diff options
Diffstat (limited to 'basic_electrical_engineering_by_nagsarkar_and_sukhija/chapter6.ipynb')
-rw-r--r-- | basic_electrical_engineering_by_nagsarkar_and_sukhija/chapter6.ipynb | 896 |
1 files changed, 896 insertions, 0 deletions
diff --git a/basic_electrical_engineering_by_nagsarkar_and_sukhija/chapter6.ipynb b/basic_electrical_engineering_by_nagsarkar_and_sukhija/chapter6.ipynb new file mode 100644 index 00000000..323d1e29 --- /dev/null +++ b/basic_electrical_engineering_by_nagsarkar_and_sukhija/chapter6.ipynb @@ -0,0 +1,896 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Chapter 6:Transformer Principles" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.1:Page number-343" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "bm= 0.7207 Wb/m2\n", + "e2= 800.0 V\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "#given\n", + "\n", + "a=50*(10**-4)\n", + "e=400\n", + "f=50\n", + "n1=500\n", + "n2=1000\n", + "#phym=bm*a\n", + "\n", + "#case a\n", + "#e=4.44*f*n*bm*a\n", + "\n", + "bm=(e)/float(4.44*f*n1*a)\n", + "\n", + "print \"bm=\",format(bm,'.4f'),\"Wb/m2\"\n", + "#case b\n", + "\n", + "e2=4.44*f*n2*bm*a\n", + "\n", + "print \"e2=\",format(e2,'.1f'),\"V\"\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.2" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "cross sectional area= 0.02065 m2\n", + "secondary voltage on no load= 440.0 V\n", + "primary magnetising current= 1.133 A\n", + "core loss= 366.7 W\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "#given\n", + "\n", + "e=3300\n", + "f=50\n", + "n1=600\n", + "n2=80\n", + "bm=1.2\n", + "h=425\n", + "l=1.6\n", + "density=7400\n", + "loss=1.5\n", + "\n", + "#case a\n", + "\n", + "phym=e/float(4.44*f*n1)\n", + "\n", + "csa=phym/bm\n", + "\n", + "print \"cross sectional area=\",format(csa,'.5f'),\"m2\"\n", + "\n", + "#case b\n", + "\n", + "sv=(e*n2)/n1\n", + "\n", + "print \"secondary voltage on no load=\",format(sv,'.1f'),\"V\"\n", + "\n", + "#case c\n", + "\n", + "mc=(h*l)/n1\n", + "\n", + "print \"primary magnetising current=\",format(mc,'.3f'),\"A\"\n", + "\n", + "#case d\n", + "\n", + "v=l*csa\n", + "m=v*density\n", + "\n", + "closs=m*loss\n", + "\n", + "print \"core loss=\",format(closs,'.1f'),\"W\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.3:Page number-356" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.0333333333333\n", + "30\n", + "number of turns of high voltage soil= 2640.0\n", + "number of turns of high voltage soil= 88.0\n", + "primary current as a step down transformer is= 1.515 A\n", + "secondary current as a step down transformer is= 45.45 A\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "#given\n", + "\n", + "#as per step up tranformer\n", + "v1=220\n", + "v2=6600\n", + "\n", + "f=50\n", + "vturn=2.5\n", + "kva=10000\n", + "\n", + "#case a\n", + "\n", + "a=v1/float(v2)\n", + "\n", + "print a\n", + "\n", + "#as per step down case b\n", + "v1=6600\n", + "v2=220\n", + "\n", + "a=v1/v2\n", + "\n", + "print a\n", + "\n", + "#case c\n", + "\n", + "#high voltage soil\n", + "\n", + "n=v1/float(vturn)\n", + "\n", + "print \"number of turns of high voltage soil=\",format(n,'.1f')\n", + "\n", + "#low voltage soil\n", + "\n", + "n1=v2/float(vturn)\n", + "\n", + "print \"number of turns of high voltage soil=\",format(n1,'.1f')\n", + "\n", + "#case d\n", + "\n", + "i=kva/float(v1)\n", + "\n", + "print \"primary current as a step down transformer is=\",format(i,'.3f'),\"A\"\n", + "\n", + "#case e\n", + "\n", + "i=kva/float(v2)\n", + "\n", + "print \"secondary current as a step down transformer is=\",format(i,'.2f'),\"A\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.4:Page number-357" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "turns ratio for impedance machting is 0.25\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "#given\n", + "rl=32\n", + "\n", + "#let ratio of sides be a\n", + "\n", + "rs=2\n", + "\n", + "a=(2/float(32))\n", + "\n", + "p=a**0.5\n", + "\n", + "print \"turns ratio for impedance machting is\",format(p,'.2f')" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.5:Page number-364" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [ + "import math\n", + "\n", + "#given\n", + "n1=2200\n", + "n2=220\n", + "kva=100\n", + "f=50\n", + "r1=0.75\n", + "r2=0.0007\n", + "x2=0.0009\n", + "\n", + "#case