2b:null 2c:["$","title",null,{"children":"Intra-day Market (IDM) | Andy Fleming | Observable"}] 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:{"id":"e8e50c760aab59a4","slug":"intra-day-market-idm","title":"Intra-day Market (IDM)","thumbnail":"a87bbcfe8fcb5a2b3b0dffb9b31f8df188f340c568260e69ab1da1904f6b383a","access_level":"public","create_time":"$D2022-08-31T13:50:02.485Z","update_time":"$D2023-07-31T11:38:12.274Z","view_time":null,"first_public_time":"$D2022-08-31T14:12:14.801Z","fork":{"id":"9f50c7afd561cf9d","slug":"sapp-dam","title":"Day-ahead Market (DAM) - Historic Analysis","owner":{"id":"21337e734770a90b","login":"andyflem","name":"Andy Fleming"}},"stars":1,"starred":false,"owner":{"type":"team","id":"21337e734770a90b","login":"andyflem","name":"Andy Fleming","avatar_url":"https://avatars-next.observableusercontent.com/fd3844143a4c29872f0df28a8ebce77bb56cebf2fa74bb669872e4def82ad809","tier":"starter_2024"},"version":5974,"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,"subscribed":null,"forks":2,"collection":{"id":"7d6d01969d5f1ad9","slug":"southern-african-power-pool","title":"Southern African Power Pool","owner":{"id":"21337e734770a90b","login":"andyflem","name":"Andy Fleming"}},"type":"notebook","body":{"title":"Intra-day Market (IDM)","cells":[{"id":0,"value":"md`# Intra-day Market (IDM)`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"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","author":"$undefined","summary":"$undefined"},{"id":5424,"value":"$31","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5456,"value":"Mozambique (EDM and HCB) and Eskom dominate the supply and NamPower, BPC and CEC dominate the consumption.","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":5482,"value":"{\n const form = html`\n `\n \n const div=container()\n div.prepend(form)\n return div \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5474,"value":"$32","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3571,"value":"$33","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4224,"value":"html`\n

Price and Volume

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

Intra-day Price Patterns

\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4312,"value":"$37","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4344,"value":"$38","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5627,"value":"In general there is an inverse relationship between hourly price and volume on the market and the daily pattern of peak and off-peak prices is also apparent in the hourly volumes traded with higher prices producing to lower volumes and lower prices leading to higher volumes. ","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":1854,"value":"viewof selected_months = {\n const form = html`\n `\n\n form.oninput = () => {\n form.value = Array.prototype.filter\n .call(form.input, i => i.checked)\n .map(i => i.value)\n }\n form.oninput()\n return form\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1064,"value":"{ \n let data = selected_months.map((m, i)=>{\n const ser = month_profiles[month_dict[m].index]\n return {\n y: [...Array(24).keys()].map(h=>ser.get(h)),\n mode: 'lines', line: {shape: 'spline', color: d3.schemeDark2[month_dict[m].group], width:3}, fill:'',\n type: 'scatter', hoverinfo: 'x,y', name: m,\n }\n })\n \n var layout = {\n height: 260, width: width-30,\n font: font, \n showlegend: true, legend: {xanchor: 'left', x:1,y: 1},\n margin: {l: 50,r: 5,b: 30,t: 0},\n xaxis: {\n title: '',\n showgrid: true, zeroline: false, dtick: 1, ticks:'outside',\n },\n yaxis: {\n range: [20,170],\n title: `$/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","author":"$undefined","summary":"$undefined"},{"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: `$/MWh`,\n showgrid: false, zeroline: false, tickformat: '.0f', ticks:'outside'\n }\n };\n\n const div=container('Mean price by time-of-day for each August since 2016.')\n plt.newPlot(div, data, layout,{displayModeBar: false});\n return div\n \n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4247,"value":"html`\n

