2d:null 2e:["$","title",null,{"children":"APP Wind Benchmark | Andy Fleming | Observable"}] 33:T5d4,{ var data = [...Array(12).keys()].map(month_no=>{ return { y:relative_disp[month_no], x:[...Array(24).keys()], mode: 'lines', line: {shape:'spline',color: d3.quantize(d3.interpolateHcl("#d66000", "#a9a9b4"), 12)[month_no],width:2}, fill:'', type: 'scatter', hoverinfo: 'name', showlegend:true, name: month_names[month_no] } }) var layout = { height: 250, width: width-30, font: font, hovermode:'closest', showlegend: true, legend: {orientation: 'h', xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks:'outside', dtick:1, }, yaxis: { title: 'Output', range: [0,1.19], showgrid: true, zeroline: false, tickformat: '%.0f', ticks:'outside' } }; const div=container('Hourly plant output relative to installed capacity by calendar month. For an undegraded plant.') plt.newPlot(div, data, layout,{displayModeBar: false}) div.on('plotly_hover', d => { var curveNumber = d.points[0].curveNumber var vals = div.data.map((_, i) => (i === curveNumber) ? 1 : 0.2) var vals2 = div.data.map((_, i) => (i === curveNumber) ? 'tozeroy' : '') plt.restyle(div, 'opacity', vals) plt.restyle(div, 'fill', vals2) }) div.on('plotly_unhover', d => { var vals = div.data.map((_, i) => 1) var vals2 = div.data.map((_, i) => '') plt.restyle(div, 'opacity', vals) plt.restyle(div, 'fill', vals2) }) return div }34:T5da,{ var data = [ { y: daily.map(d=>d.price_max).concat(daily.map(d=>d.price_min).reverse()), x: daily.map(d=>d.date).concat(daily.map(d=>d.date).reverse()), mode: 'lines', line: { width: 0}, fill:'toself', fillcolor:'rgba(100, 149, 237,0.3)', type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', } , { y: daily.map(d=>d.price_weight_av), x: daily.map(d=>d.date), mode: 'lines', line: {shape: 'spline', color:'grey', width: 1.5}, type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', }, { y: movingAverage(daily.map(d=>d.price_weight_av),14), x: daily.map(d=>d.date), mode: 'lines', line: {shape: 'spline', color:d3.schemeCategory10[3], width: 1.5}, type: 'scatter', hoverinfo: 'x,y', showlegend:false,name: '', }, ] var layout = { height: 250, width: width-30, font: font, showlegend: true, legend: {xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 5,t: 0}, xaxis: { rangeslider: {}, range:years_range, showgrid: true, zeroline: false, ticks:'outside', }, yaxis: { title: '$/MWh', range: [0,320], showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('SAPP DAM weighted average daily price. 14 day moving average in red. Blue area is the daily maximum and minimum prices.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }35:T450,{ var data = [ { y: daily_price.map(d=>d[1].price), x: daily_price.map(d=>d[0]), mode: 'lines', line: {shape: '', color:col, width: 1.5}, type: 'scatter', hoverinfo: 'x+y', showlegend:false,name: '', }, { y: movingAverage(daily_price.map(d=>d[1].price),14), x: daily_price.map(d=>d[0]), mode: 'lines', line: {shape: 'spline', color:'#566573', width: 1.5}, type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', }, ] var layout = { height: 250, width: width-30, font: font, showlegend: true, legend: {xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 5,t: 0}, xaxis: { rangeslider: {}, range: years_range, showgrid: true, zeroline: false, ticks: 'outside', }, yaxis: { title: `$/MWh`, showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('APP Wind Benchmark price calculated daily from 2016 to date. Grey line: 14 day moving average.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }36:T4f1,{ var data = [{ y: annual_mean.map(v => v[1]), x: annual_mean.map(v => v[0]), text: annual_mean.map(v => d3.format('.1f')(v[1])), name: 'Yearly mean', marker: {color:make_trans(col,0.55)}, type: 'bar', hoverinfo: 'y', showlegend:true, mode:'markers+text', textposition:'outside' }, { y: means.map(v => v.mean), x: means.map(v => v.year), text: means.map(v => d3.format('.1f')(v.mean)),name: 'Expanding average from 2025 back', line: {color:col}, type: 'scatter', hoverinfo: 'y', showlegend:true, mode:'markers+text+lines', textposition:'top' }] var layout = { height: 250, width: width *.5, font: font, barmode:'stack', showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 65,r: 10,b: 30,t: 0}, xaxis: { showgrid: false, zeroline: false, ticks:'outside', dtick:1}, yaxis: { title: '$/MWh', showgrid: true, zeroline: true, tickformat: ',.0f', ticks:'outside', range: [40,195] }}; const div=container('Annual average APP Wind Benchmark price (bars) and the expanding average from 2025 back (line).') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }37:T665,{ function series(dat, col, nam) { let p90 = dat[Math.floor(dat.length*0.1)] let p50 = dat[Math.floor(dat.length*0.5)] return [{ y: dat.map(v=>v.price), x: dat.map(v=>v.exceedance), mode: 'lines', line: {shape: 'spline', color: col, width:3}, fill:'', type: 'scatter', hoverinfo: 'x,y', name: nam, }, { y: [p90.price], x: [p90.exceedance], text: [d3.format('$.0f')(p90.price)], mode: 'markers+text', marker: {color: col, size:10}, textposition:'top-right', type: 'scatter', hoverinfo: 'none', name: nam, showlegend:false }, { y: [p50.price], x: [p50.exceedance], text: [d3.format('$.0f')(p50.price)], mode: 'markers+text', marker: {color: col, size:10}, textposition:'top-right', type: 'scatter', hoverinfo: 'none', name: nam, showlegend:false } ] } var data = [] data=data.concat(series(wind_pdc,col, '2016 to date')) data=data.concat(series(wind_pdc_recent,make_trans(col,0.5), '2021 to date')) var layout = { height: 270, width: width-30, font: font, showlegend: true, legend: {orientation:'h',xanchor: 'right', x:1, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks:'outside', tickformat: '%.0f' }, yaxis: { title: `$/MWh`, showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('Wind benchmark price exceedance curves. Median (P50) and P90 prices highlighted.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }38:T5bd,wind_chart = function(){ var data = [ { y: monthly_wind_price.map(d=>d[1].price), x: monthly_wind_price.map(d=>d[1].start_date), mode: 'lines+markers', line: {shape: '', color: col, width: 1.5}, type: 'scatter', showlegend:true, fill:'tozeroy', name:'APP Wind Benchmark', hovertemplate: "%{x}
" + "%{y:,.0f} %{yaxis.title.text}" + "", },{ y: monthly.map(d=>d.price_mean), x: monthly.map(d=>d.date), mode: 'lines+markers', line: {shape: '', color: '#444', width: 1}, marker:{size:2}, type: 'scatter', showlegend:true, fill:'', name:'SAPP DAM Average Price', hovertemplate: "%{x}
" + "%{y:,.0f} %{yaxis.title.text}" + "", } ] var layout = { height: 220, width: width-30, font: font, showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks: 'outside', range:[d3.min(monthly_wind_price, d=>d[1].start_date),d3.max(monthly_wind_price, d=>d[1].start_date)] }, yaxis: { range: [20,230], title: `$/MWh`, showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('Monthly average APP Wind Benchmark price from 2016 to date.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }39:T444,wind_variance_chart=function(){ var data = [ { y: monthly_wind_variance.map(d=>d.variance), x: monthly_wind_variance.map(d=>d.start_date), marker: {color: make_trans(col,0.7)}, type: 'bar', showlegend:false, fill:'tozeroy', name:'APP Wind Benchmark', hovertemplate: "%{x}
" + "%{y:%.0f} %{yaxis.title.text}" + "", } ] var layout = { height: 200, width: width-30, font: font, showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks: 'outside', range:[d3.min(monthly_wind_price, d=>d[1].start_date),d3.max(monthly_wind_price, d=>d[1].start_date)+20] }, yaxis: { title: ``, range:[-0.02,0.32], showgrid: true, zeroline: false, tickformat: '%.0f', ticks:'outside' } }; const div=container('Relative APP Wind Benchmark price compared to the average SAPP DAM Price.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }3a:[{"id":"f97fdeb7341d3f752a7271f84a46608de7c558c00d96c577adeee0965b8603a8c97870615569a9fa16d0c6fa12d7e7b4892657bad77501f966f08b8e13e8e6b9","href":"https://static.observableusercontent.com/files/f97fdeb7341d3f752a7271f84a46608de7c558c00d96c577adeee0965b8603a8c97870615569a9fa16d0c6fa12d7e7b4892657bad77501f966f08b8e13e8e6b9","name":"APP logo.png","type":"image/png","lastModified":1662274592126.488,"size":92844},{"id":"c454c304237cb8f85550eb2ceaad3284679841e19331e79cf71323e43ee22d583e252e9d2c8b5c467714a865a81396cac89a93c5617396b12bf180a95e951011","href":"https://static.observableusercontent.com/files/c454c304237cb8f85550eb2ceaad3284679841e19331e79cf71323e43ee22d583e252e9d2c8b5c467714a865a81396cac89a93c5617396b12bf180a95e951011","name":"unika_p50-1.csv","type":"text/csv","lastModified":1662275210746.826,"size":1267}] 31:{"id":"d46f7addbad487e8","slug":"app-wind-benchmark","title":"APP Wind Benchmark","thumbnail":"4c2482f9c46b1d47363141a8ae0d8f02ed64e0e4211684de092e9feec2108ac4","access_level":"public","create_time":"$D2022-09-04T06:56:32.126Z","update_time":"$D2026-06-05T12:06:19.801Z","view_time":null,"first_public_time":"$D2022-09-04T08:14:39.539Z","fork":{"id":"b1d9c4bee4b81200","slug":"app-solar-benchmark","title":"APP Solar Benchmark","owner":{"id":"21337e734770a90b","login":"andyflem","name":"Andy Fleming"}},"stars":0,"starred":false,"owner":{"type":"team","id":"21337e734770a90b","login":"andyflem","name":"Andy Fleming","avatar_url":"https://avatars-next.observableusercontent.com/fd3844143a4c29872f0df28a8ebce77bb56cebf2fa74bb669872e4def82ad809","tier":"starter_2024"},"version":7255,"publish_version":null,"role":null,"authored":false,"authors":[{"type":"individual","id":"96924893937b5930","login":"andyflem","name":"Andy Fleming","avatar_url":"https://avatars-next.observableusercontent.com/fd3844143a4c29872f0df28a8ebce77bb56cebf2fa74bb669872e4def82ad809","tier":null}],"members":[{"type":"individual","id":"96924893937b5930","login":"andyflem","name":"Andy Fleming","avatar_url":"https://avatars-next.observableusercontent.com/fd3844143a4c29872f0df28a8ebce77bb56cebf2fa74bb669872e4def82ad809","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":1,"collection":{"id":"7d6d01969d5f1ad9","slug":"southern-african-power-pool","title":"Southern African Power Pool","owner":{"id":"21337e734770a90b","login":"andyflem","name":"Andy Fleming"}},"type":"notebook","body":{"title":"APP Wind Benchmark","cells":[{"id":0,"value":"html`

