Swarthmore Battery OptimizationHorton AWS SimulationsHorton AWS ResultsNYC TypologiesYale Berkeley UpdateNYC Electrification Results - Capacity ConstraintsBay Area CFE AppendixNYC Electrification Results - Updated MetricsCoorsTek 9th St. RedevelopmentCharacterization Experiments100 (ish) cities to simulateDisaggregation ExplorationsUtilitiesDisaggregation Graph V2Combinations TestCharacterization ExperimentsCombinations Test First Week ConstrainedCharacterization Graph V2Model Input CalibrationUT Model ResultsUT EEM All BuildingsMIT Model Input CalibrationMIT Final Model ResultsMIT EEM All BuildingsMIT Monthly Baseline ResultsHorton Analysis ResultsHorton Solar + StorageGoogle Input CalibrationGoogle Monthly Baseline ResultsGoogle EEMsDC Energy Data AggregationEmissions VisualizationEPW ReaderSunpath DiagramPyschrometric Chart
MIT EEMs
md`# MIT EEMs`
xlsx = require('https://bundle.run/xlsx@0.14.1')
viewof binary = html`<input type=file>`
input = new Uint8Array(await Files.buffer(binary))
wb = xlsx.read(input, {type: 'array'})
excel = wb.Sheets["Baseline"];
data = xlsx.utils.sheet_to_json(excel);
height = 500
margin = ({top: 20, right: 20, bottom: 30, left: 50})
v_margin = ({top: 80, right: 100, bottom: 50, left: 340})
d3 = require("d3@^6.1")
_ = require('lodash@4.17.15/lodash.js').catch(() => window["_"])
chroma = require('chroma-js')
d3.range(1, 13).map(r => ["E" + r, "C" + r, "S" + r ]).flat()
building = binary.name.replace(".xlsx", "")
ecm_data = {
// const filtered = data.filter(d => d.Run != "Metered" && d.Run != "Baseline");
// const grouped = _.groupBy(filtered, d=> d.Run);
const map = new Map();
let baselineGHG = xlsx.utils.sheet_to_json(wb.Sheets["Baseline"]);
baselineGHG = baselineGHG.map(d => calcghg(d));
for (const key of Object.keys(b_lookup)) {
let excel = wb.Sheets[key];
let dat = xlsx.utils.sheet_to_json(excel);
let f = dat.map((d, i) => Math.max((baselineGHG[i+1] - calcghg(d))/2204, 0));
map.set(key, quartiles(f));
}
return map;
}
Type JavaScript, then Shift-Enter. Ctrl-space for more options. Arrow ↑/↓ to switch modes.
calcghg = d => {
let e = d3.range(1, 13).map(r => "E" + r).map(u => d[u] * areas[building] * factors.E || 0);
let c = d3.range(1, 13).map(r => "C" + r).map(u => d[u] * areas[building] * factors.C || 0);
let s = d3.range(1, 13).map(r => "S" + r).map(u => d[u] * areas[building] * factors.S || 0);
return _.sum(e) + _.sum(c) + _.sum(s);
}
//lbs per kbtu
factors = ({E: 0.1885, S: 0.1509, C: 0.0801})
//areas in sf
areas = ({
Building_2: 133168,
Building_10: 144463,
Building_13: 183169,
Building_16: 116006,
Building_18: 116900,
Building_37: 102777,
Building_46: 418300,
Building_56: 143940,
Building_66: 133170,
Building_68: 260390,
Building_76: 367689,
Building_E14: 173875,
Building_36: 144887,
Building_48: 57255,
Building_E25: 156676
})
quartiles = (data) => {
const values = data.sort((a, b) => a - b);
const min = values[0];
const max = values[values.length - 1];
const q1 = d3.quantile(values, 0.25);
const q2 = d3.quantile(values, 0.50);
const q3 = d3.quantile(values, 0.75);
const iqr = q3 - q1; // interquartile range
const r0 = Math.max(min, q1 - iqr * 1.5);
const r1 = Math.min(max, q3 + iqr * 1.5);
