31:T45e,{ return html`

Hydro (Ngonye Falls): ${sel_ratio_hydro.capacities.ngonye}MW
Wind (Unika 1): ${d3.format('.0f')(sel_ratio_hydro.capacities.unika)}MW
Solar (Ilute 1): ${d3.format('.0f')(sel_ratio_hydro.capacities.ilute)}MW
Total: ${d3.format('.0f')(sel_ratio_hydro.capacities.total)}MW
Range: ${d3.format('.0f')(sel_ratio_hydro.months[11].combined_power)}MW (Dec) - ${d3.format('.0f')(sel_ratio_hydro.months[5].combined_power)}MW (Jun)

Wind+Solar Storage: ${d3.format('.2f')(ratios[Math.round(ratio*99)].store_max)}hours, ${d3.format('.0f')(ratios[Math.round(ratio*99)].store_max * sel_ratio_hydro.capacities.wind_solar)}MWh
Overall CF: ${d3.format('.2f')(sel_ratio_hydro.total_cf)}
Annual range in monthly CFs: ${d3.format('.2f')(sel_ratio_hydro.combined_cf_range)}

` }32:T8bc,{ var data = [ { x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.months.map(v=>v.ngonye_power), name: 'Hydro', type: 'scatter', mode: 'lines', hoverinfo: 'name+y', stackgroup:'one', showlegend:true, line: {shape: 'spline', color: colors.ngonye}, marker: {size: 8}, }, { x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.months.map(v=>v.unika_power),name: 'Wind', type: 'scatter', mode: 'lines', hoverinfo: 'name+y', stackgroup:'one', showlegend:true, line: {shape: 'spline', color: colors.unika[5]}, marker: {size: 8}, },{ x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.months.map(v=>v.ilute_power), name: 'Solar', type: 'scatter', mode: 'lines', hoverinfo: 'name+y', stackgroup:'one', showlegend:true, line: {shape: 'spline', color: colors.ilute[5]}, marker: {size: 8}, },{ x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.combined_power, name: 'Total', text: sel_ratio_hydro.combined_power.map(v=>d3.format('.0f')(v)), type: 'scatter', mode: 'lines+markers+text', hoverinfo: 'name+y', showlegend:false, line: {shape: 'spline', color: 'grey'}, marker: {size: 8}, textposition:'top' } ] var layout = { height:220, width: d3.min([width-30,800]), font: font, margin: {l: 50,r: 5,b: 30,t: 0}, showlegend: true, legend: {orientation: 'h', x: 0,xanchor: 'left',y: 1}, xaxis: { showgrid: false, zeroline: false, ticks:'outside', tickvals: [ 1,2,3,4,5,6,7,8,9,10,11,12 ], ticktext:['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], }, yaxis: { title: 'MW',range:[0,360], zeroline: false, showline: false, separatethousands:true, tickformat: '.0f' } }; const div = container(`P50 daily firm power for the combined hydro (Ngonye ${d3.format('.0f')(sel_ratio_hydro.capacities.ngonye)}MW) wind (Unika ${d3.format('.0f')(sel_ratio_hydro.capacities.unika)}MW) and solar (Ilute ${d3.format('.0f')(sel_ratio_hydro.capacities.ilute)}MW) plants.`) plt.newPlot(div, data, layout,{displayModeBar: false}); div.setAttribute('style','justify-content: center;display: grid;') return div }33:Tb39,{ function day() { var data = [ { y:unika_hourly_cfs, x: [...Array(24).keys()].map(v=>v+1), name: 'Wind (Unika 1)', mode: 'lines', line: {shape:'spline', width:2.5,color: colors.unika[5]}, type: 'scatter', showlegend:true, hoverinfo:'x+y', textposition:'top-center' }, { y:ilute_hourly_cfs, x: [...Array(24).keys()].map(v=>v+1), name: 'Solar (Ilute 1)', mode: 'lines', line: {shape:'spline', width:2.5,color: colors.ilute[5]}, type: 'scatter', showlegend:true, hoverinfo:'x+y', textposition:'top-center' } ] var layout = { height: 200, width: (width-120)/2, font: font, hovermode:'closest', showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { showgrid: false, zeroline: false, ticks:'outside', dtick:2, }, yaxis: { title: 'Capacity factor', showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside', range:[-0.02,1.05],dtick:0.2 } }; const div=container(`Average hourly capacity factors for solar and wind plants.`) plt.newPlot(div, data, layout,{displayModeBar: false}); return div } function year() { var data = [ { y:unika_monthly_cfs, x: [...Array(12).keys()].map(v=>v+1), name: 'Wind (Unika 1)', mode: 'lines', line: {shape:'spline', width:2.5,color: colors.unika[5]}, type: 'scatter', showlegend:true, hoverinfo:'x+y', textposition:'top-center' }, { y:ilute_monthly_cfs, x: [...Array(12).keys()].map(v=>v+1), name: 'Solar (Ilute 1)', mode: 'lines', line: {shape:'spline', width:2.5,color: colors.ilute[5]}, type: 'scatter', showlegend:true, hoverinfo:'x+y', textposition:'top-center' } ] var layout = { height: 200, width: (width-120)/2, font: font, hovermode:'closest', showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { tickvals: [ 1,2,3,4,5,6,7,8,9,10,11,12 ], ticktext:['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], showgrid: false, zeroline: false, ticks:'outside', dtick:1, }, yaxis: { title: 'Capacity factor', showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside', range:[0,0.65],dtick:0.2 } }; const div=container(`Average monthly capacity factors for solar and wind plants.`) plt.newPlot(div, data, layout,{displayModeBar: false}); return div } return html`

