path: root/Generation_Of_Electrical_Energy_by_B._R._Gupta/Chapter2.ipynb

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   "cells": [
    {
     "cell_type": "heading",
     "level": 1,
     "metadata": {},
     "source": [
      "Ch-2, Loads & Load Curves"
     ]
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example - 2.1, page - 17"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from __future__ import division\n",
      "print \"solution for (a)\"\n",
      "nb=8; nf=2; nl=2 #given number of equipments is 8 bulbs 2 fans 2plugs\n",
      "lb=100 ;lf=60 ;ll=100 #corresponding wattages\n",
      "cl=nb*lb+nf*lf+nl*ll  #total connected load\n",
      "print \"connected load = %dW\\n\"%(cl) \n",
      "print \"solution for (b)\"\n",
      "t1=5 ;t2=2 ;t3=2; t4=9; t5=6; # time periods in hours\n",
      "# let = [bulb, fan, light]\n",
      "w1=1*lf #12 to 5am period of duration 5h\n",
      "w2=2*lf+1*ll #5am to 7am period of duration 2h\n",
      "w3=0 #7am to 9am period of duration 2h\n",
      "w4=2*lf #9am to 6pm period of duration 9h\n",
      "w5=4*lb+2*lf #6pm to 12pm period of duration 6h\n",
      "w=[w1 ,w2 ,w3, w4, w5]\n",
      "print \"\\nthe maximum demand is %d W\\n\"%(max(w))\n",
      "m=max(w)\n",
      "print \"solution for (c)\"\n",
      "df=m/cl\n",
      "print \"\\ndemand factor =%0.3f\\n\"%(df)\n",
      "print \"solution for (d)\"\n",
      "#energy consumed is power multiply by corresponding time\n",
      "energy=[w1*t1 ,w2*t2 ,w3*t3 ,w4*t4, w5*t5]\n",
      "e=sum(energy)\n",
      "print \"\\ntotal energy consumed during 24 hours = %d Wh = %0.2f kWh\\n\"%(e,e/1e3)\n",
      "print \"solution for (e)\" \n",
      "ec=cl*24 \n",
      "print \"\\nif all devices are used throughout the day the energy consumed = %d Wh = %.2fkWh\"%(ec,ec/1000)     \n",
      "#for 24 hours of max. load\n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "solution for (a)\n",
        "connected load = 1120W\n",
        "\n",
        "solution for (b)\n",
        "\n",
        "the maximum demand is 520 W\n",
        "\n",
        "solution for (c)\n",
        "\n",
        "demand factor =0.464\n",
        "\n",
        "solution for (d)\n",
        "\n",
        "total energy consumed during 24 hours = 4940 Wh = 4.94 kWh\n",
        "\n",
        "solution for (e)\n",
        "\n",
        "if all devices are used throughout the day the energy consumed = 26880 Wh = 26.88kWh\n"
       ]
      }
     ],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.2, page - 19"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print \"(a)\" \n",
      "mca=1.1 ;cla=2.5; mcb=1; clb=3;       #mca=maximum demand of consumera cla=connected load of a mcb=maximum load of consumer b clb=connected load of consumer b\n",
      "print \"maximum demand of consumer A = %0.1fkW \\n \\ndemand factor of consumer A = %0.2f \\n \\nmaximum demand of consumer B = %dkW\\n \\ndemand factor of consumer B = %0.3f\"%(mca,mca/cla,mcb,mcb/clb)\n",
      "print \"(b)\"\n",
      "print \"The variation in demand versus time curves are plotted and shown in Fig This is known as chronological load curve.\"\n",
      "a=([100]*5,[1100]*1,[200]*2,[0]*9,[500]*7)\n",
      "i=0\n",
      "A=range(1,25)\n",
      "for x in a:\n",
      "\n",
      "    for y in x:\n",
      "        \n",
      "        A[i]=y\n",
      "        i+=1\n",
      "\n",
      "        \n",
      "b=([0]*(7),[300]*(1),[1000]*(2),[200]*(8),[600]*(5),[0]*(1))  #time line of different periods by a and b consumers\n",
      "i=0\n",
      "B=range(1,25)\n",
      "for x in b:\n",
      "\n",
      "    for y in x:\n",
      "        \n",
      "        B[i]=y\n",
      "        i+=1\n",
      "from numpy import arange, nditer\n",
      "t=arange(1,25,1)         #for 24 hours ploting\n",
      "ma=max(A) ;mb=max(B) \n",
      "%matplotlib inline\n",
      "from matplotlib.pyplot import plot, subplot, title, title, show, hist\n",
      "\n",
      "subplot(211)        #matrix plotting\n",
      "plot(t,A) \n",