a\n", + "\n", + "#subcase 1\n", + "\n", + "#lv side leakage impedance=r2+jx2-->complex number\n", + "#hv side leakage impedance=r1+jx1\n", + "#hv side impedance referred to lv side is r1'+jx1'=(r1+jx1)/a**2=(0.0075+j0.0115)\n", + "\n", + "#shunt branch resistance referred to lv side gc-jbm=(0.0035-j0.025)\n", + "\n", + "#The equivqlent circuit is shown in the diagram\n", + "\n", + "#subcase 2\n", + "\n", + "#lv side impedance referred to hv side is r2'+jx2'=a**2*(r2+jx2)=(0.70+j0.90)ohm\n", + "\n", + "#the magnetising admittance refferred to hv side (gc-jbm)/a**2=(0.000035-j0.00025)\n", + "\n", + "#the equivalent circuit is as in figure\n", + "\n", + "#case b\n", + "\n", + "#for an approximate equivalent circuit the magnetised admittance is neglected from the exact circuit\n", + "\n", + "#subcase 1\n", + "\n", + "#equivalent impedance referred to lv side (r2+r1')+j(x2+x1')=(0.0145+j0.0205)ohm\n", + "\n", + "#equivalent circuit is shown in figure\n", + "\n", + "#subcase 2\n", + "\n", + "#equivalent impedance referred to hv side is (r1+r2')+j(x1+x2')=(1.45+j2.05)ohm\n", + "\n", + "#equivalent circuit is shown in figure\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.6:Page number-369" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "yc= 0.0050 S\n", + "gc= 0.0025 S\n", + "bm= 0.0043 S\n", + "req= 0.8500 ohm\n", + "zeq= 1.5000 ohm\n", + "xeq= 1.2359 ohm\n", + "req1= 0.2125 ohm\n", + "xeq1= 0.3090 ohm\n", + "zeq1= 0.3750 ohm\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "#case a\n", + "\n", + "#from oc test data shunt admittances are determined as follows\n", + "\n", + "#given\n", + "v1=200\n", + "i0=1\n", + "pc=100\n", + "\n", + "yc=i0/float(v1)\n", + "\n", + "print \"yc=\",format(yc,'.4f'),\"S\"\n", + "\n", + "gc=pc/float(v1**2)\n", + "\n", + "print \"gc=\",format(gc,'.4f'),\"S\"\n", + "\n", + "bm=(((0.005**2)-(0.0025**2))**0.5)\n", + "\n", + "print \"bm=\",format(bm,'.4f'),\"S\"\n", + "\n", + "#from sc test data\n", + "\n", + "p=85\n", + "isc=10\n", + "vsc=15\n", + "\n", + "req=p/float(isc**2)\n", + "\n", + "print \"req=\",format(req,'.4f'),\"ohm\"\n", + "\n", + "zeq=vsc/float(isc)\n", + "\n", + "print \"zeq=\",format(zeq,'.4f'),\"ohm\"\n", + "\n", + "xeq=(((zeq**2)-(req**2))**0.5)\n", + "\n", + "print \"xeq=\",format(xeq,'.4f'),\"ohm\"\n", + "\n", + "#case b\n", + "\n", + "a=0.5\n", + "\n", + "#equivalent impedance parameters referred to lv side\n", + "\n", + "re=(a**2)*req\n", + "\n", + "print \"req1=\",format(re,'.4f'),\"ohm\"\n", + "\n", + "xe=(a**2)*xeq\n", + "print \"xeq1=\",format(xe,'.4f'),\"ohm\"\n", + "\n", + "ze=(a**2)*zeq\n", + "print \"zeq1=\",format(ze,'.4f'),\"ohm\"\n", + "\n", + "#equivalent circuit referred to lv side is as shown" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.7:Page number-373" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "yc= 0.0035 S\n", + "gc= 0.0015 S\n", + "bm= 0.0032 S\n", + "req= 0.6000 ohm\n", + "zeq= 1.5000 ohm\n", + "xeq= 1.3748 ohm\n", + "req1= 0.1500 ohm\n", + "xeq1= 0.3437 ohm\n", + "97.0873786408\n", + "v2= 394.0 V\n", + "v2= 386.95 v\n", + "v2= 403.45 V\n" + ] + } + ], + "source": [ + "-" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.8:Page number-376" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "n=((10xScos(angle))/(10xScos(angle)+pc+0.0001x2Pcu))\n" + ] + }, + { + "data": { + "image/png": "iVBORw0KGgoAAAANSUhEUgAAAYQAAAEPCAYAAABCyrPIAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzt3Xd4VFX6wPHvS5FeFanSgigKhCIKihBsUdFFXRuiCShN\nlLJYVlQUXVkXXXUFCypWfoIdpEkRDKgI0kIkYEnoHUxogYSU9/fHnWAISZgkM7kzk/fzPPMkuXPn\n3vckcN97zrnnHFFVjDHGmDJuB2CMMSYwWEIwxhgDWEIwxhjjYQnBGGMMYAnBGGOMhyUEY4wxgJ8T\ngogMF5FfRGSdiAz3bLtYRH4WkTUiskJEOvkzBmOMMd7xW0IQkdZAf6ATEA7cICJhwAvAaFVtDzzl\n+dkYY4zLyvnx2OcDy1U1FUBEFgO3ADuBGp59agI7/BiDMcYYL4m/RiqLyPnA10AXIBVYCPwMvAQs\nBbJwaihdVHWbX4IwxhjjNb8lBAARuRcYAqQA8UAa0Bp4Q1WnichtwEBVvdpvQRhjjPGKXxPCSScS\nGQtsB8apanXPNgEOqGqNPPa3SZaMMaYIVFWK8jl/P2V0tudrY5z+gylAgoh09+xyBfB7fp9X1ZB9\nPf30067HUNJlS0tTfv9d+eYb5fXXlYceUm6+WQkPV6pVU2rVUjp2VG67TfnnP5W33lIWLFA2blTS\n090vV2n421n5gv9VHP7sVAb4QkTOBNKBIap6UEQGAq+LSAXgGDDQzzGYEqIKf/4J27fD1KmwcePJ\nr927oVEjaN78r1fnzs7XZs2gVi23S2BM6ebXhKCq3fLYthK4xJ/nNf5z/Dhs2QKJiade8DduhHLl\noGJFOHQIwsKcC/5ddzkX/XPOcd43xgQm++/pkoiICLdDyFP2XX5+F/ycd/lhYXnf5cfERBCgxfOJ\nQP3b+YqVr/QqsU7lwhIRDdTYgp03d/nZF/vcL