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demand.html
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<!DOCTYPE html>
<html lang="en">
<head>
<meta charset="utf-8">
<title>Energy Demand</title>
<script type="text/javascript" src="http://d3js.org/d3.v3.min.js" charset="utf-8"></script>
<script type="text/javascript" src="./Tangle-0.1.0/Tangle.js"></script>
<link rel="stylesheet" href="./Tangle-0.1.0/TangleKit/TangleKit.css" type="text/css">
<script type="text/javascript" src="./Tangle-0.1.0/TangleKit/mootools.js"></script>
<script type="text/javascript" src="./Tangle-0.1.0/TangleKit/sprintf.js"></script>
<script type="text/javascript" src="./Tangle-0.1.0/TangleKit/BVTouchable.js"></script>
<script type="text/javascript" src="./Tangle-0.1.0/TangleKit/TangleKit.js"></script>
<script src="http://d3js.org/d3.v3.min.js" charset="utf-8"></script>
<script type="text/javascript" src="https://ajax.googleapis.com/ajax/libs/jquery/1.6.2/jquery.min.js"></script>
<script src="https://togetherjs.com/togetherjs-min.js"></script>
</head>
<body>
<img src="http://muyueh.com/seeall/image/demand.jpeg" style="display:none;">
<script type="text/javascript">
var margin = {top:10, left: 100, right: 30, bottom: 30};
var w = 600 - margin.left - margin.right;
var h = 300 - margin.top - margin.bottom;
var svg = d3.select("body")
.append("svg")
.attr("width", w + margin.left + margin.right)
.attr("height", h + margin.top + margin.bottom)
.append("g")
.attr("transform", "translate(" + margin.left + ", " + margin.top + ")")// will only need to use width and height directily, since it has been transformed
.attr("class", "lineContainer");
var x = d3.scale.linear()
.range([0, w]);
var y = d3.scale.linear()
.range([h, 0]); //since the height 0 is top
var forecast_Everyone = [];
var forecast_Taipower = [{source: "TaiP",year: 1996, consIndus:0, consTotal:134306.7, consServi: 0, consResid:0 },
{source: "TaiP", year: 1997, consIndus:0, consTotal:143290.8, consServi: 0, consResid:0 },
{source: "TaiP", year: 1998, consIndus:0, consTotal:154569.3, consServi: 0, consResid:0 },
{source: "TaiP", year: 1999, consIndus:0, consTotal:160942.6, consServi: 0, consResid:0 },
{source: "TaiP", year: 2000, consIndus:0, consTotal:176524.6, consServi: 0, consResid:0 },
{source: "TaiP", year: 2001, consIndus:0, consTotal:180504.5, consServi: 0, consResid:0 },
{source: "TaiP", year: 2002, consIndus:0, consTotal:190266.4, consServi: 0, consResid:0 },
{source: "TaiP", year: 2003, consIndus:0, consTotal:200466, consServi: 0, consResid:0 },
{source: "TaiP", year: 2004, consIndus:0, consTotal:218826.4, consServi: 0, consResid:0 },
{source: "TaiP", year: 2005, consIndus:0, consTotal:227660.4, consServi: 0, consResid:0 },
{source: "TaiP", year: 2006, consIndus:0, consTotal:226151.7, consServi: 0, consResid:0 },
{source: "TaiP", year: 2007, consIndus:0, consTotal:233544.4, consServi: 0, consResid:0 },
{source: "TaiP", year: 2008, consIndus:0, consTotal:229794.9, consServi: 0, consResid:0 },
{source: "TaiP", year: 2009, consIndus:0, consTotal:220817.7, consServi: 0, consResid:0 },
{source: "TaiP", year: 2010, consIndus:0, consTotal:237554.4, consServi: 0, consResid:0 },
{source: "TaiP", year: 2011, consIndus:0, consTotal:242243.6, consServi: 0, consResid:0 },
