To minimize the impacts of climate change, it is increasingly clear that global CO2 emissions should be eliminated by 2050 (IPCC, 2018) and that advanced cities for carbon neutrality should have net zero emissions by 2040. However, the precise pathways by which they can reach such ambitious goals, have not been identified. As the costs of photovoltaics (PV), batteries, and electric vehicles (EV2) likely keep falling, they will play key roles for deep decarbonization. Here, we conduct a technoeconomic analysis of a city-scale energy system with PV, batteries, and EVs for the city of Kyoto, Japan. We find that aggressive EV adoption could help PV penetration in the city with substantially lower costs than just deploying PV and batteries alone. CO2 emissions from vehicle and electricity usages from the city could be reduced by 70- 80% in 2030 if 60% of current cars are replaced by EVs, at the same time reducing the costs by 40-50%.
In smart grid, smart meter (SM) samples the energy consumption of users at high frequency. By analyzing measurement data, users’ behavior patterns can be identified, which threatens consumers’ privacy. This paper studies the protection of SM privacy by solar power generation system and rechargeable battery (RB). Solar energy provides alternative power other than power grids for users. RB provides energy storage. Under the constraints of RB physical conditions and solar radiation, a “privacy-cost dual optimization model” is proposed to minimize the weighted sum of privacy leakage and power consumption costs. In order to solve the optimization problem, we propose a new optimization algorithm. The simulation results show the effectiveness of the algorithm. The effects of different target curves on privacy protection are studied.
The relationship between air temperature and energy consumption at the city level has been investigated to better understand the impact of the climate change on energy demands. Temperature rising caused by the climate change has been shown to lead to the increase of building energy demands. Buildings also contribute to climate change by radiating heat from building surfaces. In this respect, this study aims to evaluate the potential impact of building rooftop and façade surface temperatures on household energy consumption. We developed a method that combines multiple scale observations, including an Internet of things (IoT) sensor network and remote sensing, to estimate the relationship between surface temperatures and energy consumption. The results will contribute to managing building energy uses based on the better understanding of micro-scale temperature effects in urban area.
A computational fluid dynamic (CFD) model has been developed for the fuel reactor of a chemical looping gasification (CLG) system with biomass as fuel and natural hematite as oxygen carrier (OC). By coupling the fluid dynamics and the chemical kinetics, the multiphase continuum model is able to describe the motion of gas and solid phases and the heterogeneous reactions between them, which take place in a bubbling fluidized bed reactor. The simulated average concentrations of five gas species fit the experimental data provided in the literature quite well, with a deviation for each gas component lower than 2%. This verified model is then applied to investigate the effects of various gasifying agents on the compositions of syngas. The results show that the biomass CLG performance is significantly improved in the presence of CO2/H2O and their mixture. Furthermore, synergistic effect of CO2/H2O mixture can be observed based on the evolution of char mass within the reactor.
In this paper, an active support control strategy based on the third-order model of synchronous generator is proposed for battery energy storage system in renewable energy systems. The control strategy converts grid-connected inverters of energy storage system into synchronous voltage sources with excitation and speed control systems, which provides necessary inertia and damping characteristics for grid-connected renewable energy sources. The difference coefficient σbattery% of the BESS is defined by the power-frequency proportional coefficient Km and the damping coefficient D. By setting the difference coefficient σbattery%, it is possible to control the frequency modulation depth of the BESS to participate in the primary frequency response of renewable power generation system. The output power for primary frequency response of the synchronous generator is reduced, and the steady frequency deviation of the system after primary frequency modulation can be reduced. Therefore, the frequency stability of the renewable energy systems for power generation are improved.
Durability is a major issue against the commerciali-zation of proton exchange membrane fuel cells (PEMFC). Several mechanisms play an important role on the deg-radation of the cathode catalyst layer (CCL) by deterio-rating the transport properties of reactants in the CCL mainly. A pseudo three-dimensional (P3D), two-phase, and non-isothermal model is used to study the effects of cell degradation on transport properties of the CCL. Ac-curacy of the model is verified by comparing the polari-zation curves from the model with the experimental ones reported in the literature. The model is used to investi-gate the effects of CCL transport properties and agglom-erate parameters on cell performance. Results demon-strate that the cell performance is improved for thinner ionomer film around agglomerates, smaller agglomer-ates, higher exchange current density, lower transport resistance and higher proton conductivity of the CCL. The transport parameters of the CCL are varied to fit the po-larization curves to the experimental ones for an acceler-ated stress test. It is found that the transport resistances increase exponentially with the carbon loss in the CCL.
