25168042e+03 3.25168042e+03 4.99985437e+03\n", + " 5.00000000e+03 5.00000000e+03 5.00000000e+03 5.00000000e+03\n", + " 5.00000000e+03 5.00000000e+03 5.00000000e+03 5.00000000e+03\n", + " 5.00000000e+03 5.00000000e+03 5.00000000e+03 5.00000000e+03\n", + " 5.00000000e+03 3.99989923e+03 4.04987842e+03 4.04987842e+03\n", + " 4.04987842e+03 4.04987842e+03 4.04987842e+03 4.04987842e+03\n", + " 3.37343451e-01 0.00000000e+00 0.00000000e+00 0.00000000e+00\n", + " 0.00000000e+00 0.00000000e+00 0.00000000e+00 2.50963343e+01\n", + " 2.50984249e+01]\n" ] } ], @@ -327,7 +348,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 9, @@ -336,9 +357,9 @@ }, { "data": { - "image/png": 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baULD+RGxorgKzcxsCB4Bpiqv4Ft0Mf1xmGueS4GfF12EtZ6kbYGPAB8itcj+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\nSZLUYYY5SZKkDjPMSZIkdZhhTpIkqcMMc5LmSpJjkvzLgde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OdzbbHPTMzAZJmgA8HRHdVHE1Iq3mllLCnKQLSbUTu5O+4D8CfB9YQOovtQw4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\nMNinej1bjgq9l9Qsmpd1jJ5c1jEinpX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"text/plain": [ - "" + "" ] }, "metadata": {}, @@ -364,6 +385,15 @@ "ax.set_xlabel('time (h)')\n", "plt.legend()" ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] } ], "metadata": {