2c:null 2d:["$","title",null,{"children":"SAPP DAM Time of Day Arbitrage Analysis | Andy Fleming | Observable"}] 32:T70d,viewof dam_range = { var data = [ { y: daily.map(d=>d.price_max).concat(daily.map(d=>d.price_min).reverse()), x: daily.map(d=>d.date).concat(daily.map(d=>d.date).reverse()), mode: 'lines', line: { width: 0}, fill:'toself', fillcolor:'rgba(100, 149, 237,0.3)', type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', } , { y: daily.map(d=>d.price_weight_av), x: daily.map(d=>d.date), mode: 'lines', line: {shape: 'spline', color:'grey', width: 1.5}, type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', }, { y: movingAverage(daily.map(d=>d.price_weight_av),14), x: daily.map(d=>d.date), mode: 'lines', line: {shape: 'spline', color:d3.schemeCategory10[3], width: 1.5}, type: 'scatter', hoverinfo: 'x,y', showlegend:false,name: '', }, ] var layout = { height: 300, width: width-30, font: font, showlegend: true, legend: {xanchor: 'left', x:0, y: 1}, margin: {l: 90,r: 90,b: 10,t: 0}, xaxis: { rangeslider: {}, range:years_range, showgrid: true, zeroline: false, ticks:'outside', }, yaxis: { title: '$/MWh', range: [0,320], showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('Daily prices on the SAPP DAM market. Red line - 14 day moving average price. Blue - Daily price range.') const form = html`` plt.newPlot(div, data, layout,{displayModeBar: false}); div.on('plotly_relayout', d => { form.dispatchEvent(new CustomEvent("input", { detail: d['xaxis.range'],bubbles: true })); }) form.oninput = (evt) => { form.value = evt.detail; }; form.oninput({detail: [daily[0].date, daily[daily.length-1].date]}) return form; }33:T73e,{ let margin = ({top: 20, right: 65, bottom: 0, left: 73}) let height=300 let ys=timeofday.map(d => d.dayofweek == 1 ? month_names[d.month-1] : d.dayofweek == 6 ? 'Sat' : 'Sun') ys.splice(12,0,'') let y = d3.scaleBand() .domain(ys) .range([margin.top, height - margin.bottom]) .padding(0.1) .round(true) let x = d3.scaleLinear() .domain([0, 24]) .range([margin.left, width - margin.right]) .interpolate(d3.interpolateRound) const svg = d3 .create("svg") .attr("viewBox", [0, 0, width-30, height]) .style("max-width", `${width-30}px`) .style("height", "auto") svg.append("g") .attr('transform', `translate(0,${margin.top})`) .call(d3.axisTop(x).ticks(23)) .call(g => g.select(".domain").remove()) .call(g => g.selectAll(".tick text") .attr("font-size", 12)) svg.append("g") .attr('transform', `translate(${margin.left},0)`) .call(d3.axisLeft(y)) .call(g => g.select(".domain").remove()) .call(g => g.selectAll(".tick text") .attr("font-size", 12)) svg.append("g") .attr('stroke', 'white') .attr('stroke-width', '1') .attr('fill-opacity', '0.5') .selectAll("rect") .data(timeofday_flat) .join("rect") .attr('y', d=>y(d.dayofweek == 1 ? month_names[d.month-1] : d.dayofweek == 6 ? 'Sat' : 'Sun')) .attr('x', d=>x(d.hour)) .attr('width', x(1)-x(0)) .attr('height', y.bandwidth()) .attr('fill', d=>catCol(cats[d.cat].index) ) const div=container('Average time of day categories for weekdays by month and separately for saturdays and sundays. Blue - Off-peak, Orange - Morning peak, Green - Standard, Red - Evening peak.') div.prepend(svg.node()) // plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }34:T700,{ function yr(ref) { const annual_price=d3.rollups(monthly.filter(m=>m.year<2025),v=>d3.mean(v, d=>d[ref + '_price_mean']), v=>v.lux_date.startOf('year').plus({month:6})) return { y: annual_price.map(m=>Math.round(m[1])), text: annual_price.map(m=>Math.round(m[1])), x: annual_price.map(m=>m[0].toJSDate()), type: 'scatter', showlegend:false, mode: 'text+lines+markers', textposition:'top-left', line: {color: make_trans(catCol(cats[ref].index),0.4),width:2}, marker: {color: make_trans(catCol(cats[ref].index),0.8),size: 10}, hoverinfo: 'y', name: cats[ref].name } } function mon(ref) { return { y: monthly.map(m=>m[ref + '_price_mean']), x: monthly.map(m=>m['date']), mode: 'lines+markers', line: {shape:'',color: catCol(cats[ref].index), width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'none', name: cats[ref].name, showlegend:true, connectgaps: false } } var data = [] Object.values(cats).forEach(c=>{ if (Object.fromEntries(selected_cats2.map(c=>[c,c]))[c.name]) { data.push(mon(c.ref)) data.push(yr(c.ref)) } }) var layout = { height: 270, 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: { range:years_range, showgrid: true, zeroline: false, ticks:'outside', }, yaxis: { title: '$/MWh', range:[0,360], showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('Monthly and annual average prices on the SAPP DAM market by time-of-day categories.') plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }35:T70f,{ var data = [ { y: daily_differentials.filter(v=>v.day_of_week<6 && v.year>2019).map(d=>d.off_morning), x: daily_differentials.filter(v=>v.day_of_week<6 && v.year>2019).map(d=>d.lux_date.toJSDate()), mode: 'lines', line: {shape: '', color:d3.schemeCategory10[0], width: 