Energy Efficiency Severstal

2020 Highlights

In 2020 we saved 6.1% of energy costs compared to 2019 (excluding the use of natural gas in the process fuel used in hot metal production). Cherepovets Steel Mill made the biggest contribution in this result.

Power generation and consumption by Cherepovets Steel Mill, thousand kWh, GRI 302-1

Year	2016	2017	2018	2019	2020
Total consumption	6 077 806	6 096 821	6 280 738	6 274 316	6 199 626
External sources	1 686 531	1 655 118	1 714 917	1 884 579	1 530 575
Internal production	4 391 275	4 441 703	4 565 820	4 389 735	4 669 047
TPP-SS	2 602 942	2 623 499	2 661 744	2 494 701	2 730 751
TPP-PS	1 456 400	1 509 456	1 616 004	1 598 709	1 672 103
GNCT	199 477	191 765	158 274	166 399	141 827
TSC	132 455	116 983	129 798	129 926	124 367
Use in shops	5 574 273	5 610 497	5 809 378	5 795 592	5 719 739
Process consumption	5 641 968	5 666 700	5 860 781	5 844 529	5 771 657
Losses	67 695	56 203	51 403	48 937	51 918
Sales to third parties	432 650	426 542	416 376	426 074	424 560
Non-process consumption	3 188	3 579	3 582	3 713	3 409

Power consumption at other key businesses of Severstal, thousand kWh GRI 302-1

Business	2016	2017	2018	2019	2020
Olcon	388 630	391 975	426 555	446 915	458 901
Karelsky Okatysh	1 592 631	1 626 482	1 604 139	1 584 548	1 583 107
Severstal Metiz	155 157	152 509	160 117	149 891	157 571
Severstal Steel Ropes, Volgograd Branch	32 914	35 181	37 287	36 131	36 924
OSPAZ	46 463	46 323	44 907	41 058	39 392
Yakovevskiy Mine	35 678	40 123	45 427	50 472	99 100
Izhora Pipe Mill	57 602	61 062	58 605	51 096	36 089
Vorkutaugol	536 799	519 410	533 477	533 693	546 990

2020 Key Initiatives

As a part of our large-scale energy conservation investment programme, Cherepovets Steel Mill deployed a machine learning model to automate the operation of air compressors.

The software redistributes the performance of individual compressors so that the total amount of compressed air stays the same while the overall consumption goes down. Our innovations resulted in the average 2 kWh per thousand cubic metres reduction in specific power consumption.

Vorkutaugol does not have its own power generation and is a single consumer on the wholesale electricity market. It rolled out a data collection system connected to 2.5 thousand units of metering equipment. Predictive analysis with machine learning helps us improve energy consumption forecasting (by 20-25% monthly), minimize our losses due to inaccurate forecasts, and eliminate unauthorized connections to power grids and electricity theft. We are saving up to $10 million per year.

Energy Efficiency

2020 Highlights

In 2020 we saved 6.1% of energy costs compared to 2019 (excluding the use of natural gas in the process fuel used in hot metal production). Cherepovets Steel Mill made the biggest contribution in this result.

Power generation and consumption by Cherepovets Steel Mill, thousand kWh, GRI 302-1

In 2020 we saved 6.1% on energy costs compared to 2019 (excluding the use of natural gas in the process fuel used in hot metal production). Cherepovets industrial site made the biggest contribution in this result.

Fue mix at Cherepovets Steel Mill, %

Specific power consumption

Natural gas consumption, GRI 302-3

Power consumption at other key businesses of Severstal, thousand kWh GRI 302-1

2020 Key Initiatives

As a part of our large-scale energy conservation investment programme, Cherepovets Steel Mill deployed a machine learning model to automate the operation of air compressors.

Energy Efficiency

2020 Highlights

In 2020 we saved 6.1% of energy costs compared to 2019 (excluding the use of natural gas in the process fuel used in hot metal production). Cherepovets Steel Mill made the biggest contribution in this result.

Power generation and consumption by Cherepovets Steel Mill, thousand kWh, GRI 302-1

In 2020 we saved 6.1% on energy costs compared to 2019 (excluding the use of natural gas in the process fuel used in hot metal production). Cherepovets industrial site made the biggest contribution in this result.

Fue mix at Cherepovets Steel Mill, %

Specific power consumption

Natural gas consumption, GRI 302-3

Power consumption at other key businesses of Severstal, thousand kWh GRI 302-1

2020 Key Initiatives

As a part of our large-scale energy conservation investment programme, Cherepovets Steel Mill deployed a machine learning model to automate the operation of air compressors.

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