${day()}

${year()}

` }34:T66a,{ var data = unika_cfs.map((month, month_no)=>{ return { y:month, x:[...Array(24).keys()], mode: 'lines', line: {shape:'spline',color: colors.unika[month_no],width:2}, fill:'', type: 'scatter', hoverinfo: 'name', showlegend:false, name: 'Unika ' + month_names[month_no] } }) data = data.concat(ilute_cfs.map((month, month_no) => { return { y:month, x:[...Array(24).keys()], mode: 'lines', line: {shape:'spline',color: colors.ilute[month_no],width:2}, fill:'', type: 'scatter', hoverinfo: 'name', showlegend:false, name: 'Ilute ' + month_names[month_no] } })) var layout = { height: 290, width: width-30, font: font, hovermode:'closest', showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 45,t: 0}, xaxis: { title: 'Hour', showgrid: true, zeroline: false, ticks:'outside', dtick:1, }, yaxis: { title: 'Capacity Factor', showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside' } }; const div=container('Average hourly capacity factors by month for wind (Unika 1 - greens) and solar (Ilute 1 - yellows).') plt.newPlot(div, data, layout,{displayModeBar: false}); div.on('plotly_hover', d => { var curveNumber = d.points[0].curveNumber var vals = div.data.map((_, i) => i === curveNumber ? 1 : 0.2) plt.restyle(div, 'opacity', vals) }) div.on('plotly_unhover', d => { var curveNumber = d.points[0].curveNumber var vals = div.data.map((_, i) => i === curveNumber ? 1 : 1) plt.restyle(div, 'opacity', vals) }) return div }35:T797,{ var data =[ { y:ratios[10].combined_cfs[5], x:[...Array(24).keys()], mode: 'lines', line: {shape:'spline',color: colors.combined[1],width:2}, fill:'', type: 'scatter', hoverinfo: 'name', showlegend:true, name: `${d3.format('.2f')(ratios[10].ratio)}MW solar per MW wind` },{ y:optimum_ratio.combined_cfs[5], x:[...Array(24).keys()], mode: 'lines', line: {shape:'spline',color: colors.combined[4],width:4}, fill:'', type: 'scatter', hoverinfo: 'name', showlegend:true, name: `${d3.format('.2f')(optimum_ratio.ratio)}MW solar per MW wind` },{ y:ratios[90].combined_cfs[5], x:[...Array(24).keys()], mode: 'lines', line: {shape:'spline',color: colors.combined[10],width:2}, fill:'', type: 'scatter', hoverinfo: 'name', showlegend:true, name: `${d3.format('.2f')(ratios[90].ratio)}MW solar per MW wind` }] var layout = { height: 270, width: width-30, font: font, hovermode:'closest', showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 45,t: 0}, xaxis: { title: 'Hour', showgrid: true, zeroline: false, ticks:'outside', dtick:1, }, yaxis: { title: 'Capacity factor', showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside', range:[0,1] } }; const div=container(`Average capacity factor in June for a combined plant with various proportions of wind and solar capacity.`) plt.newPlot(div, data, layout,{displayModeBar: false}); div.on('plotly_hover', d => { var curveNumber = d.points[0].curveNumber var vals = div.data.map((_, i) => i === curveNumber ? 1 : 0.2) plt.restyle(div, 'opacity', vals) }) div.on('plotly_unhover', d => { var curveNumber = d.points[0].curveNumber var vals = div.data.map((_, i) => i === curveNumber ? 1 : 1) plt.restyle(div, 'opacity', vals) }) return div }36:T572,{ var dat = ratios[Math.round(ratio*99)].combined_cfs var data =dat.map((month,month_no) => { return { y:month, x:[...Array(24).keys()], mode: 'lines', line: {shape:'spline',color: colors.combined[month_no],width:2}, fill:'', type: 'scatter', hoverinfo: 'name', showlegend:true, name: month_names[month_no] } }) var layout = { height: 270, width: width-30, font: font, hovermode:'closest', showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 45,t: 0}, xaxis: { title: 'Hour', showgrid: true, zeroline: false, ticks:'outside', dtick:1, }, yaxis: { title: 'Capacity factor', showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside', range:[0,1] } }; const div=container(`Daily capacity factor profiles by month for a combined plant with ${ratio}MW solar per MW wind.`) plt.newPlot(div, data, layout,{displayModeBar: false}); div.on('plotly_hover', d => { var curveNumber = d.points[0].curveNumber var vals = div.data.map((_, i) => i === curveNumber ? 1 : 0.2) plt.restyle(div, 'opacity', vals) }) div.on('plotly_unhover', d => { var curveNumber = d.points[0].curveNumber var vals = div.data.map((_, i) => i === curveNumber ? 