      "plot(t,B) \n",
      "title(\"load curves of A and B: fig(1) \\n\")\n",
      "show()\n",
      "C=range(1,25)\n",
      "i=0\n",
      "for x,y in nditer([A,B]):\n",
      "   C[i]=x+y \n",
      "   i+=1 \n",
      "subplot(222) \n",
      "plot(t,C)  \n",
      "title(\"chronological load of group : fig(2) \\n\")\n",
      "show()\n",
      "mg=max(C)  #maximum demand of group\n",
      "print \"(c)\"\n",
      "print \"maximum demand of the group is %dW\"%(mg) \n",
      "gd=(ma+mb)/mg \n",
      "print \"group diversity factor = %.3f\"%(gd)   #group diversity factor is sum of individual maximum consumaer load to the group max load \n",
      "print \"(d)\"\n",
      "sa=sum(A)\n",
      "print \"energy consumed by A during 24 hours is = %d Wh = %0.2f kWh\"%(sa,sa/1e3)\n",
      "sb=sum(B) \n",
      "print \"(e)\" \n",
      "print \"maximum energy which A could consume in 24hours = %.2fkWh \\nmaximum energy which B consume in 24 hours is =%.2fkWh\"%(mca*24,mcb*24 ) \n",
      "print \"(f)\" \n",
      "print \"actual energy/maximum energy\" \n",
      "mca=mca*10**3; mcb=mcb*10**3\n",
      "aemea=sa/(mca*24)\n",
      "aemeb=sb/(mcb*24)\n",
      "print \"\\nfor A = %0.4f \\nfor b = %.4f\"%(sa/(mca*24),aemeb) \n"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(a)\n",
        "maximum demand of consumer A = 1.1kW \n",
        " \n",
        "demand factor of consumer A = 0.44 \n",
        " \n",
        "maximum demand of consumer B = 1kW\n",
        " \n",
        "demand factor of consumer B = 0.333\n",
        "(b)\n",
        "The variation in demand versus time curves are plotted and shown in Fig This is known as chronological load curve.\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
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       "text": [
        "<matplotlib.figure.Figure at 0x7f31dcdedc90>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7f31dcadf050>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(c)\n",
        "maximum demand of the group is 1100W\n",
        "group diversity factor = 1.909\n",
        "(d)\n",
        "energy consumed by A during 24 hours is = 5500 Wh = 5.50 kWh\n",
        "(e)\n",
        "maximum energy which A could consume in 24hours = 26.40kWh \n",
        "maximum energy which B consume in 24 hours is =24.00kWh\n",
        "(f)\n",
        "actual energy/maximum energy\n",
        "\n",
        "for A = 0.2083 \n",
        "for b = 0.2875\n"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.3 : page - 22"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cola=5 ;na=600; ns=20 \n",
      "cls=2 ;clfm=10 ;clsm=5; cll=20; i=80 \n",
      "dffl=0.7; dfsm=0.8; dfl=0.65; dfci=0.5 \n",
      "nsl=200 ;clsl=0.04 ;dfa=0.5; gdfa=3.0 \n",
      "pdfa=1.25; gdfc=2 ;pdfc=1.6; dfs=0.8  #given col||cl=connected load,n=number,df=demand factor,gdf=group diversity factor,pdf=peak diversity factor,a=appartement,c=commertials,s=shop,sl=streetlight,fm=flourmill,sm=saw mill,l=laundry,ci=cinema complex.\n",
      "mdea=cola*dfa\n",
      "print \"maximum demand of each appartment =%.2fkWh \\n\"%(mdea)\n",
      "mda=(na*mdea)/gdfa\n",
      "print \"maximum demand of 600 apatments =%.2fkW \\n\"%(mda) \n",
      "datsp=mda/pdfa\n",
      "print \"demand of 600 apartments at time of the system peak =%dkW \\n\"%(datsp)  \n",
      "mdtcc=((cls*ns*dfs)+(clfm*dffl)+(clsm*dfsm)+(cll*dfl)+(i*dfci))/gdfc\n",
      "print \"maximum demand of total commertial complex=%dkW \\n\"%(mdtcc)\n",
      "dcsp=mdtcc/pdfc\n",
      "print \"demand of the commertial load at the time of the peak = %dkW\\n\"%(dcsp) \n",
      "dsltsp=nsl*clsl\n",
      "print \"demand of the street lighting at the time of the system peak =%dkW\"%(dsltsp) \n",
      "ispd=datsp+dcsp+dsltsp\n",
      "print \"\\nincrease in system peak deamand =%dkW \"%(ispd)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "maximum demand of each appartment =2.50kWh \n",
        "\n",
        "maximum demand of 600 apatments =500.00kW \n",
        "\n",
