31:T13f6,{ const wdth = 1050 const height = wdth * 0.75 let scle = 1 const rW=140 const rH=100 const m=6 const f=16 if (width>650) { scle = 650/width } let sapp_filtered=sapp.features.filter(s=>flows_by_node.get(s.properties.ref)) let totalExtent=[d3.min(Array.from(flows_by_node),f=>f[1][2]), d3.max(Array.from(flows_by_node),f=>f[1][2])] let min=totalExtent[0] let max=totalExtent[1] const svg = d3 .create("svg") .attr("viewBox", [0, 0, wdth, height]) //.style('background-color','#fbfbfb') .style("width", d3.format('.0%')(scle)) .style("height", "auto"); var cSupply = d3.scaleSequential().domain([min,0]) .interpolator(d3.interpolateLab(sideCol(2), "#CCC")) var cConsume = d3.scaleSequential().domain([0,max]) .interpolator(d3.interpolateLab("#CCC", sideCol(5))) /* svg.append('rect') .attr('x', 0) .attr('y', 0) .attr('width', wdth) .attr('height', height) .attr('stroke', 'black') .attr('fill', 'none'); */ svg.append("g") .selectAll("path") .data(sapp.features) .join("path") .attr('stroke', '#AAA') .attr('stroke-width', '1.5') .attr('fill-opacity', '0.5') .attr("fill", d=>{ let m=flows_by_node.get(d.properties.ref) if (m) { return m[2]<0 ? cSupply(m[2]) : cConsume(m[2]) } else { return '#CCC' } }) .attr("d", projection); function make_text(parent,fX, fY, fT,bold) { parent.append("g") .attr("font-family", "sans-serif") .attr("font-size", f) .attr("fill", "#555") .attr("font-weight", bold ? 'bold' : '') .attr("stroke-linecap", "round") .attr("stroke-linejoin", "round") .attr("text-anchor", "left") .selectAll("text") .data(sapp_filtered) .join("text") .text(fT) .attr("x", fX) .attr("y", fY) } function fnX() { return (d => projection.centroid(d.geometry)[0] + node_dict[d.properties.ref].offset[0]-rW/2+m) } function fnY(line, off) { return (d => projection.centroid(d.geometry)[1] + node_dict[d.properties.ref].offset[1]-rH/2+m+f/2+3 + (f*line) + off) } make_text( svg, fnX(), fnY(0,0), (d => node_dict[d.properties.ref].member), true ) make_text( svg, fnX(), fnY(1,0), (d => node_dict[d.properties.ref].country), false ) make_text( svg, fnX(), fnY(2,2), (d=>{ let m=flows_by_node.get(d.properties.ref) if (m) { return d3.format(',.0f')(Math.abs(m[2])/1000) + ' GWh' } else { return '' } }), false ) make_text( svg, fnX(), fnY(3,2), (d=>{ let m=flows_by_node.get(d.properties.ref) if (m) { return d3.format('$,.2r')(Math.abs(m[1])/1000000) + 'm' } else { return '' } }), false ) svg.append('g') .selectAll("rect") .data(sapp_filtered) .join("rect") .attr("x", d => projection.centroid(d.geometry)[0] + node_dict[d.properties.ref].offset[0]-rW/2) .attr("y", d => projection.centroid(d.geometry)[1] + node_dict[d.properties.ref].offset[1]-rH/2) .attr('width', rW) .attr('height', rH) .attr('stroke', 'steelblue') .attr('stroke-width', '1.5') .attr('fill', 'white') .attr('fill-opacity', '0.3') svg.append('g') .selectAll("polyline") .data(sapp_filtered.filter(d=>node_dict[d.properties.ref].leader)) .join("polyline") .attr("points",d=>`${projection.centroid(d.geometry).join(',')} ${ projection.centroid(d.geometry)[0] + node_dict[d.properties.ref].offset[0] + ( (rW/2) * (node_dict[d.properties.ref].offset[0]<0?1:-1) ) },${ projection.centroid(d.geometry)[1] + node_dict[d.properties.ref].offset[1] }`) .attr('stroke', 'steelblue') .attr('stroke-width', '1.5') addPieChartsToMap(svg,1,rW,rH,m,f) addPieChartsToMap(svg,2,rW,rH,m,f) svg.append("g") .attr("font-family", "sans-serif") .attr("font-size", f - 2) .attr("fill", "grey") .attr("text-anchor", "left") .selectAll("text") .data(sapp_filtered) .join("text") .text('MWh') .attr("x", d=>projection.centroid(d.geometry)[0] + node_dict[d.properties.ref].offset[0]+rW/2 - (f * 2.2)) .attr("y", d => projection.centroid(d.geometry)[1] + node_dict[d.properties.ref].offset[1]+rH/2-3) svg.append("g") .attr("font-family", "sans-serif") .attr("font-size", f - 2) .attr("fill", "grey") .attr("text-anchor", "left") .selectAll("text") .data(sapp_filtered) .join("text") .text('$') .attr("x", d=>projection.centroid(d.geometry)[0] + node_dict[d.properties.ref].offset[0]+rW/2-(f * 0.8)) .attr("y", d => projection.centroid(d.geometry)[1] + node_dict[d.properties.ref].offset[1]+rH/2-85) const div=container('SAPP members and their total net supply (green) or consumption (brown) in