1 : 1) plt.restyle(div, 'opacity', vals) }) return div }37:T4d0,{ var dat = ratios[Math.round(ratio*99)] var data = [ { x: [...Array(12).keys()].map(v=>v+1), y: dat.monthly_store,name: '', text: dat.monthly_store.map(v=>d3.format('.2f')(v)), type: 'bar', mode: 'markers+text', hoverinfo: 'none', stackgroup:'one', showlegend:false, marker: {color: make_trans(colors.combined[5],0.6)}, textposition:'inside' }] var layout = { height: 220, width: d3.min([width-30,800]), font: font, hovermode:'closest', barmode:'stack', showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { tickvals: [ 1,2,3,4,5,6,7,8,9,10,11,12 ], ticktext:['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], showgrid: false, zeroline: false, ticks:'outside', dtick:1, }, yaxis: { title: 'Hours', dtick:0.2, showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside',range:[0,1.05] } }; const div=container(`Daily storage required in hours by month to entirely flatten the diurnal output of a combined plant with ${ratio}MW solar per MW wind.`) plt.newPlot(div, data, layout,{displayModeBar: false}); return div }38:T5f4,{ var dat = ratios[Math.round(ratio*99)] function series(dat, name, color, highlight) { return { y:dat.monthly_store, x: [...Array(12).keys()].map(v=>v+1), mode: 'lines+markers', textposition: 'top', line: {shape:'spline',color: color, width: highlight?4:2 }, marker: {size: highlight?8:5}, type: 'scatter', showlegend:true, name: name } } var data = [ series(ratios[10],`${d3.format('.2f')(ratios[10].ratio)}MW solar / wind`,colors.combined[1],false), series(optimum_ratio,`${d3.format('.2f')(optimum_ratio.ratio)}MW solar / wind`,colors.combined[4],true), series(ratios[90],`${d3.format('.2f')(ratios[90].ratio)}MW solar / wind`,colors.combined[10],false), ] var layout = { height: 230, width: d3.min([width-30,800]), font: font, hovermode:'closest', showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { tickvals: [ 1,2,3,4,5,6,7,8,9,10,11,12 ], ticktext:['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], showgrid: false, zeroline: false, ticks:'outside', dtick:1, }, yaxis: { title: 'Hours', showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside', range:[0,2.7] } }; const div=container(`Storage required by month to entirely flatten the diurnal of a combined plant for various ratios of wind and solar.`) plt.newPlot(div, data, layout,{displayModeBar: false}); return div }39:T519,{ var data = [ { y:ratios.map(v=>v.store_range), x: ratios.map(v=>v.ratio), mode: 'lines', textposition: 'top', line: {shape:'spline',color: colors.storage[2], width: 4 }, marker: {size: 5}, type: 'scatter', showlegend:false, name: '' } ] data=data.concat([{ y:[optimum_ratio.store_range], x:[optimum_ratio.ratio], text: [d3.format('.2f')(optimum_ratio.ratio)], name:'Optimum ratio',textposition:'top-center',showlegend:false, mode:'markers+text',type:'scatter', hoverinfo:'none', marker:{size:15, color:'black'} }]) var layout = { height: 200, width: d3.min([width-30,800]), font: font, hovermode:'closest', showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 45,t: 0}, xaxis: { title:'Ratio solar : wind capacity', showgrid: true, zeroline: false,tickformat: '.1f', ticks:'outside', }, yaxis: { title: 'Range, Hours', showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside', } }; const div=container(`Range (maximum month to minimum month) of storage requirement to flatten the diurnal output of the combined plant by ratio of solar to wind capacity.`) plt.newPlot(div, data, layout,{displayModeBar: false}); return div }3a:T972,{ var data =[...Array(12).keys()].map((month_no) => { return { y:ratios.map(v=>v.monthly_store[month_no]), x:ratios.map(v=>v.ratio), mode: 'lines', line: {shape:'spline',color: colors.storage[month_no],width:2}, fill:'', type: 'scatter', hoverinfo: 'name', showlegend:false, name: month_names[month_no] } }) data=data.concat([{ y:ratios.map(v=>v.store_max), x:ratios.map(v=>v.ratio), text:ratios.map(v=>d3.format('.2f')(v.store_max)),name:'Storage requirement', mode:'lines',type:'scatter', hoverinfo:'x+text', line:{shape:'spline', width:2.5, color:'red'} }]) data=data.concat([{ y:[optimum_ratio.store_max], x:[optimum_ratio.ratio], text: [d3.format('.2f')(optimum_ratio.ratio) + ','+ d3.format('.1f')(optimum_ratio.store_max)], name:'Optimum ratio',textposition:'top-center',showlegend:false, mode:'markers+text',type:'scatter', hoverinfo:'none', marker:{size:15, color:'black'} }]) data=data.concat([{ x:[ratios[Math.round(ratio*99)].ratio,ratios[Math.round(ratio*99)].ratio], y:[0,2.2], showlegend:false, mode:'lines',line:{width:1,color:'#555'} }]) var layout = { height: 270, width: width-30, font: font, hovermode:'closest', showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 50,t: 0}, xaxis: { title:'Ratio solar : wind capacity', showgrid: true, zeroline: false,tickformat: '.1f', ticks:'outside', }, yaxis: { title: 'Hours', showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside' } }; const div=container(`Daily storage requirement by month and ratio of solar to wind capacity to flatten the diurnal for a combined plant. Maximum storage requirement for the year in red. Optimum ratio is ${d3.format('.2f')(optimum_ratio.ratio)}MW solar per MW wind with ${d3.format('.1f')(optimum_ratio.store_max)} hours of storage.