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Calculate potential load shift","submit.button.font_size":"custom","submit.button.font_size_custom":1.5,"submit.button.font_weight":"bold","submit.button.font_style":"normal","submit.button.margin":0,"submit.button.padding_factor":1,"submit.button.box_shadow":false,"submit.button.use_default_styles":true,"submit.button.bg_color_custom":true,"submit.button.bg_color":"#FFFFFF","submit.button.bg_color_hover_custom":true,"submit.button.bg_color_hover":"#F5F9FF","submit.button.font_color_custom":true,"submit.button.font_color":"#000000","submit.button.font_color_hover_custom":false,"submit.button.font_color_hover":null,"submit.button.border_width":1,"submit.button.border_style":"solid","submit.button.border_color_custom":false,"submit.button.border_color":null,"submit.button.border_transparency":1,"submit.button.border_radius":5,"submit.flex_direction":"column","submit.border":true,"submit.bg_type":"color","submit.bg_color_custom":false,"submit.bg_color":null,"submit.bg_image_src":"","submit.bg_image_size":"cover","result.variables":"key = CONCATENATE(q_3, '_', q_2)\nsplit_key = CONCATENATE(q_4, '_', q_2)\nit_capacity = IF('[key]'='US – California_2024', 1496, IF('[key]'='US – California_2030', 2296, IF('[key]'='Europe – Germany_2024', 1478, IF('[key]'='Europe – Germany_2030', 4038, IF('[key]'='Europe – Ireland_2024', 1651, IF('[key]'='Europe – Ireland_2030', 2519, IF('[key]'='ASEAN – Malaysia_2024', 508, IF('[key]'='ASEAN – Malaysia_2030', 12890, IF('[key]'='US – New York_2024', 1085, IF('[key]'='US – New York_2030', 1487, IF('[key]'='ASEAN – Philippines_2024', 51, IF('[key]'='ASEAN – Philippines_2030', 400, IF('[key]'='ASEAN – Singapore_2024', 1015, IF('[key]'='ASEAN – Singapore_2030', 1700, IF('[key]'='US – Texas_2024', 7315, IF('[key]'='US – Texas_2030', 14054, IF('[key]'='Europe – UK_2024', 1690, IF('[key]'='Europe – UK_2030', 3310, 0))))))))))))))))))\nload_factor = IF('[key]'='US – California_2024', 0.5, IF('[key]'='US – California_2030', 0.49, IF('[key]'='Europe – Germany_2024', 0.48, IF('[key]'='Europe – Germany_2030', 0.48, IF('[key]'='Europe – Ireland_2024', 0.48, IF('[key]'='Europe – Ireland_2030', 0.48, IF('[key]'='ASEAN – Malaysia_2024', 0.48, IF('[key]'='ASEAN – Malaysia_2030', 0.47, IF('[key]'='US – New York_2024', 0.5, IF('[key]'='US – New York_2030', 0.49, IF('[key]'='ASEAN – Philippines_2024', 0.48, IF('[key]'='ASEAN – Philippines_2030', 0.47, IF('[key]'='ASEAN – Singapore_2024', 0.48, IF('[key]'='ASEAN – Singapore_2030', 0.47, IF('[key]'='US – Texas_2024', 0.5, IF('[key]'='US – Texas_2030', 0.49, IF('[key]'='Europe – UK_2024', 0.48, IF('[key]'='Europe – UK_2030', 0.48, 0))))))))))))))))))\npue = IF('[key]'='US – California_2024', 1.32, IF('[key]'='US – California_2030', 1.23, IF('[key]'='Europe – Germany_2024', 1.45, IF('[key]'='Europe – Germany_2030', 1.29, IF('[key]'='Europe – Ireland_2024', 1.45, IF('[key]'='Europe – Ireland_2030', 1.29, IF('[key]'='ASEAN – Malaysia_2024', 1.5, IF('[key]'='ASEAN – Malaysia_2030', 1.35, IF('[key]'='US – New York_2024', 1.32, IF('[key]'='US – New York_2030', 1.23, IF('[key]'='ASEAN – Philippines_2024', 1.5, IF('[key]'='ASEAN – Philippines_2030', 1.35, IF('[key]'='ASEAN – Singapore_2024', 1.5, IF('[key]'='ASEAN – Singapore_2030', 1.35, IF('[key]'='US – Texas_2024', 1.32, IF('[key]'='US – Texas_2030', 1.23, IF('[key]'='Europe – UK_2024', 1.45, IF('[key]'='Europe – UK_2030', 1.29, 0))))))))))))))))))\npeak_demand = IF('[key]'='US – California_2024', 47571, IF('[key]'='US – California_2030', 50498, IF('[key]'='Europe – Germany_2024', 75305, IF('[key]'='Europe – Germany_2030', 105440, IF('[key]'='Europe – Ireland_2024', 6024, IF('[key]'='Europe – Ireland_2030', 6540, IF('[key]'='ASEAN – Malaysia_2024', 20092, IF('[key]'='ASEAN – Malaysia_2030', 33000, IF('[key]'='US – New York_2024', 28990, IF('[key]'='US – New York_2030', 32200, IF('[key]'='ASEAN – Philippines_2024', 14016, IF('[key]'='ASEAN – Philippines_2030', 20069, IF('[key]'='ASEAN – Singapore_2024', 7706, IF('[key]'='ASEAN – Singapore_2030', 10950, IF('[key]'='US – Texas_2024', 85544, IF('[key]'='US – Texas_2030', 138000, IF('[key]'='Europe – UK_2024', 50052, IF('[key]'='Europe – UK_2030', 59780, 0))))))))))))))))))\nsplit_nonai = IF('[split_key]'='JLL 2026_2024', 0.77, IF('[split_key]'='JLL 2026_2030', 0.5, IF('[split_key]'='McKinsey 2025_2024', 0.47, IF('[split_key]'='McKinsey 2025_2030', 0.29, 0))))\nsplit_train = IF('[split_key]'='JLL 2026_2024', 0.09, IF('[split_key]'='JLL 2026_2030', 0.13, IF('[split_key]'='McKinsey 2025_2024', 0.25, IF('[split_key]'='McKinsey 2025_2030', 0.28, 0))))\nsplit_infer = IF('[split_key]'='JLL 2026_2024', 0.14, IF('[split_key]'='JLL 2026_2030', 0.37, IF('[split_key]'='McKinsey 2025_2024', 0.28, IF('[split_key]'='McKinsey 2025_2030', 0.43, 0))))\nmarket_name = MID(q_3, FIND('–', q_3) + 2, 50)\nsplit_nonai_pct = ROUND([split_nonai] * 100, 0)\nsplit_train_pct = ROUND([split_train] * 100, 0)\nsplit_infer_pct = ROUND([split_infer] * 100, 0)\nit_nonai = [it_capacity] * [split_nonai]\nit_train = [it_capacity] * [split_train]\nit_infer = [it_capacity] * [split_infer]\navg_nonai = [it_nonai] * [pue] * [load_factor]\navg_train = [it_train] * [pue] * [load_factor]\navg_infer = [it_infer] * [pue] * [load_factor]\navg_total = [avg_nonai] + [avg_train] + [avg_infer]\nshift_nonai = [avg_nonai] * q_5 / 100\nshift_train = [avg_train] * q_6 / 100\nshift_infer = [avg_infer] * q_7 / 100\nshift_total = [shift_nonai] + [shift_train] + [shift_infer]\nshift_share = [shift_total] / [peak_demand] * 100\nit_nonai_r = ROUND([it_nonai], 0)\nit_train_r = ROUND([it_train], 0)\nit_infer_r = ROUND([it_infer], 0)\navg_nonai_r = ROUND([avg_nonai], 0)\navg_train_r = ROUND([avg_train], 0)\navg_infer_r = ROUND([avg_infer], 0)\navg_total_r = ROUND([avg_total], 0)\nshift_nonai_r = ROUND([shift_nonai], 0)\nshift_train_r = ROUND([shift_train], 0)\nshift_infer_r = ROUND([shift_infer], 0)\nshift_total_r = ROUND([shift_total], 0)\nshift_share_r = ROUND([shift_share], 1)","result.input":"\n

