31:T70d,viewof dam_range = { var data = [ { y: daily.map(d=>d.price_max).concat(daily.map(d=>d.price_min).reverse()), x: daily.map(d=>d.date).concat(daily.map(d=>d.date).reverse()), mode: 'lines', line: { width: 0}, fill:'toself', fillcolor:'rgba(100, 149, 237,0.3)', type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', } , { y: daily.map(d=>d.price_weight_av), x: daily.map(d=>d.date), mode: 'lines', line: {shape: 'spline', color:'grey', width: 1.5}, type: 'scatter', hoverinfo: 'none', showlegend:false,name: '', }, { y: movingAverage(daily.map(d=>d.price_weight_av),14), x: daily.map(d=>d.date), mode: 'lines', line: {shape: 'spline', color:d3.schemeCategory10[3], width: 1.5}, type: 'scatter', hoverinfo: 'x,y', showlegend:false,name: '', }, ] var layout = { height: 300, width: width-30, font: font, showlegend: true, legend: {xanchor: 'left', x:0, y: 1}, margin: {l: 90,r: 90,b: 10,t: 0}, xaxis: { rangeslider: {}, range:years_range, showgrid: true, zeroline: false, ticks:'outside', }, yaxis: { title: '$/MWh', range: [0,320], showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('Daily prices on the SAPP DAM market. Red line - 14 day moving average price. Blue - Daily price range.') const form = html`` plt.newPlot(div, data, layout,{displayModeBar: false}); div.on('plotly_relayout', d => { form.dispatchEvent(new CustomEvent("input", { detail: d['xaxis.range'],bubbles: true })); }) form.oninput = (evt) => { form.value = evt.detail; }; form.oninput({detail: [daily[0].date, daily[daily.length-1].date]}) return form; }32:T73e,{ let margin = ({top: 20, right: 65, bottom: 0, left: 73}) let height=300 let ys=timeofday.map(d => d.dayofweek == 1 ? month_names[d.month-1] : d.dayofweek == 6 ? 'Sat' : 'Sun') ys.splice(12,0,'') let y = d3.scaleBand() .domain(ys) .range([margin.top, height - margin.bottom]) .padding(0.1) .round(true) let x = d3.scaleLinear() .domain([0, 24]) .range([margin.left, width - margin.right]) .interpolate(d3.interpolateRound) const svg = d3 .create("svg") .attr("viewBox", [0, 0, width-30, height]) .style("max-width", `${width-30}px`) .style("height", "auto") svg.append("g") .attr('transform', `translate(0,${margin.top})`) .call(d3.axisTop(x).ticks(23)) .call(g => g.select(".domain").remove()) .call(g => g.selectAll(".tick text") .attr("font-size", 12)) svg.append("g") .attr('transform', `translate(${margin.left},0)`) .call(d3.axisLeft(y)) .call(g => g.select(".domain").remove()) .call(g => g.selectAll(".tick text") .attr("font-size", 12)) svg.append("g") .attr('stroke', 'white') .attr('stroke-width', '1') .attr('fill-opacity', '0.5') .selectAll("rect") .data(timeofday_flat) .join("rect") .attr('y', d=>y(d.dayofweek == 1 ? month_names[d.month-1] : d.dayofweek == 6 ? 'Sat' : 'Sun')) .attr('x', d=>x(d.hour)) .attr('width', x(1)-x(0)) .attr('height', y.bandwidth()) .attr('fill', d=>catCol(cats[d.cat].index) ) const div=container('Average time of day categories for weekdays by month and separately for saturdays and sundays. Blue - Off-peak, Orange - Morning peak, Green - Standard, Red - Evening peak.') div.prepend(svg.node()) // plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }33:T700,{ function yr(ref) { const annual_price=d3.rollups(monthly.filter(m=>m.year<2025),v=>d3.mean(v, d=>d[ref + '_price_mean']), v=>v.lux_date.startOf('year').plus({month:6})) return { y: annual_price.map(m=>Math.round(m[1])), text: annual_price.map(m=>Math.round(m[1])), x: annual_price.map(m=>m[0].toJSDate()), type: 'scatter', showlegend:false, mode: 'text+lines+markers', textposition:'top-left', line: {color: make_trans(catCol(cats[ref].index),0.4),width:2}, marker: {color: make_trans(catCol(cats[ref].index),0.8),size: 10}, hoverinfo: 'y', name: cats[ref].name } } function mon(ref) { return { y: monthly.map(m=>m[ref + '_price_mean']), x: monthly.map(m=>m['date']), mode: 'lines+markers', line: {shape:'',color: catCol(cats[ref].index), width: 1.5}, marker:{size:3}, type: 'scatter', hoverinfo: 'none', name: cats[ref].name, showlegend:true, connectgaps: false } } var data = [] Object.values(cats).forEach(c=>{ if (Object.fromEntries(selected_cats2.map(c=>[c,c]))[c.name]) { data.push(mon(c.ref)) data.push(yr(c.ref)) } }) var layout = { height: 270, width: width-30, font: font, showlegend: true, legend: {orientation:'h',xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { range:years_range, showgrid: true, zeroline: false, ticks:'outside', }, yaxis: { title: '$/MWh', range:[0,360], showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside' } }; const div=container('Monthly and annual average prices on the SAPP DAM market by time-of-day categories.') plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }34:T70f,{ var data = [ { y: daily_differentials.filter(v=>v.day_of_week<6 && v.year>2019).map(d=>d.off_morning), x: daily_differentials.filter(v=>v.day_of_week<6 && v.year>2019).map(d=>d.lux_date.toJSDate()), mode: 'lines', line: {shape: '', color:d3.schemeCategory10[3], width: 1}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Offpeak to Morning Differential', }, { y: daily_differentials.filter(v=>v.day_of_week<6 && v.year>2019).map(d=>d.standard_evening), x: daily_differentials.filter(v=>v.day_of_week<6 && v.year>2019).map(d=>d.lux_date.toJSDate()), mode: 'lines', line: {shape: '', color:d3.schemeCategory10[9], width: 1}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Standard to Evening Differential', } , { y: daily_differentials.filter(v=>v.day_of_week==6 && v.year>2019).map(d=>d.saturday), x: daily_differentials.filter(v=>v.day_of_week==6 && v.year>2019).map(d=>d.lux_date.toJSDate()), mode: 'lines', line: {shape: '', color:d3.schemeCategory10[8], width: 1}, marker:{size:3}, type: 'scatter', hoverinfo: 'x+y', showlegend:true,name: 'Saturday Differential', } ] var layout = { height: 270, width: width-30, font: font, showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks: 'outside', }, yaxis: { title: `$/MWh`, showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside', range: [-10,330] } }; const div=container('Daily differentials between peak prices and off-peak prices for 2020 to date.') plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }35:T5d2,monthlychart=function(){ var data = [ { y: monthly_benchmark.filter(v=>v.lux_date.year>2010).map(d=>d.monthly_sum/1000), x: monthly_benchmark.filter(v=>v.lux_date.year>2010).map(d=>d.lux_date.toJSDate()), line:{color:'grey'}, mode:'lines', fill:'none', type: 'scatter', hoverinfo: 'none', showlegend:true,name: 'Gross' } , { y: monthly_benchmark.filter(v=>v.lux_date.year>2010).map(d=>d.monthly_sum_net/1000), x: monthly_benchmark.filter(v=>v.lux_date.year>2010).map(d=>d.lux_date.toJSDate()), text: monthly_benchmark.filter(v=>v.lux_date.year>2010).map(d=> ""+ d.lux_date.toFormat('LLL yy') + "
$" + d3.format(',.0f')(d.monthly_sum_net) + "/MWh"), marker:{color:d3.schemeCategory10[2]}, mode:'lines+markers', fill:'tozeroy', type: 'bar', hoverinfo: 'text', showlegend:true,name: 'Net' } ] var layout = { height: 270, width: width-30, font: font, showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { showgrid: true, zeroline: false, ticks: 'outside', }, yaxis: { title: `$ (000s)/MWh per month`, showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside' } }; const div=container('APP Storage Benchmark: Monthly total value of two daily storage cycles monday to saturday on the SAPP DAM.') plt.newPlot(div, data, layout,{displayModeBar: false}) return html`${div}` }36:[{"id":"f97fdeb7341d3f752a7271f84a46608de7c558c00d96c577adeee0965b8603a8c97870615569a9fa16d0c6fa12d7e7b4892657bad77501f966f08b8e13e8e6b9","href":"https://static.observableusercontent.com/files/f97fdeb7341d3f752a7271f84a46608de7c558c00d96c577adeee0965b8603a8c97870615569a9fa16d0c6fa12d7e7b4892657bad77501f966f08b8e13e8e6b9","name":"APP logo.png","type":"image/png","lastModified":1665123902784.678,"size":92844}] 2f:{"title":"APP Storage Benchmark","cells":[{"id":0,"value":"