`) plt.newPlot(div, data, layout,{displayModeBar: false}); div.on('plotly_hover', d => { var curveNumber = d.points[0].curveNumber var vals = div.data.map((_, i) => i === curveNumber ? 1 : 0.2) plt.restyle(div, 'opacity', vals) }) div.on('plotly_unhover', d => { var curveNumber = d.points[0].curveNumber var vals = div.data.map((_, i) => i === curveNumber ? 1 : 1) plt.restyle(div, 'opacity', vals) }) return div }3b:T66d,{ var dat = ratios[Math.round(ratio*99)] var data = [ { y:dat.monthly_av_cfs, name: `Unika wind and Ilute solar plants with ${ratio}MW solar / wind`, x: [...Array(12).keys()].map(v=>v+1), text: dat.monthly_av_cfs.map(v=>d3.format('.2f')(v)), mode: 'lines+markers', line: {shape:'spline', color: colors.combined[5], width:3}, type: 'scatter', showlegend:true, hoverinfo:'x+y', textposition:'top-center' } , { x: [...Array(12).keys()].map(v=>v+1), y: ngonye_cfs,name:'Ngonye Falls hydro', text: ngonye_cfs.map(mnth=>(d3.format('.2f')(mnth))), type: 'scatter', mode: 'lines+markers', textposition:'outside', hoverinfo: 'name+y', showlegend:true, line: {shape:'spline', color: make_trans(colors.ngonye,0.8), width:3}, textposition:'bottom' } ] var layout = { height: 200, width: d3.min([width-30,800]), font: font, hovermode:'closest', showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { tickvals: [ 1,2,3,4,5,6,7,8,9,10,11,12 ], ticktext:['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], showgrid: false, zeroline: false, ticks:'outside', dtick:1, }, yaxis: { title: 'Capacity factor', showgrid: true, zeroline: false, tickformat: '.1f', ticks:'outside', range:[0,1.05],dtick:0.2 } }; const div=container(`Average monthly capacity factor for a combined wind, solar plant with ${ratio}MW solar per MW wind and the Ngonye Falls hydro plant.`) plt.newPlot(div, data, layout,{displayModeBar: false}); return div }3c:T7ac,{ var dat = ratios[Math.round(ratio*99)] var data = [ { y:dat.monthly_av_cfs, x: [...Array(12).keys()].map(v=>v+1), text: dat.monthly_av_cfs.map(v=>d3.format('.2f')(v)), mode: 'lines', line: {shape:'spline', color: 'grey', width:1.5}, type: 'scatter', showlegend:false, hoverinfo:'x+y', textposition:'top-center' } , { x: [...Array(12).keys()].map(v=>v+1), y: ngonye_cfs, text: ngonye_cfs.map(mnth=>(d3.format('.2f')(mnth))), type: 'scatter', mode: 'lines', textposition:'outside', hoverinfo: 'name+y', showlegend:false, line: {shape:'spline', color: 'grey', width:1.5}, textposition:'bottom' } , { x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.combined_cf, text: sel_ratio_hydro.combined_cf.map(mnth=>(d3.format('.2f')(mnth))), type: 'scatter', mode: 'lines+markers+text', textposition:'outside', hoverinfo: 'none', showlegend:false, line: {shape: 'spline', color: colors.combined[5], width:3}, marker: {size: 8}, textposition:'bottom' }, ] var layout = { height:200, width: d3.min([width-30,800]), font: font, margin: {l: 50,r: 5,b: 30,t: 0}, showlegend: true, legend: {orientation: 'h', x: 0,xanchor: 'left',y: 1}, xaxis: { showgrid: false, zeroline: false, ticks:'outside', tickvals: [ 1,2,3,4,5,6,7,8,9,10,11,12 ], ticktext:['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], }, yaxis: { title: 'Capacity factor', range:[0,1], zeroline: false, showline: false, separatethousands:true, tickformat: '.1f' } }; const div = container(`Capacity factor by month for the combined output of hydro (Ngonye Falls), wind (Unika 1) and solar (Ilute 1) with a capacity ratio of ${d3.format('.2f')(ratio_hydro)}MW of wind power for each MW of hydro power capacity.`) plt.newPlot(div, data, layout,{displayModeBar: false}); return div }3d:T461,{ var data = [ { x: ratios_hydro.map(v=>v.ratio_hydro), y: ratios_hydro.map(v=>v.combined_cf_range), text: sel_ratio_hydro.combined_cf.map(mnth=>(d3.format('.2f')(mnth))), type: 'scatter', mode: 'lines', hoverinfo: 'x+y', showlegend:false, line: {shape: 'spline', color: colors.combined[5], width:3}, }, ] data=data.concat([{ x:[sel_ratio_hydro.ratio_hydro,sel_ratio_hydro.ratio_hydro], y:[0,1.1], showlegend:false, mode:'lines',line:{width:1,color:'#555'} }]) var layout = { height:240, width: d3.min([width-30,800]), font: font, margin: {l: 70,r: 5,b: 45,t: 0}, showlegend: true, legend: {orientation: 'h', x: 0,xanchor: 'left',y: 1}, xaxis: { showgrid: false, zeroline: false, ticks:'outside', title: 'Ratio wind : hydro capacity', tickformat: '.1f' }, yaxis: { title: 'Change
capacity factor', range:[0,1.1], zeroline: false, showline: false, separatethousands:true, tickformat: '.1f' } }; const div = container('') plt.newPlot(div, data, layout,{displayModeBar: false}); return div }3e:T4b4,{ return html`