        "demand of 600 apartments at time of the system peak =400kW \n",
        "\n",
        "maximum demand of total commertial complex=48kW \n",
        "\n",
        "demand of the commertial load at the time of the peak = 30kW\n",
        "\n",
        "demand of the street lighting at the time of the system peak =8kW\n",
        "\n",
        "increase in system peak deamand =438kW \n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.4 : page -28"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from __future__ import division\n",
      "print \"the chronological load curve is plotted in fig 1 the durition of loads is as under :\"\n",
      "LC=([20]*(5),[40]*4,[80]*9,[100]*4,[20]*2)\n",
      "\n",
      "i=0\n",
      "lc=range(1,25)\n",
      "for x in LC:\n",
      "    for y in x:\n",
      "        lc[i] = y\n",
      "        i+=1\n",
      "lc.sort()\n",
      "\n",
      "nn=len(lc)\n",
      "\n",
      "e=sum(lc)\n",
      "print lc\n",
      "print \"\\nthe load duration curve is ploted in 2 the energy produced by plant in 24 hours = %d MWh \\n\"%(e) \n",
      "lff=e/(24*max(lc)) \n",
      "print \"load factor = %0.4f= %.2f %%\"%(lff,lff*100)\n",
      "t=range(1,25)\n",
      "subplot(211) \n",
      "plot(t,lc) \n",
      "show()\n",
      "title(\"chronological curve\")\n",
      "subplot(212) \n",
      "plot(t,lc) \n",
      "title(\"load duration curve\")\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "the chronological load curve is plotted in fig 1 the durition of loads is as under :\n",
        "[20, 20, 20, 20, 20, 20, 20, 40, 40, 40, 40, 80, 80, 80, 80, 80, 80, 80, 80, 80, 100, 100, 100, 100]\n",
        "\n",
        "the load duration curve is ploted in 2 the energy produced by plant in 24 hours = 1420 MWh \n",
        "\n",
        "load factor = 0.5917= 59.17 %\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7f31f86db090>"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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1lzRN0v3pcR9JD0uaI2mCpK07Jkyz9XP9GbPK2tuCPx+YRTarFVyLxqrovfdgyhTwPDmz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\n8GZmdcoJ3sysTjnBm5nVKSd4M7M69f9mVBHwfc39XwAAAABJRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f31dc8e5090>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.5 : page - 29"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from __future__ import division\n",
      "lf=0.5917; ml=100; ic=125  #lf=load factor,ic=installed capacity,ml=maximum load,cf=capacity factor,uf=utillization factor\n",
      "cf=(ml*lf)/ic; uf=ml/ic\n",
      "print \"capacity factor =%0.3f\"%(cf)\n",
      "print \"\\nutilisation factor =%.2f\"%(uf)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "capacity factor =0.473\n",
        "\n",
        "utilisation factor =0.80\n"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.6 : page - 29"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "\n",
      "t=[24, 24-7, 24-11, 4] # Periods for running load 20,40,80,100\n",
      "l = [20,40,80,100] # different loads\n",
      "E= range(0,len(l))\n",
      "E[0] = t[0]*l[0] # MWh\n",
      "i=1\n",
      "for x in E[1:]:\n",
      "    E[i] = E[i-1]+(l[i]-l[i-1])*t[i]\n",
      "    i+=1\n",
      "\n",
      "print \"Energy at different load levels:\\nLoad(MW)\\t\\tEnergy(MWh)\\n\"\n",
      "from numpy import nditer\n",
      "for x, y in nditer([l, E]):\n",
      "    print '  ',x,'\\t\\t\\t ',y\n",
      "\n",
      "%matplotlib inline\n",
      "from matplotlib.pyplot import plot, subplot, title, xlabel, ylabel, show\n",
      "subplot(211)\n",
      "plot(E,l,'bo')\n",
      "plot(E,l)\n",
      "title('Energy Load Curve')\n",
      "xlabel('Energy MW Hrs')\n",
      "ylabel('Load MW')\n",
      "show()\n",
      "######### Mass Curve #######\n",
      "\n",
      "\n",
      "t = [5,4,9,4,2]\n",
      "l = [20,40,80,100,20] # loads on different time of day\n",
      "Es= range(0,len(l))\n",
      "Es[0] = t[0]*l[0] # MWh\n",
      "i=1\n",
      "for x in Es[1:]:\n",
      "    Es[i] = Es[i-1]+(l[i])*t[i]\n",
