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The fuel cell grid-tied power generation system usually includes a dc-dc converter and a dc-ac inverter. In a single-phase system, inherent low-order current pulsations are introduced into the system, which can have harmful effects on the fuel cell stack. For example, reducing the output voltage and output efficiency, a reduction in service life, and even accelerates the degradation rate of the membrane electrode of a proton exchange membrane fuel cell (PEMFC). In addition, dc/ac coupling power can cause distortion in the dc input current and ac grid current. To eliminate the input ripple and ensure high ac power quality on the grid side, this paper proposes a novel power decoupling control for single-phase grid-tied PEMFC systems, which uses an improved model predictive control (MPC) algorithm. With the help of the virtual vector methods, which are realized by a two-stage optimization method, excellent tracking effect and robustness can be ensured. Simulations and experimental results show that the proposed algorithm can not only completely eliminate the input current ripple and reduce the total harmonic distortion (THD) of ac current on the grid side, but also improve the transient performance of the system.

This 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.

With the large-scale use of intermittent renewable energy worldwide, such as wind energy and solar energy, energy storage systems are urgently needed and have been rapidly developed. Technologies o ...

In a wind-diesel isolated microgrid, the fluctuating output power of wind turbine generator (WTG) and the perturbation of the load demand will lead to power imbalance and frequency deviation in the system. Appropriate frequency control schemes are indispensable to guarantee power quality through maintaining the power balance. In view of the outstanding performance of Equivalent-Input-Disturbance (EID) method, it is taken to the task of load frequency control (LFC) problem of this microgrid. In this paper, novel double EID controllers are proposed for the frequency control of a wind-diesel isolated microgrid. In this integrated control design, one single EID controller is applied to the pitch angle control system to smooth output power of WTG by controlling the pitch angle. At the diesel generator side, another single EID controller is applied to adjust the output power of the diesel generator to maintain the power balance of the system and finally preserve frequency in the normal range. Battery energy storage system is connected as auxiliary regulation. The simulation studies show superior flexibility and control performance of the proposed strategy compared to the conventional PI method in a wind-diesel isolated microgrid in MATLAB.

An effective oxygen excess ratio control strategy for a proton exchange membrane fuel cell (PEMFC) can avoid oxygen starvation and optimize system performance. In this paper, a fuzzy PID control strategy based on granular function (GFPID) was proposed. Meanwhile, a proton exchange membrane fuel cell dynamic model was established on the MATLAB/Simulink platform, including the stack model system and the auxiliary system. In order to avoid oxygen starvation due to the transient variation of load current and optimize the parasitic power of the auxiliary system and the stack voltage, the purpose of optimizing the overall operating condition of the system was finally achieved. Adaptive fuzzy PID (AFPID) control has the technical bottleneck limitation of fuzzy rules explosion. GFPID eliminates fuzzification and defuzzification to solve this phenomenon. The number of fuzzy rules does not affect the precision of GFPID control, which is only related to the fuzzy granular points in the fitted granular response function. The granular function replaces the conventional fuzzy controller to realize the online adjustment of PID parameters. Compared with the conventional PID and AFPID control, the feasibility and superiority of the algorithm based on particle function are verified.

Since 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 7 h 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.

With 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 traditionally supplied by combined cycle gas turbine (CCGT) plants. 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.

To improve the heat and mass transfer performances of falling films and develop a new type of falling film evaporator, the heat and mass transfer characteristics of falling film evaporation and sensible heating in four different sizes of converging–diverging (CD) tubes were experimentally explored in this study. By analyzing the relationship between the heat transfer coefficient and the falling film flow rate, it was found that the CD tube is suitable for falling film evaporation and sensible heating with a large Reynolds number. For different sizes of tubes, the key factor affecting the heat transfer performance in falling film evaporation and sensible heating is the rib height. At the same rib height and rib pitch, the longer the converging segment of the CD tube, the better the heat transfer performance. According to the comparative analysis on heat and mass transfer performances of falling film evaporation and sensible heating inside the four CD tubes, the CD tube 3# is the best. The evaporation heat transfer coefficient (when the Reynolds number of the liquid films is 2356), evaporation mass transfer rate (when the perimeter flow rate of the liquid films is 0.173 kg/(m·s)), and sensible heating heat transfer coefficient (when the Reynolds number of the liquid films is 1635) of CD tube 3# are 62%, 38% and 63% higher than that of the smooth tube, respectively. For the same CD tube, the evaporation heat transfer coefficient is greater than the sensible heating heat transfer coefficient, but both increases as the flow rate increases. The heat transfer correlations of falling film evaporation and sensible heating in the experimental range were obtained. It will provide a useful reference for future engineering design and industrial applications.