` }3f:T86e,{ var data = [ { x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.months.map(v=>v.ngonye_power), name: 'Hydro', type: 'scatter', mode: 'lines', hoverinfo: 'name+y', stackgroup:'one', showlegend:true, line: {shape: 'spline', color: colors.ngonye}, marker: {size: 8}, }, { x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.months.map(v=>v.unika_power),name: 'Wind', type: 'scatter', mode: 'lines', hoverinfo: 'name+y', stackgroup:'one', showlegend:true, line: {shape: 'spline', color: colors.unika[5]}, marker: {size: 8}, },{ x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.months.map(v=>v.ilute_power), name: 'Solar', type: 'scatter', mode: 'lines', hoverinfo: 'name+y', stackgroup:'one', showlegend:true, line: {shape: 'spline', color: colors.ilute[5]}, marker: {size: 8}, },{ x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.combined_power, name: 'Total', text: sel_ratio_hydro.combined_power.map(v=>d3.format('.0f')(v)), type: 'scatter', mode: 'lines+markers+text', hoverinfo: 'name+y', showlegend:false, line: {shape: 'spline', color: 'grey'}, marker: {size: 8}, textposition:'top' } ] var layout = { height:220, width: d3.min([width-30,800]), font: font, margin: {l: 50,r: 5,b: 30,t: 0}, showlegend: true, legend: {orientation: 'h', x: 0,xanchor: 'left',y: 1}, xaxis: { showgrid: false, zeroline: false, ticks:'outside', tickvals: [ 1,2,3,4,5,6,7,8,9,10,11,12 ], ticktext:['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], }, yaxis: { title: 'MW',range:[0,360], zeroline: false, showline: false, separatethousands:true, tickformat: '.0f' } }; const div = container(`P50 power for the combined hydro (Ngonye ${d3.format('.0f')(sel_ratio_hydro.capacities.ngonye)}MW) wind (Unika ${d3.format('.0f')(sel_ratio_hydro.capacities.unika)}MW) and solar (Ilute ${d3.format('.0f')(sel_ratio_hydro.capacities.ilute)}MW) plants.`) plt.newPlot(div, data, layout,{displayModeBar: false}); return div }40:T77c,{ var dat = ratios[Math.round(ratio*99)] var data = [ { x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.months.map(v=>v.ngonye_energy),name: 'Ngonye', type: 'bar', mode: 'lines', hoverinfo: 'name+y', stackgroup:'one', showlegend:true, marker: {color: make_trans(colors.ngonye,0.6)}, textposition:'bottom' }, { x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.months.map(v=>v.unika_energy),name: 'Unika', type: 'bar', mode: 'lines', hoverinfo: 'name+y', stackgroup:'one', showlegend:true, marker: {color: make_trans(colors.unika[5],0.6)}, textposition:'bottom' },{ x: [...Array(12).keys()].map(v=>v+1), y: sel_ratio_hydro.months.map(v=>v.ilute_energy), name: 'Ilute', type: 'bar', mode: 'lines', hoverinfo: 'name+y', stackgroup:'one', showlegend:true, marker: {color: make_trans(colors.ilute[5],0.6)}, textposition:'bottom' } ] var layout = { height: 220, width: d3.min([width-30,800]), font: font, hovermode:'closest', barmode:'stack', showlegend: true, legend: {orientation: 'h',xanchor: 'left', x:0, y: 1.1}, margin: {l: 50,r: 5,b: 30,t: 0}, xaxis: { tickvals: [ 1,2,3,4,5,6,7,8,9,10,11,12 ], ticktext:['Jan','Feb','Mar','Apr','May','Jun','Jul','Aug','Sep','Oct','Nov','Dec'], showgrid: false, zeroline: false, ticks:'outside', dtick:1, }, yaxis: { title: 'GWh', showgrid: true, zeroline: false, tickformat: '.0f', ticks:'outside', range:[0,240], } }; const div=container(`Combined average monthly energy output for the combined hydro (Ngonye ${d3.format('.0f')(sel_ratio_hydro.capacities.ngonye)}MW) wind (Unika ${d3.format('.0f')(sel_ratio_hydro.capacities.unika)}MW) and solar (Ilute ${d3.format('.0f')(sel_ratio_hydro.capacities.ilute)}MW) plants.`) plt.newPlot(div, data, layout,{displayModeBar: false}); return div }41:T824,ratios_hydro = { let steps = 100 let out = [...Array(steps).keys()].map(v=>{ return { ratio_hydro: (1/(steps-1))*v*2 } }) out.map(rat => { rat.capacities = { ngonye: ngonye_capacity, unika: ngonye_capacity * rat.ratio_hydro, ilute: ngonye_capacity * rat.ratio_hydro * ratio, } rat.capacities.wind_solar = rat.capacities.unika+rat.capacities.ilute rat.capacities.total = rat.capacities.ngonye+rat.capacities.wind_solar rat.capacities.storage = rat.capacities.wind_solar * ratios[Math.round(ratio*99)].store_max rat.months = [...Array(12).keys()].map(month_no=> { return { ngonye_power: ngonye_cfs[month_no]*rat.capacities.ngonye, unika_power: unika_monthly_cfs[month_no]* rat.capacities.unika, ilute_power: ilute_monthly_cfs[month_no]* rat.capacities.ilute, combined_cfs: ((ngonye_cfs[month_no]*rat.capacities.ngonye)+(ratios[Math.round(ratio*99)].monthly_av_cfs[month_no]*(rat.capacities.wind_solar))) / (rat.capacities.total) } }) rat.months.map((month, month_no)=>{ month.combined_power=month.ngonye_power+month.unika_power+month.ilute_power month.ngonye_energy = month.ngonye_power * 24 * month_days(month_no+1)/1000 month.ilute_energy = month.ilute_power * 24 * month_days(month_no+1)/1000 month.unika_energy = month.unika_power * 24 * month_days(month_no+1)/1000 month.combined_energy = month.ngonye_energy + month.ilute_energy + month.unika_energy return month }) rat.combined_cf=[...Array(12).keys()].map(month_no=> { return ((ngonye_cfs[month_no]*rat.capacities.ngonye)+(ratios[Math.round(ratio*99)].monthly_av_cfs[month_no]*(rat.capacities.wind_solar))) / (rat.capacities.total) }) rat.combined_power = rat.combined_cf.map(v=>v*rat.capacities.total) rat.total_energy=d3.sum(rat.months,v=>v.combined_energy) rat.total_cf = rat.total_energy / (rat.capacities.total * 24 * 365) * 1000 rat.combined_cf_range=d3.max(rat.combined_cf)-d3.min(rat.combined_cf) }) return out } 42:[{"id":"1229021ed21c6cf79e5377cfe6f35793db9905894188d735be8e79728b8617a4113afded329733950e39b60e208561194248b6cdd74d98ba103c6786a6e60b65","href":"https://static.observableusercontent.com/files/1229021ed21c6cf79e5377cfe6f35793db9905894188d735be8e79728b8617a4113afded329733950e39b60e208561194248b6cdd74d98ba103c6786a6e60b65","name":"buffalo.png","type":"image/png","lastModified":1662103936236.725,"size":43736},{"id":"c454c304237cb8f85550eb2ceaad3284679841e19331e79cf71323e43ee22d583e252e9d2c8b5c467714a865a81396cac89a93c5617396b12bf180a95e951011","href":"https://static.observableusercontent.com/files/c454c304237cb8f85550eb2ceaad3284679841e19331e79cf71323e43ee22d583e252e9d2c8b5c467714a865a81396cac89a93c5617396b12bf180a95e951011","name":"unika_p50@1.csv","type":"text/csv","lastModified":1633439293155.964,"size":1267},{"id":"ad066e6faced1438ecf9bce03e9d10814ebaa8e03e78d8a8f25382978e162904ccc312cb6b0fc8b8e4625eb8f9420dba1bc0748f2063ec447b6398a0cb25100f","href":"https://static.observableusercontent.com/files/ad066e6faced1438ecf9bce03e9d10814ebaa8e03e78d8a8f25382978e162904ccc312cb6b0fc8b8e4625eb8f9420dba1bc0748f2063ec447b6398a0cb25100f","name":"ilute_p50_cfs.csv","type":"text/csv","lastModified":1662039527657.751,"size":1996},{"id":"efda8ed935925a23f41d4ef95d5172ddecb30205c4e5ec0b3df26575ef6091ec0dc73104eb8cdcb88782b7aa625d8560080e47cba746310be7e6ba5a9c2cf0d3","href":"https://static.observableusercontent.com/files/efda8ed935925a23f41d4ef95d5172ddecb30205c4e5ec0b3df26575ef6091ec0dc73104eb8cdcb88782b7aa625d8560080e47cba746310be7e6ba5a9c2cf0d3","name":"unika_p50_cfs.csv","type":"text/csv","lastModified":1662038887029.352,"size":2131},{"id":"f97fdeb7341d3f752a7271f84a46608de7c558c00d96c577adeee0965b8603a8c97870615569a9fa16d0c6fa12d7e7b4892657bad77501f966f08b8e13e8e6b9","href":"https://static.observableusercontent.com/files/f97fdeb7341d3f752a7271f84a46608de7c558c00d96c577adeee0965b8603a8c97870615569a9fa16d0c6fa12d7e7b4892657bad77501f966f08b8e13e8e6b9","name":"APP logo.png","type":"image/png","lastModified":1662103947819.821,"size":92844}] 2f:{"title":"Hydro, Wind, Solar and Storage Combinations","cells":[{"id":366,"value":"html`\n\n