1}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Offpeak to Morning Differential', }, { y: daily_differentials.filter(v=>v.day_of_week<6 && v.year>2019).map(d=>d.standard_evening), x: daily_differentials.filter(v=>v.day_of_week<6 && v.year>2019).map(d=>d.lux_date.toJSDate()), mode: 'lines', line: {shape: '', color:d3.schemeCategory10[3], width: 1}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Standard to Evening Differential', } , { y: daily_differentials.filter(v=>v.day_of_week==6 && v.year>2019).map(d=>d.saturday), x: daily_differentials.filter(v=>v.day_of_week==6 && v.year>2019).map(d=>d.lux_date.toJSDate()), mode: 'lines', line: {shape: '', color:d3.schemeCategory10[8], width: 1}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Saturday Differential', } ] var layout = { height: 270, 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', }, yaxis: { title: `$/MWh`, showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside', range: [-60,330] } }; const div=container('Daily differentials between peak prices and off-peak prices for 2020 to date.') plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }36:Tbe9,differentials_chart={ var data = [ { y: monthly_differentials.map(d=>d.off_morning), x: monthly_differentials.map(d=>d.lux_date.toJSDate()), mode: 'lines+markers', line: {shape: '', color:d3.schemeCategory10[0], width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Offpeak to Morning Differential', }, { y: monthly_differentials.map(d=>d.standard_evening), x: monthly_differentials.map(d=>d.lux_date.toJSDate()), mode: 'lines+markers', line: {shape: '', color:d3.schemeCategory10[3], width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Standard to Evening Differential', }, /*{ y: monthly_differentials.map(d=>d.saturday), x: monthly_differentials.map(d=>d.lux_date.toJSDate()), mode: 'lines+markers', line: {shape: '', color:d3.schemeCategory10[8], width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Saturday Differential', },*/ { y: yearly_differentials.map(d=>d.standard_evening), text: yearly_differentials.map(d=>d3.format('.0f')(d.standard_evening)), x: yearly_differentials.map(d=>d.lux_date.toJSDate()), type: 'scatter', showlegend:false, mode: 'text+lines+markers', textposition:'top-left', line: {color: make_trans(d3.schemeCategory10[3],0.4),width:2}, marker: {color: make_trans(d3.schemeCategory10[3],0.8),size: 10}, hoverinfo: 'y', name: '' }, { y: yearly_differentials.map(d=>d.off_morning), text: yearly_differentials.map(d=>d3.format('.0f')(d.off_morning)), x: yearly_differentials.map(d=>d.lux_date.toJSDate()), type: 'scatter', showlegend:false, mode: 'text+lines+markers', textposition:'top-left', line: {color: make_trans(d3.schemeCategory10[0],0.4),width:2}, marker: {color: make_trans(d3.schemeCategory10[0],0.8),size: 10}, hoverinfo: 'y', name: '' }/*, { y: yearly_differentials.map(d=>d.saturday), text: yearly_differentials.map(d=>d3.format('.0f')(d.saturday)), x: yearly_differentials.map(d=>d.lux_date.toJSDate()), type: 'scatter', showlegend:false, mode: 'text+lines+markers', textposition:'top-left', line: {color: make_trans(d3.schemeCategory10[8],0.4),width:2}, marker: {color: make_trans(d3.schemeCategory10[8],0.8),size: 10}, hoverinfo: 'y', name: '' } */ ] var layout = { height: 270, 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: {range:years_range, showgrid: true, zeroline: false, ticks: 'outside', }, yaxis: { title: `$/MWh`, showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside', range: [0,230] } }; const div=container('Monthly and annual average price differentials.') plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }37:Tb24,{ var data = [ { y: monthly_differentials.map(d=>d.off_morning_pct), x: monthly_differentials.map(d=>d.lux_date.toJSDate()), mode: 'lines+markers', line: {shape: '', color:d3.schemeCategory10[0], width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Offpeak to Morning Differential', }, { y: monthly_differentials.map(d=>d.standard_evening_pct), x: monthly_differentials.map(d=>d.lux_date.toJSDate()), mode: 'lines+markers', line: {shape: '', color:d3.schemeCategory10[3], width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'x', showlegend:true,name: 'Standard to Evening Differential', }/*, { y: monthly_differentials.map(d=>d.saturday_pct), x: monthly_differentials.map(d=>d.lux_date.toJSDate()), mode: 'lines+markers', line: {shape: '', color:d3.schemeCategory10[8], width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'x', showlegend:true,name: 'Saturday Differential', }*/, { y: yearly_differentials.map(d=>d.standard_evening_pct), x: yearly_differentials.map(d=>d.lux_date.toJSDate()), type: 'scatter', showlegend:false, mode: 'text+lines+markers', textposition:'top-left', line: {color: make_trans(d3.schemeCategory10[3],0.4),width:2}, marker: {color: make_trans(d3.schemeCategory10[3],0.8),size: 10}, hoverinfo: 'y', name: '' }, { y: yearly_differentials.map(d=>d.off_morning_pct), x: yearly_differentials.map(d=>d.lux_date.toJSDate()), type: 'scatter', showlegend:false, mode: 'text+lines+markers', textposition:'top-left', line: {color: make_trans(d3.schemeCategory10[0],0.4),width:2}, marker: {color: make_trans(d3.schemeCategory10[0],0.8),size: 10}, hoverinfo: 'y', name: '' }/*, { y: yearly_differentials.map(d=>d.saturday_pct), x: yearly_differentials.map(d=>d.lux_date.toJSDate()), type: 'scatter', showlegend:false, mode: 'text+lines+markers', textposition:'top-left', line: {color: make_trans(d3.schemeCategory10[8],0.4),width:2}, marker: {color: make_trans(d3.schemeCategory10[8],0.8),size: 10}, hoverinfo: 'y', name: '' } */ ] var layout = { height: 270, 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: {range:years_range, showgrid: true, zeroline: false, ticks: 'outside', }, yaxis: { title: ``, showgrid: true, zeroline: false, tickformat: '.0%', ticks:'outside', range: [1,7.1] } }; const div=container('Monthly and annual price differentials expressed as a percentage increase in price.') plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }38:T663,{ var data = [ { y: monthly_differentials.map(d=>d.off_morning_coeffvar), x: monthly_differentials.map(d=>d.lux_date.toJSDate()), mode: 'lines+markers', line: {shape: '', color:d3.schemeCategory10[0], width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Offpeak to Morning Differential', }, { y: monthly_differentials.map(d=>d.standard_evening_coeffvar), x: monthly_differentials.map(d=>d.lux_date.toJSDate()), mode: 'lines+markers', line: {shape: '', color:d3.schemeCategory10[3], width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Standard to Evening Differential', }/*, { y: monthly_differentials.map(d=>d.saturday_coeffvar), x: monthly_differentials.map(d=>d.lux_date.toJSDate()), mode: 'lines+markers', line: {shape: '', color:d3.schemeCategory10[8], width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Saturday Differential', }*/ ] var layout = { height: 270, width: width-30, font: font, showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: {range:years_range, showgrid: true, zeroline: false, ticks: 'outside', }, yaxis: { title: ``, showgrid: true, zeroline: false, tickformat: '.0%', ticks:'outside' } }; const div=container('Monthly coefficients of variation (standard deviation / mean) within the three differentials.') plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }39:T4be,{ function chart(ref) { var data = [{ x: daily_differentials.filter(v=>v.lux_date.year>2018).map(d => d[ref + '_pct']), marker: {color: d3.schemeCategory10[ref=='off_morning'?0:3], opacity:0.8}, type: 'histogram', hoverinfo: 'none', showlegend:false }] var layout = { height: 230, font: font, width:width*.4, showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 55,r: 5,b: 50,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks:'outside', tickformat:'.0%'}, yaxis: { title: 'no', showgrid: false, zeroline: true, tickformat: ',.0f', ticks:'outside' }}; const div=DOM.element('div') plt.newPlot(div, data, layout,{displayModeBar: false}); return div } const div=container('Histograms of daily percentage price differentials since 2019. Left Off-peak to Morning and right chart Standard to Evening differentials.') let h=html`

${chart('off_morning')}

${chart('standard_evening')}

` div.prepend(h) return html`${div}` }3a:T859,{ function series(dat, col, nam) { let p90 = dat[Math.floor(dat.length*0.1)] let p50 = dat[Math.floor(dat.length*0.5)] let p75 = dat[Math.floor(dat.length*0.25)] return [{ y: dat.map(v=>v.price), x: dat.map(v=>v.exceedance), mode: 'lines', line: {shape: 'spline', color: col, width:3}, fill:'', type: 'scatter', hoverinfo: 'x,y', name: nam, }, { y: [p90.price], x: [p90.exceedance], text: [d3.format('$.0f')(p90.price)], mode: 'markers+text', marker: {color: col, size:10}, textposition:'top-right', type: 'scatter', hoverinfo: 'none', name: nam, showlegend:false }, { y: [p75.price], x: [p75.exceedance], text: [d3.format('$.0f')(p75.price)], mode: 'markers+text', marker: {color: col, size:10}, textposition:'top-right', type: 'scatter', hoverinfo: 'none', name: nam, showlegend:false }, { y: [p50.price], x: [p50.exceedance], text: [d3.format('$.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(pdc_off_morning,d3.schemeCategory10[0], 'Off-peak to Morning')) data=data.concat(series(pdc_standard_evening,d3.schemeCategory10[3], 'Standard to Evening')) data=data.concat(series(pdc_saturday,d3.schemeCategory10[8], 'Saturday')) var layout = { height: 350, width: width, font: font, showlegend: true, legend: {orientation:'h',xanchor: 'right', x:1, y: 1}, margin: {l: 90,r: 90,b: 50,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks:'outside', tickformat: '%.0f' }, yaxis: { title: `$/MWh`, showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=DOM.element('div') plt.newPlot(div, data, layout,{displayModeBar: false}); return html` ${div}

Differential daily exceedance. Median (P50), P75 and P90 prices highlighted.

