• Energy Research
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Ocean wave energy is considered to be one of the important potential renewable energy resources for sustainable development. Various wave energy converter technologies have been proposed to harvest the energy from ocean waves. This thesis is based on the linear generator wave energy converter developed at Uppsala University. The research in this thesis focuses on the foundation optimization and the power absorption optimization of the wave energy converters and on the wave climate modelling at the Lysekil wave converter test site.The foundation optimization study of the gravity-based foundation of the linear wave energy converter is based on statistical analysis of wave climate data measured at the Lysekil test site. The 25 years return extreme significant wave height and its associated mean zero-crossing period are chosen as the maximum wave for the maximum heave and surge forces evaluation.The power absorption optimization study on the linear generator wave energy converter is based on the wave climate at the Lysekil test site. A frequency-domain simplified numerical model is used with the power take-off damping coefficient chosen as the control parameter for optimizing the power absorption. The results show a large improvement with an optimized power take-off damping coefficient adjusted to the characteristics of the wave climate at the test site.The wave climate modelling studies are based on the wave climate data measured at the Lysekil test site. A new mixed distribution method is proposed for modelling the significant wave height. This method gives impressive goodness of fit with the measured wave data. A copula method is applied to the bivariate joint distribution of the significant wave height and the wave period. The results show an excellent goodness of fit for the Gumbel model. The general applicability of the proposed mixed-distribution method and the copula method are illustrated with wave climate data from four other sites. The results confirm the good performance of the mixed-distribution and the Gumbel copula model for the modelling of significant wave height and bivariate wave climate.

Quantitative and qualitative analyses of chemical species out of CI engine tailpipe emissions fueled with pure diesel and diesel methanol blends, trapped in dinitro phenylhydrazine (DNPH) solutions, were performed. The formed hydrazine was studied using high-performance liquid chromatography (HPLC) accompanied by a detector for ultraviolet (UV). A set of carbonyl-DNPH derivative standards was developed and compared with engine tailpipe gases produced by both fuel modes. An understanding of carbonyl chemical compounds such as formaldehyde, acetaldehyde, and acrolein (HCHO, CH3CHO, and H2 = CHCHO, respectively) is essential for researchers to know how these chemicals affect human health and the environment. In both fuel modes, acetaldehyde was the main combustible product 25 ppm followed by formaldehyde 17 ppm, croton aldehydes 16 ppm, acrolein 12 ppm, and iso-valerdyhyde 10 ppm. In addition to these species, only a few other chemical species were detected in the exhaust gas. According to this study, carbonyl compounds from blended fuel contribute 15–22% of pure diesel fuel emissions. As shown by the results, engine operating conditions and fuel mode have a strong impact on the total amount of carbonyls released by the engine. Engine performance was highly influenced by different fuel modes and engine speeds. Using pure diesel, the regulated emissions, HC, CO, and NOx, registered high concentrations at a lower speed (1500 rpm) and NOx presented with the highest concentration of 4 g/kWh followed by CO with 1 g/kWh and HC with 0.5 g/kWh.

<div> <div> <div> <p>Renewable energy (RE)-powered base stations (BSs) have been considered as an attractive solution to address the exponential increasing energy demand in cellular networks while decreasing carbon dioxide (CO2) emissions. For the regions where reliable power grids are insufficient and infeasible to deploy, such as aerial platforms and harsh environments, RE has been an alternative power source for BSs. In this survey paper, we provide an overview of RE-enabled cellular networks, detailing their analysis, classification, and related works. First, we introduce the key components of RE-powered BSs along with their frequently adopted models. Second, we analyze the proposed strategies and design issues for RE-powered BSs that can be incorporated into cellular networks and categorize them into several groups to provide a good grasp. Third, we introduce feasibility studies on RE-powered BSs based on the recent literature. Fourth, we investigate RE-powered network components other than terrestrial BSs to address potential issues regarding RE-enabled networks. Finally, we suggest future research directions and conclusions. </p><p><br></p> </div> </div> </div>

Over the past decade, decarbonization and environmental issues have taken a key role in worldwide politics [...]