      "    i+=1\n",
      "\n",
      "\n",
      "print \"Energy supplied uto different times of day:\\nTime\\t\\tEnergy(MWh)\\n\"\n",
      "times = ['5am', '9am', '6pm','10pm','12pm']\n",
      "for x, y in nditer([times, Es]):\n",
      "    print x,'\\t\\t\\t ',y\n",
      "\n",
      "    \n",
      "td= range(0,len(t))\n",
      "td[0] = t[0] # MWh\n",
      "i=1\n",
      "for x in td[1:]:\n",
      "    td[i] = td[i-1]+t[i]\n",
      "    i+=1\n",
      "    \n",
      "subplot(212)\n",
      "plot(td,Es,'bo')\n",
      "plot(td,Es)\n",
      "title('Mass Curve')\n",
      "xlabel('Time')\n",
      "ylabel('Load MW')\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Energy at different load levels:\n",
        "Load(MW)\t\tEnergy(MWh)\n",
        "\n",
        "   20 \t\t\t  480\n",
        "   40 \t\t\t  820\n",
        "   80 \t\t\t  1340\n",
        "   100 \t\t\t  1420\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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E+nUjfKl5J37OdAJmSupIYdRvCeH/HfFzZouk3chy3RpM0DCza82ss5l1BYYA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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f31f86a5790>"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Energy supplied uto different times of day:\n",
        "Time\t\tEnergy(MWh)\n",
        "\n",
        "5am \t\t\t  100\n",
        "9am \t\t\t  260\n",
        "6pm \t\t\t  980\n",
        "10pm \t\t\t  1380\n",
        "12pm \t\t\t  1420\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7f31dc9118d0>"
       ]
      }
     ],
     "prompt_number": 6
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.7 : page 30"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "md=40 ;cf=0.5; uf=0.8 #maximum demand in MW capacity factor utility factor\n",
      "print \"(a)\"\n",
      "lf=cf/uf   #load factor is ratio of capacity factor to the utility  factor\n",
      "print \"load factor = capacity factor/utilisation factor =%0.3f\"%(lf)\n",
      "print \"(b)\"\n",
      "pc=md/uf   #plant capacity is ratio of maximum demand to utility factor\n",
      "print \"plant capacity = maximum demand/utilisation factor =%dMW\"%(pc)\n",
      "print \"(c)\"\n",
      "rc=pc-md   #reserve capacity is plant capacity minus maximum demand \n",
      "print \"reserve capacity =%dMW\"%(rc)\n",
      "print \"(d)\"\n",
      "print \"annual energy production =%dMWh\"%(md*lf*8760)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(a)\n",
        "load factor = capacity factor/utilisation factor =0.625\n",
        "(b)\n",
        "plant capacity = maximum demand/utilisation factor =50MW\n",
        "(c)\n",
        "reserve capacity =10MW\n",
        "(d)\n",
        "annual energy production =219000MWh\n"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.8 : pge 30"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a=[0, 5, 9 ,18, 20, 22, 24] #time in matrix format\n",
      "b=[50 ,50 ,100 ,100 ,150 ,80 ,50]#load in matrix format\n",
      "z= range (1,7)\n",
      "for x in range (1,6):\n",
      "    \n",
      "   z[x]=((b[x]+b[x+1])/2)*(a[(x+1)])-a[x]\n",
      "\n",
      "e = b[0]*a[1]+(b[2]+b[1])*(a[2]-a[1])/2+(b[3]*a[2])+(b[3]+b[4])+(b[4]+b[5])+(b[5]+b[6]) # MWh\n",
      "\n",
      "print \"energy required required by the system in 24 hrs = %d MWh\"%(e)\n",
      "#50x5MWh+((100+50)/2)x4MWh +(100x9)MWh+(100+150)MWh+(150+80)MWh+(80+50)MWh \\n =\n",
      "dlf=e/(max(b)*24)\n",
      "print \"\\ndaily load factor = %f or %0.2f %%\"%(dlf,dlf*100)\n",
      "\n",
      "#########PLOT##############\n",
      "%matplotlib inline\n",
      "from matplotlib.pyplot import plot, subplot, title, xlabel, ylabel, show\n",
      "plot(a,b)\n",
      "title('Load Curve')\n",
      "xlabel(\"TIME -->\")\n",
      "ylabel(\"MW -->\")\n",
      "show()\n",
      "#xtitle(\"load curve\"%(\"time\"%(\"MW\""
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "energy required required by the system in 24 hrs = 2060 MWh\n",
        "\n",