{source: "TaiP", year: 2012, consIndus:0, consTotal:248775.4321, consServi: 0, consResid:0 },
{source: "TaiP", year: 2013, consIndus:0, consTotal:255483.3879, consServi: 0, consResid:0 },
{source: "TaiP", year: 2014, consIndus:0, consTotal:262372.2163, consServi: 0, consResid:0 },
{source: "TaiP", year: 2015, consIndus:0, consTotal:269446.7944, consServi: 0, consResid:0 },
{source: "TaiP", year: 2016, consIndus:0, consTotal:276712.1307, consServi: 0, consResid:0 },
{source: "TaiP", year: 2017, consIndus:0, consTotal:284173.3688, consServi: 0, consResid:0 },
{source: "TaiP", year: 2018, consIndus:0, consTotal:291835.791, consServi: 0, consResid:0 },
{source: "TaiP", year: 2019, consIndus:0, consTotal:299704.822, consServi: 0, consResid:0 },
{source: "TaiP", year: 2020, consIndus:0, consTotal:307786.0327, consServi: 0, consResid:0 },
{source: "TaiP", year: 2021, consIndus:0, consTotal:316085.1444, consServi: 0, consResid:0 },
{source: "TaiP", year: 2022, consIndus:0, consTotal:324608.0325, consServi: 0, consResid:0 },
{source: "TaiP", year: 2023, consIndus:0, consTotal:333360.7309, consServi: 0, consResid:0 },
{source: "TaiP", year: 2024, consIndus:0, consTotal:342349.4362, consServi: 0, consResid:0 },
{source: "TaiP", year: 2025, consIndus:0, consTotal:351580.512, consServi: 0, consResid:0 } ]
var forecast_GCAA = [{source: "GCAA", year: 1996, consIndus:0, consTotal: 134306.7, consServi: 0, consResid:0 },
{source: "GCAA", year: 1997, consIndus:0, consTotal: 143290.8, consServi: 0, consResid:0 },
{source: "GCAA", year: 1998, consIndus:0, consTotal: 154569.3, consServi: 0, consResid:0 },
{source: "GCAA", year: 1999, consIndus:0, consTotal: 160942.6, consServi: 0, consResid:0 },
{source: "GCAA", year: 2000, consIndus:0, consTotal: 176524.6, consServi: 0, consResid:0 },
{source: "GCAA", year: 2001, consIndus:0, consTotal: 180504.5, consServi: 0, consResid:0 },
{source: "GCAA", year: 2002, consIndus:0, consTotal: 190266.4, consServi: 0, consResid:0 },
{source: "GCAA", year: 2003, consIndus:0, consTotal: 200466, consServi: 0, consResid:0 },
{source: "GCAA", year: 2004, consIndus:0, consTotal: 218826.4, consServi: 0, consResid:0 },
{source: "GCAA", year: 2005, consIndus:0, consTotal: 227660.4, consServi: 0, consResid:0 },
{source: "GCAA", year: 2006, consIndus:0, consTotal: 226151.7, consServi: 0, consResid:0 },
{source: "GCAA", year: 2007, consIndus:0, consTotal: 233544.4, consServi: 0, consResid:0 },
{source: "GCAA", year: 2008, consIndus:0, consTotal: 229794.9, consServi: 0, consResid:0 },
{source: "GCAA", year: 2009, consIndus:0, consTotal: 220817.7, consServi: 0, consResid:0 },
{source: "GCAA", year: 2010, consIndus:0, consTotal: 237554.4, consServi: 0, consResid:0 },
{source: "GCAA", year: 2011, consIndus:0, consTotal: 242243.6, consServi: 0, consResid:0 },
{source: "GCAA", year: 2012, consIndus:0, consTotal: 248775.4321, consServi: 0, consResid:0 },
{source: "GCAA", year: 2013, consIndus:0, consTotal: 255483.3879, consServi: 0, consResid:0 },
{source: "GCAA", year: 2014, consIndus:0, consTotal: 262372.2163, consServi: 0, consResid:0 },
{source: "GCAA", year: 2015, consIndus:0, consTotal: 269446.7944, consServi: 0, consResid:0 },