GWh through the IDM market from January 2020 to date.') div.prepend(svg.node()) return div }32:T87c,{ let data=[] let selected_nodes=nodes.filter(v=>v.default_show).map(v=>v.ref) let share='mwh' function get_val(p) { if (share=='mwh') { return p.flow_sum/1000 } else { return p.value/1000 } } let flow_nodes= d3.rollup(flow, v=>d3.sum(v,p=>get_val(p)), f=>f.node, f=>f.date, f=>f.flow_sum<0?'supply':'consume') //let flow_total= d3.rollup(flow_filtered, v=>d3.sum(v,p=>get_val(p)), f=>f.date, f=>f.flow_sum<0?'supply':'consume') function series(node_ref) { if (flow_nodes.get(node_ref)) { const nde=Array.from(flow_nodes.get(node_ref)) function series_side (side) { data.push({ y: nde.map((v,i)=>v[1].get(side)), x: nde.map(h=> h[0]), mode: 'lines', marker: {opacity: 0.8,shape:'spline', color: node_dict[node_ref].col, width: 2}, type: 'bar', hoverinfo: 'x,y', showlegend:side=='consume', name: node_dict[node_ref].member }) } series_side('consume') series_side('supply') } } nodes.forEach(n=>{ if (Object.fromEntries(selected_nodes.map(c=>[c,c]))[n.ref]) { series(n.ref) } }) var layout = { height: 350, width: width-30, barmode: 'relative', font: font, showlegend: true, legend: {xanchor: 'left', x:1, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { range:[ monthly[0].lux_date.minus({month:0.5}).toJSDate(), monthly[monthly.length-1].lux_date.plus({month:0.5}).toJSDate() ], showgrid: true, zeroline: false, ticks:'outside' }, yaxis: { title:share=='mwh'?'MWh':'$000s', showgrid: true, zeroline: true, tickformat: '.0f', ticks:'outside' }, annotations: [{ xref: 'paper', yref: 'paper', showarrow: false, x: 0.07, y: 0.35, font: {color: "#555",size: 17}, text: 'Sellers', }, { xref: 'paper', yref: 'paper', showarrow: false, x: 0.07, y: 0.65, font: {color: "#555",size: 17}, text: 'Buyers', }] } const div=container('Supply and consumption participation in the market.') plt.newPlot(div, data, layout,{displayModeBar: false}); return html`${div}` }33:Tbf3,{ let yrly=yearly.slice(0,yearly.length-1) function vol() { var data = [{ y: yrly.map(m=>(m[1].volume/1000)), x: yrly.map(m=>m[0]), text: yrly.map((m,i)=>d3.format(',.3r')(m[1].volume/1000) + ' GWh'), textposition:'auto', marker: {color: '#2980b9', width: 2}, type: 'bar', hoverinfo: 'none', showlegend:false }] var layout = { height: 240, font: font, width:width*.33, showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 65,r: 10,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks:'outside', dtick:1}, yaxis: { title: 'GWh', showgrid: false, zeroline: true, tickformat: ',.0f', ticks:'outside' }}; const div=DOM.element('div') plt.newPlot(div, data, layout,{displayModeBar: false}); return div } function val() { var data = [{ y: yrly.map(m=>(m[1].value/1000000)), x: yrly.map(m=>m[0]), text: yrly.map((m,i)=>d3.format('$,.3r')(m[1].value/1000000) +'m' ), textposition:'auto', marker: {color: '#d68910', width: 2}, type: 'bar', hoverinfo: 'none', showlegend:false }] var layout = { height: 240, width: width*.3, font: font, showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 65,r: 10,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks:'outside', dtick:1}, yaxis: { range:[0,16], title: '$m', showgrid: false, zeroline: true, tickformat: ',.0f', ticks:'outside' }}; const div=DOM.element('div') div.setAttribute('style',`background-color:'red'`) plt.newPlot(div, data, layout,{displayModeBar: false}); return div } function rte() { var data = [{ y: yrly.map(m=>(m[1].rate)), x: yrly.map(m=>m[0]), text: yrly.map((m,i)=>d3.format('$,.3r')(m[1].price_mean) +'/MWh' ), textposition:'auto', marker: {shape:'spline',color: '#16a085'}, type: 'bar', hoverinfo: 'none', showlegend:false }] var layout = { height: 240, width: (width-30)*.33, font: font, showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 65,r: 10,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks:'outside', dtick:1}, yaxis: { range:[0,90], title: '$/MWh', showgrid: false, zeroline: true, tickformat: ',.0f', ticks:'outside' }}; const div=DOM.element('div') div.setAttribute('style',`background-color:'red'`) plt.newPlot(div, data, layout,{displayModeBar: false}); return div } const div=container('Mean annual price, value and volume traded on the SAPP IDM market.') const inner= html`