7vLNyawiQhaxE5lSwghyJu7/HPOyfuCH0xt+bMX\nzGb8lPGkaRoVpALD7hpGz6t72vlC6HzOg4gmP3ldI4uTEOxeL0id7i6/fPmTL/Kh1pY/e8Fshr8+\nnMT2iSe2Jb7ufO+Pi5idz73z2Y1h3vyRLK2GEKCy7/I3bsz7or9nz6lP7OR81azpdgl872j6UXYd\n3sWuI7t44OEHiLsw7pR9Gq1sxHUDr/P5uee8NYcdnU6dZcXO59vzRW6JZO57c0/87Lnb9fn5Q0F+\nvxurIQSp7Lv8/C76Oe/ysztvQ+kuP1vOC/3OwzvZddj5uvPIX9/vOrKLY+nHqF+tPg2qNWDnkZ15\nHqvSGZW4qMFFPo8xpkKMna8EzpealerzcxnvhcglJTiowoIF8PLLsGFD3nf52U/shMJdflEu9PWr\nOl8bVGvABXUucLZ53qtVsdaJanLk95HMZ/4p52xeozkDO/p+aMuX1b/kD/6w8/n5fBXLVPT5uYz3\nLCGUkOXLYdQo2LkTnnoKunTx/12+vzoJj6UfO3GRz3mhP2lbES/03hp21zASX088qQ06bHUYQx8c\nWuzy2flC73zGO5YQ/OzXX+GJJ+Dnn+Hpp6Fv35Jp6ilKJ2FxLvT1q9b3yYXeW9llmDB1AqlZqVQs\nU5GhDw7121Mxdr7gPp8/JCUlcd9997FgwQLOOussnn/+eXr37p3nvhs3bmTYsGEsWbKEChUqcO+9\n9zJu3DjAGRexfPlyynkuDI0aNWLDhg0lVo6crFPZT7ZvhzFjYMYMeOQRePBBqFSp5M4f2S+S+U1P\nbVIJjw+n38h+J13os7/md6HPvrMviQu9MTnl13E6e/YSxo+fT1paOSpUyGDYsGvo2fOUiREKVNxj\nZF/83333XdasWUPPnj1ZunQpF1xwwUn7HT9+nFatWjF06FAGDRpE2bJl+e2332jTpg0APXr04J57\n7uHee+8tVPzWqRwEkpLg+efhvfdg0CD4/Xd3+gIOZxzOc/uOIztITE48cUeffZG3C70JFrNnL2H4\n8HkkJo49sS0x8QkAry/oxT1GSkoKX331FfHx8VSuXJnLLruMXr16MXnyZJ5//vmT9v3ggw9o1KgR\nI0aMOLEtOxlkC5SbX7/OdlqapKTAv/8N550HR47AL784P5dkMth9ZDev//w6ER9EsGLbijz36Viv\nI+OvG8+oy0cR3S6aa8KuofXZraldqbYlg9OYPXsJkZFPEhExhsjIJ5k9e4mdz4XzjR8//6QLOUBi\n4lgmTFjg9bmLe4zff/+dcuXK0aJFixPbwsPDiY+PP2XfZcuW0aRJE66//nrq1KlDjx49WLdu3Un7\njBo1ijp16tC1a1cWL17sdTl8zWoIxZSeDpMmwb/+Bd26wdKlcO65JXf+3Ud28+X6L/l8/ees3bOW\nnuf25B+d/8HwesN5ZOIj1mnnI764K7Xz+eZ8aWl5X7bmzSuL9/c0eR8jNbWsV58+cuQI1atXP2lb\ntWrVOHz41Jr59u3biYmJYebMmVx55ZX873//o1evXvz222+UK1eOcePGceGFF3LGGWcwdepUbrzx\nRmJjY2nevLm3hfEZSwhFlJUFn30GTz7pzPszcyZ07Fgy584vCUS2iKRiOc9je+fDGWXPCOpOu9Px\nRTvy6WRlwcGD8J//5H1HOXr0aLKyfH/BfPrp0nm+CRNGn/ZvWKFCRp7bIyMzmTs3z7fy2DeD+ad2\nsVGxYqZXn69atSqHDh06advBgwepVq3aKftWrlyZyy+/nMjISAAefvhhnnvuOTZs2ECbNm24+OKL\nT+wbFRXF1KlTmTNnDg8++KB3hfEhSwiFpArz5zuPkJYrB2+/DVdc4f/zepUEcul5dc+QSgA5FeYO\nM/uinpzs/Sspyfl66BBUrZr/XemWLWV5+23fl2/LltJ5Pm/u0IcNu4bExCdO+tuHhT3O0KHXen3+\n4h6jZcuWZGRkkJCQcKLZaO3atbRu3fqUfdu2bcuPP/544udA6S/IiyWEQsg5lmDsWLjlFgpRRS28\noiSBQOCPO3dVOHrUuVAnJcGYMXnfYd5332jatOl20sX90CGoUsWZtC/7Vbv2yT83bXryz9mvGjWc\nxJ/fHWWnTpnMnFmsouWptJ7Pmzv07H9LEyaMJjW1LBUrZjJ06LWF+jdW3GNUqVKFW265haeeeopJ\nkyaxevVqZs6cyU8//XTKvnfffTcvvfQSCxcuJCIigvHjx1OnTh1atWrFwYMHWbZsGd27d6dcuXJ8\n+umnfP/990yYMMHrsviU28u9FbAMnAaK9etVb75ZtWFD1XfeUU1P99+5dh3epa8tf027v99da/6n\npvb5so9O3zBdj6Uf899JfWjWrMUaFva4Opdw5xUW9rjOmrVYVVWzslQPHFDduFF15UrV+fNVP/lE\n9Y03VJ97TnXkSNW+fVX/9jfVrl1VL7hAtV491TPOUK1UyfkbtGmjWqPG0yedI/vVqtXTOm+e6s8/\nq/7xh+r+/b75e+VdrlEnyuVrdj5HIF0HcktKStKbbrpJq1Spok2aNNGpU6eqquqWLVu0atWqum3b\nthP7fvXVV9qiRQutXr269ujRQ9evX6+qqvv27dNOnTpptWrVtGbNmtqlSxf99ttvvTp/fr8bz/Yi\nXXdtHEIBtm2DZ56Br7+GRx/1zViCvEYPd+zS8ZSawG0X3BbwNYHcMjKge/cnWbr0uVPeq1x5NJUr\n/4vkZOduvXbtwr1q1XJWYssWGfkk8+efep7IyNHMnfsvv5Rv9uwlTJiwIMcd5dV+6XC18/3FJrfL\nnz/GIVhCyMOff8J//uOMJRg40EkGvlgjIK/RwxUXV6TMuWW4OfLmoEoCKSkQFwdr1kBsrPN1/XrI\nyhpDauqYU/bv1GkMs2ePoWZNZ9K+4sqrDyEs7HFefbVwTQcmsFlCyJ8NTPOzlBR49VVn8rlbb3XG\nEjRo4Lvjj58y/qRkAJDaPZWrN1/N/93yf747kY/t3+9c8LNfsbHOLK2tWkH79s6rb19o2xb+/ve8\n24Zr186kTh3fxeSLdmRjzMksIXDyWILLL4effvLPWII0Tctz+3E97vuTUfjOXVXYvPmvO/7s15Ej\n0K6d87r2WqdjvVWrvO/0ffEEiLd69uxmCcAYHyq1CSElBWJiYO5cZ76h887z/1iCClIhz+3+mPL3\ndI9lpqc7E+/lbPKJjYXKlU++63/1VWfFNW+fprI7d2OCV6npQ1CF+HgnAcyd6zxCetFFzh3vtddC\neLjPTpWv2Qtm0++lfuzrsu/EtrDVYbz64Ks+Hy+QX6drw4ajqV//X8THO9NvZ1/827d3agBnn+3T\nMIwpFutDyJ/1IRTSgQPw7bd/JYHy5Z2L/9ChMG0a5DGo0K96Xt2T7rHdiV0aS8MaDf06evjIkbz/\ntJUqleXVV532/qpVfX5aY0wQC6mEkJUFq1f/lQDi4qBrVycJPPqo0y/g+vxtTeFf1/2LO1vf6fND\n79/vJLrPPoPly/Me3h8Wlsmll/r81MaYEBD0s53u2QOTJ0OfPlC3LkRHOyNZn3rKeW/OHBg2DFq2\nDIBkACQkJdCidovT7+il/fvhnXfg6quhRQunRjRoEHz66TWEhT1x0r5O5+7VPju3MSa0BF0NIT0d\nli37qxaQmAhXXunUAp5/Hho3djvC/KkqCUkJhNUKK9ZxctYEVqyAyEgnCXz9tdMp7OhGxYrWuWuM\nKYSiDnH294scw7I3b1Z96y1n+ogaNVQ7dlR9/HHVJUtUjx8/3QDvwLH78G49c9yZRfrs3r3O7+Cq\nq5zfwe23q37+uWpKio+DNCaAEMBTV/z5558nTV0xZcqUfPd99tlntVGjRlqjRg2NiIjQ+Pj4Yp8/\nv98NxZi6wq81BBEZDvQHBHhHVV/1bB8KDAEygdmq+s+8Pj9ypFML2LfPuQu+5RZ4802naSgYFba5\naN8+pybw+efOmszXXptXTcCY0ievKWAK+3BGcY/xwAMPULFiRfbu3XtiCc3w8PBTltCcMWMGEydO\n5Mcff6Rx48Y8+eST3HPPPaxatapQ8ZYEvyUEEWmNkww6AenAXBGZBTQG/ga0VdV0Ecl3/Grt2vDR\nR9ChA5QJ+t4O7xKCJQFjCpbXFDCJrzvfe3tBL+4xCrOEZnx8PF27dqVp06YA9OnTh1deecWrOEua\nPy+z5wPLVTVVVTOBxcAtwGDgeVVNB1DVffkd4MknnbECoZAMwEkIWfvLn7Js