{source: "GCAA", year: 2016, consIndus:0, consTotal: 276712.1307, consServi: 0, consResid:0 },
{source: "GCAA", year: 2017, consIndus:0, consTotal: 284173.3688, consServi: 0, consResid:0 },
{source: "GCAA", year: 2018, consIndus:0, consTotal: 277879.0713, consServi: 0, consResid:0 },
{source: "GCAA", year: 2019, consIndus:0, consTotal: 271724.1892, consServi: 0, consResid:0 },
{source: "GCAA", year: 2020, consIndus:0, consTotal: 265705.6347, consServi: 0, consResid:0 },
{source: "GCAA", year: 2021, consIndus:0, consTotal: 259820.3882, consServi: 0, consResid:0 },
{source: "GCAA", year: 2022, consIndus:0, consTotal: 254065.4969, consServi: 0, consResid:0 },
{source: "GCAA", year: 2023, consIndus:0, consTotal: 248438.0736, consServi: 0, consResid:0 },
{source: "GCAA", year: 2024, consIndus:0, consTotal: 242935.2949, consServi: 0, consResid:0 },
{source: "GCAA", year: 2025, consIndus:0, consTotal: 237554.4, consServi: 0, consResid:0 }
]
var GDP_YoY = 0.03;
var PPL_5y_CAGR = 0.003;
var consByYear = [];
var projection = function(){
consByYear = [
{source: "self", year: 1996, consIndus: 62939, consServi: 27051, consResid: 27579, consTotal: 134306.7},
{source: "self", year: 1997, consIndus: 68863, consServi: 29317, consResid: 27840, consTotal: 143290.8},
{source: "self", year: 1998, consIndus: 71931, consServi: 31670, consResid: 32945, consTotal: 154569.3},
{source: "self", year: 1999, consIndus: 77467, consServi: 32774, consResid: 32511, consTotal: 160942.6},
{source: "self", year: 2000, consIndus: 86889, consServi: 35890, consResid: 34543, consTotal: 176524.6},
{source: "self", year: 2001, consIndus: 87097, consServi: 36994, consResid: 35656, consTotal: 180504.5},
{source: "self", year: 2002, consIndus: 93206, consServi: 38937, consResid: 37191, consTotal: 190266.4},
{source: "self", year: 2003, consIndus: 98404, consServi: 40818, consResid: 39100, consTotal: 200466},
{source: "self", year: 2004, consIndus: 105519, consServi: 42815, consResid: 39588, consTotal: 218826.4},
{source: "self", year: 2005, consIndus: 108545, consServi: 44995, consResid: 42305, consTotal: 227660.4},
{source: "self", year: 2006, consIndus: 113476, consServi: 46580, consResid: 42464, consTotal: 226151.7},
{source: "self", year: 2007, consIndus: 119363, consServi: 46737, consResid: 43124, consTotal: 233544.4},
{source: "self", year: 2008, consIndus: 117067, consServi: 46635, consResid: 42687, consTotal: 229794.9},
{source: "self", year: 2009, consIndus: 109694, consServi: 45188, consResid: 43067, consTotal: 220817.7},
{source: "self", year: 2010, consIndus: 124154, consServi: 46976, consResid: 43427, consTotal: 237554.4},
{source: "self", year: 2011, consIndus: 127776, consServi: 46878, consResid: 44419, consTotal: 242243.6},
{source: "self", year: 2012, consIndus: 128499, consServi: 47062, consResid: 44592, consTotal: 244615.6802}];
for(var i = 17; i < 35; i++){
var thisYear ={};
thisYear.source = "self";
thisYear.year = consByYear[i - 1].year + 1;
thisYear.consIndus = consByYear[i - 1].consIndus * (1 + GDP_YoY);
thisYear.consServi = consByYear[i - 1].consServi * (1 + PPL_5y_CAGR * 4);
thisYear.consResid = consByYear[i - 1].consResid * (1 + PPL_5y_CAGR * 4);
thisYear.consTotal = (thisYear.consIndus + thisYear.consServi + thisYear.consResid) / 0.9;
consByYear.push(thisYear);