` }3b:T6c5,{ function chrt(rego, ref) { var data = [ { y: rego.ys, x: rego.xs, mode: 'markers', marker: {color:d3.schemeCategory10[ref == 'off_morning'? 0:3], size: 5}, type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', }, { y: [rego.linearRegressionLine(d3.min(rego.xs)),rego.linearRegressionLine(d3.max(rego.xs))], x: [d3.min(rego.xs),d3.max(rego.xs)], mode: 'lines', line: {color: 'grey', width: 1, dashdot: 'dash'}, type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', }] var layout = { height: 300, width: 350, font: font, showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1}, margin: {l: 90,r: 0,b: 45,t: 0}, xaxis: { title: `${ref == 'off_morning'? 'Off-peak':'Standard'} ($/MWh)`, showgrid: true, zeroline: false, ticks: 'outside',tickformat: '.0f',dtick: 50 }, yaxis: { title: `${ref == 'off_morning'? 'Morning':'Evening'} ($/MWh)`, showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside', dtick: 50 } }; const div=DOM.element('div') plt.newPlot(div, data, layout,{displayModeBar: false}); return div } const div=container('Correlation between monthly average time-of-day differentials. Off-peak - morning r-squared: '+ d3.format('.3f')(reg_off_morning.rsquared) + '. Standard - evening r-squared: ' + d3.format('.3f')(reg_standard_evening.rsquared)) let h=html`

${chrt(reg_off_morning, 'off_morning')}

${chrt(reg_standard_evening, 'standard_evening')}

` div.prepend(h) return html`${div}` }3c:Ta20,{ var data = [ { y: yearly_differentials.map(v => v.off_morning), x: yearly_differentials.map(v => v.year), name: 'Offpeak to Morning', marker: {color:make_trans(d3.schemeCategory10[0],0.7)}, type: 'bar', hoverinfo: 'y', showlegend:true, mode:'markers', textposition:'outside' }/*, { y: means_expanding.map(v => v.off_morning), x: means_expanding.map(v => v.year), text: means_expanding.map(v => d3.format('.0f')(v.off_morning)), type: 'scatter', hoverinfo: 'y', showlegend:false, mode:'markers+text+lines', textposition:'top', line: {color:d3.schemeCategory10[3]} }*/, { y: yearly_differentials.map(v => v.standard_evening), x: yearly_differentials.map(v => v.year), name: 'Standard to Evening', marker: {color:make_trans(d3.schemeCategory10[3],0.7)}, type: 'bar', hoverinfo: 'y', showlegend:true, mode:'markers', textposition:'outside' }/*, { y: means_expanding.map(v => v.standard_evening), x: means_expanding.map(v => v.year), text: means_expanding.map(v => d3.format('.0f')(v.standard_evening)),name: 'Expanding mean from 2022 back', type: 'scatter', hoverinfo: 'y', showlegend:false, mode:'markers+text+lines', textposition:'top', line: {color:d3.schemeCategory10[9]} }*/, { y: yearly_differentials.map(v => v.saturday), x: yearly_differentials.map(v => v.year), name: 'Saturday', marker: {color:make_trans(d3.schemeCategory10[8],0.6)}, type: 'bar', hoverinfo: 'y', showlegend:true, mode:'markers', textposition:'outside' }/*, { y: means_expanding.map(v => v.saturday), x: means_expanding.map(v => v.year), text: means_expanding.map(v => d3.format('.0f')(v.saturday)), type: 'scatter', hoverinfo: 'y', showlegend:false, mode:'markers+text+lines', textposition:'top', line: {color:d3.schemeCategory10[8]} }*/] var layout = { height: 300, width: width *.75, font: font, showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 90,r: 90,b: 30,t: 0}, xaxis: { showgrid: false, zeroline: false, ticks:'outside', dtick:1}, yaxis: { title: '$/MWh', showgrid: true, zeroline: true, tickformat: ',.0f', ticks:'outside', range: [0,220] }}; const div=container('Average differentials by year.') plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }3d:Ta4f,{ var data = [ { y: yearly_differentials.map(v => v.off_morning_pct), x: yearly_differentials.map(v => v.year), name: 'Offpeak to Morning', marker: {color:make_trans(d3.schemeCategory10[0],0.7)}, type: 'bar', hoverinfo: 'none', showlegend:true, mode:'markers', textposition:'outside' }/*, { y: means_expanding.map(v => v.off_morning_pct), x: means_expanding.map(v => v.year), text: means_expanding.map(v => d3.format('.0%')(v.off_morning_pct)), type: 'scatter', hoverinfo: 'y', showlegend:false, mode:'markers+text+lines', textposition:'top', line: {color:d3.schemeCategory10[3]} }*/, { y: yearly_differentials.map(v => v.standard_evening_pct), x: yearly_differentials.map(v => v.year), name: 'Standard to Evening', marker: {color:make_trans(d3.schemeCategory10[3],0.7)}, type: 'bar', hoverinfo: 'none', showlegend:true, mode:'markers', textposition:'outside' }/*, { y: means_expanding.map(v => v.standard_evening_pct), x: means_expanding.map(v => v.year), text: means_expanding.map(v => d3.format('.0%')(v.standard_evening_pct)),name: 'Expanding mean from 2022 back', type: 'scatter', hoverinfo: 'y', showlegend:false, mode:'markers+text+lines', textposition:'top', line: {color:d3.schemeCategory10[9]} }*/, { y: yearly_differentials.map(v => v.saturday_pct), x: yearly_differentials.map(v => v.year), name: 'Saturday', marker: {color:make_trans(d3.schemeCategory10[8],0.6)}, type: 