4L59zroK2R3DCxc6\nSWDXLvj0U2caDUsGxjjymgImsX0iE6Z6P2V0cY9RmCU0r7zySn766Sf++OMP0tPT+fDDD7nuuuu8\njrUk+bPJaB0wVkRqA6nA9cBKoCXQTUT+7dn+sKqu9GMcAWNJ/FJ+nVGVvd++f2Lb9987TwLdeGM3\nqwkY44X8poCZt3Ee8oyXjxJuApqeujk1K9WrjxdmCc2LL76Y6OhozjvvPMqWLUvjxo1ZuHChd3GW\nML8lBFX9VUTGAfOBFCAWp8+gHFBLVTuLSCfgM6DkFw91QezWDRz69cuTth07NparrhrNp5/a0z/G\neCO/KWAim0cy92nv1tCM3BzJfE6dhdHbaWQKs4Tma6+9xsKFC9m+fTv16tVj8uTJXHHFFcTHx1Op\nuPPp+5hfO5VV9T3gPQARGQtsx2lK+srz/goRyRKRM1X1z9yfHzNmzInvIyIiiIiI8Ge4fpWRAUfK\nJ0PSqX0I6eneLextjIFhdw0j8fXEk5p8wlaHMfTBoSV2jMIsoTl37lx69+5NA8/UydHR0YwYMYIN\nGzbQoUMHr2POT0xMDDExMcU+DuDfx06Bsz1fGwMbgOrAIOAZz/aWwNZ8PlukR7EC0bp1qu0v/VNl\nVAWFrFNW+YqMfNLtEI0JSPldB2bNn6WR/SK1e3R3jewXqbPmzyr0sYt7jDvvvFN79+6tKSkp+v33\n32uNGjVOrISW06hRo7Rr1666Z88ezczM1I8++kirVq2qBw8eLHTMOeX3u6EYj536OyEsAeJxmot6\neLaVByYDvwCrgIh8PlusX1YgSE9X/fe/Vc88U/Wf45dr2AstS3SZQmOCXSBfB7xdQjMlJUXvu+8+\nrVu3rlavXl07duyo8+bNK/b5/ZEQSs1spyUtPh769XMWaZ80CX48NIWvf/uaqEoPlOgyhcYEM5vt\nNH+2hGYQyMiAF1+El16CsWOdJThF4NnFz5KWkcbYK8ee/iDGGMASQkFs+usAl7NWsGoVNGny13sJ\nSQn0aNrDveCMMeY0QmTIl7syMpyJ9bp3h/vug/nzT04G4PtZTo0xxteshlBMBdUKcrKEYIwJdFZD\nKCJvagXZDqUdIiU9hXpV65VskMYYUwhWQygCb2sF2RKTEgmrFYYEwgo9xhiTD6shFEJhagU5WXOR\nMSYYWA3BS4WtFeRkCcEYEwyshnAaRa0V5GQJwZjS480336Ru3bpUr16d5ORkt8MpFEsIBYiPh0sv\nhUWLnFrBoEHOILPCSki2hGBMaZCens5DDz3EwoULOXToELVq1fL6s6NHj6ZNmzaUL1+eZ555xo9R\n5s8SQh58USvIyWoIxpQOu3fvJjU1lVatWhX6s+eeey4vvvgiPXv2dO0BlFLfhzB79hLGj59PWlo5\nKlTIoFeva/jgg25F6ivIS8rxFJKOJdGoeiPfBGyMcV3Tpk0ZPHgwkydPZteuXdx0002MGDGCLl26\nAFCzZk0uueQSvv32W6+PGRUVBcDHH3/s2nQdpTohzJ69hOHD55GY+Nf8Qt9++wSDB8Nrr3UrUvNQ\nbhuTN9KsZjPKiFXGjAklU6ZMYf78+VSuXJkbb7yRzz//nPXr19OsWTMOHjxIGc/av23btmXbtm15\nHqNPnz689tprJRl2gUp1Qhg/fv5JyQAgK2ssiYmjEfHNDKSJyYmE1Q7zybGMMSfzVctKYW/IRYQH\nH3yQhg0bAvDEE08wdOhQ+vfvf8q+cXFxvgixRJTqhJCcnHfxU1N9t4JZQlICLWpZ/4Ex/uDmRKjn\nnHPOie8bN27Mzp073QvGR0plO8avv8I990BsbEae71esmOmzc1mHsjGhaevWrSd9n11byO3CCy+k\nWrVqeb6GDBmS52fc6lQuVQlh3Tq4807o1g1atYL/+79rCAt74qR9wsIeZ+jQq312TksIxoQeVeWN\nN95gx44dJCUlMXbsWO644448O4Pj4+M5fPhwnq833njjxH4ZGRmkpqaSmZlJeno6qampZGVllWSx\nSkeTUWwsPPcc/PADjBwJ77wD1aoBdKNKFZgwYXSOFcyu9ekKZpYQjAk9IsJdd93FNddcw86dO7np\nppt48skn2b17d5Hv7vv3789HH3104uexY8fywQcfnHj6qCSE9IppK1fCv/4FK1bAI484q5dVqeKj\nAL2QlpFG9f9UJ+XxFMqVKRW51xifCtQV05o1a8a7777LFVdc4VoM/lgxLSSbjJYtg5494aab4Kqr\nIDER/vGPkk0GAJsObKJxjcaWDIwxQSGkrlQ//ADPPgu//QajRsFXX0GFCu7FY81FxphgEvQJQRUW\nL3YSwebN8PjjEBUFZ5zhdmT2yKkxoWrTpk1uh+AXQZsQVOHbb51EsHs3PPkk3HUXlC/vdmR/SUyy\nQWnGmOARdAlBFebOdRLBgQNOIrjjDigXgCVJSE4gskWk22EYE5Sm/zrd7RBKnQC8jP4lImIMFSpk\nMGzYNVx/fTdmznSeGkpNdRLBrbdCWd8NKvY560MwpvAOph5k+Nzh/LD1B7dDKXUC+rFTcGKrW/cJ\nKleOpHr1bjz1lPP0UJkAfz4qPTOdqs9X5dBjh6hQzsWebWOCyKJNi+j3dT96ntuTF65+gWoVqrkd\nUkDz9WOnAV1DyLZnz1jatx/NqlW+mYG0JGw9uJX6VetbMjDGC0fTj/LYt48x7ddpTLpx0omm1kC9\nYQ1VAX6f/Zfq1csGTTIAay4yxlvLty+n/VvtSTqWRNzgOOt3c1FQ1BDAtxPOlQRLCMYU7HjmcZ5d\n/CyTVk/itetf49YLbnU7pFLPrzUEERkuIr+IyDoRGZ7rvYdEJEtEap/uOL6ecK4kWEIwJn/r9q7j\nkkmXsHbPWmIHx1oyCBB+qyGISGugP9AJSAfmisgsVU0UkXOAq4EtBR2je/cxfplwriQkJCfQrUlw\nxWyMv2VmZfLyTy/zwtIXGHfVOPq16+faVM/mVP5sMjofWK6qqQAishi4BXgReBl4FPi6oAPExIzx\nY3j+lZiUaDUEY3JITEqk79d9KStlWTFgBU1rNnU7JJOLP5uM1gGXi0htEakMXA+cIyK9gO2qGjzr\nyhVSZlYmmw5sonmt5m6HYozrVJWJKyfS+d3O/L3V31kUvciSQYDyWw1BVX8VkXHAfCAFiAUqAKOA\na3Lsmm99ccyYMSe+j4iIICIiwh+h+tyOwzuoXak2Vc4o4elVjQkwOw7toP/M/uw/up8lfZfQqk4r\nt0MKOTExMcTExPjkWCU2ME1ExgJ7gCeAo57NjYAdwMWqujfX/sVeD8EtizYt4pnFz7C472K3QzHG\nFarKJ+s+YcS8EQy5aAiPX/445csG0ERjISxgB6aJyNmquldEGuP0H1yiquNzvL8J6KiqSf6Mo6TZ\nLKemNNt/dD9DZg8hfl88c+6aQ8cGHd0OyXjJ3wPTvhCReGAGMERVD+V6PzirAKdhj5ya0mrW77MI\nnxhO4xqNWTVwlSWDIOPXGoKqFvjcpaqGZK9rQlICvVv3djsMY0rMobRDjJw3kkWbFjHllil0b9rd\n7ZBMEQTN1BXBxGoIpjRZvHkx4RPDEYS1g9daMghiQTN1RbBQVRKTbWEcE/qOpR/jiUVP8Gn8p7x9\nw9v0bNnT7ZBMMVlC8LHdR3ZTpXwVqleo7nYoxvjNyp0riZoWRZu6bYgbHMeZlc90OyTjA6dtMhKR\nl0XkwpIIJhRYc5EJZemZ6YyJGUPPKT15qvtTfHrrp5YMQog3NYQNwNsiUh54D5iqqgf9G1bwsoRg\nQtX6feuJmhZFnSp1WDNoDQ2qNXA7JONjp60hqOo7qnoZEAU0BX4RkSki0sPfwQUjSwgm1GRpFq/8\n9ArdP+jOgA4DmHPXHEsGIcqrPgQRKYszWV0rYB+wFhgpIoNV9Q4/xhd0EpIT6HVeL7fDMMYnNh/Y\nTN/pfcnUTJbdt8welghx3vQhvAL8hjM53VhV7aiq41T1RqCdvwMMNlZDMKFAVXl39bt0eqcTN7S8\ngZjoGEsGpYA3NYQ44ElVTcnjvUt8HE9QU1VLCCbo7T6ym/4z+rPz8E6+i/6O1me3djskU0K8GZh2\nEDgxK5WI1BSRmwBU9YC/AgtG+4/up6yUpXal0y4CZ0xA+jz+c9pNbEf7eu1Z1n+ZJYNSxpsawtOq\n+lX2D6p6QETGANP9FlWQsgFpJlglHUviwTkPsnrXamb0nsHFDS92OyTjAm9qCHlNo1rW14GEAmsu\nMsFoXsI82r7ZlrOrnM3qQastGZRi3tQQVonIy8DrOMnhAWCVX6MKUjbttQkmR44f4ZH5j/BNwjd8\ndPNHXNHsCrdDMi7zpoYwFEgHPgU+AVJxkoLJxWoIJlj8sPUH2k1sR2pmKmsHr7VkYAAvagiqegT4\nZwnEEvQSkhK4/6L73Q7DmHylZaTx1HdP8VHcR0zsOZFe59uYGfOX0yYEETkPeBhnlHL2/qqqdkuR\ni9UQTCCL3R3LPdPuoeWZLYkbHEedKnXcDskEGG/6ED4H3gQmAZmebSG50llxJB9LJi0zjbOrnO12\nKMacJCMrg3E/jOPV5a/ycuTL9GnTB5EiLblrQpw3CSFdVd/0eyRBLjE5kRa1W9h/NBNQftv/G9HT\no6lWoRqrBq7inBrnuB2SCWDedCrPFJEHRKS+iNTOfvk9siBjzUUmkGRpFhOWT6Dr+125p+09zLt7\nniUDc1re1BD64jQRPZxrezOfRxPEEpMSCatlg9KM+7Ye3Eq/r/txLP0YS+9dyrlnnut2SCZIeDP9\ndVNVbZb7VRLBBZOEZKshGHepKh/GfshFb1/E1c2v5vt+31syMIXizVNGVYCRQGNVHSAi5wLnqeos\nv0cXRBKSEogOj3Y7DFNK7U3Zy6BZg0hMSmTBPQsIrxfudkgmCHnTh/A+cBy41PPzTmCs3yIKUtaH\nYNwybcM0wieGc/6Z57NiwApLBqbIvOlDCFPV20XkTgBVTbEnaU525PgRDqYetFWkTIk6kHqA4XOH\ns3TbUr68/UsuPefS03/ImAJ4U0NIE5FK2T+ISBiQ5r+Qgk9iUiLNazWnjHjz6zSm+L7d+C1t32xL\n1fJViR0Ua8nA+IQ3NYQxwFygkYhMAS7DefLIeFhzkSkpR9OP8s8F/2T6b9N592/vck3YNW6HZEKI\nN3MZzReR1UBnz6Zhqrrfv2EFF0sIpiQs276MqGlRXNLoEuIGx1GrUi23QzIhJt+EICKtVHWDiHTE\nGYewy/NWYxFprKqrSyTCIJCQlEDHBh3dDsOEqOOZx3km5hneXfMur1//On+/4O9uh2RCVEE1hJHA\nAOAl8p67qIc3JxCR4UB/nLUU3lHVV0XkReAGnKeXEoF+qnqwMIEHksTkRG6/8Ha3wzAhKG5PHFHT\nomhSswlrB6+lbtW6bodkQpio+m+eOhFpDUwFOuGsqTAXGAw0BxaqapaI/AdAVR/L9Vn1Z2y+1PiV\nxizuu5hmtWy8nvGNzKxM/rv0v/z3p//y4tUvEh0ebfNkGa+ICKpapH8s3gxMewCYoqrJnp9rAb1V\n9Q0vjn8+sFxVUz2fXQzcoqov5thnORC0deBj6cfYm7LX5okxPpOQlED09GjOKHsGKwespEnNJm6H\nZEoJb56THJidDAA83w/08vjrgMs9E+JVBnoCjXLtcy8wx8vjBZxNBzbRpGYTypXx5oEtY/Knqry5\n4k26vNuF2y+4nYVRCy0ZmBLlzVWsjIiUUdUsABEpC5T35uCq+quIjAPmAynAGiAr+30ReQI4rqpT\n8vr8mDFjTnwfERFBRESEN6ctUfaEkfGF7Ye2c9+M+0g+lsz3/b7n/LPOdzskEyRiYmKIiYnxybFO\n24cgIv8FGgNv4XQMDwK2qupDhT6ZyL89n50oIn1xOq2vzG5SyrVvUPQhvPzTy2w5sIVXr3vV7VBM\nEFJVpvxKhxPMAAAaFElEQVQyhX/M+wdDLx7KqMtHWW3TFItf+xBw1lMeCGQvFrwAZ/U0r4jI2aq6\nV0QaAzcDl4jItcAjQPe8kkEwSUhKoNVZrdwOwwSh/Uf3c//s+1m/bz1z755Lh/od3A7JlHLeTH+d\nqapvquqtntdbqpp5us/l8IWIxAMzgCGqegiYAFQFFojIGhHxpoM6IFmTkSmKmb/NpO2bbWlaoymr\nBq6yZGACQkED0z5X1dtEZB2njkNQVW3rzQlUtVse20JmkvbspTON8cahtEP8Y+4/+G7zd3xy6yd0\na3LKfw9jXFNQk9Fwz9eeOH0HJpfjmcfZfmi7PQlivBKzOYa+0/sSGRbJ2sFrqVahmtshGXOSghLC\nLKAD8Jyq3lNC8QSVLQe20LBaQ84oe4bboZgAdiz9GI8vfJzP1n/GOze+w/XnXu92SMbkqaCEUEFE\n+gCXicgtnFxLUFX9yr+hBT7rPzCns2LHCqKmRxFeN5y4wXGcWflMt0MyJl8FJYTBQB+gBnBjHu9b\nQrCEYPKRnpnOc0ueY+KqiYy/djx3tL7D7ZCMOa2CEkI9VR0sIqtV9e0SiyiIWEIweYnfG0/U9Cjq\nVa1H7KBY6ler73ZIxniloMdOH/d8vb+AfUq1hGRLCOYvmVmZvLT0JSI+jGBwx8HM6j3LkoEJKgXV\nEP4UkQVAMxGZmes9VdW/+TGuoGA1BJNtU/Im+n7dF1Vlef/lNK/V3O2QjCm0ghLC9ThPGf0f8F9y\ndSr7M6hgkJmVyZYDW+w/fimnqkxaPYnHFz3OY5c9xojOIyhbpqzbYRlTJPkmBFU9DiwTkS6quk9E\nqqhqSgnGFtC2HdrG2VXOpmK5im6HYlyy6/Au+s/sz+4ju4mJjuHCsy90OyRjisWb6a/PFZH1wK8A\nItIumKea8JWEpATCaoe5HYZxyWfxn9HurXZcVP8ilt23zJKBCQneTG73P+Ba4GsAVY0Vke5+jSoI\nJCQl0KKW9R+UNknHknhgzgPE7o5lVu9ZdGrYye2QjPEZb2oIqOrWXJsy/BBLULEO5dLnmz++oe2b\nbalXpR6rB662ZGBCjjc1hK0ichmAiJwBDAM2+DWqIJCQlECXRl3cDsOUgCPHj/DQvIeYlziPyTdP\npkezHm6HZIxfeFNDuB94AGgI7ADae34u1ayGUDp8v+V7wieGk5GVQdz9cZYMTEg7bQ1BVfcBd5VA\nLEEjS7PYmLzROpVDWGpGKqMXjebjXz7mrRve4sbz8pq9xZjQYmv1FcHOwzupUbEGVc+o6nYoxg9W\n71pN1LQozj/rfNYOXkudKnXcDsmYEmEJoQisuSg0ZWRl8Pz3zzPh5wm8EvkKd7W5CxFbCsSUHpYQ\niiAxyVZJCzW/7v+VqGlR1KxYk9WDVtOoeiO3QzKmxHn12CmAiHQWkbkislhEbvZnUIEuISmBsFrW\nfxAKsjSL8cvH0/W9rvRr1495d8+zZGBKrYLWVK6nqrtzbHoIuMXz/c/ANH8GFsgSkhP4e6u/ux2G\nKaYtB7bQ7+t+pGWmsaz/Mqv1mVKvoBrCRBF5SkSyJ+s5APwdJykc9HtkAcz6EIKbqvL+mve56J2L\niAyLZEnfJfb3NIaCJ7e7SURuBGaJyEfACJzHTysBN5VQfAFHVa3JKIjtObKHgbMGsvnAZhZGLaRt\n3bZuh2RMwCiwD0FVZwKRQE2cJqLfVHW8Z2xCqbQ3ZS8VylagVqVabodiCunL9V8SPjGc1nVas2LA\nCksGxuRSUB9CL5xaQSYwFpgMjBaRIcATqppYMiEGFmsuCj4HUg8w9JuhLN++nGl3TKPLOTbliDF5\nKaiG8BzOIjm3AS+oarKqjgRGA/8uieACkSWE4LIgcQFt3mxDjQo1WDNojSUDYwpQ0DiEg8DNQBVg\nT/ZGVf0DuMPPcQUsSwjBIeV4Co8ueJSZv8/k/V7vc1Xzq9wOyZiAV1AN4WbgLKAsNpfRCYnJNigt\n0C3dtpR2b7Xj8PHDxN0fZ8nAGC8V9JTRPmB8CcYSFOwJo8CVlpHGM4uf4b017/FGzze4pdUtp/+Q\nMeYEr0cqF4WIDBeRX0RknYgM92yrLSILROR3EZkvIjX9GYOvWZNRYIrbE8fFky5m/b71rB281pKB\nMUXgt4QgIq2B/kAnIBy4QUTCgMeABaraEljo+TkoJB1LIlMzOavyWW6HYjyyJ6S78qMrGdl5JNPu\nmEbdqnXdDsuYoOTPye3OB5araiqAiCzGGen8NyB7TeYPgRiCJClk1w5sBszA8MeffxA9PZpK5Sux\nauAqGtdo7HZIxgQ1fzYZrQMu9zQRVcZ5hLURUFdVs59a2gMEze2cNRcFBlXljRVvcOl7l9K7dW8W\n3LPAkoExPuC3GoKq/ioi44D5QAoQizPILec+KiKa3zHGjBlz4vuIiAgiIiL8Equ3EpISaFHLEoKb\nth/azr1f38vBtIP80O8HzjvrPLdDMsZVMTExxMTE+ORYoprv9dinRGQssB0YDkSo6m4RqQ98p6rn\n57G/llRs3oqaFkWPpj3o176f26GUOqrKx798zMh5Ixl2yTAe6/oY5crYch7G5CYiqGqR2rX9+j9K\nRM5W1b0i0hhnltTOQDMgGhjn+TrdnzH4UmJyIgM6DHA7jFJnX8o+Bs8ezO9//s68u+fRvn57t0My\nJiT59bFT4AsRiQdmAENU9SDwH+BqEfkduMLzc1BISEogrLaNQShJM36bQfjEcMJqhbFiwApLBsb4\nkV9rCKraLY9tSUDQDR09lHaII8ePUL9qfbdDKRUOph5kxLwRLNmyhE9v/ZTLm1zudkjGhDx/1xBC\nRmJSImG1wuyR0xLw3abvCJ8YToWyFVg7eK0lA2NKiPXKeckeOfW/o+lHGfXtKL7c8CWT/jaJa1tc\n63ZIxpQqVkPwkiUE//p5x890eKsD+47uI+7+OEsGxrjAagheSkhK4JJGl7gdRsg5nnmc55Y8x1ur\n3mLCdRO4/cLb3Q7JmFLLEoKXEpIT6NO2j9thhJR1e9cRNS2KBtUaEDsolvrVrMPeGDdZk5GXrMnI\ndzKzMnnxxxfp8WEPHuj0ADN7z7RkYEwAsBqCF46mHyXpWBKNqjdyO5SgtzF5I9HToykjZfi5/880\nq9XM7ZCMMR5WQ/DCxuSNNK3ZlDJiv66iUlXeXvU2l0y6hJvPv5nvor+zZGBMgLEaghesuah4dh7e\nSf8Z/dmbspfFfRdzQZ0L3A7JGJMHu+X1gs1yWnSfrPuE9m+15+KGF/PTfT9ZMjAmgFkNwQsJSQm0\nObuN22EElT+P/smQOUP4Zc8vzL5rNhc1uMjtkIwxp2E1BC9Yk1HhzPljDm0ntqVhtYasGrjKkoEx\nQcJqCF6whOCdw2mHeWj+QyzYuICPb/mYiKYRbodkjCkEqyGcRlpGGruO7KJJzSZuhxLQlmxZQvjE\ncLI0i7WD11oyMCYIWQ3hNDYd2ETjGo1tda58pGak8sTCJ5i6bipv3/g2N7S8we2QjDFFZFe500hM\nSrTmonys2rmKqOlRXFDnAuLuj+Osyme5HZIxphgsIZxGQlICYbVslbSc0jPTef6H53l9xeu8EvkK\nvVv3tnUijAkBlhBOwzqUT7Zh3waipkdxZqUzWT1wNQ2rN3Q7JGOMj1in8mkkJFtCAMjSLP637H90\n+6Ab97W/j2/6fGPJwJgQYzWE07AaAmw+sJl+X/cjPTOdZfctI6y2NaEZE4qshlCA9Mx0th7cSrOa\npXMSNlXlvTXv0emdTlzX4joW911sycCYEGY1hAJsPbiV+lXrU6FcBbdDKXG7j+xm4MyBbD24lUVR\ni2hT16buMCbUWQ2hAKW1ueiL9V/QbmI72tZty88DfrZkYEwpYTWEApS2hJB8LJmh3wzl5x0/M/3O\n6XRu1NntkIwxJchqCAVITC49g9LmJ86n7cS21K5Um9jBsZYMjCmFrIZQgISkBC5vfLnbYfhVyvEU\nHlnwCLP/mM0HvT7gyuZXuh2SMcYlVkMoQKg3Gf249UfCJ4ZzNP0ocYPjLBkYU8pZDSEfmVmZbDqw\niea1mrsdis+lZaTxdMzTfLj2Q97s+SY3nX+T2yEZYwKAXxOCiIwC7gaygF+AfkA48BpQHsgAhqjq\nCn/GURQ7Du+gdqXaVDmjituh+FTs7liipkXRonYL1g5ey9lVznY7JGNMgPBbk5GINAUGAB1UtQ1Q\nFrgTGAeMVtX2wFPAC/6KoThCrbkoIyuDf3//b66ZfA0PX/owX97+pSUDY8xJ/FlDOASkA5VFJBOo\nDOwEdgM1PPvUBHb4MYYiS0hKoEWt0EgIv//5O9HTo6lSvgorB66kcY3GbodkjAlAfksIqpokIi8B\nW4FjwDxVXSAivwM/iMh/cWooXfwVQ3GEQg0hS7N4Y8UbPLP4GZ7u/jRDOg2hjNhzBMaYvPktIYhI\nGDACaAocBD4XkT44/QjDVHWaiNwGvAdc7a84iiohKYHerXu7HUaRbTu4jXtn3MvhtMP8eO+PtDyz\npdshGWMCnD+bjC4ClqrqnwAi8hVwGXCxql7l2ecLYFJ+BxgzZsyJ7yMiIoiIiPBXrKcI1kFpqsrk\nuMk8PP9hRnQewaOXPWrLfxoTwmJiYoiJifHJsURVfXKgUw4sEg58DHQCUoH3gZU4NYSRqrpYRK4E\n/qOqnfL4vPorttNRVao+X5VdD+2ieoXqrsRQFPtS9jFo1iD+SPqDyTdPpl29dm6HZIwpYSKCqhZp\nCUN/9iGsFZGPcJJAFrAaeAtYBrwuIhVw+hYG+iuGotp9ZDdVylcJqmQw/dfp3D/7fqLDo5n696ml\ncoZWY0zx+LUtQVVf4NTHSlcCl/jzvMUVTB3KB1MPMnzucH7Y+gNf3PYFlzW+zO2QjDFByh45yUOw\nJISFGxfSdmJbKpevTOzgWEsGxphisd7GPAR6QjiafpTHvn2Mab9OY9KNk4hsEel2SMaYEGA1hDwk\nJAduQli+fTnt32pP0rEk4gbHWTIwxviM1RDyEIg1hOOZx3l28bNMWj2J165/jVsvuNXtkIwxIcYS\nQi6qSmJSYI1BWLd3HfdMu4dG1RsROziWelXruR2SMSYEWZNRLn8e+5MyUobalWq7HQqZWZm88OML\n9PiwB0MvHsqMO2dYMjDG+I3VEHJJSEogrHaY22GQmJRI9PRoypUpx4oBK2has6nbIRljQpzVEHJx\nu/9AVZm4ciKd3+3MrRfcyqLoRZYMjDElwmoIubg57fWOQzvoP7M/+4/uZ0nfJbSq08qVOIwxpZPV\nEHJxo4agqkz9ZSrt32pP54adWXrvUksGxpgSZzWEXBKSErj/ovtL7Hz7j+5nyOwhxO+L55s+39Cx\nQccSO7cxxuRkNYRcSrKGMOv3WYRPDKdxjcasGrjKkoExxlVWQ8jhQOoB0jLT/L7W8KG0Q4ycN5JF\nmxYx5ZYpdG/a3a/nM8YYb1gNIYfsAWkiRZpK3CuLNy8mfGI4grB28FpLBsaYgGE1hBz82Vx0LP0Y\nTyx6gk/jP+XtG96mZ8uefjmPMcYUlSWEHBKSEgir5ftBaSt3riRqWhRt6rYhbnAcZ1Y+0+fnMMaY\n4rKEkENCcgKXneO7NQXSM9MZ+/1Y3lz5Jq9e+yp3tr7TZ8c2xhhfs4SQQ0JSAtHh0T451vp964ma\nFkWdKnVYM2gNDao18MlxjTHGX6xTOQdf9CFkaRYv//Qy3T/ozoAOA5hz1xxLBsaYoGA1BI8jx49w\nMPVgsS7emw9spu/0vmRqJsvuWxYQk+QZY4y3rIbgkZiUSPNazSkjhf+VqCrvrn6XTu904oaWNxAT\nHWPJwBgTdKyG4FHU5qJdh3cxYOYAdh7eyXfR39H67NZ+iM4YY/zPaggeicmFXyXt8/jPafdWO9rX\na8+y/sssGRhjgprVEDwSkhLoUL+DV/smHUviwTkPsnrXamb2nsnFDS/2c3TGGON/VkPw8HZQ2tyE\nubR9sy11Ktdh9aDVlgyMMSHDaggep+tDOHL8CA/Pf5i5CXP56OaPuKLZFSUYnTHG+J/VEHDmGdqb\nspdzapyT5/s/bP2BdhPbkZaZxtrBay0ZGGNCktUQgE0HNtGkZhPKlTn515GakcpT3z3F5LjJTOw5\nkV7n93IpQmOM8T+/1hBEZJSIxIvILyIyRUQqeLYPFZENIrJORMb5MwZv5NVcFLs7lk7vdCIxOZG4\nwXGWDIwxIc9vCUFEmgIDgA6q2gYoC9wpIj2AvwFtVbU18F9/xeCthKQEWtRyEkJGVgZjl4zlmsnX\n8M/L/skXt31BnSp1fH7OmJgYnx8zUIRy2cDKF+xCvXzF4c8awiEgHagsIuWAysBOYDDwvKqmA6jq\nPj/GcFqzF8zmf2P/x+x3ZtP17q5c+OiFxGyJYdXAVdzd9m6/LZYTyv8oQ7lsYOULdqFevuLwW0JQ\n1STgJWArTiI4oKoLgJZANxFZJiIxInKRv2I4ndkLZjP89eFs67SNxPBEfjz3R5LWJTGs7rB8O5iN\nMSZU+bPJKAwYATQFGgBVRaQPTkd2LVXtDDwCfOavGE5n/JTxJLZPPGnb/i77ef2T112KyBhj3COq\n6p8Di9wBXK2q/T0/3wN0BpoD/1HVxZ7tCcAlqvpnrs/7JzBjjAlxqlqktm5/Pnb6KzBaRCoBqcBV\nwM9AHHAFsFhEWgJn5E4GUPQCGWOMKRq/JQRVXSsiHwErgSxgNfC25+33ROQX4DgQ5a8YjDHGeM9v\nTUbGGGOCi+tTV4jIOSLynWcA2zoRGebZXltEFojI7yIyX0Rquh1rcYhIWRFZIyIzPT+HTPlEpKaI\nfOEZbLheRC4JlfLlNbgymMsmIu+JyB5PDT17W77l8ZT/DxH5VUSucSdq7+VTvhc9/zbXishXIlIj\nx3tBX74c7z0kIlkiUjvHtkKVz/WEgDNW4R+qeiFOp/MDItIKeAxYoKotgYWen4PZcGA9kF0lC6Xy\nvQrMUdVWQFuc/qOgL19+gysJ7rK9D1yba1ue5RGRC4A7gAs8n3lDpAhLCpasvMo3H7hQVcOB34FR\nEFLlQ0TOAa4GtuTYVujyuV54Vd2tqrGe748AG4CGOKOZP/Ts9iFwkzsRFp+INAKuByYB2Z3lIVE+\nz93W5ar6HoCqZqjqQUKjfPkNrgzasqnq90Byrs35lacXMFVV01V1M5AABPR873mVT1UXqGqW58fl\nQCPP9yFRPo+XgUdzbSt0+VxPCDl57sja4/zR6qrqHs9be4C6LoXlC6/gjLnIyrEtVMrXDNgnIu+L\nyGoReUdEqhAC5StgcGXQly2X/MrTANieY7/tODdrwexeYI7n+5Aon4j0AraralyutwpdvoBJCCJS\nFfgSGK6qh3O+p07Pd1D2fovIDcBeVV3DX7WDkwRz+XCeVOsAvKGqHYAUcjWhBGv58hlceXfOfYK1\nbPnxojxBW1YReQI4rqpTCtgtqMonIpWBx4Gnc24u4CMFli8gEoKIlMdJBpNVdbpn8x4Rqed5vz6w\n1634iulS4G8isgmYClwhIpMJnfJtx7k7WeH5+QucBLE7BMp3EbBUVf9U1QzgK6ALoVG2nPL7t7gD\nyDmHSyPPtqAjIn1xmm375NgcCuULw7lhWeu5xjQCVolIXYpQPtcTgjizx70LrFfV/+V4awYQ7fk+\nGpie+7PBQFUfV9VzVLUZTofkIlW9h9Ap325gm2eQITgDEOOBmQR/+X4FOotIJc+/06twHgwIhbLl\nlN+/xRk4MxSfISLNgHNxBpcGFRG5FqfJtpeqpuZ4K+jLp6q/qGpdVW3mucZsx3kIYg9FKZ+quvoC\nuuK0rccCazyva4HawLc4TwXMB2q6HasPytodmOH5PmTKB4QDK4C1OHfRNUKlfDgddfHALzgdruWD\nuWw4tdSdOINCtwH9CioPTnNEAk5yjHQ7/iKU717gD5ynb7KvL2+EQPnSsv9+ud7fCNQuavlsYJox\nxhggAJqMjDHGBAZLCMYYYwBLCMYYYzwsIRhjjAEsIRhjjPGwhGCMMQawhGCCkIjUEZEfPFNS98qx\nfXr2iNtCHmu5iKwSkctyvXe5Z+rr1SJSoYBjxIhIB8/3m3NOP5xjnzy3F5aI9BWRCcU9jjF5sYRg\nglFv4A2cmRtHAIjIjcBqdUZOF8aVQJyqdlTVH3O91wf4t6p2UNW0Ao6h+Xyf3z7GBCRLCCYYHQeq\nABWBTBEpi7PexAv5fUBEmorIIs8iKd+KszBTO2Ac0EucxYsq5ti/P3Ab8C8R+T8R6S6exY08778m\nItGnnun0RGSkp3bzi4gMz7F9moisFGehqAE5tvcTkd9EZDnO3FjG+IUlBBOMpuDM9T4fGAs8AHyk\nJ89Tk9sE4H11Fkn5GBivzjocTwGfqGr7nJ9X1Uk4c8E8rKp3c+oMkkWa5VREOgJ9cWo3nYEBnsQE\ncK+qXgR0AoaJSC3PZHNjcBJBV5zFTqy2YfzCEoIJOqp6SFVvUNVOOHNg3QB86VmL4XMR6ZzHxzrj\nJBKA/8O5uIJzoS9ouuCC3iss8Zz3K1U9pqopOHM/Xe55f7iIxAI/4cxM2RK4BIhRZ8bVdOBTH8dk\nzAnl3A7AmGIaDTwH3AUswZlG/SvyWGaQol1Is+/GMzj5BqpSEY6VfbyccQiAiETg9Gd0VtVUEfkO\np0ksd23AkoHxG6shmKAlIucCDVR1Cc4FOvvimdfFeinO9OPgdBYv8fY0nq9bgAs8UwnXBK4oQsgK\nfA/c5JlSuwrOcpVLgOpAsicZnI9To1Gc1QO7i0htz7ohtxXhvMZ4xWoIJpg9hzO9LzjTAk/HWa1t\ndB77DgXeF5FHcBaA6efZ7tUKYaq6TUQ+A9YBm4DVhYw1+zhrROQD/pqX/h1VXSsiG4DBIrIe+A2n\n2QhV3S0iYzw/H8CZvtn6EIxf2PTXxhhjAGsyMsYY42EJwRhjDGAJwRhjjIclBGOMMYAlBGOMMR6W\nEIwxxgCWEIwxxnhYQjDGGAPA/wMqL97FjXaK2wAAAABJRU5ErkJggg==\n", + "text/plain": [ + "<matplotlib.figure.Figure at 0x7f42d136e490>" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import math\n", + "\n", + "#case a\n", + "\n", + "#transformer output=0.01x1000cos(angle)W\n", + "\n", + "#loss=10xScos(angle)\n", + "#transformer efficiency n=(10xScos(angle)/(10xScos(angle)+pc+0.0001x2Pcu))\n", + "\n", + "print \"n=((10xScos(angle))/(10xScos(angle)+pc+0.0001x2Pcu))\"\n", + "\n", + "%matplotlib inline\n", + "import matplotlib.pyplot as plt\n", + "\n", + "x1=20.5\n", + "x2=30\n", + "x3=40\n", + "x4=50\n", + "x5=60.5\n", + "x6=70\n", + "x7=80\n", + "x8=90\n", + "x9=100\n", + "x10=110\n", + "y1=94.3\n", + "y2=95\n", + "y3=96\n", + "y4=96.5\n", + "y5=96.8\n", + "y6=96.9\n", + "y7=97\n", + "y8=97\n", + "y9=97\n", + "y10=97\n", + "plt.plot([x1,x2,x3,x4,x5,x6,x7,x8,x9,x10],[y1,y2,y3,y4,y5,y6,y7,y8,y9,y10],marker='o',color='b',label='0.65')\n", + "\n", + "\n", + "p1=120.5\n", + "p2=30\n", + "p3=40\n", + "p4=50\n", + "p5=70\n", + "p6=80\n", + "p7=90\n", + "p8=100\n", + "p9=110\n", + "q1=95.3\n", + "q2=86\n", + "q3=96.7\n", + "q4=97.2\n", + "q5=97.5\n", + "q6=97.5\n", + "q7=97.5\n", + "q8=97.5\n", + "q9=97.5\n", + "plt.plot([p1,p2,p3,p4,p5,p6,p7,p8,p9],[q1,q2,q3,q4,q5,q6,q7,q8,q9],marker='o',color='g',label='0.8')\n", + "\n", + "\n", + "\n", + "x2=[20.5,30,40,50,70,80,90,100,110]\n", + "y2=[96.2,96.6,97.4,97.6,98,98,98,98,98]\n", + "plt.plot(x2,y2,label='pf=1')\n", + "\n", + "\n", + "plt.xlabel('% of full load')\n", + "plt.ylabel('% efficiency')\n", + "plt.legend()\n", + "plt.show()\n", + "\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.10:Page number-378\n" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "15306.122449\n", + "306.12244898\n", + "0.971216989926\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "#at unity power factor\n", + "\n", + "op=15000\n", + "n=0.98\n", + "\n", + "i=op/float(n)\n", + "print i\n", + "\n", + "loss=i-op\n", + "print loss\n", + "\n", + "pc=float(loss)/2000 #actually division by 2 but value given only to make pc 0.153 instead of 