}
forecast_Everyone = [];
forecast_Everyone.push(forecast_Taipower);
forecast_Everyone.push(forecast_GCAA);
forecast_Everyone.push(consByYear);
};
projection();
x.domain([
d3.min(forecast_Everyone, function(d){ return d3.min(d, function(v) { return v.year; })}),
d3.max(forecast_Everyone, function(d){ return d3.max(d, function(v) { return v.year; })})
]);
y.domain([
// d3.min(forecast_Everyone, function(d){ return d3.min(d, function(v) { return v.consTotal; })}),
0,
d3.max(forecast_Everyone, function(d){ return d3.max(d, function(v) { return v.consTotal; })})
]);
var color = d3.scale.category10();
var line = d3.svg.line()
.interpolate("line")
.x(function(d){
// console.log(d);
return x(d.year); })
.y(function(d){ return y(d.consTotal); });
var container = svg.selectAll(".dataLine")
.data(forecast_Everyone)
.enter()
.append("path")
.attr("d", line)
.attr("stroke", function(d, i){ return color(i); })
.attr("stroke-width", 2)
.attr("fill", "none")
.attr("class", "dataLine");
svg.selectAll(".lineContainer")
.select(".labels")
.data(forecast_Everyone)
.enter()
.append("text")
.datum(function(d) {
// console.log(d[d.length - 1].source);
return {source: d[d.length - 1].source, consTotal: d[d.length - 1].consTotal, year: d[d.length - 1].year};
})
.attr("transform", function(d, i) {
// console.log(d);
return "translate(" + x(d.year) + "," + y(d.consTotal) + ")"; })
.attr("x", 3)
.attr("dy", ".35em")
.text(function(d) {
if(d.source === "TaiP"){
return "2025-台電預估";
}
else if(d.source === "GCAA"){
return "2025-綠盟-用電零成長";
}
else if(d.source === "self"){
return "2030-你的預估";
}
return d.source;
}).attr("text-anchor", "end")
.attr("font-size", "10px")
.attr("class", "labels");
var redraw = function(){
svg.selectAll(".dataLine")
.data(forecast_Everyone);
svg.selectAll(".dataLine")
.transition()
.attr("d", line);
svg.selectAll(".labels")
.data(forecast_Everyone)
.datum(function(d) {
// console.log(d[d.length - 1].source);
return {source: d[d.length - 1].source, consTotal: d[d.length - 1].consTotal, year: d[d.length - 1].year};
})
.transition()
.attr("transform", function(d, i) {
// console.log(d);
return "translate(" + x(d.year) + "," + y(d.consTotal) + ")"; });
}
var xAxis = d3.svg.axis()
.scale(x)
.orient("bottom")
.tickFormat(d3.format("d"));
var yAxis = d3.svg.axis()
.scale(y)
.orient("left")
.ticks(5);
svg.append("g")
.attr("class", "x axis")
.attr("transform", "translate(0," + h + ")")
.call(xAxis);
svg.append("g")
.attr("class", "y axis")
.attr("transform", "translate(0, 0)")
.call(yAxis)
.append("text")
.attr("transform", "rotate(-90)")
.attr("y", 6)
.attr("dy", ".71em")
.style("text-anchor", "end")
.text("GWH");
// ---for bar chart---
var supplyYear = {key: "Year", value:[1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013,2014,2015,2016,2017,2018,2019,2020,2021,2022,2023,2024,2025]};
var supply = [
{key: "Coal", value:[42846,44487,46765,46608,49325,51294,53619,55942,58805,62076,64440,63073,60890,56629,60731,62669,58129,58129,55043,55043,55043,55043,55043,55043,55043,55043,55043,55043,55043,55043]},
{key: "Oil", value:[31547,26171,29352,28188,29607,20904,19288,19143,19085,19390,19219,19454,18781,17180,18503,17508,17102,17102,17102,17102,13244,8100,8100,8100,4088,4088,4088,4088,4088,4088]},