'bar', hoverinfo: 'none', showlegend:true, mode:'markers', textposition:'outside' }/*, { y: means_expanding.map(v => v.saturday_pct), x: means_expanding.map(v => v.year), text: means_expanding.map(v => d3.format('.0%')(v.saturday_pct)), type: 'scatter', hoverinfo: 'y', showlegend:false, mode:'markers+text+lines', textposition:'top', line: {color:d3.schemeCategory10[8]} }*/] var layout = { height: 300, width: width *.75, font: font, showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 90,r: 90,b: 30,t: 0}, xaxis: { showgrid: false, zeroline: false, ticks:'outside', dtick:1}, yaxis: { title: '', showgrid: true, zeroline: true, tickformat: '.0%', ticks:'outside', range: [0,4.5] }}; const div=container('Average percent differentials by year.') plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }3e:T680,{ var data = [ { y: calmonthly_differentials.map(d=>d.off_morning), x: ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], mode: 'lines+markers', line: {shape: 'spline', color:d3.schemeCategory10[0], width: 2}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Offpeak to Morning Differential', }, { y: calmonthly_differentials.map(d=>d.standard_evening), x: ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], mode: 'lines+markers', line: {shape: 'spline', color:d3.schemeCategory10[3], width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Standard to Evening Differential', }, { y: calmonthly_differentials.map(d=>d.saturday), x: ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], mode: 'lines+markers', line: {shape: 'spline', color:d3.schemeCategory10[8], width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Saturday Differential', } ] var layout = { height: 270, 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', }, yaxis: { title: `$/MWh`, range: [20,130], showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('Average price differentials by calendar month.') plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }3f:T554,{ var data = [ { y: reg.ys, x: reg.xs, mode: 'markers', marker: {color:d3.schemeTableau10[1], size: 5}, type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', }, { y: [reg.linearRegressionLine(0),reg.linearRegressionLine(170)], x: [0,170], mode: 'lines', line: {color: 'grey', width: 1, dashdot: 'dash'}, type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', }] var layout = { height: 370, width: 380, font: font, showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1}, margin: {l: 90,r: 0,b: 90,t: 0}, xaxis: { title: `Standard to Evening Diff ($/MWh)`, showgrid: true, zeroline: false, ticks: 'outside',tickformat: '.0f',dtick: 50, range: [0,170] }, yaxis: { title: `Off to Morning Diff ($/MWh)`, showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside', dtick: 50,range: [0,170] } }; const div=container('Monthly average differential between Offpeak and Morning prices (y-axis) and between Standard and Evening prices (x-axis). y = ' + d3.format('.3f')(reg.linearRegression.m) + 'x + ' + d3.format('.1f')(reg.linearRegression.b) + '. r-squared: ' + d3.format('.3f')(reg.rsquared)) plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }40:T5ab,monthly_differentials = { let ret = d3.rollups(daily_differentials, v => { return { lux_date: v[0].lux_date, year: v[0].year, month: v[0].month, off_morning: d3.mean(v.filter(n=>n.day_of_week<6), m=>m.off_morning), standard_evening: d3.mean(v.filter(n=>n.day_of_week<6), m=>m.standard_evening), saturday: d3.mean(v.filter(n=>n.day_of_week==6), m=>m.saturday), off_morning_pct: d3.mean(v.filter(n=>n.day_of_week<6), m=>m.off_morning_pct), standard_evening_pct: d3.mean(v.filter(n=>n.day_of_week<6), m=>m.standard_evening_pct), saturday_pct: d3.mean(v.filter(n=>n.day_of_week==6), m=>m.saturday_pct), off_morning_sd: d3.deviation(v.filter(n=>n.day_of_week<6), m=>m.off_morning), standard_evening_sd: d3.deviation(v.filter(n=>n.day_of_week<6), m=>m.standard_evening), saturday_sd: d3.deviation(v.filter(n=>n.day_of_week==6), m=>m.saturday), off_morning_coeffvar: d3.deviation(v.filter(n=>n.day_of_week<6), m=>m.off_morning) / d3.mean(v.filter(n=>n.day_of_week<6), m=>m.off_morning), standard_evening_coeffvar: d3.deviation(v.filter(n=>n.day_of_week<6), m=>m.standard_evening) / d3.mean(v.filter(n=>n.day_of_week<6), m=>m.standard_evening), saturday_coeffvar: d3.deviation(v.filter(n=>n.day_of_week==6), m=>m.saturday) / d3.mean(v.filter(n=>n.day_of_week==6), m=>m.saturday), } }, v => DateTime.fromObject({year: v.year, month: v.month}) ) return ret.map(v=>v[1]) } 41:[] 30:{"id":"0d60aafe001c76bc","slug":"sapp-dam-time-of-day-arbitrage-analysis","title":"SAPP DAM Time of Day Arbitrage Analysis","thumbnail":"2e5ee2af419f30c235e907981b9ac5073c959c85b5170c6287bd852291fb1794","access_level":"public","create_time":"$D2022-07-26T08:41:10.037Z","update_time":"$D2024-07-18T08:37:20.448Z","view_time":null,"first_public_time":"$D2022-07-26T19:51:27.667Z","has_unpublished_edits":null,"fork":false,"stars":2,"starred":false,"owner":{"type":"team","id":"21337e734770a90b","login":"andyflem","name":"Andy Fleming","avatar_url":"https://avatars-next.observableusercontent.com/fd3844143a4c29872f0df28a8ebce77bb56cebf2fa74bb669872e4def82ad809","tier":"starter_2024"},"version":690,"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":3,"collection":null,"type":"notebook","body":{"titling":"auto","title":"SAPP DAM Time of Day Arbitrage Analysis","cells":[{"id":0,"value":"

