Browsing by Author "Hu, Yukun"
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Item Open Access Control of supercritical organic Rankine cycle based waste heat recovery system using conventional and fuzzy self-tuned PID controllers(Springer, 2019-08-19) Chowdhury, Jahedul Islam; Thornhill, David; Soulatiantork, Payam; Hu, Yukun; Balta-Ozkan, Nazmiye; Varga, Liz; Nguyen, Bao KhaThis research develops a supercritical organic Rankine cycle (ORC) based waste heat recovery (WHR) system for control system simulation. In supercritical ORC-WHR systems, the evaporator is a main contributor to the thermal inertia of the system, which is greatly affected by transient heat sources during operation. In order to capture the thermal inertia of the system and reduce the computation time in the simulation process, a fuzzy-based dynamic evaporator model was developed and integrated with other component models to provide a complete dynamic ORC-WHR model. This paper presents two control strategies for the ORC-WHR system: evaporator temperature control and expander output control, and two control algorithms: a conventional PID controller and a fuzzy-based self-tuning PID controller. The performances of the proposed controllers are tested for set point tracking and disturbance rejection ability in the presence of steady and transient thermal input conditions. The robustness of the proposed controllers is investigated with respect to various operating conditions. The results show that the fuzzy self-tuning PID controller outperformed the conventional PID controller in terms of set point tracking and disturbance rejection ability at all conditions encountered in the paper.Item Open Access Coupling detailed radiation model with process simulation in Aspen Plus: A case study on fluidized bed combustor(Elsevier, 2017-08-31) Hu, Yukun; Wang, Jihong; Tan, C. K.; Sun, Chenggong; Liu, HaoWhile providing a fast and accurate tool for simulating fluidized beds, the major limitations of classical zero-dimensional ideal reactor models used in process simulations become irreconcilable, such as models built into commercial software (e.g. Aspen Plus®). For example, the limitations of incorporating heat absorption by the water wall and super-heaters and inferring thermal reciprocity between each reactor model/module. This paper proposes a novel modelling approach to address these limitations by incorporating an external model that marries the advantages of the zone method and Aspen Plus to the greatest extent. A steady state operation of a 0.3 MW atmospheric bubbling fluidized-bed combustor test rig was simulated using the developed modelling approach and the results were compared with experimental data. The comparison showed that the predictions were in agreement with the measurements. Further improvement is to be expected through incorporating more realistic zoned geometry and more complex reaction mechanisms. In addition, the developed model has a relatively modest computing demand and hence demonstrates its potential to be incorporated into process simulations of a whole power plant.Item Open Access Data underpinning research article "Optimising Renewable Energy Integration in New Housing Developments with Low Carbon Technologies"(Cranfield University, 2021-02-09 00:33) Chowdhury, Jahedul; Ozkan, Nazmiye; Hart, Phil; Varga, Liz; Hu, YukunThis file includes data for energy demand and generation profile for different house types in the UK. It also contains data for daily average solar irradiance for typical UK weather conditions that were used for calculating PV outputs.Item Open Access Data underpinning research article "Techno-environmental analysis of battery storage for grid level energy services"(Cranfield University, 2020-07-17 09:07) Chowdhury, Jahedul; Ozkan, Nazmiye; Goglio, Pietro; Hu, Yukun; Varga, Liz; McCabe, LeahThis file includes data from the National Grid, UK for electricity supply and demand which was modified according to the research methodology laid out in the paper here (https://doi.org/10.1016/j.rser.2020.110018). Also, all the data needed for reproducing figures presented in the journal article are also included in the data file.Item Open Access Feasibility study of biomass gasification integrated with reheating furnaces in steelmaking process(DEStech Publication Inc., 2019-11-04) Hu, Yukun; Chowdhury, Jahedul Islam; Katsaros, Giannis; Tan, C. K.; Balta-Ozkan, Nazmiye; Varga, Liz; Tassou, Savvas; Wang, ChunshengThis paper investigates the integration of biosyngas production, reheating furnace and heat recovery steam cycle, in order to use biosyngas directly as fuel in the furnace. A system model was developed to evaluate the feasibility of the proposed system from the perspective of heat and mass balance. To particularly study the impacts of fuel switching on the heating quality of the furnace, a three-dimensional furnace model considering detailed heat transfer processes was embedded into the system through an Aspen PlusTM user defined model. The simulation results show that biosyngas is suitable for direct use as fuel for reheating furnaces. Should CO capture be considered in the proposed system, it has a potential to achieve the capture without external energy input which results in so-called negative emissions of CO.Item Open Access Function value-based multi-objective optimisation of reheating furnace operations using Hooke-Jeeves algorithm(MDPI, 2018-09-03) Gao, Bo; Wang, Chunsheng; Hu, Yukun; Tan, C. K.; Roach, Paul Alun; Varga, LizImproved thermal efficiency in energy-intensive metal-reheating