Time-of-day prices

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

Volatility

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

Price seasonality

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

Price distribution

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

Market volume and traded power

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

Market value

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

Volume, power and value seasonality

\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"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","author":"$undefined","summary":"$undefined"},{"id":4656,"value":"$41","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2818,"value":"{ \n \n let data = selected_months3.map((m, i)=>{\n const ser = month_profiles_volume[month_dict[m].index]\n return {\n y: [...Array(24).keys()].map(h=>ser.get(h)),\n mode: 'lines', line: {shape: 'spline', color: d3.schemeCategory10[month_dict[m].group], width:3}, fill:'',\n type: 'scatter', hoverinfo: 'x,y', name: m,\n }\n })\n \n var layout = {\n height: 270, width: width-30,\n font: font, \n showlegend: true, legend: {xanchor: 'left', x:1,y: 1},\n margin: {l: 50,r: 5,b: 30,t: 0},\n xaxis: {\n title: '',\n showgrid: true, zeroline: false, dtick: 1, ticks:'outside',\n },\n yaxis: {\n range:[0,85],\n title: `MW`,\n showgrid: false, zeroline: false, tickformat: '.0f', ticks:'outside'\n }\n }\n\n const div=container('Daily power profiles for selected months.')\n plt.newPlot(div, data, layout, {displayModeBar: false});\n return div\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3480,"value":"$42","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5412,"value":"