APP Wind Benchmark

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6825,"value":"

\n\n

\n The APP Wind Benchmark is a reference price (in $/MWh) that would be achieved by a grid-connected wind plant that sells all of its energy on the Southern African Power Pool (SAPP) Day-ahead Market (DAM).\n

\n The APP Wind Benchmark is calculated by combining the hourly settlement price of the SAPP DAM market with the hourly relative output of a wind plant located in Eastern Zambia.\n

\n
\n

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":7211,"value":"wind_chart()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7221,"value":"wind_variance_chart()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6968,"value":"

Calculating the benchmark

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","output":"","database":"$undefined"},{"id":5584,"value":"html`\n

Wind plant

\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6895,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5593,"value":"html`\n

Market Price

\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6536,"value":"html`\nThe price on the Southern African Power Pool (SAPP) day-ahead market (DAM) varies hour by hour and average daily prices vary over time. On average prices are lowest at night (and on Sundays and public holidays) and there are two peak periods in during weekday mornings and evenings. An intermediate price occurs during the day on weekdays. \n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1924,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6517,"value":"{ \n var selected_months=['Mar','Jun', 'Aug', 'Dec']\n let data = selected_months.map((m, i)=>{\n const ser = month_profiles[month_dict[m].index]\n return {\n y: [...Array(24).keys()].map(h=>ser.get(h)),\n mode: 'lines', line: {shape: 'spline', color: d3.schemeDark2[month_dict[m].group], width:3}, fill:'',\n type: 'scatter', hoverinfo: 'x,y', name: m,\n }\n })\n \n var layout = {\n height: 250, width: width-30,\n font: font, \n showlegend: true, legend: {xanchor: 'left', x:1,y: 1},\n margin: {l: 50,r: 5,b: 30,t: 0},\n xaxis: {\n title: '',\n showgrid: true, zeroline: false, dtick: 1, ticks:'outside',\n },\n yaxis: {\n range: [20,230],\n title: `$/MWh`,\n showgrid: false, zeroline: false, tickformat: '.0f', ticks:'outside'\n }\n };\n\n const div=container('Average price on the SAPP DAM market by time-of-day for selected months from 2020 to date.')\n plt.newPlot(div, data, layout,{displayModeBar: false});\n return div\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5599,"value":"html`\n