\n Load shifting could reduce demand on the grid by {{shift_total_r}} MW, equal to {{shift_share_r}}% of peak power demand in {{q_2}}.\n

\n\n\n\n

See how this is calculated

\n\n

\n \n

1. Data centre IT capacity

In {{market_name}}, {{q_2}}: {{it_capacity}} MW

\n\n \n

2. Split by workload type

IT capacity split using the {{q_4}} workload split:

\n \n \n \n \n \n \n \n \n \n \n \n \n \n

Workload	Share of IT capacity	IT capacity
Non-AI	{{split_nonai_pct}}%	{{it_nonai_r}} MW
AI training	{{split_train_pct}}%	{{it_train_r}} MW
AI inference	{{split_infer_pct}}%	{{it_infer_r}} MW

\n\n \n

3. Average load on the grid, by workload type

IT capacity × PUE ({{pue}}) × load factor ({{load_factor}}):

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n

Workload	IT capacity	Average load
Non-AI	{{it_nonai_r}} MW	{{avg_nonai_r}} MW
AI training	{{it_train_r}} MW	{{avg_train_r}} MW
AI inference	{{it_infer_r}} MW	{{avg_infer_r}} MW
Total	—	{{avg_total_r}} MW

\n\n \n

4. Potential load shifting, by workload type

Average load × flexibility depth:

\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n

Workload	Average load	Flexibility depth	Load shifting
Non-AI	{{avg_nonai_r}} MW	{{q_5}}%	{{shift_nonai_r}} MW
AI training	{{avg_train_r}} MW	{{q_6}}%	{{shift_train_r}} MW
AI inference	{{avg_infer_r}} MW	{{q_7}}%	{{shift_infer_r}} MW
Total	{{shift_total_r}} MW

\n\n \n

5. Share of peak power demand

\n {{shift_total_r}} MW ÷ {{peak_demand}} MW peak power demand in {{market_name}}, {{q_2}}\n =\n {{shift_share_r}}%\n

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