SAPP DAM Time of Day Arbitrage Analysis

","pinned":false,"hidden":false,"mode":"md","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":56,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":419,"value":"The SAPP DAM market provides a platform for participating utilities and other members across southern Africa to buy and sell electricity for delivery the following day. Bids and offers are made by the hour.","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":398,"value":"{ \n \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: 270, 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: [20,210],\n title: `$/MWh`,\n showgrid: false, zeroline: false, tickformat: '.0f', ticks:'outside'\n }\n };\n \n const div=container('Average prices on the SAPP DAM market by time-of-day for selected months.')\n plt.newPlot(div, data, layout,{displayModeBar: false})\n return html`${div}`\n \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":416,"value":"Due to patterns in supply and demand the average price for power traded on the SAPP DAM has a distinct daily pattern with lower prices during the nighttime, Off-peak period, moderately higher prices during the daytime, Standard period and two peak, high price periods in the Morning and Evening.\n

\nThe pattern of time-of-day pricing also changes through the year driven by changing day length and average temperatures in the region.\n

\nThis pattern of higher and lower pricing periods through the day presents an opportunity to buy lower priced electricity in the Off-peak and Standard periods, to store in a grid connected battery and then sell this electricity back to the market during the higher priced peak periods, Morning and Evening. ","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":5,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":520,"value":"Two charge and discharge cycles are available for each day of the week except Sunday where on average no significant time of day price differentials exit.","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":145,"value":"$34","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":524,"value":"The average market price for each of the four time of day categories varies daily depending on supply and demand market conditions. Average prices for the evening peak have risen steadily since 2018. Morning peak prices have also risen over the same period but not to the same extent.","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":240,"value":"$35","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":100,"value":"$36","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":529,"value":"The opportunity for trading between peak and offpeak market prices using battery storage depends on the difference in prices on any particular day between peak and off peak periods. As with the overall market price these differentials have historically risen and fallen depending on suplpy and demand considerations.\n

\nSince late 2019 the greatest differential has generally been beween the Standard period and Evening peak period with a slightly lower differential between the nightime Off-peak period and Morning peak.","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":340,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":585,"value":"Price differentials are appear more stable when the peak price is expressed as a percentage of the offpeak price. However there is still an increase in the volatility in more recent years.","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":327,"value":"$38","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":542,"value":"$39","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":635,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":362,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":200,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":611,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":606,"value":"The average Standard to Evening period differential has risen steadily since 2017 on an absolute basis. ","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":182,"value":"$3e","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":595,"value":"There is some seasonality in the price differentials, particularly in the Off-peak to Morning values with an increase in the cold winter months June, July and August. The bump in November is probably an outlier. ","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":108,"value":"$3f","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":600,"value":"