        "daily load factor = 0.572222 or 57.22 %\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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Vr0C7drEjyWSmqqXmlBzOBO5Jnt8PfC9/4YhIpSjWKqWUSh8M12hyMLPtgWOA8QDuvhJ4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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f31fa1d4f50>"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.9: page 31"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print \"load duration curve in fig1\"\n",
      "print \"the energy consumed upto different times is as \"\n",
      "a=[0, 5 ,9 ,18, 20, 22, 24]  #time in matrix format\n",
      "b=[50, 50 ,100 ,100 ,150 ,80 ,50] #load in matrix format\n",
      "\n",
      "z = range(0,6)\n",
      "for x in range (0,6):\n",
      "   z[x]=((b[x]+b[x+1])/2)*(a[x+1]-a[x])\n",
      "\n",
      "et=0\n",
      "q = range(0,7)\n",
      "m = range(0,7)\n",
      "ett = range(0,6)\n",
      "for x in range(0,6):\n",
      "    et=et+z[x] \n",
      "    A=a[(x)]\n",
      "    ett[x]=et \n",
      "    q[x]=a[x+1]\n",
      "    print \"\\nfrom mid night upto %d,energy=%dMWh\"%(A,et)\n",
      "n = sorted(range(len(b)), key=lambda k: b[k], reverse=True)\n",
      "m = sorted(b, reverse=True)\n",
      "print \"energy curve in fig 2\"\n",
      "t=[0, 3.88, 15.88 ,19.88, 23]\n",
      "k = range(0,6)\n",
      "for j in range(0,6):\n",
      "    k[j]=a[(j+1)]\n",
      "M =range(0,5)\n",
      "#rearranging for mass  curve\n",
      "for i in range(0,5):\n",
      "    M[i] = m[i]\n",
      "Q = range(0,6)\n",
      "for i in range(0,6):\n",
      "    Q[i] = q[i]\n",
      "    \n",
      "    \n",
      "subplot(121) \n",
      "plot(t,M) \n",
      "title(\"load duration\")\n",
      "xlabel(\"hours\")\n",
      "ylabel(\"MW\")\n",
      "subplot(122) \n",
      "plot(Q,ett) \n",
      "title(\"energy curve\")\n",
      "xlabel(\"time\")\n",
      "ylabel(\"MWh\")\n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "load duration curve in fig1\n",
        "the energy consumed upto different times is as \n",
        "\n",
        "from mid night upto 0,energy=250MWh\n",
        "\n",
        "from mid night upto 5,energy=550MWh\n",
        "\n",
        "from mid night upto 9,energy=1450MWh\n",
        "\n",
        "from mid night upto 18,energy=1700MWh\n",
        "\n",
        "from mid night upto 20,energy=1930MWh\n",
        "\n",
        "from mid night upto 22,energy=2060MWh\n",
        "energy curve in fig 2\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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HH81ZZ51F69aVj8ziySF3rV0b+jFstFGY5tMHyaw5Tw4uNp9+Cl27hqeHXXeN\nOxro27cv77//PkcccQS9e/dmr732qtF+nhxy19VXw8svwwsv5G7/mlzlycHFaujQ0HP65ZehXqUz\nhWRHvXr1Kh1PSRLLly+vdJsnh9wzfDj87W9hus+ttoo7mvzjycHFas2aMITBqafCn/4UdzR148kh\n97z0EvTuDRMnQvv2cUeTnzw5uNh9+GFoWvjmm9C2bdzR1J4nh9zy0Udw0EEwcqQPp78h0jpNqHN1\n0b49XHYZnHtuqKh2rq6WLAn9aG64wRNDHDw5uLS7/PIweuvw4XFH4vLVTz/B8ceHobf79487muLk\nxUouI955Bw47LIzc2qpV3NHUnBcrxc8MTj8dVq6ERx+Nv3FDIfBiJZczOnaEP/4x/OTj3zxJwyQt\nkjQjYV1zSRMkzZI0XlLThG0DJX0s6UNJhyes7yJpRrRtaLavIx/97W+h7ur++z0xxMn/613GXH11\n6P/w8MNxR1Inw4FeSesGABPMbFfgxeg10WRVvYEO0T53SOu6aN0J9DezdkA7ScnHdAlGjgy97ceM\ngRqMsO4yyJODy5iNN4Zhw+DSS+Grr+KOpnbMbBKwLGn10cCIaHkEcGy0fAxhOPtVZjYH+AToFk2F\n28TMpkbvuy9hH5dk8mS4+GJ45hnYdtu4o3GeHFxGde0a5p2+8MK4I0mLbcxsUbS8CNgmWm5FmBir\n3DzCdLfJ6+dH612STz8Nlc8jRkANO7O7DPPk4DLuuuvgrbfgySfjjiR9otrjPKxNyT3ffBOarF5z\nDfz2t3FH48rl4BiartA0agT33AN9+kDPnnk9Y9ciSS3NbGFUZLQ4Wj8faJPwvu0ITwzzo+XE9ZXO\nhVJaWrpuuaSkhJKSkvREncNWrQpTzh52WP72qs9FZWVllJWVbdAxvCmry5oLLgjNE4cNizuSyiU2\n+ZPUFnjazPaKXg8GvjazmyQNAJqa2YCoQvohoCuh2OgFYBczM0mvAxcBUwlT7f7LzJ5Lcd6iu7fN\nQmfJBQvgqaegfv24IypcPnyGy2krVoTy5P/8B37zm7ijSa38QyRpJNATaEGoX7gWeAoYBWwPzAFO\nMrNvov3+ApwFrAYuNrPno/VdgHuBTYFxZnZRJectunv75pvD0NuTJkGTJnFHU9g8ObicN358+LY4\nY0Zu/kHwTnDZ8cQToZHClCnQpk3173cbxpODywtnnQWbbgq33x53JBV5csi8t94KE0M99xx06RJ3\nNMXBk4M/oWGpAAARRElEQVTLC8uWheKlBx8MFdS5xJNDZs2dC927w223wbHe4yNrfPgMlxeaNQtP\nDWefHSqoXXFYsSI0Wb3kEk8M+cCfHFxs+vSB1q1DxWSu8CeHzFi9Go45Jvy+//Mfn/8527xYyeWV\nr74KxUtPPQXdusUdTeDJITMuvhhmzoRx42CjjeKOpvh4sZLLK1ttBUOGhArqn36KOxqXKbfdBhMm\nhOG3PTHkj1iSQzS88fvRUMYPSdq4quGQXeHq3RvatYPrr487EpcJ48aF3+3YsdDUP9F5JevFSlGv\n0/8Bu5vZT5IeAcYBewBLzGywpKuAZmY2IGnfgn70LlZffgmdOoVvlx07xhuLFyulz7vvwqGHhjG1\n9t8/7miKW74UKy0HVgGNJDUAGgFfUvlwyK7AtWoFN90EZ54Zxtpx+W/BAjjqKBg61BNDvsp6cjCz\npcAtwBeEpPCNmU2g8uGQXRE444xQB5FLLZdc3axcCUcfHZoq9+kTdzSurrI+KquknYFLgLbAt8Cj\nkk5LfE80YFnKZ+xiHLmyGEhw112hWOn882GLLbJz3nSMXunWW7s2zN+x++5hCG6Xv+Koc+gNHGZm\nZ0ev+wL7AQcDv04YDvklM2uftG/Blcu6XzrmmDDpy+mnx3N+r3PYMAMGhBndJkwIMwG63JAvdQ4f\nAvtJ2jSaZ/dQYCbwNNAvek8/oICmhnE11bs3PPJI3FG4urj7bhg9Ogyq54kh/8XSCU7SlYQEsBZ4\nGzgbaEIlwyEn7FcQ365c5VasgO22g88+g+bNs39+f3KomxdfhFNOgYkTYbfd4o7GJfMe0q4gnHBC\nmC6yf//sn9uTQ+198EEYQHHUKPAqwNyUL8VKzlXJi5byx1dfhcH0Bg/2xFBo/MnB5ZyVK0Pfh1mz\nYOuts3tuf3KouR9/DJ3cevb0Hu65zp8cXEFo1CgUK40eHXckrjJmodivVSv461/jjsZlgicHl5NO\nPtmLlnLZddfB7NkwYgTU878iBcmLlVxO+ukn2HZbeO+98O00W7xYqXoPPghXXw2vvw7b+DgGecGL\nlVzB2HjjMDbPY4/FHYlL9MorcOml8MwznhgKnScHl7O81VJumT07NDO+/37Yc8+4o3GZ5sVKLmf9\n/HMoUpo2Ddq0yc45vVgptWXLoHv3MKPbeefFHY2rLS9WcgWlYcMwEf2oUXFHUtx+/jmMd3XEEZ4Y\nioknB5fTeveGhx+OO4riZRYSQuPG8I9/xB2NyyZPDi6n/frX8PnnobzbZd/gwfD22/DQQ1C/ftzR\nuGzy5OByWoMGoRLUi5ay77HH4Lbb4Omnw5ODKy6eHFzO81ZL2Td1aihOGjMmjJLrio8nB5fzDjgA\nFi+Gjz6KO5Li8MUXcNxxcM890Llz3NG4uHhycDmvfn048UR/esiG5cvhyCPh8svDPNCueHlycHnB\ni5Yyb/Xq8P98wAFwySVxR+Pi5snB5YX99guzxL33XtyRFCaz0MFt7Vr4179AWe8G6HKNJweXF+rV\ng5NO8j4PmfL//h+8/HJoFbbRRnFH43KBJweXN8qH8c7hUSby0jPPwI03hn+32CLuaFyu8OTg8kaX\nLqHYY9q0uCMpHNOnw5lnwuOPQ9u2cUfjcoknB5c3JK+YTqcPPgjDot9+e6jTcS6RJweXV3r3DuXi\ncRctSZoj6V1J0yRNjdY1lzRB0ixJ4yU1TXj/QEkfS/pQ0uHxRR5MmgQlJWHu55NOijsal4s8Obi8\nsvfeYSKgqVPjjgQDSsyss5l1jdYNACaY2a7Ai9FrJHUAegMdgF7AHZJi++yNGhVGWX3gATj99Lii\ncLnOk4PLKzlWtJTc4PNoYES0PAI4Nlo+BhhpZqvMbA7wCdCVLDODW26Byy6DCRPgsMOyHYHLJ54c\nXN4pL1pauzbWMAx4QdKbks6J1m1jZoui5UVA+USarYB5CfvOA1pnJ8xgzZrQj+Hee2HyZOjYMZtn\nd/moQdwBOFdbHTpAs2bw6qtw4IGxhdHDzBZI2gqYIOnDxI1mZpKqqhmpsK20tHTdcklJCSUlJWkJ\n9Icf4NRT4ZtvQl1D06bV7+PyW1lZGWVlZRt0DJ8m1OWl66+HBQvCkNLpVJfpFCUNAr4DziHUQyyU\ntC3wkpm1lzQAwMxujN7/HDDIzF5POEZG7u0lS0KLpJ13DgPpbbxx2k/h8oBPE+qKRu/eYb6BNWuy\nf25JjSQ1iZY3Aw4HZgBjgH7R2/oBT0bLY4CTJTWUtCPQDsh4lfrs2bD//mHCpPvu88TgaieW5CCp\nqaTHJH0gaaakblU1A3Qu2S67QOvWYciHGGwDTJI0HXgdeMbMxgM3AodJmgUcHL3GzGYCo4CZwLPA\n+Zl+BJ46NQyg9+c/ww03hOFHnKuNWIqVJI0AXjazYZIaAJsBVwNLzGywpKuAZmY2IGk/L1Zy6wwe\nHL4d/+c/6TtmXR6/03TetN3bY8ZA//4wbFgoUnKuTsWl2f5jK2kLYJqZ7ZS0/kOgp5ktktQSKDOz\n9knv8eTg1pkzB/bdF778Mn2DxeV7crjzTvjrX+Gpp8L/jXOQP3UOOwJfSRou6W1J/43KbStrBuhc\nSm3bhorW//0v7kjit3YtDBwIt94aWiR5YnAbKo7k0AD4FXCHmf0K+J6oJ2m56CuUPyK4auVQh7jY\n/PQT9O0b6l8mTw4J07kNFUc/h3nAPDN7I3r9GDAQWCipZUIzwMWpds5UW3CXn048MRSj3Hln3Vrj\npKM9eJy++SbM99y8Obz4Imy6adwRuUIRV4X0ROBsM5slqRRoFG362sxuitqFN/UKaVcTBx0EV1yR\nnsrXfKpz+OILOOIIOOQQ+Oc/w1zbzqWSFxXSAJI6AncDDYHZwJlAfUJzv+2BOcBJZvZN0n6eHFwF\nt98OU6aEgeQ2VL4kh+nTQzK89NLw49N6uqrkTXKoK08OLpVFi6B9+9BqaUOLVfIhOUyYEIbDuO02\nH27b1Uy+tFZyLq222QZ+9St49tm4I8m8e++F006D0aM9MbjM8uTgCkKht1oyg//7P7juOigri3XA\nQVckvFjJFYQlS0ITzi+/hM02q/txcrFYadUqOO+8MHf22LHQsmWWg3N5z4uVXNFq0QK6d4enn447\nkvT67js4+uiQ9F5+2RODyx5PDq5gFFrR0sKF0LMnbLddGC+pceO4I3LFxIuVXMH45hvYYQeYOxc2\n37xux8iVYqUPPgh9GPr3h6uv9qaqbsN4sZIrak2bhm/aTz0VdyQbZtIkKCmB0lK45hpPDC4enhxc\nQcn3oqVRo+D3vw8d+vr1q/79zmWKFyu5grJiRSijnzMnzDNdW3EWK918szFkCDzzDHTsmO0IXCHz\nYiVX9Jo0gUMPhSeeiDuS2hs+PIyq6onB5QJPDq7g5GvR0iuvQJs2cUfhXODFSq7gfP89tGoFn3wC\nW21Vu31zpbWSc+nkxUrOEXpIH3FEGH/IOVc3nhxcQcrXoiXncoUnB1eQevUKQ2qsXh13JM7lJ69z\ncC6B1zm4QuR1Ds4559LCk4NzzrkKPDk455yrwJODc865Cjw5OOecq8CTg3POuQo8OTjnnKvAk4Nz\nzrkKPDk455yrwJODc865Cjw5OOecq8CTg3POuQpiSw6S6kuaJunp6HVzSRMkzZI0XlLTuGJzLt0k\n9ZL0oaSPJV0VdzzOVSfOJ4eLgZlA+VCUA4AJZrYr8GL0OmeUlZUV1XnjPHec15wJkuoDtwG9gA5A\nH0m7xxtVzeTq78LjyrxYkoOk7YAjgLuB8mFkjwZGRMsjgGNjCK1SxfiHshivOUO6Ap+Y2RwzWwU8\nDBwTc0w1kqu/C48r8+J6crgVuAJYm7BuGzNbFC0vArbJelTOZUZrYG7C63nROudyVtaTg6TfAYvN\nbBrrnxp+IZr1xGc+cYXC72WXd7I+E5ykG4C+wGpgE2Bz4HFgX6DEzBZK2hZ4yczaJ+3rHzKXceme\nCU7SfkCpmfWKXg8E1prZTQnv8XvbZVRt7+tYpwmV1BO43MyOkjQY+NrMbpI0AGhqZjlVKe1cXUhq\nAHwEHAJ8CUwF+pjZB7EG5lwVGsQdAOsfuW8ERknqD8wBTootIufSyMxWS7oAeB6oD9zjicHlulif