\n

Setup

","pinned":false,"hidden":false,"mode":"html","author":"$undefined","summary":"$undefined"},{"id":5882,"value":"selected_months3=[\"Mar\", \"Jun\", \"Oct\", \"Dec\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5713,"value":"import {differentials_chart} from \"@andyflem/sapp-dam-time-of-day-arbitrage-analysis\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5705,"value":"selected_cats2=[\"Evening\", \"Morning\", \"Standard\", \"Off-peak\"]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5568,"value":"solcol='#d68910'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5438,"value":"pie = d3\n .pie()\n .sort(null)\n .value(d => d)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5445,"value":" projection=d3.geoPath(d3.geoEquirectangular().center([25,-14]).scale(1300))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5443,"value":"$43","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5415,"value":"container = function(captionText) {\n const div=DOM.element('div')\n div.setAttribute(\"class\",\"border m-2 p-2\")\n if (captionText) {\n const caption=DOM.element('figcaption')\n caption.append(captionText)\n div.append(caption)\n }\n return div\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3972,"value":"countries={\n return {\n 'Botswana': {ref: 'BOT', country: 'Botswana', col: 1},\n 'Mozambique': {ref: 'MOZ', country: 'Mozambique', col: 2},\n 'Namibia': {ref: 'NAM', country: 'Namibia', col: 3},\n 'South Africa': {ref: 'RSA', country: 'South Africa',col:7 },\n 'Zambia': {ref: 'ZAM', country: 'Zambia', col: 5},\n 'Zimbabwe': {ref: 'ZIM', country: 'Zimbabwe', col: 4},\n 'Lesotho': {ref: 'LES', country: 'Lesotho', col: 8},\n 'Swaziland': {ref: 'ESW', country: 'Swaziland', col: 9},\n 'DRC': {ref: 'DRC', country: 'DRC', col: 9},\n 'Tanzania': {ref: 'TNZ', country: 'Tanzania', col: 3},\n 'Malawi': {ref: 'MAL', country: 'Malawi', col: 6},\n 'Angola': {ref: 'ANG', country: 'Angola', col: 2},\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5466,"value":"import {nodes} from \"@andyflem/day-ahead-market-dam-market-participants\"","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3927,"value":"sapp=topojson.feature(sapptopo, sapptopo.objects.sapp)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3798,"value":"sapptopo=FileAttachment(\"sapp.json\").json()","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3929,"value":"topojson = require('topojson')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3027,"value":"make_trans=function(col,opacity) {\n let c=d3.color(col)\n c.opacity=opacity\n return c.formatRgb()\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3491,"value":"years_range= [monthly[0].lux_date.plus({month:-0.5}).toJSDate(),monthly[monthly.length-1].lux_date.plus({month:0.5}).toJSDate()]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4377,"value":"cats_means={\n return [\n ['off', d3.mean(monthly, d=>d.off_price_mean)],\n ['morning', d3.mean(monthly, d=>d.morning_price_mean)], \n ['standard', d3.mean(monthly, d=>d.standard_price_mean)],\n ['evening', d3.mean(monthly, d=>d.evening_price_mean)], \n ]\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":3512,"value":"yearly=d3.rollups(monthly,m=>{\n return {\n rate: d3.sum(m,d=>d.value)/d3.sum(m,d=>d.volume),\n value:d3.sum(m,d=>d.value),\n volume:d3.sum(m,d=>d.volume),\n price_mean: d3.mean(m,d=>d.price_mean),\n }\n},m=>m.year)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1914,"value":"md `\n### Daily\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4910,"value":"monthly_volatility=d3.rollups(daily_price_1st_difference, v=> { return {\n off: d3.mean(v, d => Math.abs(d.off)),\n morning: d3.mean(v, d => Math.abs(d.morning)),\n standard: d3.mean(v, d => Math.abs(d.standard)),\n evening: d3.mean(v, d => Math.abs(d.evening)),\n} }, v=>v.date)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4800,"value":"daily_price_1st_difference=\n{\n let last = {\n off: 0,\n standard: 0,\n morning: 0,\n evening: 0\n }\n \n let dif = daily.map((day, i) => {\n let cur = {}\n if (i>0) {\n cur = {\n year: day.year,\n month: day.month,\n day: day.day,\n date: DateTime.fromObject({year: day.year, month:day.month}),\n off: day.off_price_mean-last.off, \n standard: day.standard_price_mean ? day.standard_price_mean-last.standard : null, \n morning: day.morning_price_mean ? day.morning_price_mean-last.morning : null, \n evening: day.evening_price_mean ? day.evening_price_mean-last.evening : null\n }\n }\n last.off=day.off_price_mean\n if (day.standard_price_mean) { last.standard = day.standard_price_mean }\n if (day.morning_price_mean) { last.morning = day.morning_price_mean }\n if (day.evening_price_mean) { last.evening = day.evening_price_mean }\n return cur\n })\n dif.shift()\n return dif\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5315,"value":"pdcs={\n let out={}\n Object.keys(cats).forEach(c=>{\n let prices=daily.filter(a=>a[c + '_price_mean']).sort((a,b)=>a[c + '_price_mean']-b[c + '_price_mean'])\n out[c]=prices.map((d,i)=>{\n return {\n exceedance: 1-(i/prices.length),\n price: d[c + '_price_mean']?d[c + '_price_mean']:0\n }\n })\n }) \n return out\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4761,"value":"pdcs_2122={\n let out={}\n Object.keys(cats).forEach(c=>{\n let prices=daily.filter(a=>a.year>2020).filter(a=>a[c + '_price_mean']).sort((a,b)=>a[c + '_price_mean']-b[c + '_price_mean'])\n out[c]=prices.map((d,i)=>{\n return {\n exceedance: 1-(i/prices.length),\n price: d[c + '_price_mean']?d[c + '_price_mean']:0\n }\n })\n }) \n return out\n}\n","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4314,"value":"days=[...Array(month.lux_date.daysInMonth).keys()].map(i=>month.lux_date.plus({day:i}))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4316,"value":"month=monthly.filter(v=>v.year==2022 && v.month==8)[0]","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4318,"value":"selected_month=29","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1471,"value":"md `\n### Flows\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5447,"value":"flows_total=d3.rollup(flow,v=>[\n d3.sum(v,d=>d.value)/d3.sum(v,d=>d.flow_sum),\n d3.sum(v,d=>d.value),\n d3.sum(v,d=>d.flow_sum)\n ],v=>v.side)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5435,"value":"flows_by_node=d3.rollup(flow,v=>[\n d3.sum(v,d=>d.value)/d3.sum(v,d=>d.flow_sum),\n d3.sum(v,d=>d.value),\n d3.sum(v,d=>d.flow_sum)\n ],v=>v.node)","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1521,"value":"node_dict=Object.fromEntries(nodes.map(n=>[n.ref,n]))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5250,"value":"hourly = {\n const raw = (await d3.csv(base_url + market_ref + \"_hourly_slim.