${rte()}

${val()}

${vol()}

` div.prepend(inner) return div }34:T6a9,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: 50,r: 53,b: 10,t: 0}, xaxis: { rangeslider: {}, range:years_range, showgrid: true, zeroline: false, ticks:'outside', }, yaxis: { title: '$/MWh', range: [0,320], showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container() const form = html`` plt.newPlot(div, data, layout,{displayModeBar: false}); div.on('plotly_relayout', d => { form.dispatchEvent(new CustomEvent("input", { detail: d['xaxis.range'],bubbles: true })); }) form.oninput = (evt) => { form.value = evt.detail; }; form.oninput({detail: [daily[0].date, daily[daily.length-1].date]}) return form; }35:T60f,{ var data = [ { y: daily.map(d=>d.volume/1000), x: daily.map(d=>d.date), mode: 'lines', line: {shape: 'spline', color:'grey', width: 1.5}, type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', }, { y: daily.map(d=>d.volume/24), x: daily.map(d=>d.date), mode: 'lines', line: {shape: 'spline', color:'grey', width: 0.5}, yaxis: 'y2', type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', }, { y: movingAverage(daily.map(d=>d.volume/1000),14), x: daily.map(d=>d.date), mode: 'lines', line: {shape: 'spline', color:d3.schemeCategory10[3], width: 1.5}, type: 'scatter', hoverinfo: 'x,y', showlegend:false,name: '', } ] var layout = { height: 200, width: width-30, font: font, showlegend: true, legend: {xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 50,b: 30,t: 0}, xaxis: { range: dam_range, showgrid: true, zeroline: false, ticks:'outside', }, yaxis: { title: 'GWh/day', range:[0,16], showgrid: false, zeroline: false, tickformat: '.0f', ticks:'outside' }, yaxis2: { title:'MW', range:[0,16000/24], overlaying: 'y', side: 'right' } }; const div=container('SAPP IDM weighted average daily price (top) and daily volume and equivalent power (bottom). 14 day moving average in red. Blue area is the daily maximum and minimum prices.') plt.newPlot(div, data, layout,{displayModeBar: false}); return html`${div}` }36:T4c0,{ var data = [] data.push({ y: monthly.map(m=>m['price_mean']), x: monthly.map(m=>m['date']), mode: 'lines+markers', line: {color: 'black', width: 2}, marker:{size:5}, type: 'scatter', hoverinfo: 'x+y', showlegend:true, name:'Average price' }) data.push({ y: yearly.map(m=>m[1].price_mean), text: yearly.map(m=>'$' + d3.format('.0f')(m[1].price_mean) + '/MWh'), textposition:'top-left', x: yearly.map(m=>DateTime.fromObject({year: m[0], month: 6, day: 15}).toJSDate()), mode: 'markers+text', line: {color: 'red', width: 2}, marker:{size:10}, type: 'scatter', hoverinfo: 'text', showlegend:false }) var layout = { height: 270, width: width-30, font: font, showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks:'outside',showspikes: false, range:years_range }, yaxis: {title: '$/MWh',showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside'} }; const div=container('Monthly and annual average market price.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }37:T6a2,{ function priceChart() { let ymax=d3.max(selected_hours,h=>h.price)*1.1 var data = [] days.forEach(d=>{ if (d.weekday==6) { data.push({ x:[d.toJSDate(),d.endOf('day').toJSDate()],showlegend:false, y:[ymax,ymax], fillcolor:make_trans('#f4a4a4',0.3), line: {width:0},mode:'lines', fill:'tozeroy', hoverinfo:'none' }) } if (d.weekday==7) { data.push({ x:[d.toJSDate(),d.endOf('day').toJSDate()],showlegend:false, y:[ymax,ymax], fillcolor:make_trans('#f4a4a4',0.5), line: {width:0},mode:'lines', fill:'tozeroy', hoverinfo:'none' }) } }) data.push({ y: selected_hours.map(h=>h.price), x: selected_hours.map(h=>h.date), mode: 'lines', line: {color:'#555', width: 1.4}, type: 'scatter', hoverinfo: 'x,y', showlegend:false,name: '', }) var layout = { height: 270, width: width-30, font: font, showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { range: [selected_hours[0].date,selected_hours[selected_hours.length-1].date], showgrid: true, zeroline: false, ticks:'outside' }, yaxis: { range:[0,ymax], title: '$/MWh', showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=DOM.element('div') plt.newPlot(div, data, layout,{displayModeBar: false}); return div } const div=container('A representative hourly price pattern during the first half of Aug 2022. Weekends are highlighted.') div.prepend(priceChart()) return div }38:T5d4,{ function priceChart() { var data = [] data.push({ y: selected_hours.map(h=>h.price/d3.max(daily.filter(d=>d.year==month.year && d.month==month.month),v=>v.price_max)), x: selected_hours.map(h=>h.date), mode: 'lines', line: {color:'#555', width: 1.5}, type: 'scatter', hoverinfo: 'x', showlegend:true,name: 'Price % of Monthly Max', }) data.push({ y: selected_hours.map(h=>h.volume/d3.max(daily.filter(d=>d.year==month.year && d.month==month.month),v=>v.power_max)), x: selected_hours.map(h=>h.date), marker: {color:make_trans(d3.schemeDark2[1],0.6)}, line: {width: 0}, type: 'bar', hoverinfo: 'x', showlegend:true,name: 'Volume % of Monthly Max', }) var layout = { height: 270, width: width-30, font: font, showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.2}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { range: [selected_hours[0].date,selected_hours[selected_hours.length-1].date], showgrid: true, zeroline: false, ticks:'outside' }, yaxis: { title: '', showgrid: true, zeroline: false, tickformat: '%.0f', ticks:'outside' } }; const div=DOM.element('div') plt.newPlot(div, data, layout,{displayModeBar: false}); return div } const div=container('Hourly price and volume relative to the monthly max during the first half of July 2018.') div.prepend(priceChart()) return div }39:T70e,{ function yr(ref) { const annual_price=d3.rollups(monthly.filter(m=>m.year<2022),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: 300, 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 average prices for each time-of-day category and overall market volume weighted average price.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }3a:T619,{ function series(ref) { return [{ y: monthly.map(m=>m[ref + '_price_mean'] + m[ref + '_price_stdev']).concat(monthly.map(m=>m[ref + '_price_mean'] - m[ref + '_price_stdev']).reverse()), x: monthly.map(m=>m['date']).concat(monthly.filter(m=>m[ref + '_price_max']).map(m=>m['date']).reverse()), mode: 'lines', line: {shape:'spline',color: catCol(cats[ref].index), width: 1}, fill:'toself', type: 'scatter', hoverinfo: 'none', name: cats[ref].name, }, { y: monthly.map(m=>m[ref + '_price_mean']), x: monthly.map(m=>m['date']), mode: 'lines', line: {shape:'spline',color: catCol(cats[ref].index), width: 1}, fill:'', type: 'scatter', hoverinfo: 'x,y', name: cats[ref].name, showlegend:false, }, ] } var data = [] Object.values(cats).forEach(c=>{ if (Object.fromEntries(selected_cats2.map(c=>[c,c]))[c.name]) { data=data.concat(series(c.ref)) } }) var layout = { height: 270, width: width-30, font: font, showlegend: true, legend: {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: { range:[0,360], title: '$/MWh', showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('Monthly average prices and Bollinger bands (+ and - 1 standard deviation) by time-of-day categories.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }3b:T597,{ function series(ref) { return { y: calmonthly.map(v=>v[ref + '_price_mean']), x: ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], mode: 'lines', line: {shape: 'spline', color: catCol(cats[ref].index), width:3}, fill:'', type: 'scatter', hoverinfo: 'x,y', name: cats[ref].name, } } function series2(ref) { return { y: calmonthly.map(v=>v[ref + '_price_median']), x: ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], mode: 'lines', line: {shape: 'spline', color: catCol(cats[ref].index), width:3}, fill:'', type: 'scatter', hoverinfo: 'x,y', name: cats[ref].long_name, showlegend: false, } } var data = [ series('off'), series('morning'), series('standard'), series('evening'), ] var layout = { height: 270, width: width-30, font: font, showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks:'outside', range: [-0.1,11.1] }, yaxis: { range:[0,220], title: `$/MWh`, showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('Mean price by calendar month for each time-of-day category.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }3c:T4a7,{ function chart(ref) { var data = [{ x: daily.map(d => d[ref + '_price_mean']), marker: {color: catCol(cats[ref].index), opacity:0.8}, type: 'histogram', hoverinfo: 'none', showlegend:false }] var layout = { height: 200, font: font, width:(width-40)*.25, showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 55,r: 5,b: 50,t: 0}, xaxis: {range:[0,300], showgrid: true, zeroline: false, ticks:'outside', title: '$/MWh'}, 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 prices for each time-of-day category.') let inner = html`