Effectively treating industrial SO2 emissions depends on the synergy of different factors from the industrial SO2 generation source to the end of treatment. This study proposes a multi-region decomposition and attribution analysis approach to analyze the contributions of SO2 emissions treatment. The approach can decompose industrial SO2 emissions into six specific driving factors, including three whole process treatment (WPT) dimensions (i.e. source prevention, process control, and end-of-pipe treatment). This provides more detailed information about each factor’s treatment effect from both temporal and spatial perspectives, and the contribution of each region to the key driving factors. The empirical study across 30 regions in China using data from 2005-2015 shows that the end-of-pipe treatment is the dominant dimension for decreasing industrial SO2 emissions, of which Shandong, Inner Mongolia and Guangdong are the main contributors. The energy structure is the main factor promoting industrial SO2 emissions reduction in the source prevention dimension. The treatment emphases are different among regions, and regions can be classified into four categories. Based on the empirical results, this paper identifies the policy implications of promoting China’s industrial SO2 emissions reduction.
Process simulation with stoichiometric mass, energy and exergy balance analysis of a pilot bio-light olefin production facility via gasification and methanol synthesis from forestry residues were investigated using Aspen Plus software. The mass yield of the process was 0.127kg light olefins per kg dry feedstock, which was comparable to the current status for biofuel production. 40.7% of potential energy of the forestry residue feedstock leaves as bio-light olefin, together with 2.33% as electricity export. The exergetic analysis of the whole process indicated that 22.6%, 22.2% and 11.5% of feedstock exergy were irreversible lost in the boiler/turbogenerator, gasifier and light olefin separation. And the exergetic efficiency of light olefins was 32.1%. The calculation procedure and balance evaluation criterial presented offered a valuable theoretical basis for improving process performance for bio-light olefin production application.
Amorphous silicon (a-Si) have a lower thermal coefficient, but the electrical performance is undermined by the fact of Staebler-Wronski (S-W) effect. Study on the effects of temperature on a-Si cells shows that a-Si cells can obtain higher electrical output at higher operating temperatures. This property makes a-Si cells more suitable for photovoltaic/thermal (PV/T) system where the operating temperature can easily reach higher level. At present, a-Si cells have attracted less attention in the PV/T application, but are promising photovoltaic (PV) materials for PV/T system. Research on the effects of temperature on a solo a-Si cell is already available, but the long-term impact on the a-Si PV/T system is still lacking. In a PV/T system, the operating temperature not only affects the electrical and thermal performance, but also the technical and thermodynamic reliability. To investigate the effect of temperature on the performance of a-Si PV/T system, long-term outdoor experiments of two identical a-Si PV/T systems operating at medium temperature (60°C) and low temperature (30°C) have been conducted from December 2017 to June 2019. At the initial phase of the long-test test, the electrical efficiency of the a-Si PV/T system operating at 30°C is 6.14%, which is much higher than that at 60°C (5.69%). During the long-term operation, both the electrical performances at 30°C and 60°C show an obvious download trend owing to the S-W effect. The initial difference in the electrical efficiency between 30°C and 60°C is 0.47%, while the gap eventually narrows to only 0.13%. In the past year and a half, the two a-Si PV/T systems operated stably without significant degradation in thermal and electrical performance. Through the long-term performance monitoring at different operation temperatures, it is demonstrated that a-Si cells are suitable for the PV/T application.
Accurate capacity estimation is of vital importance for lithium-ion battery management. In this paper, an adaptive battery capacity estimation method based on incremental capacity analysis (ICA) is proposed. First of all, the second-order central least squares method is employed to smooth the charging data and obtain the incremental capacity (IC) curve. Then some battery experiments, including the complete charging and partial charging, are designed and conducted. For the complete charging, the relationship between the features of IC curves and battery capacity fading is investigated. For the limitation of ICA on partial charging, the correction method considering the charging initial SOC and battery aging status is proposed. Finally, the algorithm framework of the adaptive capacity estimation based on ICA is put forward.