APP Storage Benchmark

","pinned":false,"hidden":false,"mode":"md"},{"id":791,"value":"

\n\n

\n The APP Storage Benchmark is a reference gross margin (in $/MWh/day) that could be achieved by a grid-connected storage system (battery) that buys off-peak energy and sells peak energy on the Southern African Power Pool (SAPP) Day-ahead Market (DAM). The benchmark assumes two storage cycles per day monday to saturday and a round-trip storage efficiency of ${d3.format('.0%')(storage_efficiency)}.\n

\n The APP Solar Benchmark is calculated by using the hourly settlement price of the SAPP DAM market.\n

\n
\n

","pinned":false,"hidden":false,"mode":"html"},{"id":760,"value":"monthlychart()","pinned":false,"hidden":false,"mode":"ojs"},{"id":800,"value":"

Calculating the benchmark

","pinned":false,"hidden":false,"mode":"html"},{"id":56,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":419,"value":"The SAPP DAM market provides a platform for participating utilities and other members across southern Africa to buy and sell electricity for delivery the following day. Bids and offers are made by the hour.\n

\nDue to patterns in supply and demand the average price for power traded on the SAPP DAM has a distinct daily pattern with lower prices during the nighttime, Off-peak period, moderately higher prices during the daytime, Standard period and two peak, high price periods in the Morning and Evening.","pinned":false,"hidden":false,"mode":"html"},{"id":398,"value":"{ \n \n let data = selected_months.map((m, i)=>{\n const ser = month_profiles[month_dict[m].index]\n return {\n y: [...Array(24).keys()].map(h=>ser.get(h)),\n mode: 'lines', line: {shape: 'spline', color: d3.schemeDark2[month_dict[m].group], width:3}, fill:'',\n type: 'scatter', hoverinfo: 'x,y', name: m,\n }\n })\n \n var layout = {\n height: 270, width: width-30,\n font: font, \n showlegend: true, legend: {xanchor: 'left', x:1,y: 1},\n margin: {l: 50,r: 5,b: 30,t: 0},\n xaxis: {\n title: '',\n showgrid: true, zeroline: false, dtick: 1, ticks:'outside',\n },\n yaxis: {\n range: [20,260],\n title: `$/MWh`,\n showgrid: false, zeroline: false, tickformat: '.0f', ticks:'outside'\n }\n };\n \n const div=container('Average prices on the SAPP DAM market by time-of-day for selected months for 2020 to date.')\n plt.newPlot(div, data, layout,{displayModeBar: false})\n return html`${div}`\n \n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":416,"value":"\nThe pattern of time-of-day pricing also changes through the year driven by changing day length and average temperatures in the region.\n

\nThis pattern of higher and lower pricing periods through the day presents an opportunity to buy lower priced electricity in the Off-peak and Standard periods, to store in a grid connected battery and then sell this electricity back to the market during the higher priced peak periods, Morning and Evening. ","pinned":false,"hidden":false,"mode":"html"},{"id":5,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":520,"value":"Two charge and discharge cycles are available for each day of the week except Sunday where on average no significant time of day price differentials exit.","pinned":false,"hidden":false,"mode":"html"},{"id":145,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":524,"value":"The average market price for each of the four time of day categories varies daily depending on supply and demand market conditions. Average prices for the evening peak have risen steadily since 2018. Morning peak prices have also risen over the same period but not to the same extent.","pinned":false,"hidden":false,"mode":"html"},{"id":240,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":529,"value":"The opportunity for trading between peak and offpeak market prices using battery storage depends on the difference in prices on any particular day between peak and off peak periods. As with the overall market price these differentials have historically risen and fallen depending on suplpy and demand considerations.","pinned":false,"hidden":false,"mode":"html"},{"id":726,"value":"{\n var data = [\n {\n y: daily_differentials.filter(v=>v.day_of_week<7 && v.year>2019).map(d=>d.daily),\n x: daily_differentials.filter(v=>v.day_of_week<7 && v.year>2019).map(d=>d.lux_date.toJSDate()),\n mode: 'lines', line: {shape: '', color:d3.schemeCategory10[2], width: 1}, marker:{size:3},\n type: 'scatter', hoverinfo: 'x+y', showlegend:false,name: '',\n } \n ]\n \n var layout = {\n height: 270, width: width-30,\n font: font, \n showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1},\n margin: {l: 50,r: 5,b: 30,t: 0},\n xaxis: {\n showgrid: true, zeroline: false, ticks: 'outside',\n },\n yaxis: {\n title: `$/MWh`,\n showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside', range: [-10,430]\n }\n };\n \n const div=container('Total daily peak to offpeak differential from two cycles available on the SAPP DAM excluding Sundays.')\n plt.newPlot(div, data, layout,{displayModeBar: false})\n return html`${div}`\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":825,"value":"monthlychart()","pinned":false,"hidden":false,"mode":"ojs"},{"id":787,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":720,"value":"

Params

","pinned":false,"hidden":false,"mode":"html"},{"id":676,"value":"storage_efficiency=0.86","pinned":false,"hidden":false,"mode":"ojs"},{"id":680,"value":"trading_cost_dollers_per_mwh = 100","pinned":false,"hidden":false,"mode":"ojs"},{"id":715,"value":"

DAM

","pinned":false,"hidden":false,"mode":"html"},{"id":740,"value":"monthly_benchmark = d3.rollups(daily_differentials.filter(v=>v.day_of_week<7),v=>{\n return {\n lux_date:v[0].lux_date,\n mean_daily: d3.mean(v, w=>w.daily),\n mean_daily_net: d3.mean(v, w=>w.daily_net),\n monthly_sum: d3.sum(v, w=>w.daily),\n monthly_sum_net: d3.sum(v, w=>w.daily_net),\n \n }\n},v=>v.lux_date.year+v.lux_date.month/12).map(p=>p[1])","pinned":false,"hidden":false,"mode":"ojs"},{"id":70,"value":"daily_differentials = {\n return daily.map(d => {\n let ret = {\n year: d.year,\n month: d.month,\n day: d.day,\n lux_date: d.lux_date,\n day_of_week: d.lux_date.weekday\n }\n if (d.lux_date.weekday<6) {\n ret.off_morning = d.morning_price_mean - d.off_price_mean\n ret.off_morning_pct = d.morning_price_mean / d.off_price_mean\n ret.standard_evening = d.evening_price_mean - d.standard_price_mean\n ret.standard_evening_pct = d.evening_price_mean / d.standard_price_mean\n ret.daily = (ret.off_morning + ret.standard_evening)\n }\n if (d.lux_date.weekday === 6) {\n ret.saturday = d.standard_price_mean - d.off_price_mean\n ret.saturday_pct = d.standard_price_mean / d.off_price_mean\n ret.daily = ret.saturday * 2\n }\n if (d.lux_date.weekday === 7) {\n ret.daily = 0\n }\n ret.daily_net = ret.daily*storage_efficiency\n return ret\n })\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":64,"value":"daily = {\n const raw = (await d3.csv(base_url + market_ref + \"_daily.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n raw.forEach(r=>{\n r.lux_date=DateTime.fromObject({year: r.year, month: r.month, day: r.day})\n r.date=r.lux_date.toJSDate()\n }) \n return raw.filter(v=>v.year>2010)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":60,"value":"monthly = {\n const raw = (await d3.csv(base_url + market_ref + \"_monthly.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n raw.map(r=>{\n r.lux_date=DateTime.fromObject({year: r.year, month: r.month, day: 1, hour: 0, zone: 0})\n r.date=r.lux_date.toJSDate()\n })\n return raw\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":703,"value":"

