Case Study: Blast Furnace Gas Distribution

Transcription

1 Consultancy. Project Delivery. Innovation. Case Study: Blast Furnace Gas Distribution Dynamic Simulation models distribution of blast gas across a steel mill and optimises modifications Client: Multinational Steel Company

2 Who are we? Process engineering consultancy Specialising in advanced modelling techniques, to give answers that are more accurate, reliable and robust Expertise in HYSYS Dynamics and Dynsim Decades of process and mechanical engineering experience Combine cutting edge simulation with real world understanding, to provide you with solutions that are effective and practical. Core team of eight engineers, supported by a wide network of associates. Extensive simulation experience across a range of industries Page 2

3 Project Background Proposed new power plant will consume large amounts of blast gas Best location for new blast gas connection unclear. Pipes are large >84, so high capital cost implications. Potential capital cost savings by using 96 against 108 pipes. Conventional hydraulic calculations suggest that pressure drop is a problem due to proposed location but does not take into account fluctuations in pressure Low pressure at inlet to power plant risks tripping adjacent power plant as no provision to cope with low pressure. Dynamic model expected to converge a better pressure profile and take into account transient features that affect system pressure Page 3

4 Proposed Tie Points Straight Length for metering section Location of New Power Plant Page 4

5 Dynamic Simulation Scope Blast Furnace Outlet Blast Gas Distribution Main to Consumers All Consumers (Stoves, Power Plants, Coke Ovens) Flares and Pressure Control Gas Holder Model developed from isometrics, plant survey, trended operating data and plant trials. Page 5

6 Simulation Model Hysys Dynamics Power Plant Flares 1 & 2 Gas Holder Power Plant Coke Ovens Blast Furnaces & Stoves New Power Plant Boilers Page 6

7 Pressure, mbarg Flow, knm 3 /hr Rating of Models Continuous changes in system pressure observed from plant data Dynamic fluctuations in production and consumption built into model Equipment cycling and controller behaviour reproduced in model Causes of pressure instability explained by modelling complex coincident events May-15 00:00:00 03-May-15 00:57:36 03-May-15 01:55:12 03-May-15 02:52:48 03-May-15 03:50:24 Page 7

8 Main Modelling Observations Large pressure fluctuations originate from a combination of rapid changes in stoves blast gas consumption and furnace gas production Largest fluctuation originate from older furnace as stoves consumption erratic and furnace top cone valve oversized or poorly tuned Gas holder level sensitive to flare flows due to its physical location on site Some water seals present high pressure drops suggesting partial blockage. Gas temperature seen to fall quickly in pipes, resulting in significant condensation of water vapour. Page 8

9 Design Scenarios Scenarios only run when model fully rated and accurately reflects plant operation including equipment cycling and fluctuations Client-led scenario definition involving all team members to ensure that scenarios are relevant and prioritised Proposed tie-in points examined with a variety of flow conditions reflecting current and future operating states Looked at the impact of a sudden trip on the system and amount of recovery time available to operator Examined commissioning a larger inlet line to Gas Holder to dampen fluctuations and improve trip recovery time Page 9

10 Conclusion The main purpose of the study was to examine best location for new pipe tie ins, however, other benefits were realised when the model was available Concluded that the proposed tie in locations are not feasible at the maximum design rates without making the following plant changes: 1) Gas train modifications to adjacent power plant to cope with lower inlet pressures 2) Stabilising blast gas pressures from older furnace 3) Commissioning larger line into the gas holder to dampen pressure spikes Page 10

11 Summary Dynamic Model demonstrated that a blast gas distribution system could be modelled with sufficient detail to allow system characteristics to be analysed Static and transient characteristics that were invisible to a static hydraulic model or through simple analysis of excel data were better explained Ease of running scenarios, engaged interest from relevant parties and helped process understanding Restarted optimisation projects previously shelved through lack of data Avoided project failure, by identifying significant shortcomings in proposed design Page 11

12 Summary Consultancy. Project Delivery. Innovation. Page 12 Please get in touch to find out how we can help your business today. E: W: flexprocess.co.uk T: