• Energy Research
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Abstract The urge to increase renewable energy penetration into the power supply mix has been frequently highlighted in response to climate change. South Korea was analyzed as a case study for which the government has shown motivation to increase renewable energy penetration. Herein, a hybrid renewable energy system (HRES) including solar and wind energies were selected due to their relatively stable and mature technology. In addition, Power-to-X has been incorporated to cover other renewable energy options such as hydrogen and synthetic natural gas (SNG). Therefore, an approach of forecasting the weather characteristics and demand loading over a relatively long timeframe was implemented via deep learning techniques (LSTM and GRU) and statistical approaches (Fbprophet and SARIMA), respectively. A deployment strategy incorporating HRES and Power-to-X is then proposed in correspondence to the forecasted results of the 15 regions considered in this study. An extension of this, the reliability of the designed system is further assessed based on the probability of the demand losses with the aid of Monte-Carlo simulation. With the proposed deployment strategy, a total annual cost of 9.88 × 1011 $/year and a greenhouse gas reduction of 1.24 × 106 tons/year are expected for a 35% renewable energy penetration. However, only SNG shows relatively competitive cost (at 23.20 $/m3 SNG), whereas the average costs of electricity (0.133 $/kWh) and hydrogen (7.784 $/kg H2) across the regions are yet to be competitive compared to the current market prices. Nonetheless, the priority of deployment across regions has been identified via TOPSIS.

This study proposed a hybrid model consisting of a characteristic time combustion (CTC) model and a closed reactor model for the combustion modelling with detailed chemistry in RCCI engines. In the light of the basic idea of the CTC model of achieving chemical equilibrium in high temperature, this hybrid model uses the CTC model to solve the species conversion and heat release in the diffusion flame. Except for the diffusion flame, the auto-ignition in RCCI combustion is computed by a closed reactor model with the CHEMKIN library by assuming that the computational cells are closed reactors. The border of the transition between the CTC model and closed reactor model is determined by two criteria, a critical temperature and a critical Damkohler number. On the formulation of this hybrid model, emphasis is placed on coupling detailed chemistry into this hybrid model. A CEQ solver for species equilibrium calculations at certain temperature, pressure was embedded with CTC for detailed chemistry calculation. Then this combustion model was integrated with the CFD framework KIVA4 and the chemical library CHEMKIN-II and validated in a RCCI engine. The predicted in-cylinder pressure and heat release rate (HRR) show a good consistency with the data from the experiment and better accuracy than that computed from the sole closed reactor model. More importantly, it is observed that this model could save computational time compared with closed reactor model due to less stiff ordinary differential equations (ODEs) computation. A sensitivity analysis of the critical temperature and critical Damkohler number was conducted to demonstrate the effect of these two parameters in the current model.

In-situ biomethanisation reduces the CO2 in biogas to CH4 via direct H2 injection into an anaerobic digester, but volumetric methane production (VMP) is limited by organic loading. Ex-situ biomethanisation, where gaseous substrates are fed to pure or mixed cultures of hydrogenotrophic methanogens, offers higher VMP but requires an additional reactor and supply of essential nutrients. This work combined the two approaches in a novel hybrid application achieving simultaneous in-situ and ex-situ biomethanisation within an organically-loaded anaerobic digester receiving supplementary biogas. Conventional stirred-tank digesters were first acclimated to H2 addition, increasing biogas methane content from 50% to 95% and VMP from 0.86 to 1.51 L L-1 day-1 at a moderate loading rate of 3 g organic chemical oxygen demand per L per day (g CODorg L-1 day-1). Externally-produced biogas was then added to demonstrate simultaneous biomethanisation of endogenous and imported CO2. This further increased VMP to 2.76 L L-1 day-1 without affecting organic substrate degradation. In-situ CO2 reduction can alter digester pH by reducing bicarbonate buffering: the combined process operated stably at around pH 8.0 with 3-5% CO2 in the headspace. Microbial community analysis indicated the process was mediated by bacterial syntrophic acetate oxidation and highly enriched hydrogenotrophic methanogenic archaea (up to 97% of the archaeal population). This approach presents the opportunity to retrofit a single digester for H2 injection to convert and upgrade biogas from several others, minimising capital and operating costs by utilising both existing infrastructure and waste-derived feedstock nutrients for simultaneous biogas upgrading and power-to-methane.