The design of the facility is described in terms of its use as an investigation tool for evaluating crop growth in space with reference to required emerging technologies. NASA's CELSS Test Facility (CTF) is designed to permit the measurement of crop-plant productivity under microgravity conditions including biomass production, food production, water transpiration, and O2/CO2 exchanges. Crucial hardware tests and qualifications are identified to assure the operation of CTF technologies in space including the nutrient-delivery, water-condensation, and gas-liquid-mixing subsystems. The design concept and related scientific requirements are described and shown to provide microgravity crop research. The CTF is expected to provide data for plant research and for concepts for bioregenerative life-support systems for applications to Martian, lunar, and space-station missions.

The rapid evolution of wind energy in reducing CO2 emissions worldwide is undeniable, which is, in fact, expected to continue or even increase its impressive yearly capacity growth. In this regard, optimizing operations and maintenance of wind turbines (WTs) and farms is considered to be one of the options for reducing the levelized cost of electricity of wind energy. This can be achieved by developing innovative condition monitoring methods. To this end, the use of the windowed scalogram difference (WSD) algorithm, based on wavelets, is proposed as an alternative solution, combined with current signature analysis (CSA). The electric generator is one of the major contributors to WT failure rates and downtime, and doubly-fed induction generators (DFIGs) are the dominant technology in variable-speed WTs. In the present work, operational data on an in-service WT DFIG are analyzed over a period of eight months, in contrast to the majority of the studies in this field, which rely on laboratory or simulated data. The evolution of the fault, namely rotor mechanical asymmetry, at an early stage, is analyzed and quantified implementing WSD to the stator current signals, supported by the previous diagnosis achieved through CSA. The combination of CSA and WSD shows strong potential for diagnosing and tracking, respectively, incipient faults in in-service WT DFIGs. This work was supported in part by the Council of Communities of Castilla-La Mancha under Grant SBPLY/19/180501/000287, and in part by the European Union Fondo Europeo de Desarrollo Regional (FEDER).

With the increasingly prominent environmental problems in the world today, the development of an integrated energy system and the introduction of a carbon-trading mechanism have become important means to realize the low carbonization of the energy industry. Based on this, this paper introduces the carbon-trading mechanism into the research on the optimal dispatch of an integrated energy system. The mechanism of integrated energy demand response participating in low-carbon economic dispatch is analyzed. The relationship between carbon emissions and carbon-trading price in carbon-trading mechanism is described. On the basis of considering the commodity attributes of the electricity and gas load and the flexible supply characteristics of the thermal load, an incentive-type comprehensive energy demand response model is established. Finally, aiming at the lowest comprehensive operating cost, a comprehensive energy system model considering the power balance and equipment constraints of the electric–gas–heat system is established, using an improved particle swarm algorithm to solve it. Simulations verify the effectiveness of the proposed method in reducing the carbon emissions and operating costs of integrated energy systems.

Although battery electric vehicles (BEVs) are locally emission-free and assist automakers in reducing their carbon footprint, two major disadvantages are their shorter range and higher production costs compared to combustion engines. These drawbacks are primarily due to the battery, which is generally the heaviest and most expensive component of a BEV. Lightweight measures (strategies to decrease vehicle mass, e.g., by changing materials or downsizing components) lower energy consumption and reduce the amount of battery energy required (and in turn battery costs). Careful selection of lightweight measures can result in their costs being balanced out by a commensurate reduction in battery costs. This leads to a higher efficiency vehicle, but without affecting its production and development costs. In this paper, we estimate the lightweight potential of BEVs, i.e., the cost limit below which a lightweight measure is fully compensated by the cost savings it generates. We implement a parametric energy consumption and mass model and apply it to a set of BEVs. Subsequently, we apply the model to quantify the lightweight potential range (in €/kg) of BEVs. The findings of this paper can be used as a reference for the development of cheaper, lighter, and more energy-efficient BEVs.