153\n", + "\n", + "t=pc*24 #iron loss in a day\n", + "\n", + "toteng=20+96+108 #sum of energy outputs\n", + "\n", + "engloss=0.109+1.224+1.632 #sum of energy losses\n", + "\n", + "n=toteng/float(engloss+toteng+t)\n", + "\n", + "print n" + ] + }, + { + "cell_type": "markdown", + "metadata": { + "collapsed": true + }, + "source": [ + "## Example 6.11:Page number-381" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.9726443769\n", + "30\n", + "0.990625\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "kva=10000\n", + "pf=0.8\n", + "iloss=75\n", + "closs=150\n", + "a=0.5\n", + "\n", + "#case a\n", + "po=kva*pf\n", + "loss=75+150\n", + "\n", + "n=po/float(po+loss)\n", + "\n", + "print n\n", + "\n", + "#case b\n", + "\n", + "i2=(10*1000)/(200)\n", + "\n", + "i1=i2+((10*1000)/400)\n", + "\n", + "kvar=(600*50)/1000\n", + "\n", + "print kvar\n", + "\n", + "po=30*0.8\n", + "\n", + "n=1-(0.225/24)\n", + "\n", + "print n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.12:Page number-382" + ] + }, + { + "cell_type": "code", + "execution_count": 22, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "sat= 180.0 Kva\n", + "sat= 900.0 kva\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "#case 1\n", + "\n", + "#2300 winding used as secondary\n", + "#given and derived\n", + "\n", + "st=150\n", + "v1=13800\n", + "v2=2300\n", + "\n", + "a=(v1-v2)/v2\n", + "\n", + "b=a+1\n", + "\n", + "sat=(6*150)/5\n", + "\n", + "print \"sat=\",format(sat,'.1f'),\"Kva\"\n", + "\n", + "#case 2\n", + "\n", + "v1=13.8\n", + "v2=11.5\n", + "\n", + "a=(v1-v2)/v2\n", + "\n", + "sat=((1+a)/a)*150\n", + "\n", + "print \"sat=\",format(sat,'.1f'),\"kva\"" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.13:Page number-391" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "v2l= 440.0 V\n", + "i2p= 86.6 A\n", + "i2l= 150.0 A\n", + "v2p= 254.0 V\n", + "v2l= 440.0 V\n", + "i2p=i2l= 150.0 A\n", + "v2p= 440.0 V\n", + "v2l= 762.1 V\n", + "i2p= 86.6 A\n", + "v2p= 254.0 V\n", + "i2p= 150.0 A\n", + "i2l= 259.8 A\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "#given and 1.732 is the value of root 3\n", + "v=6600\n", + "i=10\n", + "n=15\n", + "\n", + "#case a\n", + "\n", + "v2l=v/n\n", + "\n", + "print \"v2l=\",format(v2l,'.1f'),\"V\"\n", + "\n", + "i1p=10/1.732\n", + "\n", + "i2p=i1p*n\n", + "\n", + "print \"i2p=\",format(i2p,'.1f'),\"A\"\n", + "\n", + "i2l=n*i1p*1.732\n", + "\n", + "print \"i2l=\",format(i2l,'.1f'),\"A\"\n", + "\n", + "#case b\n", + "\n", + "v2p=v/(n*1.732)\n", + "\n", + "print \"v2p=\",format(v2p,'.1f'),\"V\"\n", + "\n", + "v2l=v2p*1.732\n", + "\n", + "print \"v2l=\",format(v2l,'.1f'),\"V\"\n", + "\n", + "i2l=i2p=n*i\n", + "\n", + "print \"i2p=i2l=\",format(i2p,'.1f'),\"A\"\n", + "\n", + "#case c\n", + "\n", + "v2p=v/n\n", + "\n", + "print \"v2p=\",format(v2p,'.1f'),\"V\"\n", + "\n", + "v2l=(v*1.732)/n\n", + "\n", + "print \"v2l=\",format(v2l,'.1f'),\"V\"\n", + "\n", + "i1p=i/1.732\n", + "\n", + "i2p=i2l=(n*i1p)\n", + "\n", + "print \"i2p=\",format(i2p,'.1f'),\"A\"\n", + "\n", + "#case d\n", + "\n", + "v1p=v/1.732\n", + "\n", + "v2p=v2l=v/(n*1.732)\n", + "\n", + "print \"v2p=\",format(v2p,'.1f'),\"V\"\n", + "\n", + "i1p=10\n", + "\n", + "i2p=i1p*n\n", + "\n", + "print \"i2p=\",format(i2p,'.1f'),\"A\"\n", + "\n", + "i2l=i2p*1.732\n", + "\n", + "print \"i2l=\",format(i2l,'.1f'),\"A\"\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example 6.14" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "metadata": { + "collapsed": false + }, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "ihv= 3.69402 A\n" + ] + } + ], + "source": [ + "import math\n", + "\n", + "#given\n", + "\n", + "hp=75\n", + "v=415\n", + "n=0.9\n", + "pf=0.85\n", + "\n", + "op=75*746 #since its horse power\n", + "ip=op/n\n", + "\n", + "ilv=ip/(1.732*v*pf) #line current on low voltage start side\n", + "\n", + "a=(6600*1.732)/415 #given in question\n", + "\n", + "ihv=ilv/a\n", + "\n", + "print \"ihv=\",format(ihv,'.5f'),\"A\"\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": true + }, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 2", + "language": "python", + "name": "python2" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 2 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython2", + "version": "2.7.9" + } + }, + "nbformat": 4, + "nbformat_minor": 0 +} |