${chart('off')}

${chart('morning')}

${chart('standard')}

${chart('evening')}

` div.prepend(inner) return div }3d:T6fa,{ function series(ref) { let p90 = pdcs[ref][Math.floor(pdcs[ref].length*0.1)] let p50 = pdcs[ref][Math.floor(pdcs[ref].length*0.5)] return [{ y: pdcs[ref].map(v=>v.price), x: pdcs[ref].map(v=>v.exceedance), mode: 'lines', line: {shape: 'spline', color: catCol(cats[ref].index), width:3}, fill:'', type: 'scatter', hoverinfo: 'x,y', name: cats[ref].name, }, { y: [p90.price], x: [p90.exceedance], text: [d3.format('$.0f')(p90.price)], mode: 'markers+text', marker: {color: catCol(cats[ref].index), size:10}, textposition:'top-right', type: 'scatter', hoverinfo: 'none', name: cats[ref].name, showlegend:false }, { y: [p50.price], x: [p50.exceedance], text: [d3.format('$.0f')(p50.price)], mode: 'markers+text', marker: {color: catCol(cats[ref].index), size:10}, textposition:'top-right', type: 'scatter', hoverinfo: 'none', name: cats[ref].name, showlegend:false } ] } var data = [] data=data.concat(series('off')) data=data.concat(series('morning')) data=data.concat(series('standard')) data=data.concat(series('evening')) 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('Price exceedance curves by time-of-day category. Median (P50) and P90 prices highlighted.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }3e:T4e1,{ function series(ref) { return { y: monthly.map(v=>v[ref + '_volume']/1000), x: monthly.map(h=> h.date), mode: 'lines', marker: {color: make_trans(catCol(cats[ref].index),0.7), width:1}, fill:'tonexty', type: 'bar', hoverinfo: 'x,y', name: cats[ref].name, stackgroup: 'one', } } var data = [ series('evening'), series('morning'), series('standard'), series('off'), { y: monthly.map(v=>v['volume']/1000), x: monthly.map(h=> h.date), mode: 'lines', line: {shape: 'spline', color: 'grey', width:2}, type: 'scatter', hoverinfo: 'x,y', name: 'Total', showlegend:false, } ] var layout = { height: 270, width: width-30, font: font, barmode: 'stack', showlegend: true, legend: {xanchor: 'right', x:1, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { range:years_range, showgrid: true, zeroline: false, ticks:'outside', }, yaxis: { range:[0,60], title: `GWh`, showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('Mean monthlhy volumes, total and by time of day.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }3f:T53d,{ function series(ref) { return [ { y: monthly.filter(m=>m[ref + '_power']).map(m=>m[ref + '_power']), x: monthly.filter(m=>m[ref + '_power']).map(m=>m['date']), mode: 'lines', line: {shape:'spline',color: catCol(cats[ref].index), width: 2}, fill:'', type: 'scatter', hoverinfo: 'x,y', name: cats[ref].name, showlegend:true, }, ] } var data = [] Object.values(cats).forEach(c=>{ data=data.concat(series(c.ref)) }) data.push( { y: monthly.map(m=>m.volume/24/31), x: monthly.map(m=>m.date), mode: 'lines', line: {shape:'spline',color: 'black', width: 3}, fill:'', type: 'scatter', hoverinfo: 'x,y', name: '', showlegend:false, }) 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: { range: [0,110], title: 'MW', showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('Power traded on the market for each time-of-day category and the overall market average.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }40:T580,{ let value_total= Array.from(d3.rollup(flow.filter(f=>f.side=='consume'), v=>d3.sum(v,p=>p.value), f=>f.date)) function series(ref) { return { y: monthly.map(v=>v[ref + '_value']/1000000), x: monthly.map(h=> h.date), mode: 'lines', marker: {shape: 'spline', color: make_trans(catCol(cats[ref].index),0.7), width:1}, fill:'tonexty', type: 'bar', hoverinfo: 'x,y', name: cats[ref].name, stackgroup: 'one', } } var data = [ series('evening'), series('morning'), series('standard'), series('off'), { y: monthly.map(v=>v['value']/1000000), x: monthly.map(h=> h.date), mode: 'lines', line: {shape: 'spline', color: 'grey', width:2}, type: 'scatter', hoverinfo: 'x,y', name: 'Total', showlegend:false, }, ] var layout = { height: 270, width: width-30, font: font, barmode:'stack', showlegend: true, legend: {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: `$m`, showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside' } }; const div=container('Value of energy traded on the market for each time-of-day category and the overall total value.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }41:T43b,{ function series(ref) { return { y: calmonthly.map(v=>v[ref + '_power']/(d3.mean(calmonthly.map(v=>v[ref + '_power'])))-1), x: ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], mode: 'lines', line: {shape: 'spline', color: catCol(cats[ref].index), width:3}, fill:'', type: 'scatter', hoverinfo: 'x,y', name: cats[ref].long_name, } } var data = [ series('off'), series('morning'), series('evening'), series('standard'), ] var layout = { height: 270, width: width-30, font: font, showlegend: true, legend: {xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks:'outside', range: [-0.1,11.1] }, yaxis: { title: ``, showgrid: true, zeroline: true, tickformat: '.0%', ticks:'outside' } }; const div=container('Variation in power relative to the mean annual power for each time-of-day category.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }42:T536,{ function series(ref) { return { y: calmonthly.map(v=>v[ref + '_value']/1000000), x: ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], marker: {color: make_trans(catCol(cats[ref].index),0.8), width:1}, type: 'bar', hoverinfo: 'x,y', name: cats[ref].name, } } var data = [ series('evening'), series('morning'), series('standard'), series('off'), { y: calmonthly.map(v=>v['value']/1000000), x: ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], mode: 'lines', line: {shape: 'spline', color: 'grey', width:2}, type: 'scatter', hoverinfo: 'x,y', name: 'Total', showlegend:false, } ] var layout = { height: 270, width: width-30, font: font, barmode:'stack', showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { showticklabels:true, showgrid: true, zeroline: false, ticks:'outside', }, yaxis: { range:[0,3], title: `$m`, showgrid: true, zeroline: false, tickformat: ',.1f', ticks:'outside' }, }; const div=container('Mean market value by calendar month for each time-of-day category.') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }43:T450,addPieChartsToMap = function(map,index, rW, rH, m, f) { // Create segments for each region sapp.features.forEach(feat => { let flw=flows_by_node.get(feat.properties.ref) if (flw) { const rad=f function fnX(d) { return projection.centroid(d.geometry)[0] + node_dict[d.properties.ref].offset[0]+rW/2-rad-m } function fnY(d) { return projection.centroid(d.geometry)[1] + node_dict[d.properties.ref].offset[1]+rH/2-rad-m - (index==1?(rad*2 + m):0) - (f/2)-1 } let x = fnX(feat) let y = fnY(feat) let arcs = pie([Math.abs(flw[index]),flows_total.get('consume')[index]-Math.abs(flw[index])]) map .append('g') .attr("transform", "translate(" + x + "," + y + ")") .attr('stroke', 'grey') .selectAll('path') .data(arcs) .join('path') .attr('fill', (d,i)=> [flw[index]>0 ? sideCol(5):sideCol(2),'white'][i]) .attr('fill-opacity', (d,i)=> [1,0][i]) .attr("d", d3 .arc() .innerRadius(0) .outerRadius(rad)) } }); }44:[{"id":"f97fdeb7341d3f752a7271f84a46608de7c558c00d96c577adeee0965b8603a8c97870615569a9fa16d0c6fa12d7e7b4892657bad77501f966f08b8e13e8e6b9","href":"https://static.observableusercontent.com/files/f97fdeb7341d3f752a7271f84a46608de7c558c00d96c577adeee0965b8603a8c97870615569a9fa16d0c6fa12d7e7b4892657bad77501f966f08b8e13e8e6b9","name":"APP logo.png","type":"image/png","lastModified":1661953802485.277,"size":92844},{"id":"057ef0b5dd0e520a9be2a77bad99a70d2f85fdd133ca99dc821899e6ac74130d84d5eb7a818867487c356c8b893dbf6d256953734722a765b4719da9e513de10","href":"https://static.observableusercontent.com/files/057ef0b5dd0e520a9be2a77bad99a70d2f85fdd133ca99dc821899e6ac74130d84d5eb7a818867487c356c8b893dbf6d256953734722a765b4719da9e513de10","name":"sapp.json","type":"application/json","lastModified":1661953802485.277,"size":55475}] 2f:{"title":"Intra-day Market (IDM)","cells":[{"id":0,"value":"md`# Intra-day Market (IDM)`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4173,"value":"