furnaces has attracted much attention recently in efforts to reduce both fuel consumption, and CO2 emissions. Thermal efficiency of these furnaces has improved in recent years (through the installation of regenerative or recuperative burners), and improved refractory insulation. However, further improvements can still be achieved through setting up reference values for the optimal set-point temperatures of the furnaces. Having a reasonable expression of objective function is of particular importance in such optimisation. This paper presents a function value-based multi-objective optimisation where the objective functions, which address such concerns as discharge temperature, temperature uniformity, and specific fuel consumption, are dependent on each other. Hooke-Jeeves direct search algorithm (HJDSA) was used to minimise the objective functions under a series of production rates. The optimised set-point temperatures were further used to construct an artificial neural network (ANN) of set-point temperature in each control zone. The constructed artificial neural networks have the potential to be incorporated into a more advanced control solution to update the set-point temperatures when the reheating furnace encounters a production rate change. The results suggest that the optimised set-point temperatures can highly improve heating accuracy, which is less than 1 °C from the desired discharge temperature.Item Open Access Further improvement of fluidized bed models by incorporating zone method with aspen plus interface(Elsevier, 2017-06-01) Hu, Yukun; Wang, Jihong; Tan, Chee Keong; Sun, Chenggong; Liu, HaoWhile providing a fast and accurate tool of simulating fluidized beds, the major limitation of classical zero-dimensional ideal reactor models used in process simulators, such as models built into commercial software (e.g. Aspen Plus®), has been the difficulties of involving thermal reciprocity between each reactor model and incorporating heat absorption by the water wall and super-heaters which is usually specified as model inputs rather than predicted by the models themselves. This aspect is of particular importance to the geometry design and evaluation of operating conditions and flexibility of fluidized beds. This paper proposes a novel modelling approach to resolve this limitation by incorporating an external model that marries the advantages of zone method and Aspen Plus in a robust manner. The improved model has a relatively modest computing demand and hence may be incorporated feasibly into dynamic simulations of a whole power plant.Item Open Access Fuzzy nonlinear dynamic evaporator model in supercritical organic Rankine cycle waste heat recovery systems(MDPI, 2018-04-11) Chowdhury, Jahedul Islam; Nguyen, Bao Kha; Thornhill, David; Hu, Yukun; Soulatiantork, Payam; Balta-Ozkan, Nazmiye; Varga, LizThe organic Rankine cycle (ORC)-based waste heat recovery (WHR) system operating under a supercritical condition has a higher potential of thermal efficiency and work output than a traditional subcritical cycle. However, the operation of supercritical cycles is more challenging due to the high pressure in the system and transient behavior of waste heat sources from industrial and automotive engines that affect the performance of the system and the evaporator, which is the most crucial component of the ORC. To take the transient behavior into account, the dynamic model of the evaporator using renowned finite volume (FV) technique is developed in this paper. Although the FV model can capture the transient effects accurately, the model has a limitation for real-time control applications due to its time-intensive computation. To capture the transient effects and reduce the simulation time, a novel fuzzy-based nonlinear dynamic evaporator model is also developed and presented in this paper. The results show that the fuzzy-based model was able to capture the transient effects at a data fitness of over 90%, while it has potential to complete the simulation 700 times faster than the FV model. By integrating with other subcomponent models of the system, such as pump, expander, and condenser, the predicted system output and pressure have a mean average percentage error of 3.11% and 0.001%, respectively. These results suggest that the developed fuzzy-based evaporator and the overall ORC-WHR system can be used for transient simulations and to develop control strategies for real-time applications.Item Open Access Model-based multi-objective optimisation of reheating furnace operations using genetic algorithm(Elsevier, 2018-01-30) Hu, Yukun; Tan, C. K.; Broughton, Jonathan; Roach, Paul Alun; Varga, LizAn effective optimisation strategy for metal reheating processes is crucial for the economic operation of the furnace while supplying products of a consistent quality. An optimum reheating process may be defined as one which produces heated stock to a desired discharge temperature and temperature uniformity while consuming minimum amount of fuel energy. A strategic framework to solve this multi-objective optimisation problem for a large-scale reheating furnace is presented in this paper. For a given production condition, a model-based multi-objective optimisation strategy using genetic algorithm was adopted to determine an optimal temperature trajectory of the bloom so as to minimise an appropriate cost function. Definition of the cost function has been facilitated by a set of fuzzy rules which is easily adaptable to different trade-offs between the bloom desired discharge temperature, temperature uniformity and specific