Abstract Performance characteristics due to fouling in a vapor compression cycle with integrated mechanical sub-cooling are investigated for various applications. Considering the first set of refrigerants i.e. R134a, R410A and R407C, from a first law standpoint, the COP indicates that R134a always performs better unless only the evaporator is being fouled. From a second law standpoint, the second-law efficiency indicates that R134a performs the best in all cases. Considering the second set of refrigerants i.e. R717, R404A and R290, the COP indicates that R717 always performs better unless only the evaporator is being fouled; however, the second-law efficiency indicates that R717 performs the best in all cases. Furthermore, the performance degradation due to fouling of the evaporator always has a larger effect on cooling load capacity while the performance degradation of the condenser always has an overall larger effect on the sub-cooler compressor power requirement as well as the COP of the system. In light of the data generated, a new performance degradation law, presented earlier, is shown to be applicable for this system as well that can reduce the amount of experimentation and help predict relevant quantities of the refrigeration system.

Abstract To transform the original centralized scheduling framework of integrated community energy systems (ICES), a decentralized scheduling method is proposed for the optimal operation of ICES. Firstly, linearized mathematical models of the electric distribution system and natural gas distribution system are established to eliminate the nonconvexity and nonlinearity of the multi-energy systems. Meanwhile, an improved energy hub model is proposed by introducing the state variable, which is able to obtain the optimal solution with better accuracy and higher efficiency. Secondly, a decentralized scheduling framework is developed via an improved consensus-based alternating direction method of multipliers (ADMM). By introducing several coupling links as consensus variables, the optimal operation of the ICES is decoupled according to the physical interactions among each sub-system, in which the original model can be solved parallelly in a decentralized manner. Only the consensus variables are exchanged among sub-systems so that the privacy and confidential items of each sub-system operated by different entities can be ensured. Finally, two different ICES test cases with different system scales are utilized to demonstrate the effectiveness of the proposed method, which is able to provide scheduling scheme same as the centralized method. Dynamic step size modification is further considered in the consensus-based ADMM. By updating the step size during each iteration, the computation expense of optimization process is reduced with less consuming time, iteration and apparent oscillation, by which the convergence performance of ADMM is improved with higher computation efficiency.

The unpredictable nature of renewable energies is drawing attention to lithium-ion batteries. In order to make full utilization of these batteries, some research works are focused on the management of existing systems, while others propose sizing techniques based on business models. However, in order to optimise the global system, a comprehensive methodology that considers both battery sizing and management at the same time is needed. This paper proposes a new optimisation algorithm based on a combination of dynamic programming and a region elimination technique that makes it possible to address both problems at the same time. This is of great interest, since the optimal size of the storage system depends on the management strategy and, in turn, the design of this strategy needs to take account of the battery size. The method is applied to a real installation consisting of a 100 kWp rooftop photovoltaic plant and a Li-ion battery system connected to a grid with variable electricity price. Results show that, unlike conventional optimisation methods, the proposed algorithm reaches an optimised energy dispatch plan that leads to a higher net present value. Finally, the tool is used to provide a sensitivity analysis that identifies key informative variables for decision makers The authors would like to acknowledge the support of the Spanish State Research Agency and FEDER-UE under grants DPI2016-80641-R and DPI2016-80642-R; of Government of Navarra through research project PI038 INTEGRA-RENOVABLES; and the FPU Program of the Spanish Ministry of Education, Culture and Sport (FPU13/00542).

Abstract The rapid development of power electronic devices has made them have higher power density, which puts forward higher requirements for cooling technology. The contribution of this paper is the integrated design of the liquid cooled heat sink for a 30 kW motor inverter considering the distribution of power devices. In order to find an optimal heat sink configuration, the cooling performance of three different configurations of heat sinks was investigated. And the distribution characteristics of the temperature and fluid velocity field were compared and analyzed. The heat sink with serpentine channel configuration was selected due to its best temperature uniformity and cooling characteristic. In addition, the effects of geometric parameters (fin thickness) and flow parameters (flow rate) on cooling performance were further studied. On this basis, the geometrical configuration of the heat sink was optimized. The experimental results of the optimized heat sink are in good agreement with the numerical simulation results. The motor inverter achieves high power density of 9.677 kW/kg.

Abstract With the increase of energy consumption and wastes generation due to human activities, anaerobic digestion (AD), a technology which turns wastes into bio-energy, is receiving more and more attention in the world. It is well known that there are at least three stages involved in anaerobic digestion, i.e., hydrolysis, acidification, and methanogenesis. Until now, however, the advances in enhancing acidification and methanogenesis have not been reviewed. This review provides a comprehensive overview of the methods reported to enhance each step involved in anaerobic digestion. More important, enzymes are the key to anaerobic digestion, and the strategies for improving enzyme activity are summarized. As electron transfer has been reported to play an important role in anaerobic digestion, the research progress of the approaches for the acceleration of direct interspecies electron transfer in methane production is also introduced. In addition, the recent advances in increasing the reduction of carbon dioxide to methane, which has been widely observed in methanogenesis step, are reviewed. Furthermore, the techno-economic assessment of anaerobic digestion is made, and the key points for future studies are proposed.