After a major event affecting the world economy, oil prices tend to fluctuate due to the event in the next few months or even years. It can be seen that oil prices may have long-term correlation. In the processing of time series, the traditional ARMA model cannot accurately describe long memory, which leads to the deviation of parameter estimation during the modeling process. In order to better describe the long memory in the time series, this paper establishes the ARFIMA model to perform fractional difference on the series, and obtains the series satisfying the zero-mean ARMA process, then estimates the parameters. Further research shows that the Caputo fractional difference process is a specialized Grunwald-Letnikov (G-L) fractional differential process. Therefore, this paper introduces the Caputo fractional L1 formula into the time series model, and constructs a new fractional difference method to deal with Brent futures price return rate and perform ARFIMA modeling. This method works better in predicting than the traditional ARMA model and the G-L differential ARFIMA model. It can provide more effective assessments in economic markets such as oil price risk measurement and control, helping investors to better avoid market risks and obtain greater returns.
Deciding the location of bio refinery is an important task for management in biofuel supply and demand. This work presents a single-period deterministic model for the optimal location of butanol refinery. The developed model considers a whole system approach for butyric acid supply, butanol refinery and delivery systems. The proposed model determines where and how many refineries to be constructed and components (butyric acid and butanol) to be transported for minimizing the expected total network cost and satisfying regional demand of biofuel. The real scenario of the biofuel demand by region in South Korea is applied to validate the mathematical model. The optimization results will help to determine investment strategies for butanol production.
Microalgae biomass is composed of various bio‐ compounds which can be converted to biofuels. One type of solid fuel which can be derived from microalgae is biochar through torrefaction. However, the production of torrefied microalgae biochar may include environmental impact as it consumes raw materials and energy. A life cycle assessment of the production of torrefied microalgae biochar is proposed in the study using the torrefaction severity index. The results show the electricity requirement of the torrefaction largely contributes to the environmental impact and energy consumption. While the resulting global warming potential of the production of torrefied microalgae biochar using the torrefaction severity index yielded a non‐linear relation.
Research on upgrading of bio-oil in supercritical alcohols shows a potential to produce vehicle fuels from bio-crude. However, the separation of solvent alcohols and upgraded oil remains a problem. In this paper, biocrude derived from fast pyrolysis of rice husk was upgraded in supercritical CO2 with the catalysts of Pd, Ru, Pt (supported on activated carbon), in order to recycle the solvent from upgraded oil spontaneously. Results reveal that increase of reaction temperature promotes both esterification reaction and hydrogenation reaction, while increase of initial H2 pressure promotes the conversion of aldehydes, but decrease the conversion of phenols and sugars. On this basis, the production process of fast pyrolysis and supercritical CO2 upgrading was established and simulated with Aspen plus software. Through life cycle inventory analysis, the environmental impact of this process were studied, and then compared with upgrading in supercritical ethanol. The result shows weaknesses centered in the agricultural production and upgrading process. At last, the analytic hierarchy process is used to consider the weights of various environmental indicators to obtain a comprehensive LCA result. The final results display a slightly better environmental impact potential than that of ethanol.
Nowadays, the fundamental idea of district heating (DH) is to utilize local heat resources to satisfy local heat demands, otherwise those resources would be wasted. However, the mismatch between the achievable resources and fluctuating demand is challenging. This study analyzed the possibilities to solve this problem by introducing a short-term thermal storage and a seasonal thermal storage. A water tank (WT) and a borehole thermal storage (BTS) were chosen as the thermal storages. The DH system of a Norwegian university campus was selected as the case study. A high order system model was built in Modelica language. The results showed that the mismatch might be solved. The BTS brought about 3 GWh annual heat saving, and the WT brought about 110 kW average peak load shaving. However, around 0.8 GWh/year electricity was used by heat pump to recover the stored heat in the ground.
China is a vast country with great regional variations in economy level, resource endowments, industrial structure, demographics, and CO2 emissions level. Previous studies on regional CO2 emissions were usually confined to production- or consumption-based perspectives and neglected the emissions under income-based perspective as they also can be enabled by the use of primary inputs. To fill this gap, we investigate the variations of provincial CO2 emissions under these three perspectives in China during 2007–2012 and intend to identify out which type of final demand and primary input contributes most to the variations of provincial CO2 emissions. Results show that variations of domestic outflow and gross fixed capital formation contributed most to the emissions growth for most provinces under consumption-based perspective, while variations of domestic inflow and compensation of employees did so under income-based perspective. This work can help guide the development of just and effective mitigation policies for various provinces in China.
This article aims to model the transmission architecture of a planetary power split Hybrid Electric Vehicle (HEV) to improve fuel efficiency as well as to reduce emission, conforming sustainable design. The model is developed using model based equations, retrieved from literature and Design of Experiment with response surface solution mode. Development of power management strategy for the above, utilizing associated mathematical modeling of the proposed gearset topology guided transmission architecture is disseminated in this work. Design solution for suitable gearset topology is derived by utilizing response surface method and genetic algorithm. The result shows that connection between planetary gear stages, amongst considered variables, holds highest significance and also helps to infer that most suitable configuration is to couple the engine with the second planet carrier for a two-stage power split device. The modelling-based result depicts successful implementation of two stage planetary gear train as power split device with fossil fuel consumption reduction of 49.16%, maximizing electric power utilization for greener transportation.
Large scale utilization of solar energy has become an inevitable trend of an energy-efficient and environment-friendly society. A two-stage robust allocation model of solar energy equipments in district integrated energy systems is proposed in this paper with the uncertainty of solar irradiance and operating constraints of energy networks. To improve the solvability, the above non-convex non-linear model is converted to a 0-1 mixed integer second-order cone problem. The validity of the model is verified by typical cases.
Driven by climate change concerns, our energy system has been under steady change. Renewable energy sources are increasingly used to decarbonize our energy system, making it also more decentralized. At the same time, information and communications technologies (ICT) are enabling smart services for consumers, offering financial benefits through demand side management (DSM) programs. This study investigates various DSM solutions for a detached house in Northern Finnish conditions in 2050. A thermal model is used to model the thermal behavior of the building and test out DSM programs in direct electric space heating and underfloor heating alternatives. The 2050 scenarios are created from climate change projections, existing data on electricity generation and from projections on the future energy system and cost of electricity. The results indicate that load shifting with photovoltaic (PV) generation is a potential way of reducing costs and CO2 emissions both today and in 2050, but it lacks economic feasibility due to long payback times of the investments. Cost optimized direct electric space heating and underfloor heating are both able to provide economic and environmental benefits when compared to manually controlled heating. The scenarios presented in the paper suggest that 95-96% emission reduction can be achieved; however, the electricity cost of households is expected to increase by 174-253%. At the same time electricity consumption from the grid is expected to reduce by 3- 10% in all the scenarios.
Thermal management of large-format Li-ion cells is crucial due to their spatial- and temperature-dependent electrochemical reaction kinetics and heat generation. However, existing battery modeling mostly employs a pseudo-2D model which is not able to capture the local current density and temperature across the entire cell geometry. Therefore, in this paper, we propose a simplified 3D electrochemical/thermal model to investigate the temperature and voltage responses of a Li-ion pouch cell. Concurrently, a lock-in thermography experiment is conducted. The model can achieve good accuracy in predicting the surface temperature and cell voltage of the battery during cycling. A scaling analysis is subsequently carried out to determine the dimensionless numbers that affect the battery performance. The proposed approach helps to facilitate a fundamental understanding of the dominant mechanisms related to voltage polarization, heat generation and temperature non-uniformity.