Energy efficiency assessment by process heating assessment and survey tool (PHAST) and feasibility analysis of waste heat recovery in the reheat furnace at a steel company

Si, Minxing; Thompson, Shirley; Calder, Kurtis

doi:10.1016/j.rser.2011.02.035

Cited by 39 publications

(19 citation statements)

References 11 publications

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“…The main impacts on scheduling parameters include: 1 Permissible charging temperature is different for various materials; 2 Initial forging temperature is different for various materials; 3 Maximum permissible temperature of the heating furnace is different according to the initial forging temperature; 4 The time of heating to the initial forging temperature is different for various materials; 5 The minimum and maximum heating preservation time is different for various materials.…”

Section: Characteristics Of Furnace Chargingmentioning

confidence: 99%

“…Generally, the shape of billets are round steel or square steel, and the main influence on scheduling parameters are as follows: 1 The permissible charging temperature and maximum heating preservation time are the same when the diameter (d) of round steel equals to side length (l) of the square steel section; 2 The heating time of billets is irrelevant to its length, only to the diameter or side length; 3 There are longer heating times if the billets have larger sizes under the same shape.…”

Section: Characteristics Of Furnace Chargingmentioning

confidence: 99%

“…Currently, studies about heating furnace energy conservation are mainly focused on equipment optimization and reform [1], waste gas heat recycling and utilization [2], development and application of new materials (non-quenched and tempered steel, alloy metals, and so on) [3][4][5], improvement of heat treatment process [6,7], etc. However, the studies about energy-saving scheduling are still limited.…”

Section: Introductionmentioning

confidence: 99%

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Research on Energy-Saving Scheduling of a Forging Stock Charging Furnace Based on an Improved SPEA2 Algorithm

Shen

Guan

et al. 2017

Sustainability

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Abstract:In order to help the forging enterprise realize energy conservation and emission reduction, the scheduling problem of furnace heating was improved in this paper. Aiming at the charging problem of continuous heating furnace, a multi-objective furnace charging model with minimum capacity difference and waiting time was established in this paper. An improved strength Pareto evolutionary algorithm 2 (SPEA2) algorithm was designed to solve this problem. The original fitness assignment strategy, crossover operator and population selection mechanism of SPEA2 are replaced with DOPGA (Domination Power of an Individual Genetic Algorithm), adaptive cross operator, and elitist strategy. Finally, the effectiveness and feasibility of the improved SPEA2 was verified by actual arithmetic example. The comparison of results gained from three methods shows the superiority of the improved SPEA2 in solving this problem. Compared with strength Pareto evolutionary algorithm (SPEA) and SPEA2, the improved SPEA2 can get a better solution without increasing time complexity, the heating time is reduced by total 93 min, and can save 7533GJ energy. The research in this paper can help the forging enterprise improve furnace utilization, reduce heating time and unnecessary heating preservation time, as well as achieve sustainable energy savings and emissions reduction.

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Section: Characteristics Of Furnace Chargingmentioning

confidence: 99%

Section: Characteristics Of Furnace Chargingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Research on Energy-Saving Scheduling of a Forging Stock Charging Furnace Based on an Improved SPEA2 Algorithm

Shen

Guan

et al. 2017

Sustainability

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“…Besides, Ren and Wang (2011) investigate the development status of iron and steel industry in Shandong province in response to the energy-saving and emission-reduction policy in China, and propose four measures--improving the technical equipment and equipment capacity, optimizing process, decreasing iron-steel ratio and optimizing energy structure--to realize the target of sustainable and low-carbon economic development in Shandong's iron and steel industry. Si et al (2011) analysis the feasibility of waste heat recovery and assesses energy efficiency at a steel company, Gerdau Ameristeel in Selkirk, Manitoba.…”

Section: Iron and Steel Industrymentioning

confidence: 99%

Engineering Management Based on the Reduction of Carbon Dioxide Emissions: a Review

2016

EJSD

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“…Si ve ark. [8] yaptıkları çalışmada Kanada, Manitoba'da bulunan bir çelik fabrikasının enerji verimliliğini değerlendirmiş ve atık ısı geri kazanımının olabilirliğini analiz etmişlerdir. Proses ısıtma değerlendirmesi ve gözden geçirme aracı (PHAST) ile yapılan çalışmada tav fırını verimi %60 olarak hesaplanmıştır.…”

Section: Gi̇ri̇ş (Introduction)unclassified

Endüstri̇yel Tav Firinlarinda Enerji̇ Tasarrufu Ve Emi̇syon Azaltim Firsatlari

Eyidoğan¹,

Kaya²,

Dursun³

et al. 2014

Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi

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ÖZETBu çalışmada, bir sanayi kuruluşunun LNG (sıvılaştırılmış doğalgaz) yakıtlı haddehane tav fırınında enerji verimliliği çalışması yapılmıştır. Bu kapsamda fırın işletme koşullarında çalışırken sıcaklık, basınç, hız ve yanma gazı ölçümleri yapılmış, ölçüm verileri kullanılarak kütle ve enerji dengesi kurulmuştur. Yapılan hesaplamalarda; fırın genel verimi %52,76 olarak bulunmuştur. Başlıca verim kayıpları; fırının yüksek hava fazlalık katsayısıyla çalıştırılması, reküperatör ısı transfer yüzey alanının yetersiz kalması ve fırın yüzeyi ısı kayıpları olarak belirlenmiştir.Anahtar Kelimeler: Haddehane tav fırını, reküperatör, enerji verimliliği, enerji tasarrufu, atık ısı geri kazanımı, emisyon azaltımı ENERGY SAVING AND EMISSION REDUCTION OPPORTUNITIES IN AN INDUSTRIAL ANNEALING FURNACES ABSTRACTIn this study, "energy efficiency" study has been performed for a LNG (Liquefied Natural Gas) fuel annealing furnace. Within this frame, temperature, pressure, velocity, and gas analysis measurements have been made and energy and mass balances have been formed. From the measured data, the furnace total efficiency was calculated as 52.76%. The main efficiency losses: operating furnace at high air excessiveness coefficient, inadequacy of air preheater heater (recuperator) heat transfer surface area and surface thermal losses.

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Energy efficiency assessment by process heating assessment and survey tool (PHAST) and feasibility analysis of waste heat recovery in the reheat furnace at a steel company

Cited by 39 publications

References 11 publications

Research on Energy-Saving Scheduling of a Forging Stock Charging Furnace Based on an Improved SPEA2 Algorithm

Research on Energy-Saving Scheduling of a Forging Stock Charging Furnace Based on an Improved SPEA2 Algorithm

Engineering Management Based on the Reduction of Carbon Dioxide Emissions: a Review

Endüstri̇yel Tav Firinlarinda Enerji̇ Tasarrufu Ve Emi̇syon Azaltim Firsatlari

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