\n The Southern African Power Pool (SAPP) was created in August 1995. SAPP has seventeen members from twelve member countries including national utilities, transmission companies and independent generators. SAPP established the Short-Term Energy Market in April 2001. From January 2004, SAPP started the development of a competitive electricity market for the SADC region.\n

\n
\nThe Day-ahead Market (DAM) matches buyers and sellers in hourly intervals for settlement the following day. The DAM has historically been the largest SAPP market accounting for at least 50% of total turnover. \n

\n\n

","pinned":false,"hidden":false,"mode":"html"},{"id":5424,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":5456,"value":"Mozambique (EDM and HCB) and Eskom dominate the supply and NamPower, BPC and CEC dominate the consumption.","pinned":false,"hidden":false,"mode":"html"},{"id":5482,"value":"{\n const form = html`\n `\n \n const div=container()\n div.prepend(form)\n return div \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":5474,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":3571,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":4224,"value":"html`\n

Price and Volume

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1924,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":2427,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":4994,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":4232,"value":"html`\n

Intra-day Price Patterns

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4312,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":4344,"value":"$38","pinned":false,"hidden":false,"mode":"ojs"},{"id":5627,"value":"In general there is an inverse relationship between hourly price and volume on the market and the daily pattern of peak and off-peak prices is also apparent in the hourly volumes traded with higher prices producing to lower volumes and lower prices leading to higher volumes. ","pinned":false,"hidden":false,"mode":"html"},{"id":1854,"value":"viewof selected_months = {\n const form = html`\n `\n\n form.oninput = () => {\n form.value = Array.prototype.filter\n .call(form.input, i => i.checked)\n .map(i => i.value)\n }\n form.oninput()\n return form\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1064,"value":"{ \n let data = selected_months.map((m, i)=>{\n const ser = month_profiles[month_dict[m].index]\n return {\n y: [...Array(24).keys()].map(h=>ser.get(h)),\n mode: 'lines', line: {shape: 'spline', color: d3.schemeDark2[month_dict[m].group], width:3}, fill:'',\n type: 'scatter', hoverinfo: 'x,y', name: m,\n }\n })\n \n var layout = {\n height: 260, width: width-30,\n font: font, \n showlegend: true, legend: {xanchor: 'left', x:1,y: 1},\n margin: {l: 50,r: 5,b: 30,t: 0},\n xaxis: {\n title: '',\n showgrid: true, zeroline: false, dtick: 1, ticks:'outside',\n },\n yaxis: {\n range: [20,170],\n title: `$/MWh`,\n showgrid: false, zeroline: false, tickformat: '.0f', ticks:'outside'\n }\n };\n\n const div=container('Mean price by time-of-day for selected months.')\n plt.newPlot(div, data, layout,{displayModeBar: false});\n return div\n \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":5660,"value":"{ \n function ser(no, col) {\n return yearly_month_profiles.map((y,i)=>{\n const ser = y.profile[no]\n return {\n y: ser,\n mode: 'lines', line: {shape: 'spline', color: make_trans(col,(i+2)/10), width:3}, fill:'',\n type: 'scatter', hoverinfo: 'x,y', name: y.year,\n }\n })\n }\n let data = []\n data=data.concat(ser(7,'black'))\n \n var layout = {\n height: 260, 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: [20,260],\n title: `$/MWh`,\n showgrid: false, zeroline: false, tickformat: '.0f', ticks:'outside'\n }\n };\n\n const div=container('Mean price by time-of-day for each August since 2016.')\n plt.newPlot(div, data, layout,{displayModeBar: false});\n return div\n \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4247,"value":"html`\n

Time-of-day prices

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3001,"value":"$39","pinned":false,"hidden":false,"mode":"ojs"},{"id":4740,"value":"html`\n

Volatility

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4730,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs"},{"id":4253,"value":"html`\n

Price seasonality

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2262,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs"},{"id":4861,"value":"html`\n

Price distribution

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4808,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs"},{"id":4758,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs"},{"id":4260,"value":"html`\n

Market volume and traded power

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":280,"value":"$3e","pinned":false,"hidden":false,"mode":"ojs"},{"id":789,"value":"{ \n\n function series(ref) {\n\n return {\n y: monthly.map((v,i)=>v[ref + '_volume']/v['volume']),\n x: monthly.map(h=> h.date), \n mode: 'lines', line: {shape: 'spline',color:catCol(cats[ref].index), width:1}, fill:'tonexty',\n type: 'scatter', hoverinfo: 'x,y', name: cats[ref].name, stackgroup: 'one',\n } \n }\n \n var data = [\n series('evening'),\n series('morning'), \n series('standard'),\n series('off'),\n ]\n \n var layout = {\n height: 230, width: width-30,\n font: font, \n showlegend: false, legend: {xanchor: 'left', x:0, y: 1},\n margin: {l: 50,r: 5,b: 30,t: 0},\n xaxis: {\n range:years_range,\n showgrid: true, zeroline: false, ticks:'outside',\n },\n yaxis: {\n title: 'GWh %',\n showgrid: true, zeroline: false, tickformat: '.0%', ticks:'outside'\n }\n };\n\n const div=container('Proportion of traded volume by time-of-day categories.')\n plt.newPlot(div, data, layout,{displayModeBar: false});\n return div\n \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2227,"value":"$3f","pinned":false,"hidden":false,"mode":"ojs"},{"id":4281,"value":"html`\n

Market value

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":3454,"value":"$40","pinned":false,"hidden":false,"mode":"ojs"},{"id":5851,"value":"{ \n\n function series(ref) {\n\n return {\n y: monthly.map((v,i)=>v[ref + '_value']/v['value']),\n x: monthly.map(h=> h.date), \n mode: 'lines', line: {shape: 'spline',color:catCol(cats[ref].index), width:1}, fill:'tonexty',\n type: 'scatter', hoverinfo: 'x,y', name: cats[ref].name, stackgroup: 'one',\n } \n }\n \n var data = [\n series('evening'),\n series('morning'), \n series('standard'),\n series('off'),\n ]\n \n var layout = {\n height: 230, width: width-30,\n font: font, \n showlegend: false, legend: {xanchor: 'left', x:0, y: 1},\n margin: {l: 50,r: 5,b: 30,t: 0},\n xaxis: {\n range:years_range,\n showgrid: true, zeroline: false, ticks:'outside',\n },\n yaxis: {\n title: '',\n showgrid: true, zeroline: false, tickformat: '.0%', ticks:'outside'\n }\n };\n\n const div=container('Proportion of traded value by time-of-day categories.')\n plt.newPlot(div, data, layout,{displayModeBar: false});\n return div\n \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4256,"value":"html`\n

Volume, power and value seasonality

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4647,"value":"{ \n function series(ref) {\n return {\n y: calmonthly.map(v=>v[ref + '_power']),\n x: ['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'],\n mode: 'lines', line: {shape: 'spline', color: catCol(cats[ref].index), width:3}, fill:'',\n type: 'scatter', hoverinfo: 'x,y', name: cats[ref].long_name,\n } \n }\n \n var data = [\n series('off'),\n series('morning'), \n series('standard'),\n series('evening'),\n ]\n \n var layout = {\n height: 270, width: width-30,\n font: font, \n showlegend: true, legend: {orientation:'v',xanchor: 'left', x:0, y: 1},\n margin: {l: 50,r: 5,b: 30,t: 0},\n xaxis: {\n showgrid: true, zeroline: false, ticks:'outside', range: [-0.1,11.1]\n },\n yaxis: {\n title: `MW`,\n showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside'\n }\n };\n\n const div=container('Mean power by calendar month and time-of-day category.')\n plt.newPlot(div, data, layout,{displayModeBar: false});\n return div\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4656,"value":"$41","pinned":false,"hidden":false,"mode":"ojs"},{"id":2818,"value":"{ \n \n let data = selected_months3.map((m, i)=>{\n const ser = month_profiles_volume[month_dict[m].index]\n return {\n y: [...Array(24).keys()].map(h=>ser.get(h)),\n mode: 'lines', line: {shape: 'spline', color: d3.schemeCategory10[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:[0,85],\n title: `MW`,\n showgrid: false, zeroline: false, tickformat: '.0f', ticks:'outside'\n }\n }\n\n const div=container('Daily power profiles for selected months.')\n plt.newPlot(div, data, layout, {displayModeBar: false});\n return div\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3480,"value":"$42","pinned":false,"hidden":false,"mode":"ojs"},{"id":5412,"value":"