\nHJxzzuWmvOkhHWcnIklzJL0bddqbmsHzDJO0SNKMhHUZ7xxYyXlLJc2LrnmapF7pPm90njaSXpL0\nvqT3JF0Urc/odVdx3qxcd1IsWbm/ahBHLPdfHePK+u8pRVyx3LsbEFft/s/MLOd/CI/inwBtgY2A\n6cDuWTz/Z0DzLJznQKAzMCNh3WDgymj5KuDGLJ13EPDnLFxzS6BTtNyYUDa/e6avu4rzZuW647i/\n6ngfZPz+q2NcWf891eIeivX/LF33dr48OeRCJ6K0tmBJxcwmAcuSVme8c2Al54XsXPNCM5seLX8H\nfEDoA5DR667ivJCF604hjnP+Qlz3X3XivD+rEte9uwFxQS3+z/IlOcTdiciAFyS9KemcLJ4X4u0c\neKGkdyTdk41HY0ltCd8QXyeL151w3teiVVm9buK9v6qTy51Ts/17qlRc9251NuTezpfkEHeteQ8z\n6wz8FviTpAPjCMLCc2K2/i/uBHYEOgELgFsyeTJJjYHRwMVmtiJxWyavOzrvY9F5vyPL1x3Jifur\nOlm+/6oTx+8ppbju3RrGVed7O1+Sw3ygTcLrNoSnh6wwswXRv18BTxCKubJlkaSWAFHnwMXZOKmZ\nLbYIYQysjF2zpI0IH677zezJaHXGrzvhvA+Unzeb110u5vurOrHcf9WJ4/eUSlz3bi3iqvO9nS/J\n4U2gnaS2khoCvYEx2TixpEaSmkTLmwGHAzOq3iutxgD9ouV+wJNVvDdtopu63HFk6JolCbgHmGlm\nQxI2ZfS6Kztvtq474Xxx31/VieX+q062f0+VxBDLvVvXuGr9f5bNWvQN+SE8cn9EaLU0MIvn3ZHQ\nOmo68F4mzw2MJPSg/ZlQx3Im0Bx4AZgFjCf0HM/0ec8C7gPeBd4h3NzbZOiaDyAMwDgdmBb99Mr0\ndVdy3t9m67rjuL9y9f7L5fszF+/dOsZV63vbO8E555yrIF+KlZxzzmWRJwfnnHMVeHJwzjlXgScH\n55xzFXhycM45V4EnB+eccxV4csgTUQfAXOoc5VxaSdpC0nnR8raSHo07pmLmyaGIKUxf6VyuaAac\nD2FIETM7MeZ4iponh/xSX9Jd0QQez0vaRFInSa9FIy0+Xj7SoqQySV2i5RaSPouWz5A0RtKLwARJ\nLSVNjCb/mCHpgBivzxW3G4Gdo3txVPmTcnTPPhlNnPOZpAskXS7pbUlTJDWL3rezpGej0W0nStot\n1qvJc54c8ks74DYz2xP4Bvg9Ybz4K8ysI2GslEHRe6saDbIz8Hsz+zVwKvCchVFB9yZ0uXcuDlcB\ns6N78YqkbXsQxgPaF7geWG5mvwKmAKdH77kLuNDM9on2vyMrURcoL1bIL5+Z2bvR8lvAzoRxWyZF\n60YANSmnHW9m30TLU4Fh0SiOT5rZO2mN2LmaUyXLAC+Z2ffA95K+AZ6O1s8A9o4GLdwfeDSMOwdA\nw0wGW+j8ySG//JSwvAZInqwj8QO1mvW/302S3reyfCFKLAcShkW/V1Lf9ITqXFol3vtrE16vJXzJ\nrQcsM7POCT97ZDvIQuLJIb99CyxNqCfoC5RFy3OAfaLlEyo7gKTtga/M7G7CGO+dMxKpc9VbATSp\n5T4CsDDJzmeSToAwbLWkvdMcX1HxYqX8klyHYMAZwL8lNQJmE4ZZBrgZGCXpXGBswr7JdRElwBWS\nVhE+nKfjXAzM7GtJr0YV0R9Q+T2bvFz++lTgTknXABsRhvp+F1cnPmS3c865CrxYyTnnXAWeHJxz\nzlXgycE551wFnhycc85V4MnBOedcBZ4cnHPOVeDJwTnnXAWeHJxzzlXw/wGo6EfWAVPtJwAAAABJ\nRU5ErkJggg==\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f31dc93f790>"
       ]
      }
     ],
     "prompt_number": 9
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.10 : page 31"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "egd1=438*10**4 ;plp=0.2; pcf=0.15 #annual load duration  annual  load factor plant capacity factor\n",
      "pml=egd1/(plp*8760)\n",
      "pc=(pml*plp)/pcf\n",
      "print \"annual load factor =energy generated during 1 year/(max. load)x8760=%.1f \\n maximum load =%dkW\"%(plp,pml)\n",
      "print \"\\ncapacity factor =(max.load/plant capacity)x(load factor)\\n plant capacity =max.load/0.75 =%fMW \\n reserve capacity =3.333-2.5=%fMW\"%(pc,pc-pml)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "annual load factor =energy generated during 1 year/(max. load)x8760=0.2 \n",
        " maximum load =2500kW\n",
        "\n",
        "capacity factor =(max.load/plant capacity)x(load factor)\n",
        " plant capacity =max.load/0.75 =3333.333333MW \n",
        " reserve capacity =3.333-2.5=833.333333MW\n"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.11: page 32"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "p1=10; p2=6; p3=8; p4=7 #peak demands of 4 areas\n",
      "df=1.5 ;lf=0.65 ;imdp=0.6 #diversity factor  annual load factor  ratio of maximum demand\n",
      "p=p1+p2+p3+p4\n",
      "md=p/df\n",
      "ae=md*lf*8760\n",
      "imd=imdp*md\n",
      "ic=md+imd\n",
      "print \" sum of maximum=%dMW\"%(p)\n",
      "print \"\\n maximum demand = sum of max.demands/diversity factor =%d/%f = %fMW\"%(p,df,md)\n",
      "print \"\\n annual energy =%fMWh \\n increase in maximum demand =%fMW \\n installed capacity =%fMW\"%(ae,imd,ic)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        " sum of maximum=31MW\n",
        "\n",
        " maximum demand = sum of max.demands/diversity factor =31/1.500000 = 20.666667MW\n",
        "\n",
        " annual energy =117676.000000MWh \n",
        " increase in maximum demand =12.400000MW \n",
        " installed capacity =33.066667MW\n"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.12 : page 32"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from __future__ import division\n",