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"","database":"$undefined"},{"id":392,"value":"container = function(captionText) {\n const div=DOM.element('div')\n div.setAttribute(\"class\",\"border m-2 p-2\")\n const caption=DOM.element('figcaption')\n caption.append(captionText)\n div.append(caption)\n return div\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":396,"value":"selected_months=[\"Mar\", \"Jun\", \"Aug\", \"Sep\", \"Oct\", \"Dec\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":400,"value":"month_profiles=[...Array(12).keys()].map(m=>month_profile_price(m+1))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":654,"value":"pdc_saturday=pdc('saturday')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":652,"value":"pdc_standard_evening=pdc('standard_evening')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":649,"value":"pdc_off_morning=pdc('off_morning')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":623,"value":"pdc= function(param) {\n let out={}\n let prices=daily_differentials.filter(v=>v[param] && v.lux_date.year>2018).sort((a,b)=>a[param]-b[param])\n out=prices.map((d,i)=>{\n return {\n exceedance: 1-(i/prices.length),\n price: d[param]\n }\n })\n return out\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":402,"value":"function month_profile_price(month_no) {\n return d3.rollup(calmonthly_hours.filter(m=>m.month==month_no),v=>d3.mean(v,m=>m.price),t=>t.hour)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":404,"value":"calmonthly_hours = {\n const raw = (await d3.csv(base_url + market_ref + \"_calmonthly_hours.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":359,"value":"reg_standard_evening = {\n let ret = {\n xs: monthly.map(d=>d.standard_price_mean),\n ys: monthly.map(d=>d.evening_price_mean)\n }\n ret.ds = ret.xs.map((x, i) => [x, ret.ys[i]])\n ret.linearRegression = ss.linearRegression(ret.ds)\n ret.linearRegressionLine = ss.linearRegressionLine(ret.linearRegression)\n ret.rsquared = ss.rSquared(ret.ds, ret.linearRegressionLine)\n return ret\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":356,"value":"reg_off_morning = {\n let ret = {\n xs: monthly.map(d=>d.off_price_mean),\n ys: monthly.map(d=>d.morning_price_mean)\n }\n ret.ds = ret.xs.map((x, i) => [x, ret.ys[i]])\n ret.linearRegression = ss.linearRegression(ret.ds)\n ret.linearRegressionLine = ss.linearRegressionLine(ret.linearRegression)\n ret.rsquared = ss.rSquared(ret.ds, ret.linearRegressionLine)\n return ret\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":208,"value":"means_expanding = {\n return yearly_differentials.map(v => { return {\n year: v.year, \n standard_evening: d3.mean(yearly_differentials.filter(m => m.year >= v.year), y => y.standard_evening), \n off_morning: d3.mean(yearly_differentials.filter(m => m.year >= v.year), y => y.off_morning), \n saturday: d3.mean(yearly_differentials.filter(m => m.year >= v.year), y => y.saturday),\n\n standard_evening_pct: d3.mean(yearly_differentials.filter(m => m.year >= v.year), y => y.standard_evening_pct), \n off_morning_pct: d3.mean(yearly_differentials.filter(m => m.year >= v.year), y => y.off_morning_pct), \n saturday_pct: d3.mean(yearly_differentials.filter(m => m.year >= v.year), y => y.saturday_pct)}})\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":130,"value":"reg = {\n let ret = {\n xs: monthly_differentials.filter(v=>v.year>2010).map(d=>d.standard_evening),\n ys: monthly_differentials.filter(v=>v.year>2010).map(d=>d.off_morning)\n }\n ret.ds = ret.xs.map((x, i) => [x, ret.ys[i]])\n ret.linearRegression = ss.linearRegression(ret.ds)\n ret.linearRegressionLine = ss.linearRegressionLine(ret.linearRegression)\n ret.rsquared = ss.rSquared(ret.ds, ret.linearRegressionLine)\n return ret\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":177,"value":"calmonthly_differentials = {\n let ret = d3.rollups(monthly_differentials, v => { return { \n month: v[0].month,\n off_morning: d3.mean(v, m=>m.off_morning),\n standard_evening: d3.mean(v, m=>m.standard_evening),\n saturday: d3.mean(v, m=>m.saturday)\n \n } }, v => v.month )\n\n return ret.map(v=>v[1])\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":166,"value":"yearly_differentials={\n let ret = d3.rollups(monthly_differentials, v => { return { \n lux_date: DateTime.fromObject({year: v[0].year, month: 7}),\n year: v[0].year,\n off_morning: d3.mean(v, m=>m.off_morning),\n standard_evening: d3.mean(v, m=>m.standard_evening),\n saturday: d3.mean(v, m=>m.saturday),\n off_morning_pct: d3.mean(v, m=>m.off_morning_pct),\n standard_evening_pct: d3.mean(v, m=>m.standard_evening_pct),\n saturday_pct: d3.mean(v, m=>m.saturday_pct) \n } }, v => DateTime.fromObject({year: v.year}) )\n\n return ret.map(v=>v[1])\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":87,"value":"$40","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":70,"value":"daily_differentials = {\n return daily.map(d => {\n let ret = {\n year: d.year,\n month: d.month,\n day: d.day,\n lux_date: d.lux_date,\n day_of_week: d.lux_date.weekday\n }\n if (d.lux_date.weekday<6) {\n ret.off_morning = d.morning_price_mean - d.off_price_mean\n ret.off_morning_pct = d.morning_price_mean / d.off_price_mean\n ret.standard_evening = d.evening_price_mean - d.standard_price_mean\n ret.standard_evening_pct = d.evening_price_mean / d.standard_price_mean\n } else {\n if (d.lux_date.weekday === 6) {\n ret.saturday = d.standard_price_mean - d.off_price_mean\n ret.saturday_pct = d.standard_price_mean / d.off_price_mean \n }\n }\n return ret\n })\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":430,"value":"selected_cats2 = [\"Evening\", \"Morning\", \"Standard\", \"Off-peak\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":64,"value":"daily = {\n const raw = (await d3.csv(base_url + market_ref + \"_daily.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n raw.forEach(r=>{\n r.lux_date=DateTime.fromObject({year: r.year, month: r.month, day: r.day})\n r.date=r.lux_date.toJSDate()\n }) \n return raw.filter(v=>v.year>2010)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":60,"value":"monthly = {\n const raw = (await d3.csv(base_url + market_ref + \"_monthly.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n raw.map(r=>{\n r.lux_date=DateTime.fromObject({year: r.year, month: r.month, day: 1, hour: 0, zone: 0})\n r.date=r.lux_date.toJSDate()\n })\n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":58,"value":"years_range= [monthly[0].lux_date.plus({month:-0.5}).toJSDate(),monthly[monthly.length-1].lux_date.plus({month:0.5}).toJSDate()]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":51,"value":"month_names={\n return {\n 0:'Jan',\n 1:'Feb',\n 2:'Mar',\n 3:'Apr',\n 4:'May',\n 5:'Jun',\n 6:'Jul',\n 7:'Aug',\n 8:'Sep',\n 9:'Oct',\n 10:'Nov',\n 11:'Dec',\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":48,"value":"month_dict={\n return {\n 'Jan':{index: 0, group: 1},\n 'Feb':{index: 1, group: 1},\n 'Mar':{index: 2, group: 6},\n 'Apr':{index: 3, group: 6},\n 'May':{index: 4, group: 2},\n 'Jun':{index: 5, group: 2},\n 'Jul':{index: 6, group: 3},\n 'Aug':{index: 7, group: 3},\n 'Sep':{index: 8, group: 4},\n 'Oct':{index: 9, group: 4},\n 'Nov':{index: 10, group: 4},\n 'Dec':{index: 11, group: 1},\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":44,"value":"timeofday = {\n const raw = (await d3.csv(base_url + market_ref + \"_timeofday.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":42,"value":"timeofday_flat={\n let o=[]\n timeofday.forEach(t=>{\n [...Array(24).keys()].forEach((h,i)=>{\n o.push({month: t.month, hour: i, dayofweek: t.dayofweek, cat: t[i]}) \n })\n })\n return o\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":39,"value":"cats = {\n return {\n evening: { index: 3, name: 'Evening', ref: 'evening', long_name: 'Evening Peak'}, \n morning: { index: 1, name: 'Morning', ref: 'morning', long_name: 'Morning Peak'}, \n standard: {index: 2, name: 'Standard', ref: 'standard', long_name: 'Daytime Standard'},\n off: {index: 0, name: 'Off-peak', ref: 'off', long_name: 'Night Off-peak'}, \n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":36,"value":"base_url='https://data.africanpowerprojects.com/sapp/output/'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":33,"value":"market_ref='dam'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":26,"value":"function catCol(index) {\n return d3.schemeCategory10[index]\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":150,"value":"make_trans=function(col,opacity) {\n let c=d3.color(col)\n c.opacity=opacity\n return c.formatRgb()\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":66,"value":"function movingAverage(values, N) {\n let i = 0;\n let sum = 0;\n const means = new Float64Array(values.length).fill(NaN);\n for (let n = Math.min(N - 1, values.length); i < n; ++i) {\n sum += values[i];\n }\n for (let n = values.length; i < n; ++i) {\n sum += values[i];\n means[i - Math.floor(N / 2)] = sum / N;\n sum -= values[i - N + 1];\n }\n return means;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":28,"value":"font = ({\n family: 'Courier New, monospace',\n size: 13,\n color: '#6f6f6f'\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":122,"value":"ss = require('simple-statistics')","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":23,"value":"d3 = require(\"d3@6\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":20,"value":"plt = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":16,"value":"html`\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":13,"value":"style=html`css `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":7,"value":"DateTime = luxon.DateTime","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"},{"id":9,"value":"luxon = require(\"luxon@1/build/amd/luxon.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","providerMetadata":"$undefined","attachments":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W41","stdlib":"1"}} 31:"$30:body"