\n

Setup

","pinned":false,"hidden":false,"mode":"html"},{"id":5882,"value":"selected_months3=[\"Mar\", \"Jun\", \"Oct\", \"Dec\"]","pinned":false,"hidden":false,"mode":"ojs"},{"id":5713,"value":"import {differentials_chart} from \"@andyflem/sapp-dam-time-of-day-arbitrage-analysis\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":5705,"value":"selected_cats2=[\"Evening\", \"Morning\", \"Standard\", \"Off-peak\"]","pinned":false,"hidden":false,"mode":"ojs"},{"id":5568,"value":"solcol='#d68910'","pinned":false,"hidden":false,"mode":"ojs"},{"id":5438,"value":"pie = d3\n .pie()\n .sort(null)\n .value(d => d)","pinned":false,"hidden":false,"mode":"ojs"},{"id":5445,"value":" projection=d3.geoPath(d3.geoEquirectangular().center([25,-14]).scale(1300))","pinned":false,"hidden":false,"mode":"ojs"},{"id":5443,"value":"$43","pinned":false,"hidden":false,"mode":"ojs"},{"id":5415,"value":"container = function(captionText) {\n const div=DOM.element('div')\n div.setAttribute(\"class\",\"border m-2 p-2\")\n if (captionText) {\n const caption=DOM.element('figcaption')\n caption.append(captionText)\n div.append(caption)\n }\n return div\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3972,"value":"countries={\n return {\n 'Botswana': {ref: 'BOT', country: 'Botswana', col: 1},\n 'Mozambique': {ref: 'MOZ', country: 'Mozambique', col: 2},\n 'Namibia': {ref: 'NAM', country: 'Namibia', col: 3},\n 'South Africa': {ref: 'RSA', country: 'South Africa',col:7 },\n 'Zambia': {ref: 'ZAM', country: 'Zambia', col: 5},\n 'Zimbabwe': {ref: 'ZIM', country: 'Zimbabwe', col: 4},\n 'Lesotho': {ref: 'LES', country: 'Lesotho', col: 8},\n 'Swaziland': {ref: 'ESW', country: 'Swaziland', col: 9},\n 'DRC': {ref: 'DRC', country: 'DRC', col: 9},\n 'Tanzania': {ref: 'TNZ', country: 'Tanzania', col: 3},\n 'Malawi': {ref: 'MAL', country: 'Malawi', col: 6},\n 'Angola': {ref: 'ANG', country: 'Angola', col: 2},\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":5466,"value":"import {nodes} from \"@andyflem/day-ahead-market-dam-market-participants\"","pinned":false,"hidden":false,"mode":"ojs"},{"id":3927,"value":"sapp=topojson.feature(sapptopo, sapptopo.objects.sapp)","pinned":false,"hidden":false,"mode":"ojs"},{"id":3798,"value":"sapptopo=FileAttachment(\"sapp.json\").json()","pinned":false,"hidden":false,"mode":"ojs"},{"id":3929,"value":"topojson = require('topojson')","pinned":false,"hidden":false,"mode":"ojs"},{"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"},{"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"},{"id":4377,"value":"cats_means={\n return [\n ['off', d3.mean(monthly, d=>d.off_price_mean)],\n ['morning', d3.mean(monthly, d=>d.morning_price_mean)], \n ['standard', d3.mean(monthly, d=>d.standard_price_mean)],\n ['evening', d3.mean(monthly, d=>d.evening_price_mean)], \n ]\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":3512,"value":"yearly=d3.rollups(monthly,m=>{\n return {\n rate: d3.sum(m,d=>d.value)/d3.sum(m,d=>d.volume),\n value:d3.sum(m,d=>d.value),\n volume:d3.sum(m,d=>d.volume),\n price_mean: d3.mean(m,d=>d.price_mean),\n }\n},m=>m.year)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1914,"value":"md `\n### Daily\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4910,"value":"monthly_volatility=d3.rollups(daily_price_1st_difference, v=> { return {\n off: d3.mean(v, d => Math.abs(d.off)),\n morning: d3.mean(v, d => Math.abs(d.morning)),\n standard: d3.mean(v, d => Math.abs(d.standard)),\n evening: d3.mean(v, d => Math.abs(d.evening)),\n} }, v=>v.date)","pinned":false,"hidden":false,"mode":"ojs"},{"id":4800,"value":"daily_price_1st_difference=\n{\n let last = {\n off: 0,\n standard: 0,\n morning: 0,\n evening: 0\n }\n \n let dif = daily.map((day, i) => {\n let cur = {}\n if (i>0) {\n cur = {\n year: day.year,\n month: day.month,\n day: day.day,\n date: DateTime.fromObject({year: day.year, month:day.month}),\n off: day.off_price_mean-last.off, \n standard: day.standard_price_mean ? day.standard_price_mean-last.standard : null, \n morning: day.morning_price_mean ? day.morning_price_mean-last.morning : null, \n evening: day.evening_price_mean ? day.evening_price_mean-last.evening : null\n }\n }\n last.off=day.off_price_mean\n if (day.standard_price_mean) { last.standard = day.standard_price_mean }\n if (day.morning_price_mean) { last.morning = day.morning_price_mean }\n if (day.evening_price_mean) { last.evening = day.evening_price_mean }\n return cur\n })\n dif.shift()\n return dif\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":5315,"value":"pdcs={\n let out={}\n Object.keys(cats).forEach(c=>{\n let prices=daily.filter(a=>a[c + '_price_mean']).sort((a,b)=>a[c + '_price_mean']-b[c + '_price_mean'])\n out[c]=prices.map((d,i)=>{\n return {\n exceedance: 1-(i/prices.length),\n price: d[c + '_price_mean']?d[c + '_price_mean']:0\n }\n })\n }) \n return out\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4761,"value":"pdcs_2122={\n let out={}\n Object.keys(cats).forEach(c=>{\n let prices=daily.filter(a=>a.year>2020).filter(a=>a[c + '_price_mean']).sort((a,b)=>a[c + '_price_mean']-b[c + '_price_mean'])\n out[c]=prices.map((d,i)=>{\n return {\n exceedance: 1-(i/prices.length),\n price: d[c + '_price_mean']?d[c + '_price_mean']:0\n }\n })\n }) \n return out\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":4314,"value":"days=[...Array(month.lux_date.daysInMonth).keys()].map(i=>month.lux_date.plus({day:i}))","pinned":false,"hidden":false,"mode":"ojs"},{"id":4316,"value":"month=monthly.filter(v=>v.year==2022 && v.month==8)[0]","pinned":false,"hidden":false,"mode":"ojs"},{"id":4318,"value":"selected_month=29","pinned":false,"hidden":false,"mode":"ojs"},{"id":1471,"value":"md `\n### Flows\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":5447,"value":"flows_total=d3.rollup(flow,v=>[\n d3.sum(v,d=>d.value)/d3.sum(v,d=>d.flow_sum),\n d3.sum(v,d=>d.value),\n d3.sum(v,d=>d.flow_sum)\n ],v=>v.side)","pinned":false,"hidden":false,"mode":"ojs"},{"id":5435,"value":"flows_by_node=d3.rollup(flow,v=>[\n d3.sum(v,d=>d.value)/d3.sum(v,d=>d.flow_sum),\n d3.sum(v,d=>d.value),\n d3.sum(v,d=>d.flow_sum)\n ],v=>v.node)","pinned":false,"hidden":false,"mode":"ojs"},{"id":1521,"value":"node_dict=Object.fromEntries(nodes.map(n=>[n.ref,n]))","pinned":false,"hidden":false,"mode":"ojs"},{"id":5250,"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"},{"id":982,"value":"md `\n### Months\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1077,"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"},{"id":1094,"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"},{"id":972,"value":"md `\n### Calendar Months\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":5647,"value":"yearly_month_profiles=yearly.map(y=>{ \n return { \n year: y[0],\n profile: [...Array(12).keys()].map(m=>yearly_month_profile_price(y[0], m+1)).map(v=>v.map(l=>l[1]))\n }\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1039,"value":"month_profiles=[...Array(12).keys()].map(m=>month_profile_price(m+1))","pinned":false,"hidden":false,"mode":"ojs"},{"id":2816,"value":"month_profiles_volume=[...Array(12).keys()].map(m=>month_profile_volume(m+1))","pinned":false,"hidden":false,"mode":"ojs"},{"id":2814,"value":"function month_profile_volume(month_no) {\n return d3.rollup(calmonthly_hours.filter(m=>m.month==month_no),v=>d3.mean(v,m=>m.volume),t=>t.hour)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":5639,"value":"function yearly_month_profile_price(year , month_no) {\n let dat = yearly_calmonthly_hours.filter(v=>v.year==year)\n return d3.rollups(dat.filter(m=>m.month==month_no),v=>d3.mean(v,m=>m.price),t=>t.hour)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1036,"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"},{"id":967,"value":"md `\n### Hours and Categories\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":2125,"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"},{"id":4499,"value":"md `\n### Data Load\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":5637,"value":"yearly_calmonthly_hours = {\n const raw = (await d3.csv(base_url + market_ref + \"_yearly_calmonthly_hours.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs"},{"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, hour: 0, zone: 0})\n r.date=r.lux_date.toJSDate()\n })\n return raw\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2260,"value":"calmonthly = {\n const raw = (await d3.csv(base_url + market_ref + \"_calmonthly.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2289,"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"},{"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"},{"id":4321,"value":"selected_hours = {\n const url=`https://data.africanpowerprojects.com/sapp/input/monthly/idm_2022_08.json?${Math.floor(Math.random() * 1000)}`\n \n const rw = (await d3.json(url,d3.autoType))\n rw.shift()\n \n let hours=[]\n rw.forEach(h=> {\n const lux = DateTime.fromFormat(h[0].slice(1,15),'yyyy/LL/dd) HH')\n if (lux.isValid) {\n hours.push({\n raw: h,\n lux_date: lux,\n hour: parseInt(h[0].slice(13,15)),\n price: parseFloat(h[1]),\n volume: parseInt(h[2])\n })\n }\n })\n hours=hours.map(h=>{\n h.date=h.lux_date.toJSDate()\n return h\n })\n return hours.filter(d=>d.lux_date.day<14)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":2645,"value":"flow = {\n const raw = (await d3.csv(base_url + market_ref + \"_flow_monthly_cat.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: 1,hour:0,minute:0, zone:0})\n r.date = r.lux_date.toJSDate()\n })\n return raw\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4509,"value":"base_url='https://data.africanpowerprojects.com/sapp/output/'","pinned":false,"hidden":false,"mode":"ojs"},{"id":4512,"value":"market_ref='idm'","pinned":false,"hidden":false,"mode":"ojs"},{"id":964,"value":"md `\n### Imports\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4692,"value":"function sideCol(index) {\n return d3.schemeCategory10[index]\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":4702,"value":"function catCol(index) {\n return d3.schemeCategory10[index]\n}","pinned":false,"hidden":false,"mode":"ojs"},{"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"},{"id":14,"value":"font = ({\n family: 'Courier New, monospace',\n size: 13,\n color: '#6f6f6f'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":16,"value":"d3 = require(\"d3@6\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":18,"value":"plt = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":1201,"value":"ss = require('simple-statistics')","pinned":false,"hidden":false,"mode":"ojs"},{"id":1703,"value":"html`\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":4407,"value":"style=html`css `","pinned":false,"hidden":false,"mode":"ojs"},{"id":2137,"value":"luxon = require(\"luxon@1/build/amd/luxon.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":2140,"value":"DateTime = luxon.DateTime","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W44","stdlib":"1","titling":"auto"}