• Energy Research

This paper presents an analytic hierarchy process (AHP)-fuzzy inference system (FIS) model to aid decision-makers in the risk assessment and mitigation of overseas steel-plant projects. Through a thorough literature review, the authors identified 57 risks associated with international steel construction, operation, and transference of new technologies. Pairwise comparisons of all 57 risks by 14 subject-matter experts resulted in a relative weighting. Furthermore, to mitigate human subjectivity, vagueness, and uncertainty, a fuzzy analysis based on the findings of two case studies was performed. From these combined analyses, weighted individual risk soring resulted in the following top five most impactful international steel project risks: procurement of raw materials; design errors and omissions; conditions of raw materials; technology spill prevention plan; investment cost and poor plant availability and performance. Risk mitigation measures are also presented, and risk scores are re-assessed through the AHP-FIS analysis model depicting an overall project risk score reduction. The model presented is a useful tool for industry performing steel project risk assessments. It also provides decision-makers with a better understanding of the criticality of risks that are likely to occur on international steel projects.

This paper presents an analytic hierarchy process (AHP)-fuzzy inference system (FIS) model to aid decision-makers in the risk assessment and mitigation of overseas steel-plant projects. Through a thorough literature review, the authors identified 57 risks associated with international steel construction, operation, and transference of new technologies. Pairwise comparisons of all 57 risks by 14 subject-matter experts resulted in a relative weighting. Furthermore, to mitigate human subjectivity, vagueness, and uncertainty, a fuzzy analysis based on the findings of two case studies was performed. From these combined analyses, weighted individual risk soring resulted in the following top five most impactful international steel project risks: procurement of raw materials; design errors and omissions; conditions of raw materials; technology spill prevention plan; investment cost and poor plant availability and performance. Risk mitigation measures are also presented, and risk scores are re-assessed through the AHP-FIS analysis model depicting an overall project risk score reduction. The model presented is a useful tool for industry performing steel project risk assessments. It also provides decision-makers with a better understanding of the criticality of risks that are likely to occur on international steel projects.

In this study, an advanced-ultra super critical (A-USC) simulation model was developed using the Performance Evaluation of power system efficiencies (PEPSE) software and data collected from a 500 MW ultra-supercritical (USC) coal-fired power plant in South Korea. Using the operational USC and a typical A-USC power plant steam conditions, the model analyzed the impacts of adding an additional feedwater heater (FWH) and reheater to the baseline single reheater (SR) and 8 FWH case. Through the process of introducing reheat and/or regenerative cycles, the authors found: (1) A-USC steam conditions offers an approximate 4% power plant efficiency increase in comparison to the baseline USC steam conditions and; (2) power plant efficiencies increase approximately 1.5% when a 9th FWH and double reheater are added, however; (3) this also results in an approximate 64 °C increase in the superheating of extraction stream. This excessive rise in the superheating of extraction steam was found to cause overall energy loss, reducing the overall efficiency of the power plant. Therefore, it was surmised that if the increase in the superheat degree of extraction steam from the improved steam cycle, which can effectively reduce, the efficiency of the power plant could be further improved. To determine the efficiency variations based on the reduction of the superheat degree of extraction steam, the authors applied a regenerative turbine (RT) to the model. Introducing the RT to the A-USC DR and 9 FWH was found to decrease from the average extraction steam temperature from 221 °C to 108 °C and result in an increase in power plant efficiency of approximately 0.3% to 49.5%. An economic analysis was also performed to assess the fiscal feasibility of adding an RT. Assuming the initial investment to be USD 1409 million, implementing an RT equated to a net present value increase of approximately USD 33 million as compared to that of similar life (30 years of durability) expectancy of A-USC without using an RT. The findings of this study have the potential to improve South Korea’s energy policy, reducing the superheat degree of extraction steam that rises excessively during A-USC steam condition optimization. While this study is focused on South Korea, said findings are also generalizable to worldwide energy policies, serving as an effective method to not only increase system efficiencies, but enhance the economic feasibility as well.