Buffalo Energy and African Power Projects

Hydro, Wind, Solar and Storage Combinations

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":1048,"value":"

\nBuffalo Energy and African Power Projects are collaborating on the development of three complimentary, large-scale, grid-connected renewable energy projects as well as battery-backed energy storage in Zambia. In combination these plants could provide predictable, firm power for industrial offtakers. \n

","pinned":false,"hidden":false,"mode":"html"},{"id":1475,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":1484,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":1029,"value":"

Diurnal firm power from Wind and Solar with Storage

","pinned":false,"hidden":false,"mode":"html"},{"id":1224,"value":"The Unika 1 wind project (planned 200MW) and Ilute 1 solar pv project (25MW with site for 100MW) are both late-stage development renewable power projects in Zambia. Solar PV and to a lesser extent wind power both exhibit a strong diurnal production profile. Solar PV has zero output during the night and conversely wind speeds are, on average, higher during the night.","pinned":false,"hidden":false,"mode":"html"},{"id":1267,"value":"$33","pinned":false,"hidden":false,"mode":"ojs"},{"id":189,"value":"$34","pinned":false,"hidden":false,"mode":"ojs"},{"id":1233,"value":"Because of these complimentary daily production profiles, combining the output of the two plants produces a much smoother diurnal power profile. Due to the seasonal nature of the output of the wind plant the effect of mixing the output of the two projects changes through the year. ","pinned":false,"hidden":false,"mode":"html"},{"id":656,"value":"$35","pinned":false,"hidden":false,"mode":"ojs"},{"id":1292,"value":"The shape of the daily production profiles for the combined plant depend on the proportion of capacity provided by the two plants. The daily production profile for the combined plants will never be entirely flat.","pinned":false,"hidden":false,"mode":"html"},{"id":467,"value":"viewof ratio = {\n const form = html``;\n form.oninput = () => {\n form.querySelector(\"[id=rate_disp]\").textContent =\n form.rate.valueAsNumber;\n form.value = form.rate.valueAsNumber;\n };\n form.oninput();\n return form;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1228,"value":"$36","pinned":false,"hidden":false,"mode":"ojs"},{"id":1400,"value":"To produce completely consistent output, intraday storage capacity needs to be added to the system. This could be in the form of batteries or using hydro power reservoirs. The storage need not be co-located with either the wind or solar plants and if it was provided by hydro reservoirs then it almost certainly would not.