fuel consumption. A number of scenarios with respect to these trade-offs were evaluated and the results suggested that the developed furnace model was able to provide insight into the dynamic heating behaviour with respect to the multi-objective criteria. Suggest findings that current furnace practice places more emphasis on heated product quality than energy efficiency.Item Open Access Modelling and simulation of steel reheating processes under oxy-fuel combustion conditions – Technical and environmental perspectives(Elsevier, 2019-07-11) Hu, Yukun; Tan, C. K.; Niska, John; Chowdhury, Jahedul; Balta-Ozkan, Nazmiye; Varga, Liz; Roach, Paul Alun; Wang, ChunshengThis paper investigates the impact of flameless oxy-fuel combustion on the thermal performance of a pilot-scale steel reheating furnace. A comprehensive mathematical model, based on the zone method of radiation analysis, was developed, which takes into account the non-grey behaviour of the furnace atmosphere under oxy-fuel combustion conditions. The model was subsequently used to simulate the temperature profile of an instrumented slab used in the experiment. The results showed that the predicted slab temperature profile along the furnace is in good agreement with measurement. However the model over predicted the absolute slab temperatures due to the influence of formation of oxide scales on the slab surface, which was not taken into account in the current model. When compared to air-fuel combustion simulation, the results of oxy-fuel combustion also indicated a marked improvement in the furnace specific fuel consumption (approximately 16%). This was mainly due to the enhanced radiative properties of the furnace atmosphere and reduced exhaust energy losses as the result of less dilution effect from nitrogen. This resulted in reduction in the overall heating time by approximately 14 min. Furthermore, if the economics of carbon capture is taken into consideration, theoretically, the energy consumption per kilogram of CO2 captured can be reduced from 3.5 to 4.2 MJ kg−1 to 0.96 MJ kg−1. In conclusion, the current studies support the view that oxy-fuel combustion retrofitting to reheating furnaces is a promising option, both from a technical and from an environmental point of view.Item Open Access Nonlinear dynamic simulation and control of large-scale reheating furnace operations using a zone method based model(Elaevier, 2018-02-14) Hu, Yukun; Tan, C. K.; Broughton, Jonathan; Roach, Paul Alun; Varga, LizModern reheating furnaces are complex nonlinear dynamic systems having heat transfer performances which may be greatly influenced by operating conditions such as stock material properties, furnace scheduling and throughput rate. Commonly, each furnace is equipped with a tailored model predictive control system to ensure consistent heated product quality such as final discharge temperature and temperature uniformity within the stock pieces. Those furnace models normally perform well for a designed operating condition but cannot usually cope with a variety of transient furnace operations such as non-uniform batch scheduling and production delay from downstream processes. Under these conditions, manual interventions that rely on past experience are often used to assist the process until the next stable furnace operation has been attained. Therefore, more advanced furnace control systems are useful to meet the challenge of adapting to those circumstances whilst also being able to predict the dynamic thermal behaviour of the furnace. In view of the above, this paper describes in detail an episode of actual transient furnace operation, and demonstrates a nonlinear dynamic simulation of this furnace operation using a zone method based model with a self-adapting predictive control scheme. The proposed furnace model was found to be capable of dynamically responding to the changes that occurred in the furnace operation, achieving about ±10 °C discrepancies with respect to measured discharge temperature, and the self-adapting predictive control scheme is shown to outperform the existing scheme used for furnace control in terms of stability and fuel consumption (fuel saving of about 6%).Item Open Access Optimising renewable energy integration in new housing developments with low carbon technologies(Elsevier, 2021-01-14) Gil, Gemma Oliver; Chowdhury, Jahedul Islam; Balta-Ozkan, Nazmiye; Hu, Yukun; Varga, Liz; Hart, PhilSince buildings account for more than one-third of final energy use, it is important to integrate renewable energy sources for new housing developments to reduce demand for grid energy and carbon emissions. This research investigates the potential of solar PV, energy storage, and electric vehicles in new housing developments and their associated grid impacts by taking the UK’s Cambridge, Milton Keynes, Oxford arc as a case study. Using published data on electrical loads for different types of dwellings, energy demands for new housing developments with and without renewable and low carbon technologies are analysed using techno-economic modelling frameworks. Technical analysis includes sizing and optimisation of PV and storage while economic analysis covers cost-benefit analyses, by considering a range of existing and future tariffs and subsidy schemes including Standard, Economy 7 (cheaper electricity for seven hours at night), Feed-in tariff, and the Smart Export Guarantee. Results show that installing PV panels and storage systems not only reduces the dwellings’ grid energy demand by 31% in January but also helps the dwellings to become