In order to analyze the factors that affect energy consumption in Hunan Province comprehensively, firstly, this paper used the Logarithmic Mean Divisia Index (LMDI) and divided the total energy consumption growth of three industries from 2006 to 2015 in Hunan Province into scale effect, structure effect and efficiency effect. Secondly, the long-term energy alternatives planning (LEAP) system was used, and the LEAP-Hunan model with benchmark, scale effect, structure effect, efficiency effect and comprehensive adjustment scenarios was set up to analyze the impacts of the three kinds of effects on the total energy consumption profoundly. LMDI qualitative decomposition results show that the scale effect promotes the rapid growth of energy consumption, and efficiency effect can reduce energy consumption in Hunan Province, while inhibition of the structure effect is not prominent on the growth of energy consumption. The quantitative results of LEAP model are highly consistent with it, whose influence on the structure effect is reasonably extrapolated. This phenomenon shows that the structure effect and efficiency effect will jointly bear the inhibitory effect on the growth of total energy consumption in the future. In addition, the LEAP model has predictions about energy consumption from 2016 to 2040 in Hunan Province.

In this paper, a framework of multi-energy system (MES) integrating with a liquid air energy storage (LAES) system was proposed. LAES, where liquid air works as an energy storage media, is a powerful and eco-friendly technology for storing renewable energy resources and reducing grid curtailment. Considering the characteristics of LAES (i.e. cold and heat circulation), the incorporation of LAES system into the Combined Cooling, Heating and Power system can achieve integrated use of energy and effectively save energy. Moreover, the prices of electricity will affect the overall cost of the MES. In other words, the decision-makers of the MES need to consider the uncertainty of electricity prices when making power dispatching decisions. To model the uncertainty of electricity prices, the information gap decision theory method was used to study power dispatching strategies of the MES. Three different strategies were proposed, including risk-neutral, risk-averse and risk-taker. In addition, demand response algorithms were used to study load transfer strategies. The results show that the demand responses of the three strategies are effective in terms of load transfer and cost saving. The total operation cost in the risk-neutral strategy with demand response can be 6.82% less than that without demand response; In the risk-taker strategy with demand response, the allowable grid electricity price is reduced by 25.24% when the opportunity cost drops by $8,000, and 23.32% without demand response. With additional robustness cost, the acceptable price change ratio using demand response is 21.91% in the risk-averse strategy, and 20.04% without demand response.

While 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.

This 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 CO2 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 CO2.

The massive use of renewable energy has driven the development of energy storage. Compressed CO2 energy storage technology is a promising technology. To gain a deeper understanding of the process of compressing carbon dioxide energy storage (CCES) technology, in order to support technological advances, this paper experimentally studied the performance of compressed CO2 energy storage system. The key parameters, such as the pressure of the storage tanks, the power consumption of the compressor, and the power of the expander were investigated.

The combined-cycle gas turbine (CCGT) power plants are often required to provide the essential fast grid balance service between the load demand and power supply with the increase of the intermittent power generation from renewable energy sources. It is extremely challenging to ensure CCGT power plants operating flexibly and also maintaining its efficiency at the same time. This paper presents the feasibility study of a CCGT power plant combined with the cascaded latent heat storage (CLHS) for plant flexible operation. A 420 MW CCGT power plant and a CLHS dynamic models are developed in Aspen Plus based on a novel modelling approach. The plant start-up processes are studied, and large amount of thermal energy can be accumulated by CLHS during the start-up. For load-following operation, extensive dynamic simulation study is conducted and the simulation results show that the extracted exhaust gas can be used for thermal energy storage charging, and the stored heat can be discharged to produce high temperature and high pressure steam fed to the steam turbine. Besides, the stored heat can also be used to maintain the heat recovery steam generator (HRSG) under warm condition to reduce plant restart-up time. The simulation results demonstrate that the integration of CLHS with CCGT power plant is feasible during the start-up, load-following and standstill operations.