There would be beneftis for co-locating storage with either the wind or solar plants (or both) where possible including shared O&M resources, grid access and reduced transmission losses and costs.","pinned":false,"hidden":false,"mode":"html"},{"id":1455,"value":"$37","pinned":false,"hidden":false,"mode":"ojs"},{"id":584,"value":"$38","pinned":false,"hidden":false,"mode":"ojs"},{"id":1319,"value":"The amount of storage required to completely flatten the daily output of the combined plant depends on the relative proportion of capacity for the wind and solar plants and the month. Greater storage capacity is particularly needed in months where the wind plant has a higher diurnal range of output.","pinned":false,"hidden":false,"mode":"html"},{"id":1355,"value":"$39","pinned":false,"hidden":false,"mode":"ojs"},{"id":1375,"value":"To entirely flatten the dirunal output in every month then the storage capacity (in hours) must be sized for the month with the greatest storage requirement. For plant ratios with a high range in monthly storage requirement (between the month with the highest storage requirement and the month with the lowest) the storage will either be insufficient in some months or underutilised in some month. Both situations lead to inefficieny. ","pinned":false,"hidden":false,"mode":"html"},{"id":670,"value":"$3a","pinned":false,"hidden":false,"mode":"ojs"},{"id":1383,"value":"The ratio of solar capacity to wind capacity that minimises the relative storage requirement (in hours) can be determined by plotting the storage required to completely flatten the diurnal output of the combined plant for a range of capacity ratios for each month. For the Unika and Ilute plants this shows that ${d3.format('.2f')(optimum_ratio.ratio)}MW of solar per MW of wind capacity minimises the storage requirement at ${d3.format('.1f')(optimum_ratio.store_max)} hours to flatten the average diurnal output. ","pinned":false,"hidden":false,"mode":"html"},{"id":879,"value":"

Annual Capacity with Hydro and diurnal firm Wind, Solar and Storage","pinned":false,"hidden":false,"mode":"html"},{"id":1406,"value":"A combination of wind and solar backed by storage can deliver constant, statistically firm, baseload power on a daily basis. However a combined plant will still have a seasonal production curve particularly due to the season nature of the wind resource which is higher during the dry season, April to October and drops during the rains season from November to March.","pinned":false,"hidden":false,"mode":"html"},{"id":783,"value":"$3b","pinned":false,"hidden":false,"mode":"ojs"},{"id":1427,"value":"The production profile for the run-of-river Ngonye Falls hydropower project is driven by the hydrology of the Zambezi river with increased output January to June and lower output from July to December. Because of the size of the catchment and characteristic hydrology, the Ngonye Falls project has a completely constant diurnal (intraday) power profile and delivers baseload without storage.","pinned":false,"hidden":false,"mode":"html"},{"id":923,"value":"$3c","pinned":false,"hidden":false,"mode":"ojs"},{"id":1429,"value":"Combining output from the wind, solar and hydro power plants can produce a more constant average output through the year.

\n\nThe capacity of the hydropower plant is determined by the hydrology of the river and topography of the plant site and is fixed at 180MW. The final variability in output of the combined power stations depends on the ratio of wind and solar capacity to the fixed hydropower capacity.","pinned":false,"hidden":false,"mode":"html"},{"id":1196,"value":"$3d","pinned":false,"hidden":false,"mode":"ojs"},{"id":1445,"value":"Depending on the ratio of wind (and therefore solar) power capacity to hydropower capacity the combined plant output has more or less variation during the year. In general adding more wind and solar capacity produces a flatter annual production curve necessitating less 'topup'power from other sources to maintain constant consumption.

\nHowever there is a diminishing return in additional wind and hydro capacity and this also requires additional storage to produce a flat diurnal output.

\nThe current plan for the Unika 1 wind project envisages 200MW of wind capacity which corresponds to a hydro to wind capacity ratio of around 1.12.","pinned":false,"hidden":false,"mode":"html"},{"id":901,"value":"viewof ratio_hydro = {\n const form = html`
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\n
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Wind to hydro Capacity Ratio
\n
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MW/MW
\n
\n
\n
`;\n form.oninput = () => {\n form.querySelector(\"[id=rate_disp]\").textContent =\n form.rate.valueAsNumber;\n form.value = form.rate.valueAsNumber;\n };\n form.oninput();\n return form;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":973,"value":"$3e","pinned":false,"hidden":false,"mode":"ojs"},{"id":941,"value":"$3f","pinned":false,"hidden":false,"mode":"ojs"},{"id":988,"value":"$40","pinned":false,"hidden":false,"mode":"ojs"},{"id":819,"value":"