Wind benchmark price

\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6541,"value":"html`\nThe price achieved by a wind plant selling onto the SAPP DAM market over the historic period is a product of the wind yield curves and the historic market prices.\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5332,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7228,"value":"wind_chart()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7232,"value":"wind_variance_chart()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6584,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6974,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6006,"value":"html`\n

\n

Setup

\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6942,"value":"col='#2980b9'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6913,"value":"container = function(captionText) {\n const div=DOM.element('div')\n div.setAttribute(\"class\",\"border m-2 p-2\")\n const caption=DOM.element('figcaption')\n caption.append(captionText)\n div.append(caption)\n return div\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7200,"value":"$38","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7218,"value":"$39","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1469,"value":"md `\n## Wind\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6862,"value":"specific_yield = yield_total/capacity","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6860,"value":"capacity = 200","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6857,"value":"yield_total = d3.sum(monthly_yield_totals)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7137,"value":"wind_pdc_recent={\n let out={}\n\n let prices=JSON.parse(JSON.stringify(daily_price.filter(a=>a[1].lux_date.year>2020))).sort((a,b)=>a[1]['price']-b[1]['price'])\n out=prices.map((d,i)=>{\n return {\n exceedance: 1-(i/prices.length),\n price: d[1]['price']?d[1]['price']:0\n }\n })\n return out\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7139,"value":"wind_pdc={\n let out={}\n let prices=JSON.parse(JSON.stringify(daily_price)).sort((a,b)=>a[1]['price']-b[1]['price'])\n out=prices.map((d,i)=>{\n return {\n exceedance: 1-(i/prices.length),\n price: d[1]['price']?d[1]['price']:0\n }\n })\n return out\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6469,"value":"monthly_yield_totals = {\n return monthly_hours_p50.map(m => {\n let obs=Object.entries(m)\n obs.pop()\n return d3.sum(obs, v => v[1])\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6057,"value":"relative_yield_profiles = {\n return monthly_hours_p50.map((month, month_no) => {\n let tmp = Object.keys(month).map(hour_no=>{\n return month[hour_no]/monthly_yield_totals[month_no]\n })\n //tmp.pop()\n return tmp\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6878,"value":"relative_disp = monthly_hours_p50.map((m,i) => Object.values(m).slice(0,24).map(h=>h/month_days(i+1)/capacity))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6031,"value":"md `\n### SAPP DAM\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6522,"value":"month_profiles=[...Array(12).keys()].map(m=>month_profile_price(m+1))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6524,"value":"function month_profile_price(month_no) {\n return d3.rollup(calmonthly_hours.filter(m=>m.month==month_no),v=>d3.mean(v,m=>m.price),t=>t.hour)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3491,"value":"years_range= [monthly[0].lux_date.plus({month:-0.5}).toJSDate(),monthly[monthly.length-1].lux_date.plus({month:0.5}).toJSDate()]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6681,"value":"means={\n return annual_mean.map(v => { return {year: v[0], mean: d3.mean(annual_mean.filter(m => m[0] >= v[0]), y => y[1])}})\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6588,"value":"annual_mean = d3.rollups(monthly_wind_price, v => d3.mean(v, d => d[1].price), v => DateTime.fromJSDate(v[1].start_date).year)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7215,"value":"monthly_wind_variance = monthly_wind_price.map((d,month_no)=>\n{\n return {\n lux_date: d[1].lux_date,\n start_date: d[1].start_date,\n variance:(d[1].price-monthly[month_no].price_mean)/monthly[month_no].price_mean\n}\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5341,"value":"monthly_wind_price = {\n \n let ret = d3.rollups(\n daily_price.map(v => v[1]),\n v => {\n return {\n lux_date: v[0].lux_date,\n start_date: d3.min(v, d => d.date),\n weekday_price: d3.mean(v.filter(p => p.lux_date.weekday < 6), d => d.price),\n saturday_price: d3.mean(v.filter(p => p.lux_date.weekday == 6), d => d.price),\n sunday_price: d3.mean(v.filter(p => p.lux_date.weekday == 7), d => d.price),\n price: d3.mean(v, d => d.price),\n }\n },\n v => v.lux_date.year + '_' + v.lux_date.month\n )\n return ret\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7092,"value":"daily_price","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5294,"value":"daily_price = {\n \n let ret= d3.rollups(hourly_weighted_price, v => { \n return {\n date: v[0].date,\n lux_date: DateTime.fromJSDate(v[0].date),\n millis:DateTime.fromJSDate(v[0].date).toMillis(),\n price: d3.sum(v, d => d.weighted_price)\n }\n}, v => v.date)\n return ret.sort((a,b)=>d3.ascending(a[0],b[0]))\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5273,"value":"hourly_weighted_price={\n return hourly.map(h => {\n return {\n date: h.date,\n hour: h.hour,\n weighted_price: h.price * relative_yield_profiles[h.lux_date.month-1][h.hour],\n }\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4499,"value":"md `\n### Data Load\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6526,"value":"calmonthly_hours = {\n const raw = (await d3.csv(base_url + market_ref + \"_calmonthly_hours.