net exporters of green electricity to the grid in July and hence saves a substantial amount of money by taking advantage of Feed-in and Economy 7 tariffs.Item Open Access Potentials of load-shifting with renewable energy storage: An environmental and economic assessment for the UK(US Association for Energy Econimics, 2018-09-26) Chowdhury, Jahedul Islam; Balta-Ozkan, Nazmiye; Goglio, Pietro; Hu, Yukun; Varga, Liz; McCabe, LeahThe Paris Agreement set targets to limit global warming to less than 2°C above the pre-industrial level to significantly reduce the risks and impacts associated with climate change [1]. Globally, the energy supply sector is responsible for 25% of greenhouse gas (GHG) emissions [2]. In addition to ratifying Paris Agreement, the UK government has adopted legally binding 80% emissions reduction target from 1990 levels by 2050 as outlined in Climate Change Act. The decarbonisation of power supply, along with electrification of heat and transport, are highlighted as key elements of this transition by both policy and academic research [3]–[5]. Storage systems, via the multiple services they offer across the electricity supply chain [6] at different operational scales stand to create system-wide benefits, enhanced flexibility and reliability for effective management of the grid [7]. The potential contributions storage systems can make towards minimizing the carbon intensity of UK grid with high levels of renewables is recognised by the government as well [8]. This study aims i) to determine the amount of load shifting that can be achieved by the combination of current renewable energy mainly wind and solar and UK grid level storage, ii) analyse the amount of renewable energy generation and storage (RES) needed to phase out programmable gas power generation during the periods of peak demand and iii) assess their economic and environmental implications. The environmental impacts considered are the life cycle emissions associated with electricity generation from the UK mix and the production, installation and use of batteries. The analysis will be extended to cover the future energy scenarios.Item Open Access Power generation expansion optimization model considering multi-scenario electricity demand constraints: a case study of Zhejiang Province, China(MDPI, 2018-06-08) Wang, Peng; Wang, Chunsheng; Hu, Yukun; Varga, Liz; Wang, WeiReasonable and effective power planning contributes a lot to energy efficiency improvement, as well as the formulation of future economic and energy policies for a region. Since only a few provinces in China have nuclear power plants so far, nuclear power plants were not considered in many provincial-level power planning models. As an extremely important source of power generation in the future, the role of nuclear power plants can never be overlooked. In this paper, a comprehensive and detailed optimization model of provincial-level power generation expansion considering biomass and nuclear power plants is established from the perspective of electricity demand uncertainty. This model has been successfully applied to the case study of Zhejiang Province. The findings suggest that the nuclear power plants will contribute 9.56% of the total installed capacity, and it will become the second stable electricity source. The lowest total discounted cost is 1033.28 billion RMB and the fuel cost accounts for a large part of the total cost (about 69%). Different key performance indicators (KPI) differentiate electricity demand in scenarios that are used to test the model. Low electricity demand in the development mode of the comprehensive adjustment scenario (COML) produces the optimal power development path, as it provides the lowest discounted cost.Item Open Access Reducing industrial energy demand in the UK: A review of energy efficiency technologies and energy saving potential in selected sectors(Elsevier, 2018-07-26) Chowdhury, Jahedul Islam; Hu, Yukun; Haltas, Ismail; Balta-Ozkan, Nazmiye; Matthew, George Jr.; Varga, LizCurrently UK industrial and manufacturing sectors are facing dual challenges of contributing to national 80% reduction targets in CO2 emissions by 2050 (compared to 1990 levels) and improving economic competitiveness in the face of low cost imports. Since energy consumption is the main source of CO2 emissions and directly related to products being manufactured, improving energy efficiency in energy intensive sectors is key to achieve CO2 targets. Energy consumption is unlikely to meet the targets unless energy efficiency opportunities and technologies are fully explored and timely changes are made to business models and policies This study explores potential energy efficiency improvements from three perspectives: system efficiency of steam networks, waste heat recovery technologies and bioenergy/waste utilisation. Two UK energy-intensive sectors, iron and steel, and food and drink, are selected for analysis and discussion. Potential business models for energy efficiency are also reviewed as there are now a variety of energy service companies who can support adoption of appropriate technologies. Furthermore, drivers and barriers to the adoption of energy efficiency technologies are considered in this paper revealing the factors affecting the diffusion of energy efficient and waste heat recovery technologies and their interactions and interdependencies to energy consumptions. Findings show that it is possible to achieve energy consumption reduction in excess of 15% from a technical point of view, however improving energy efficiency in UK industry has