      "#Arranging data for Load Duration Curve\n",
      "#week days 5-9pm load\n",
      "L1=350 #MW\n",
      "t1=4*5 #hours\n",
      "#week days 8-12am & 1-5pm load\n",
      "L2=250 #MW\n",
      "t2=t1+8*5 #hours\n",
      "#saturday & sunday 5-9pm load\n",
      "L3=200 #MW\n",
      "t3=t2+4*2 #hours\n",
      "#All days 150MW load\n",
      "L4=150 #MW\n",
      "t4=t3+6*5+15*2 #hours\n",
      "#All days 100MW load\n",
      "L5=100 #MW\n",
      "t5=t4+6*5+5*2 #hours\n",
      "A=31600 #Total Load Curve Area\n",
      "LF=A/L1/24/7*100 #%#Weekly load factor\n",
      "print \"Weekly Load factor = %0.2f %%\"%LF\n",
      "print \"Load Duration Curve is shown in figure.\" \n",
      "#Load Duration Curve\n",
      "L=[L1 ,L2, L3, L4, L5] #MW\n",
      "T=[t1 ,t2 ,t3 ,t4 ,t5] #hours\n",
      "%matplotlib inline\n",
      "from matplotlib.pyplot import plot, title, xlabel, ylabel, show\n",
      "plot(T,L) \n",
      "title('Load Duration Curve')\n",
      "xlabel('Time(Hours)')\n",
      "ylabel('Load(MW)') \n",
      "show()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Weekly Load factor = 53.74 %\n",
        "Load Duration Curve is shown in figure.\n"
       ]
      },
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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34ygG9ncgPTAPOBX4bvbv3Kr1MyVdRGpy2hW4q/OLe/tGzcysd3JNFJJmAQcB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\nYWZmNTlRmJlZTU4UZmZW0/8H23KohObdSwQAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f31f86a5950>"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.13 : page 33"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "dlf=0.825    #daily load factor\n",
      "lptmlp=0.87   #average daily peak load to monthly load peak\n",
      "mlptalp=0.78   #average monthly peak load to annual load peak\n",
      "print \"annual load factor = %fx%fx%f = %0.2f\"%(dlf,lptmlp,mlptalp,dlf*lptmlp*mlptalp)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "annual load factor = 0.825000x0.870000x0.780000 = 0.56\n"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "heading",
     "level": 2,
     "metadata": {},
     "source": [
      "example -  2.14 : page 35"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "print \"(a)\"\n",
      "#given\n",
      "transformer1_motorload=300 \n",
      "transformer1_demandfactorm=0.6 \n",
      "tarnsformer1_commercialload=100 \n",
      "transformer1_demandfactorc=0.5 \n",
      "transformer1_diversityfactor=2.3\n",
      "transformer2_residentalload=500 \n",
      "transformer2_demandfactor=0.4 \n",
      "transformer2_diversitryfactor=2.5 \n",
      "transformer3_residentalload=400 \n",
      "transformer3_demandfactor=0.5 \n",
      "transformer3_diversityfactor=2.0 \n",
      "diversitybtwxmer=1.4\n",
      "peakloadoftransformer1=((transformer1_motorload*transformer1_demandfactorm)+(tarnsformer1_commercialload*transformer1_demandfactorc))/transformer1_diversityfactor\n",
      "peakloadonxmer=(transformer2_residentalload*transformer2_demandfactor)/transformer2_diversitryfactor\n",
      "peakloadonxmer3=(transformer3_residentalload*transformer3_demandfactor)/(transformer3_diversityfactor)\n",
      "print \"peak load on transformer 1 =(300x0.6+100x0.5)/2.3 =%dkW \\npeak load on transformer 2 =%dkW \\n peak load on transformer 3 =%dkW\"%(peakloadoftransformer1,peakloadonxmer,peakloadonxmer3)\n",
      "print \"(b)\"\n",
      "peakloadonfeeder=(peakloadoftransformer1+peakloadonxmer+peakloadonxmer3)/diversitybtwxmer\n",
      "print \"peak load on feeder =(100+80+100)/1.4 =%dkW\"%(peakloadonfeeder)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "(a)\n",
        "peak load on transformer 1 =(300x0.6+100x0.5)/2.3 =100kW \n",
        "peak load on transformer 2 =80kW \n",
        " peak load on transformer 3 =100kW\n",
        "(b)\n",
        "peak load on feeder =(100+80+100)/1.4 =200kW\n"
       ]
      }
     ],
     "prompt_number": 16
    }
   ],
   "metadata": {}
  }
 ]
}