{key: "LNG", value:[19836,33220,38700,46069,56716,69317,77064,85168,91248,94820,100370,107634,106030,103064,114305,117998,115262,115262,115262,115262,112690,108760,108760,108760,108760,108760,104907,104907,104907,104907]},
{key: "Nuclear", value:[37788,36269,36824,38416,38503,35486,39553,38892,39490,39972,39870,40539,40827,41571,41629,42116,41336,41336,41336,41336,41336,41336,36226,31115,31115,23200,23200,15284,15284,15284]},
{key: "Hydro", value:[9044,9567,10608,8942,8878,9179,6368,6896,6556,7825,7999,8350,7772,7053,7255,6902,7598,7598,7598,7598,7598,7598,7598,7598,7598,7598,7598,7598,7598,7598]},
{key: "Solar", value:[0,0,0,0,0,0,0,0,1,1,1,2,5,9,25,67,71,71,71,71,71,71,71,71,71,71,71,71,71,71]},
{key: "Windonshore", value:[0,0,0,0,1,12,16,24,25,91,276,440,588,787,1026,1493,1236,1236,1236,1236,1236,1236,1236,1236,1236,1236,1236,1236,1236,1236]},
{key: "Windoffshore", value:[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]},
{key: "Geothermal", value:[0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]},
{key: "Biomass", value:[375,272,249,277,352,339,383,376,363,336,385,609,486,495,539,327,471,471,471,471,471,471,471,471,471,471,471,471,471,471]},
{key: "Waste", value:[527,500,687,973,1480,2010,2546,2633,2825,2853,2902,3014,2935,2907,3036,3092,3004,3004,3004,3004,3004,3004,3004,3004,3004,3004,3004,3004,3004,3004]}
];
var addUp = function(){
var Total;
for(var i = 0; i < consByYear.length; i++ ){
// console.log(consByYear[i].year);
if(consByYear[i].year === 2030){
Total = (consByYear[i].consTotal);
}
}
return Total;
}
function setUpTangle () {
var element = document.getElementById("text");
var tangle = new Tangle(element, {
initialize: function () {
this.GDP_YoY = 0.03;
this.PPL_5y_CAGR = 0.003;
this.forecast_2030 = Math.floor( addUp());
},
update: function () {
GDP_YoY = this.GDP_YoY;
PPL_5y_CAGR = this.PPL_5y_CAGR;
projection();
redraw();
this.forecast_2030 = Math.floor(addUp());
}
});
}
window.onload = function(){
setUpTangle();
}
Tangle.formats.comma =
function numberWithCommas(value) {
return value.toString().replace(/\B(?=(\d{3})+(?!\d))/g, ",");
};
</script>
<div id="text">
<h3>電力需求成長</h3>
<ul>
<li><p>GDP 為 <span data-var="GDP_YoY" class="TKAdjustableNumber" data-step="0.01" data-min="-0.03" data-max="0.1"></span></p></li>
<li><p>人口複合成長率為 <span data-step="0.0001" data-var="PPL_5y_CAGR" class="TKAdjustableNumber" data-min="0.0030" data-max="0.0038"></span></p></li>
<li><p>2030 年的總電力需求為 <span data-var="forecast_2030" data-format="comma"></span> GWH</p></li>
</ul>
</div>
<pre><code>
n = year after;
Total_Consumption = Industrial + Service + Residential;
Future_Indusrial_Consumption = Current_Industrial_Consumption * (1 + GDP_YoY ) ^ n;
Future_Service_Consumption = Current_Service_Consumption * (1 + PPL_5y_CAGR * 4) ^ n;
Future_Residential_Consumption = Current_Residentiak_Consumption * (1 + PPL_5y_CAGR * 4) ^ n;
Current_Industrial_Consumption = 127776;
Current_Service_Consumption = 46878;
Current_Residentiak_Consumption = 44419;
The above three sector accounts for 90% of Taiwan power structure, using a linear model to deduce total.
GDP YoY, -3%~10% in last 18 years = 3% ;
ppl 5y CAGR, 0.30%~0.38% in last 5 years = 0.30% ;
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