ToD

","pinned":false,"hidden":false,"mode":"html"},{"id":400,"value":"month_profiles=[...Array(12).keys()].map(m=>month_profile_price(m+1))","pinned":false,"hidden":false,"mode":"ojs"},{"id":402,"value":"function month_profile_price(month_no) {\n return d3.rollup(calmonthly_hours.filter(m=>m.month==month_no),v=>d3.mean(v,m=>m.price),t=>t.hour)\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":404,"value":"calmonthly_hours = {\n const raw = (await d3.csv(base_url + market_ref + \"_calmonthly_hours.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n return raw\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":42,"value":"timeofday_flat={\n let o=[]\n timeofday.forEach(t=>{\n [...Array(24).keys()].forEach((h,i)=>{\n o.push({month: t.month, hour: i, dayofweek: t.dayofweek, cat: t[i]}) \n })\n })\n return o\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":44,"value":"timeofday = {\n const raw = (await d3.csv(base_url + market_ref + \"_timeofday.csv?\" + Math.floor(Math.random() * 1000),d3.autoType))\n \n return raw\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":396,"value":"selected_months=[\"Mar\", \"Jun\", \"Aug\", \"Sep\", \"Oct\", \"Dec\"]","pinned":false,"hidden":false,"mode":"ojs"},{"id":430,"value":"selected_cats2 = [\"Evening\", \"Morning\", \"Standard\", \"Off-peak\"]","pinned":false,"hidden":false,"mode":"ojs"},{"id":698,"value":"

General

","pinned":false,"hidden":false,"mode":"html"},{"id":58,"value":"years_range= [monthly[0].lux_date.plus({month:-0.5}).toJSDate(),monthly[monthly.length-1].lux_date.plus({month:0.5}).toJSDate()]","pinned":false,"hidden":false,"mode":"ojs"},{"id":51,"value":"month_names={\n return {\n 0:'Jan',\n 1:'Feb',\n 2:'Mar',\n 3:'Apr',\n 4:'May',\n 5:'Jun',\n 6:'Jul',\n 7:'Aug',\n 8:'Sep',\n 9:'Oct',\n 10:'Nov',\n 11:'Dec',\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":48,"value":"month_dict={\n return {\n 'Jan':{index: 0, group: 1},\n 'Feb':{index: 1, group: 1},\n 'Mar':{index: 2, group: 6},\n 'Apr':{index: 3, group: 6},\n 'May':{index: 4, group: 2},\n 'Jun':{index: 5, group: 2},\n 'Jul':{index: 6, group: 3},\n 'Aug':{index: 7, group: 3},\n 'Sep':{index: 8, group: 4},\n 'Oct':{index: 9, group: 4},\n 'Nov':{index: 10, group: 4},\n 'Dec':{index: 11, group: 1},\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":39,"value":"cats = {\n return {\n evening: { index: 3, name: 'Evening', ref: 'evening', long_name: 'Evening Peak'}, \n morning: { index: 1, name: 'Morning', ref: 'morning', long_name: 'Morning Peak'}, \n standard: {index: 2, name: 'Standard', ref: 'standard', long_name: 'Daytime Standard'},\n off: {index: 0, name: 'Off-peak', ref: 'off', long_name: 'Night Off-peak'}, \n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":36,"value":"base_url='https://data.africanpowerprojects.com/sapp/output/'","pinned":false,"hidden":false,"mode":"ojs"},{"id":33,"value":"market_ref='dam'","pinned":false,"hidden":false,"mode":"ojs"},{"id":26,"value":"function catCol(index) {\n return d3.schemeCategory10[index]\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":150,"value":"make_trans=function(col,opacity) {\n let c=d3.color(col)\n c.opacity=opacity\n return c.formatRgb()\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":66,"value":"function movingAverage(values, N) {\n let i = 0;\n let sum = 0;\n const means = new Float64Array(values.length).fill(NaN);\n for (let n = Math.min(N - 1, values.length); i < n; ++i) {\n sum += values[i];\n }\n for (let n = values.length; i < n; ++i) {\n sum += values[i];\n means[i - Math.floor(N / 2)] = sum / N;\n sum -= values[i - N + 1];\n }\n return means;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":392,"value":"container = function(captionText) {\n const div=DOM.element('div')\n div.setAttribute(\"class\",\"border m-2 p-2\")\n const caption=DOM.element('figcaption')\n caption.append(captionText)\n div.append(caption)\n return div\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":28,"value":"font = ({\n family: 'Courier New, monospace',\n size: 13,\n color: '#6f6f6f'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":122,"value":"ss = require('simple-statistics')","pinned":true,"hidden":false,"mode":"ojs"},{"id":23,"value":"d3 = require(\"d3@6\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":20,"value":"plt = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":16,"value":"html`\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":13,"value":"style=html`css `","pinned":false,"hidden":false,"mode":"ojs"},{"id":7,"value":"DateTime = luxon.DateTime","pinned":false,"hidden":false,"mode":"ojs"},{"id":9,"value":"luxon = require(\"luxon@1/build/amd/luxon.js\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W36","stdlib":"1","titling":"auto"}