In this study, an advanced-ultra super critical (A-USC) simulation model was developed using the Performance Evaluation of power system efficiencies (PEPSE) software and data collected from a 500 MW ultra-supercritical (USC) coal-fired power plant in South Korea. Using the operational USC and a typical A-USC power plant steam conditions, the model analyzed the impacts of adding an additional feedwater heater (FWH) and reheater to the baseline single reheater (SR) and 8 FWH case. Through the process of introducing reheat and/or regenerative cycles, the authors found: (1) A-USC steam conditions offers an approximate 4% power plant efficiency increase in comparison to the baseline USC steam conditions and; (2) power plant efficiencies increase approximately 1.5% when a 9th FWH and double reheater are added, however; (3) this also results in an approximate 64 °C increase in the superheating of extraction stream. This excessive rise in the superheating of extraction steam was found to cause overall energy loss, reducing the overall efficiency of the power plant. Therefore, it was surmised that if the increase in the superheat degree of extraction steam from the improved steam cycle, which can effectively reduce, the efficiency of the power plant could be further improved. To determine the efficiency variations based on the reduction of the superheat degree of extraction steam, the authors applied a regenerative turbine (RT) to the model. Introducing the RT to the A-USC DR and 9 FWH was found to decrease from the average extraction steam temperature from 221 °C to 108 °C and result in an increase in power plant efficiency of approximately 0.3% to 49.5%. An economic analysis was also performed to assess the fiscal feasibility of adding an RT. Assuming the initial investment to be USD 1409 million, implementing an RT equated to a net present value increase of approximately USD 33 million as compared to that of similar life (30 years of durability) expectancy of A-USC without using an RT. The findings of this study have the potential to improve South Korea’s energy policy, reducing the superheat degree of extraction steam that rises excessively during A-USC steam condition optimization. While this study is focused on South Korea, said findings are also generalizable to worldwide energy policies, serving as an effective method to not only increase system efficiencies, but enhance the economic feasibility as well.

To meet the United Nation’s sustainable development energy goal, the Korean Ministry of Commerce announced they would increase renewable energy generation to 5.3% by 2029. These energy sources are often produced in small-scale power plants located close to the end users, known as distributed generation (DG). The use of DG is an excellent way to reduce greenhouse gases but has also been found to reduce power quality and safety reliability through an increase in voltage volatility. This paper performs a life-cycle cost analysis on the use of step voltage regulators (SVR) to reduce said volatility, simulating the impact they have on existing Korean solar photovoltaic (PV) DG. From the data collected on a Korean Electrical Power Corporation 30 km/8.2 megawatts (MW) feeder system, SVRs were found to increase earnings by one million USD. SVR volatile voltage mitigation increased expected earnings by increasing the estimated allowable PV power generation by 2.7 MW. While this study is based on Korean PV power generation, its findings are applicable to any DG sources worldwide.

To meet the United Nation’s sustainable development energy goal, the Korean Ministry of Commerce announced they would increase renewable energy generation to 5.3% by 2029. These energy sources are often produced in small-scale power plants located close to the end users, known as distributed generation (DG). The use of DG is an excellent way to reduce greenhouse gases but has also been found to reduce power quality and safety reliability through an increase in voltage volatility. This paper performs a life-cycle cost analysis on the use of step voltage regulators (SVR) to reduce said volatility, simulating the impact they have on existing Korean solar photovoltaic (PV) DG. From the data collected on a Korean Electrical Power Corporation 30 km/8.2 megawatts (MW) feeder system, SVRs were found to increase earnings by one million USD. SVR volatile voltage mitigation increased expected earnings by increasing the estimated allowable PV power generation by 2.7 MW. While this study is based on Korean PV power generation, its findings are applicable to any DG sources worldwide.

To overcome profitability deterioration in executing steel price projects, companies are seeking overseas expansion, which increases market size while reducing profit certainty. Special purpose companies (SPCs) have been found to better manage these risks through tolling agreements which transfer the local pricing volatility risks (raw material, steel sales, licensing and income tax) to the project sponsor. The energy market has benefited from policy changes allowing the use of the tolling model, finding an increase in profitability for both project sponsors and SPCs through more effective risk sharing. While successes have been published in the energy, gas, and highway sectors, the tolling model’s efficacy has yet to be tested on the steel sector. As such, this research adds to the existing body of knowledge by testing the financial feasibility of using the tolling model on three million ton/year capacity steel projects. The data analyzed has been collected from “Company A”, a company with 50 years of domestic and 20 years international steel-iron plant project execution and operation experience. An economic analysis is performed on the best, most likely, and worst-case cost/revenue scenarios of a virtual project (which represents the average of all Company A projects) and two Company A projects under construction/operation. The findings support the use of the tolling model in volatile markets, showing a net present value (NPV) profitability increase of up to $940 versus the traditional project company model under worst case market conditions. However, the traditional project company model was found to be superior in best case market conditions. With these findings, international steel companies are able to consider alternative financing structures when executing projects in volatile markets, potentially resulting in greater project sponsor and SPC profit.