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Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022). This version includes an update of heat storage of global ocean heat content, where one additional product (Li et al., 2022) had been included to the initial estimate. The Earth heat inventory had been updated accordingly, considering also the update for continental heat content (Cuesta-Valero et al., 2023).

The Danish energy system is undergoing a transition from a system based on storable fossil fuels to a system based on fluctuating renewable energy sources. At the same time, more of and more of the energy system is becoming electrified; transportation, heating and fuel usage in industry and elsewhere. This article investigates the development of the Danish energy system in a medium year 2030 situation as well as in a long-term year 2050 situation. The analyses are based on scenario development by the Danish Climate Commission. In the short term, it is investigated what the effects will be of having flexible or inflexible electric vehicles and individual heat pumps, and in the long term it is investigated what the effects of changes in the load profiles due to changing weights of demand sectors are. The analyses are based on energy systems simulations using EnergyPLAN and demand forecasting using the Helena model. The results show that even with a limited short-term electric car fleet, these will have a significant effect on the energy system; the energy system’s ability to integrated wind power and the demand for condensing power generation capacity in the system. Charging patterns and flexibility have significant effects on this. Likewise, individual heat pumps may affect the system operation if they are equipped with heat storages. The analyses also show that the long-term changes in electricity demand curve profiles have little impact on the energy system performance. The flexibility given by heat pumps and electric vehicles in the long-term future overshadows any effects of changes in hourly demand curve profiles. International Journal of Sustainable Energy Planning and Management, Vol 7 (2015)

Cathode materials have been the focal point of research in the quest for high-performance secondary battery technology in consumer electronics and electric vehicles. The present work investigates the effect of the microstructural morphology of major cathode materials (LiCoO2, LiMn2O4, and LiFePO4) on the performance of the Li-ion battery related to the charge and species transport. Simulated annealing method (SAM) was implemented to generate a virtual 3D domain of the electrode microstructure using a spherical particles, average radius of 3 and 6 mu m. An equivalent circuit composed of resistance, capacitance and Warburg impedance was used to model the impedance response of the overall electrochemical reaction occur inside a typical battery system. Electrochemical impedance spectroscopy (EIS) results show that the ionic and electronic mobility in the solid electrode and bulk electrolyte were significantly determined by the morphology of the electrode microstructure. Higher porosity microstructures usually tend to have larger solid-electrolyte interface (SEI) area and lower pore tortuosity which improves the ionic diffusivity in solid and electrolyte phase. Furthermore, the Bruggeman's exponent for effective conductivity and diffusivity was derived from geometrical parameters of the reconstructed microstructure. The real and imaginary parts of the impedance were then presented in Nyquist plot on a frequency range of 20 kHz to 10 mHz.

This paper proposes a home health care location-routing problem with a mixed fleet of electric and conventional vehicles that considers battery swapping stations. It aims to simultaneously determine the locations of HHC centers, the scheduling of caregivers with respect to skill requirements, and a routing plan for a mixed fleet under specific time windows, load capacities, synchronized visits, and driving ranges. To address this problem, the paper proposes a novel competitive simulated annealing (CSA) algorithm in which a series of problem-specific effective local search operators expand the solution space of the CSA algorithm, with a competitive mechanism to adaptively adjust these operators to accelerate convergence speed and improve exploration ability. To enhance the exploitation ability, it employs a modified simulated annealing algorithm with a heating strategy and variable neighborhood descent. The code of competitive simulated annealing algorithm is provided here in order to address home health care location-routing problem with a mixed fleet and battery swapping stations

The main aim of the paper is to estimate the demand for road-based passenger mobility in India and subsequently project the energy demand and CO2 emissions resulting from the same. Based on a data set of the four major motorized modes of transport – buses, cars (including jeeps and taxis), two-wheelers, and auto-rickshaws from 1950-51 to 2000-01, long-term trends in motorized traffic volume and modal split are projected up to the year 2030-31. It is found that the road-based traffic volume in India will increase from 3079 billion passenger-kilometers in 2000-01 to 12546 billion passenger-kilometers in 2030-31. Between 2000-01 and 2030-31, the aggregate share of private- and para-transit modes is projected to increase from 24.3% to 55.3% whereas the share of public transport mode is estimated to decrease from 75.7% to 44.7%. Based on the projected values of aggregate traffic volume, modal split, and modal intensities for energy demand and CO2 emissions, the paper then estimated the level of energy demand and CO2 emission from the road-based passenger transport sector in India. If there is no reduction in modal intensities, energy demand is projected to increase from 954 peta joules in 2000-01 to 5897 peta joules in 2030- 31 whereas CO2 emission is estimated to increase from 17.27 to 93.22 million metric tons of carbon equivalent during the same period. Even when we assume a reduction of 1% per year in energy and CO2 intensity of all modes of transport, energy demand and CO2 emission is projected to increase by a 4.6- and 4.0-fold respectively from 2000-01 to 2030-31.

Project: GCOS Earth Heat Inventory - A study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory (EHI), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period from 1960 to present. Summary: The file “GCOS_EHI_1960-2020_Earth_Heat_Inventory_Ocean_Heat_Content_data.nc” contains a consistent long-term Earth system heat inventory over the period 1960-2020. Human-induced atmospheric composition changes cause a radiative imbalance at the top-of-atmosphere which is driving global warming. Understanding the heat gain of the Earth system from this accumulated heat – and particularly how much and where the heat is distributed in the Earth system - is fundamental to understanding how this affects warming oceans, atmosphere and land, rising temperatures and sea level, and loss of grounded and floating ice, which are fundamental concerns for society. This dataset is based on a study under the Global Climate Observing System (GCOS) concerted international effort to update the Earth heat inventory published in von Schuckmann et al. (2020), and presents an updated international assessment of ocean warming estimates, and new and updated estimates of heat gain in the atmosphere, cryosphere and land over the period 1960-2020. The dataset also contains estimates for global ocean heat content over 1960-2020 for different depth layers, i.e., 0-300m, 0-700m, 700-2000m, 0-2000m, 2000-bottom, which are described in von Schuckmann et al. (2022).

The photovoltaic spectral features and the behaviors of photocurrent versus the electrode potential for near surface In0.15Ga0.85As/GaAs quantum well electrodes have been investigated in nonaqueous solutions of ferrocene and acetylferrocene. The photovoltaic spectrum shows a sharp structure that reflects confined state-to-state exciton transition in the quantum well. Deep dips are observed in the photocurrent versus the electrode potential curves in both electrolytes at the different electrode potentials under the illumination of exciton resonance wavelength. These dips are qualitatively explained by considering the interfacial tunneling transfer of photogenerated electron within the quantum well.

PolyU Library Call No.: [THS] LG51 .H577P EE 2016 Luo ; xvi, 167 pages :color illustrations ; Global environmental crises, such as the global climate change and awful air pollution in major cities over the world, are causing profound changes to both the power system and the transportation sector. On one hand, power systems worldwide are evolving towards a greener version by integrating increasing amount of renewable energy sources, especially wind power (WP). On the other hand, as an effective way to reduce greenhouse gas emission, plug-in electric vehicles (PEVs) are currently incentivized in many countries and more and more types of PEV are being rolled out by various automakers. With the adoption of PEV surging, a rapid increase of PEV charging load can be expected in the coming years. The uncertainty and variability of WP generation will weaken the controllability on the supply side of the power system and require more fast-reacting reserve, while bulk uncontrolled PEV charging may severely stress the network at all voltage levels, threatening the system reliability, lowering its efficiency, and jeopardizing the system economy. Controlled PEV charging, however, could be a valuable source for large-scale demand response (DR). The DR is identified as a very effective tool to facilitate smooth WP integration, and clean electricity from WP to propel PEVs can significantly decarbonize the transportation sector. Thus, a lot of synergies can be explored between the PEV charging load and the WP generation. As an effort to safely accommodate the PEV charging load at the initial stage of PEV adoption before the upgrade of the network infrastructure, this thesis firstly proposes a real-time scheduling scheme for PEV charging in low-voltage residential distribution network. This scheme schedules PEV charging to either minimize system losses or prevent over-low voltage, depending on the PEV penetration level. Since most often voltage drop would become a binding constraint when a low-voltage distribution feeder is subject to high PEV penetration level, a scheduling method is first developed to enlarge the voltage safety margin. Then, a novel factor is derived to allow the scheduling scheme to be flexibly adjusted from being voltage-safety-oriented to loss-minimization-oriented, or vice versa. Simulation results verify that the proposed scheduling scheme is fast and effective with circuit losses close to optimal at low PEV penetration level and voltage drops maintained within the tolerable limit at high PEV penetration level. ; To facilitate the PEV demand response, a decentralized charging control scheme is devised in this thesis. In the proposed control scheme, individual PEV would autonomously adjust its power in response to two system-level directional signals. Since the power adjustment would also take into account the PEV's urgency level of charging (ULC), the charging/discharging power among PEVs will be distributed automatically according to their heterogeneous charging requirements. The mechanism that can trigger divergent PEV power adjustment is analyzed to obtain the stability condition for the proposed control scheme. For the control inaccuracy caused by interrupted individual PEV power adjustments, a remedy is proposed and proved. As an application, the power of a PEV fleet is controlled by the proposed decentralized charging control scheme to compensate undesired fluctuations in a wind farm's power output. Simulation results verify that the controlled PEV power can respond to undesired WP fluctuations timely and accurately, and the power distribution among PEVs is consistent with the heterogeneous PEV charging requirements. Increasing amount of WP in the power system will force conventional generators to go through more frequent cycling operations which have damaging effects on generator components. In this context, a 3-level hierarchical scheme is proposed to utilize the PEV power to hedge against the unit ramp cycling (URC) operations. A general URC operation model is proposed for the first time. Net load variation range (NLVR) is used to capture the WP forecast uncertainty. The top-level scheduling model reshapes the NLVR by coordinating PEV charging load to minimize the URC operations that can be caused by the possible net load realizations in the NLVR. Based on updated WP forecasts, the middle-level dispatch model exempts the over-scheduled anti-URC regulation onus on PEVs to promote PEV charging. Nevertheless, the actual dispatch of net load is confined within the reshaped NLVR from the top-level scheduling to avoid overly restoring the PEV power. At the bottom-level is the proposed decentralized charging control scheme to implement the PEV power dispatch instruction. Simulation results show that with the proposed hierarchical scheme, the PEV-aided URC operation mitigation is effective and most of the desired charging energy is preserved to satisfy the charging requirements for the majority of PEVs. The effectiveness of the proposed scheme is shown to be robust to WP forecast errors. The associated cost to accommodate the WP uncertainty and variability (WPUnV) in a power system is referred as the wind power uncertainty cost (WPUC) which would increase rapidly with WP penetration level. This thesis investigates to what extent the controlled PEV power would help reduce this WPUC. A comprehensive WPUC model is proposed in which generator cycling costs are included. Also, the proposed decentralized charging control scheme is used to obtain a realistic response of the PEV load to the system dispatch instruction. With the WPUnV decomposed into two components, namely hourly WP forecast errors and sub-hourly WP fluctuations, the WPUC raised by each of the components will be evaluated. Simulation results show that generator cycling costs are non-negligible parts of the WPUC and controlled PEV power has a favorable effect on reducing the overall WPUC. The controlled PEV power, however, may not be as helpful as expected to mitigate the WPUC induced by the WP forecast errors on hourly scale. Yet, the WPUC raised by sub-hourly WP fluctuations can be largely reduced with the controlled PEV power. ; Department of Electrical Engineering ; Ph.D., Department of Electrical Engineering, The Hong Kong Polytechnic University, 2016 ; Doctorate ; published_final

The adoption of electric vehicles (EVs) is considered a promising solution to address the negative impacts of conventional vehicles on the environment and human health. This paper provides a comprehensive review of the current state of EVs, including their types, technology, adoption, government policies, environmental impact, and future prospects. The review reveals that EVs have the potential to significantly reduce air pollution, greenhouse gas emissions, and noise pollution. However, their adoption has been hindered by various factors such as perceived usefulness, ease of use, and risk, which can be addressed through policy interventions and infrastructure development. The paper highlights the significance of the Faster Adoption and Manufacturing of Electric Vehicles (FAME) scheme in India and other international policies and initiatives to support the adoption of EVs. The review also identifies the technological advances and battery development as promising opportunities for the future of EVs. The paper concludes by providing implications for policy and practice, including the need for incentives and infrastructure development to promote EV adoption and recommends further research on the consumer trends and challenges in the adoption of EVs.