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5278,"value":"hourly = {\n const raw = (await d3.csv(base_url + market_ref + \"_hourly_slim.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n raw.forEach(r=>{\n r.lux_date=DateTime.fromJSDate(r.date)\n }) \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":7000,"value":"monthly_hours_p50=[...Array(12).keys()].map(month_no=> {\n return Object.fromEntries(monthly_hours_p50_raw.map((hour,hour_no)=>[hour_no,parseFloat(hour[month_no+1])*1000]))\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6993,"value":"monthly_hours_p50_raw = FileAttachment(\"unika_p50-1.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5090,"value":"monthly_hours_p50_sol = {\n const raw = (await d3.csv(\"https://data.africanpowerprojects.com/sapp/output/pv/25mw_p50.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2118,"value":"monthly = {\n const raw = (await d3.csv(base_url + market_ref + \"_monthly.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n raw.map(r=>{\n r.lux_date=DateTime.fromObject({year: r.year, month: r.month, day: 1})\n r.date=r.lux_date.toJSDate()\n })\n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":1918,"value":"daily = {\n const raw = (await d3.csv(base_url + market_ref + \"_daily.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n raw.forEach(r=>{\n r.lux_date=DateTime.fromObject({year: r.year, month: r.month, day: r.day})\n r.date=r.lux_date.toJSDate()\n })\n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":6028,"value":"md `\n### Setup\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4509,"value":"base_url='https://data.africanpowerprojects.com/sapp/output/'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4512,"value":"market_ref='dam'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5103,"value":"function month_days(i) {\n if(i === 4 || i === 6 || i === 9 || i === 11) {\n\t\treturn 30\n\t} else if(i === 2) {\n\t\treturn 28\n\t} else {\n\t\treturn 31\n\t}\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5108,"value":"month_names={\n return {\n 0:'Jan',\n 1:'Feb',\n 2:'Mar',\n 3:'Apr',\n 4:'May',\n 5:'Jun',\n 6:'Jul',\n 7:'Aug',\n 8:'Sep',\n 9:'Oct',\n 10:'Nov',\n 11:'Dec',\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5152,"value":"month_dict={\n return {\n 'Jan':{index: 0, days: 31},\n 'Feb':{index: 1, days: 28},\n 'Mar':{index: 2, days: 31},\n 'Apr':{index: 3, days: 30},\n 'May':{index: 4, days: 31},\n 'Jun':{index: 5, days: 30},\n 'Jul':{index: 6, days: 31},\n 'Aug':{index: 7, days: 31},\n 'Sep':{index: 8, days: 30},\n 'Oct':{index: 9, days: 31},\n 'Nov':{index: 10, days: 30},\n 'Dec':{index: 11, days: 31},\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":964,"value":"md `\n### Imports\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4702,"value":"function catCol(index) {\n return d3.schemeCategory10[index]\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":3027,"value":"make_trans=function(col,opacity) {\n let c=d3.color(col)\n c.opacity=opacity\n return c.formatRgb()\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4690,"value":"function movingAverage(values, N) {\n let i = 0;\n let sum = 0;\n const means = new Float64Array(values.length).fill(NaN);\n for (let n = Math.min(N - 1, values.length); i < n; ++i) {\n sum += values[i];\n }\n for (let n = values.length; i < n; ++i) {\n sum += values[i];\n means[i - Math.floor(N / 2)] = sum / N;\n sum -= values[i - N + 1];\n }\n return means;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":14,"value":"font = ({\n family: 'Courier New, monospace',\n size: 13,\n color: '#6f6f6f'\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":16,"value":"d3 = require(\"d3@7\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":18,"value":"plt = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5957,"value":"html`\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5117,"value":"html`\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":4407,"value":"style=html`css\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2137,"value":"luxon = require(\"luxon@1/build/amd/luxon.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":2140,"value":"DateTime = luxon.DateTime","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W3a","stdlib":"1","titling":"auto"}} 32:"$31:body"