With the rapid increase of photovoltaic (PV) penetration and distributed grid access, photovoltaic generation (PVG)-integrated multi-area power systems may be disturbed by more uncertain factors, such as PVG, grid-tie inverter parameters, and resonance. These uncertain factors will exacerbate the frequency fluctuations of PVG integrated multi-area interconnected power systems. For such system, this paper proposes a load frequency control (LFC) strategy based on double equivalent-input-disturbance (EID) controllers. The PVG linear model and the multi-area interconnected power system linear model were established, respectively, and the disturbances were caused by grid voltage fluctuations in PVG subsystem and PV output power fluctuation and load change in multi-area interconnected power system. In PVG subsystems and multi-area interconnected power systems, two EID controllers add differently estimated equivalent system disturbances, which has the same effect as the actual disturbance, to the input channel to compensate for the impact of actual disturbances. The simulation results in MATLAB/Simulink show that the frequency deviation range of the proposed double EID method is 6% of FA-PI method and 7% of conventional PI method, respectively, when the grid voltage fluctuation and load disturbance exist. The double EID method can better compensate for the effects of external disturbances, suppress frequency fluctuations, and make the system more stable.

Energy storage technologies are crucial to the future integrated energy system (IES) in the context of energy internet (EI). Liquid air energy storage (LAES) technology has been widely researched and implemented in the United Kingdom, since there are no special restrictions on geography compared to other technologies. However, there is little attention on LAES in China. In this paper, a linear programming model for the optimal scheduling of multicarrier energy networks considering LAES is established based on the concept of cryogenic energy hub, that is LAES-HUB. The results show that the daily operation cost of LAES-HUB model is 43735.28 RMB, which is even higher than the energy networks works without LEAS. LAES can achieve load shifting through peak and off-peak operations, providing an auxiliary function for energy balance in multi-carrier energy networks.

Improved 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 &deg, C from the desired discharge temperature.

This paper developed an agent-based trip chain model (ABTCM) to study the distribution of electric vehicles (EVs) charging demand and its dynamic characteristics, including flexibility and uncertainty, at different types of location. Key parameters affecting charging demand include charging strategies, i.e. uncontrolled charging (UC) and off-peak charging (OPC), and EV supply equipment, including three levels of charging equipment. The results indicate that the distributions of charging demand are similar as the travel patterns, featured by traffic flow at each location. A discrete peak effect was found in revealing the relation between traffic flow and charging demand, and it results in the smallest equivalent daily charging demand and peak load at public locations. EV charging and vehicle-to-grid (V2G) flexibility were examined by instantaneous adjustable power and accumulative adjustable amount of electricity. The EVs at home locations have the largest charging and V2G flexibility under the UC strategy, except for a period of regular working time. The V2G flexibility at work and public locations is generally larger than charging flexibility. Due to the fast charging application, the uncertainties of charging demand at public locations are the highest in all locations. In addition, the OPC strategy mitigates the uncertainty of charging demand.

Currently 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.

Reasonable 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.

The 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.

An 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.

Traditional 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.

The Combined-Cycle Gas Turbine (CCGT) power plants are increasingly required to provide the service for balancing the load demand and power supply with the increase of the intermittent power generation from renewable energy sources. To ensure CCGT power plants to operate flexibly and efficiently, it is necessary to find the suitable strategy. This paper presents the feasibility of a CCGT power plant combined with the Thermal Energy Storage (TES) to improve the plant operation flexibility. The dynamic simulation models of a 420MW CCGT power plant and TES system are presented in this paper. The TES charging and discharging strategies are investigated. The simulation results show that TES charging or discharging processes provide the additional mechanisms for regulating the output power of the CCGT power plant.

While 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.

In order to estimate the thermal behavior of a working beam type reheat furnace, this paper describes the development of a two-dimensional (2D) mathematical model with the Monte Carlo Ray-Tracing Method for radiation analysis. It is used to simulate the thermal performance of a walking-beam reheating furnace, such as the temperature distribution in the furnace and the heated billets. The results show that the model predictions are in agreement with the experience data and that this kind of coupling greatly reduces the computational effort without much affecting the accuracy. Overall, we evidence that the model can be a quite effective alternative for the furnace simulations.