\n

Setup

","pinned":false,"hidden":false,"mode":"html"},{"id":1056,"value":"colors={\n return {\n ngonye: '#746cd3',\n unika: d3.quantize(d3.interpolateHcl(\"#1e8449\", \"#45b39d\"), 12),\n ilute: d3.quantize(d3.interpolateHcl(\"#d68910\", \"#f4d03f\"), 12),\n combined: d3.quantize(d3.interpolateHcl(\"#922b21\", \"#797d7f\"), 12),\n storage: d3.quantize(d3.interpolateHcl(\"#2874a6\", \"#aed6f1\"), 12),\n \n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":1182,"value":"sel_ratio_hydro=ratios_hydro[Math.round((ratio_hydro/2)*99)]","pinned":false,"hidden":false,"mode":"ojs"},{"id":1140,"value":"$41","pinned":false,"hidden":false,"mode":"ojs"},{"id":1518,"value":"optimum_ratio.combined_cfs","pinned":true,"hidden":false,"mode":"ojs"},{"id":768,"value":"optimum_ratio=ratios.filter(w=>w.store_max==d3.min(ratios.map(v=>v.store_max)))[0]","pinned":false,"hidden":false,"mode":"ojs"},{"id":644,"value":"ratios = {\n let steps = 100\n let ret = [...Array(steps).keys()].map(v=>{\n return {\n ratio: (1/(steps-1))*v\n }\n })\n\n ret.map(ratio => {\n ratio.combined_cfs = [...Array(12).keys()].map(month_no=>{\n return [...Array(24).keys()].map(hour_no=> ((ilute_cfs[month_no][hour_no]*ratio.ratio) + unika_cfs[month_no][hour_no])/(1+ratio.ratio))\n })\n\n ratio.monthly_av_cfs = [...Array(12).keys()].map(month_no=>{\n return d3.mean(ratio.combined_cfs[month_no])\n })\n\n ratio.monthly_store = [...Array(12).keys()].map(month_no=>{\n return d3.sum(ratio.combined_cfs[month_no].map(v=>v>ratio.monthly_av_cfs[month_no]?v-ratio.monthly_av_cfs[month_no]:0))\n })\n ratio.store_hours = [...Array(12).keys()].map(month_no=>{\n return ratio.combined_cfs[month_no].filter(v=>v>ratio.monthly_av_cfs[month_no]).length\n }) \n ratio.store_max = d3.max(ratio.monthly_store)\n ratio.store_range = d3.max(ratio.monthly_store) - d3.min(ratio.monthly_store) \n \n return ratio\n })\n\n return ret\n}\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":24,"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":25,"value":"function month_days(i) {\n if(i === 4 || i === 6 || i === 9 || i === 11) {\n\t\treturn 30\n\t} else if(i === 2) {\n\t\treturn 28.25\n\t} else {\n\t\treturn 31\n\t}\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":825,"value":"ilute_monthly_cfs=ilute_cfs.map(month=>d3.mean(month))","pinned":false,"hidden":false,"mode":"ojs"},{"id":1249,"value":"ilute_hourly_cfs = [...Array(24).keys()].map(hour_no=>{\n return d3.mean(ilute_cfs.map(month=>month[hour_no]))\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":1255,"value":"unika_hourly_cfs = [...Array(24).keys()].map(hour_no=>{\n return d3.mean(unika_cfs.map(month=>month[hour_no]))\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":827,"value":"unika_monthly_cfs=unika_cfs.map(month=>d3.mean(month))","pinned":false,"hidden":false,"mode":"ojs"},{"id":517,"value":"unika_cfs = [...Array(12).keys()].map(month_no=>{\n return [...Array(24).keys()].map(hour_no=> parseFloat(unika_p50_cfs[hour_no][month_no+1]))\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":526,"value":"ilute_cfs = [...Array(12).keys()].map(month_no=>{\n return [...Array(24).keys()].map(hour_no=> parseFloat(ilute_p50_cfs[hour_no][month_no+1])).map(v=>v?v:0)\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":514,"value":"ilute_p50_cfs = FileAttachment(\"ilute_p50_cfs.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":516,"value":"unika_p50_cfs = FileAttachment(\"unika_p50_cfs.csv\").csv()","pinned":false,"hidden":false,"mode":"ojs"},{"id":886,"value":"ngonye_capacity=180","pinned":false,"hidden":false,"mode":"ojs"},{"id":882,"value":"ngonye_cfs = ngonye_calmonths.map((month, month_no) => month.Energy_median / (month_days(month_no+1) * ngonye_capacity *24 ))","pinned":false,"hidden":false,"mode":"ojs"},{"id":859,"value":"ngonye_calmonths = ngonye_calmonths_water.map(v => { return {...v}}).sort((a, b) => a.Month-b.Month)","pinned":false,"hidden":false,"mode":"ojs"},{"id":857,"value":"ngonye_calmonths_water=(await d3.csv(\"https://gis.westernpower.org/data/output_data/scenarios/extendhead_pe_calmonthly.csv?\" + Math.floor(Math.random() * 1000), d3.autoType))","pinned":false,"hidden":false,"mode":"ojs"},{"id":42,"value":"html`\n

Imports

\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":861,"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":680,"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":52,"value":"font = ({\n family: 'Courier New, monospace',\n size: 13,\n color: '#6f6f6f'\n})","pinned":false,"hidden":false,"mode":"ojs"},{"id":166,"value":"html`\n\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":46,"value":"style=html`css\n`","pinned":false,"hidden":false,"mode":"ojs"},{"id":28,"value":"luxon = require(\"luxon@1/build/amd/luxon.js\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":30,"value":"DateTime = luxon.DateTime","pinned":false,"hidden":false,"mode":"ojs"},{"id":32,"value":"d3 = require(\"d3@6\")","pinned":false,"hidden":false,"mode":"ojs"},{"id":34,"value":"plt = require(\"https://cdn.plot.ly/plotly-latest.min.js\")","pinned":false,"hidden":false,"mode":"ojs"}],"files":"$W42","stdlib":"1","titling":"auto"}