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n raw.forEach(r=>{\n r.lux_date=DateTime.fromJSDate(r.date)\n }) \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":982,"value":"md `\n### Months\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1077,"value":"month_names={\n return {\n 0:'Jan',\n 1:'Feb',\n 2:'Mar',\n 3:'Apr',\n 4:'May',\n 5:'Jun',\n 6:'Jul',\n 7:'Aug',\n 8:'Sep',\n 9:'Oct',\n 10:'Nov',\n 11:'Dec',\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1094,"value":"month_dict={\n return {\n 'Jan':{index: 0, group: 1},\n 'Feb':{index: 1, group: 1},\n 'Mar':{index: 2, group: 6},\n 'Apr':{index: 3, group: 6},\n 'May':{index: 4, group: 2},\n 'Jun':{index: 5, group: 2},\n 'Jul':{index: 6, group: 3},\n 'Aug':{index: 7, group: 3},\n 'Sep':{index: 8, group: 4},\n 'Oct':{index: 9, group: 4},\n 'Nov':{index: 10, group: 4},\n 'Dec':{index: 11, group: 1},\n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":972,"value":"md `\n### Calendar Months\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5647,"value":"yearly_month_profiles=yearly.map(y=>{ \n return { \n year: y[0],\n profile: [...Array(12).keys()].map(m=>yearly_month_profile_price(y[0], m+1)).map(v=>v.map(l=>l[1]))\n }\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1039,"value":"month_profiles=[...Array(12).keys()].map(m=>month_profile_price(m+1))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2816,"value":"month_profiles_volume=[...Array(12).keys()].map(m=>month_profile_volume(m+1))","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2814,"value":"function month_profile_volume(month_no) {\n return d3.rollup(calmonthly_hours.filter(m=>m.month==month_no),v=>d3.mean(v,m=>m.volume),t=>t.hour)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5639,"value":"function yearly_month_profile_price(year , month_no) {\n let dat = yearly_calmonthly_hours.filter(v=>v.year==year)\n return d3.rollups(dat.filter(m=>m.month==month_no),v=>d3.mean(v,m=>m.price),t=>t.hour)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1036,"value":"function month_profile_price(month_no) {\n return d3.rollup(calmonthly_hours.filter(m=>m.month==month_no),v=>d3.mean(v,m=>m.price),t=>t.hour)\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":967,"value":"md `\n### Hours and Categories\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2125,"value":"cats = {\n return {\n evening: { index: 3, name: 'Evening', ref: 'evening', long_name: 'Evening Peak'}, \n morning: { index: 1, name: 'Morning', ref: 'morning', long_name: 'Morning Peak'}, \n standard: {index: 2, name: 'Standard', ref: 'standard', long_name: 'Daytime Standard'},\n off: {index: 0, name: 'Off-peak', ref: 'off', long_name: 'Night Off-peak'}, \n }\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4499,"value":"md `\n### Data Load\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":5637,"value":"yearly_calmonthly_hours = {\n const raw = (await d3.csv(base_url + market_ref + \"_yearly_calmonthly_hours.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2118,"value":"monthly = {\n const raw = (await d3.csv(base_url + market_ref + \"_monthly.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n raw.map(r=>{\n r.lux_date=DateTime.fromObject({year: r.year, month: r.month, day: 1, hour: 0, zone: 0})\n r.date=r.lux_date.toJSDate()\n })\n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2260,"value":"calmonthly = {\n const raw = (await d3.csv(base_url + market_ref + \"_calmonthly.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2289,"value":"calmonthly_hours = {\n const raw = (await d3.csv(base_url + market_ref + \"_calmonthly_hours.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1918,"value":"daily = {\n const raw = (await d3.csv(base_url + market_ref + \"_daily.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n raw.forEach(r=>{\n r.lux_date=DateTime.fromObject({year: r.year, month: r.month, day: r.day})\n r.date=r.lux_date.toJSDate()\n }) \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4321,"value":"selected_hours = {\n const url=`https://data.africanpowerprojects.com/sapp/input/monthly/idm_2022_08.json?${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","author":"$undefined","summary":"$undefined"},{"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","author":"$undefined","summary":"$undefined"},{"id":4509,"value":"base_url='https://data.africanpowerprojects.com/sapp/output/'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4512,"value":"market_ref='idm'","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":964,"value":"md `\n### Imports\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4692,"value":"function sideCol(index) {\n return d3.schemeCategory10[index]\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4702,"value":"function catCol(index) {\n return d3.schemeCategory10[index]\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4690,"value":"function movingAverage(values, N) {\n let i = 0;\n let sum = 0;\n const means = new Float64Array(values.length).fill(NaN);\n for (let n = Math.min(N - 1, values.length); i < n; ++i) {\n sum += values[i];\n }\n for (let n = values.length; i < n; ++i) {\n sum += values[i];\n means[i - Math.floor(N / 2)] = sum / N;\n sum -= values[i - N + 1];\n }\n return means;\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":14,"value":"font = ({\n family: 'Courier New, monospace',\n size: 13,\n color: '#6f6f6f'\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":16,"value":"d3 = require(\"d3@6\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":18,"value":"plt = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1201,"value":"ss = require('simple-statistics')","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":1703,"value":"html`\n\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":4407,"value":"style=html`css `","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2137,"value":"luxon = require(\"luxon@1/build/amd/luxon.js\")","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"},{"id":2140,"value":"DateTime = luxon.DateTime","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined"}],"files":"$W44","stdlib":"1","titling":"auto"}} 30:"$2f:body"