been hindered due to some inter-related technical, economic, regulatory and social barriers. The findings help to demonstrate the significant potential for energy efficiency improvement in two industrial sectors, as well as showing the specific types of technologies relevant for different sectoral processes. The range of business models show opportunities for implementation and for developing innovative business models, addressing barriers, and using enablers to accelerate the diffusion of energy efficiency technologies in UK industry.Item Open Access System dynamics of oxyfuel power plants with liquid oxygen energy storage(Elsevier, 2017-12-15) Hu, Yukun; Tewari, Anurag; Varga, Liz; Li, Hailong; Yan, JinyueTraditional energy storage systems have a common feature: the generating of secondary energy (e.g. electricity) and regenerating of stored energy (e.g. gravitational potential, and mechanical energy) are separate rather than deeply integrated. Such systems have to tolerate the energy loss caused by the second conversion from primary energy to secondary energy. This paper is concerned with the system dynamics of oxyfuel power plants with liquid oxygen energy storage, which integrates the generation of secondary energy (electricity) and regeneration of stored energy into one process and therefore avoids the energy loss caused by the independent process of regeneration of stored energy. The liquid oxygen storage and the power load of the air separation unit are self-adaptively controlled based on current-day power demand, day-ahead electricity price and real-time oxygen storage information. Such an oxyfuel power plant cannot only bid in the day-ahead market with base load power but also has potential to provide peak load power through reducing the load of the air separation unit in peak time. By introducing reasoning rules with fuzzy control, the oxygen storage system has potential to be further extended by integrating renewable energy resources into the system to create a cryogenic energy storage hub.Item Open Access System integration study of oxy-biosyngas combustion based metal heating process using Aspen Plus(ICAE, 2020-12-10) Hu, Yukun; Chowdhury, Jahedul Islam; Katsaros, Giannis; Balta-Ozkan, Nazmiye; Varga, Liz; Li, Kang; Tassou, Savvas; Wang, ChunshengGiven the increasing concerns on emissions, efficient and environmentally friendly combustion technologies are urgently needed to address energy trilemma. Metal heating is a large component of energy-intensive processes, as its energy consumption accounts for one third of the steel manufacturing process. Early attempts at using a new flameless oxy-fuel combustion burner give high performance, low NOx, and low-cost heating for the steel industry, while biosyngas is considered as an alternative fuel for reheating furnace with aiming at CO2 mitigation. Yet, all these technical solutions are developed in isolation. This paper investigates the system integration of biosyngas production, air separation unit (ASU), reheating furnace and heat recovery (HR) steam cycle, in order to enhance energy efficiency of steel industry and enable so-called negative emissions. An integrated system model was developed using Aspen Plus to evaluate the feasibility of the proposed integration from the perspective of heat and mass balance. In particular, to study the impacts of fuel switching on the heating quality of the furnace, a three-dimensional furnace model considering detailed heat transfer processes was embedded into the system. The simulation results show that the proposed system integration strategy is technically feasible. The electricity generation of the HR steam cycle used can compensate for about 90% of ASU’s energy consumption. The system is carbon capture-ready for being further integrated with CO2 conditioning and transportation processesItem Open Access Techno-environmental analysis of battery storage for grid level energy services(Elsevier, 2020-06-10) Chowdhury, Jahedul Islam; Balta-Ozkan, Nazmiye; Goglio, Pietro; Hu, Yukun; Varga, Liz; McCabe, LeahWith more and more renewable energy sources (RES) going into power grids, the balancing of supply and demand during peak times will be a growing challenge due to the inherent intermittency and unpredictable nature of RES. Grid level batteries can store energy when there is excess generation from wind and solar and discharge it to meet variable peak demand that is currently supplied by combined cycle gas turbine (CCGT) plants in the UK. This paper assesses the potential of battery storage to replace CCGT in responding to variable peak demand for current and future energy scenarios (FES) in the UK from technical and environmental perspectives. Results from technical analysis show that batteries, assuming size is optimised for different supply and demand scenarios proposed by the National Grid, are able to supply 6.04%, 13.5% and 29.1% of the total variable peak demand in 2016, 2020 and 2035, respectively while CCGT plants supply the rest of the demand. Particularly, to phase out CCGT variable generation from the UK grid in 2035, electricity supply from wind and solar needs to increase by 1.33 times their predicted supply in National Grid’s FES. The environmental implications of replacing CCGT by batteries are studied and compared through a simplified life cycle assessment (LCA). Results from LCA studies show that if batteries are used in place of CCGT, it can reduce up to 87% of greenhouse gas emissions and that is an estimated 1.98 MtCO2 eq. for an optimal supply, 29.1%, of variable peak demand in 2035