values.quartiles = [q1, q2, q3];
values.range = [r0, r1];
values.outliers = values.filter(v => v < r0 || v > r1); // TODO
return values;
}
b_lookup = ({
"Envelope": "Envelope Upgrades",
"HRV": "Heat Recovery Ventilation",
"STR60": "Supply Air Temperature Reset",
"WAC": "Enhanced SAT Reset",
"VENT2": "Ventilation Measures",
"VENT3": "Enhanced Ventilation Measures",
"FanPower": "Fan Energy Reductions",
"LPD": "LPD Reductions",
"Combined_Select_0305": "Select EEMs*",
"Combined": "All Measures Combined"
})
Array.from(ecm_data.values()).map(d => d.range[1])
b_y = d3.scaleBand()
.domain(Object.keys(b_lookup).reverse())
.range([b_height - b_margin.bottom, b_margin.top])
.padding(.1)
.paddingOuter(.5)
b_x = d3.scaleLinear()
.domain([0, d3.max(Array.from(ecm_data.values()).map(d => d.range[1]))]).nice()
.range([b_margin.left, width - b_margin.right])
b_xAxis = g => g
.attr("transform", `translate(0,${v_margin.top})`)
.call(d3.axisTop(b_x).tickPadding(10).tickFormat(d3.format("~s")))
// .call(g => g.select(".domain").remove())
.call(g => g.select(".tick:first-of-type text").clone()
.attr("y", -50)
.attr("x", -3)
.attr("text-anchor", "start")
.attr("font-weight", "bold")
.html("Annual GHG Reductions (MT CO2e/yr)"))
.call(g => g.selectAll(".tick line").clone()
.attr("stroke-opacity", 0.1)
.attr("y2", b_height - b_margin.bottom - 80))
b_yAxis = g => g
.attr("transform", `translate(${5},0)`)
.call(d3.axisRight(b_y).tickFormat(d => b_lookup[d]))
.call(g => g.select(".domain").remove())
.call(g => g.selectAll(".tick line").remove())
b_margin = ({top: 80, right: 100, bottom: 50, left: 280})
b_height = 775
showtick = d => {
if (ecm_data.get(d).quartiles[1] < 10) {
return 0;
}
else if (ecm_data.get(d).quartiles[2] - ecm_data.get(d).quartiles[0] < b_x.domain()*.05) {
return 0;
}
else { return 1;}
}
//reset to filter ecms
ecm_highlight = d => {
if (ecm_data.get(d).quartiles[1] < b_x.domain()[1]*.10) {
return "#00a1b0";
//return "#bfbfbf"
}
else { return "#00a1b0";}
}
//reset to turn on labels
text_highlight = d => {
if (ecm_data.get(d).quartiles[1] < b_x.domain()[1]*.10) {
return 0;
}
else { return 0;}
//else { return 1;}
}
percentage_savings = d => {
const reduction = ecm_data.get(d).quartiles[1] / (data.map(d => d["GHG"]).reduce((a, b) => a + b)/ data.length / 2204);
return d3.format(".0%")(reduction)
}
t_x = d3.scaleBand()
.domain([0, 1])
.range([margin.left, width - margin.right])
.padding(0.1)
.paddingOuter(1)
t_y = d3.scaleLinear()
.domain([0, calcghg(data[0])/2204 * 1.3]).nice()
.range([height - margin.bottom, margin.top])
runs = ["Baseline (Current)", "With All Measures Combined"]
t_xAxis = g => g
.attr("transform", `translate(0,${height - margin.bottom})`)
.call(d3.axisBottom(t_x).tickFormat(i => runs[i]).tickSizeOuter(.5).tickPadding(12))
t_yAxis = g => g
.attr("transform", `translate(${margin.left},0)`).attr("class", "axis")
.call(d3.axisLeft(t_y).tickPadding(8).ticks(5).tickFormat(d3.format("~s")))
.call(g => g.select(".domain").remove())
.call(g => g.select(".tick:last-of-type text").clone()
.attr("x", 3)
.attr("text-anchor", "start")
.attr("font-weight", "bold")
.html("Annual GHG Emissions MT CO2e"))
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