481 resultados para Renewable diesels


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The global efforts to reduce carbon emissions from power generation have favoured renewable energy resources such as wind and solar in recent years. The generation of power from the renewable energy resources has become attractive because of various incentives provided by government policies supporting green power. Among the various available renewable energy resources, the power generation from wind has seen tremendous growth in the last decade. This article discusses various advantages of the upcoming offshore wind technology and associated considerations related to their construction. The conventional configuration of the offshore wind farm is based on the alternative current internal links. With the recent advances of improved commercialised converters, voltage source converters based high voltage direct current link for offshore wind farms is gaining popularity. The planning and construction phases of offshore wind farms, including related environmental issues, are discussed here.

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In order to protect our planet and ourselves from the adverse effects of excessive CO2 emissions and to prevent an imminent non-renewable fossil fuel shortage and energy crisis, there is a need to transform our current ‘fossil fuel dependent’ energy systems to new, clean, renewable energy sources. The world has recognized hydrogen as an energy carrier that complies with all the environmental quality and energy security, demands. This research aimed at producing hydrogen through anaerobic fermentation, using food waste as the substrate. Four food waste substrates were used: Rice, fish, vegetable and their mixture. Bio-hydrogen production was performed in lab scale reactors, using 250 mL serum bottles. The food waste was first mixed with the anaerobic sewage sludge and incubated at 37°C for 31 days (acclimatization). The anaerobic sewage sludge was then heat treated at 80°C for 15 min. The experiment was conducted at an initial pH of 5.5 and temperatures of 27, 35 and 55°C. The maximum cumulative hydrogen produced by rice, fish, vegetable and mixed food waste substrates were highest at 37°C (Rice =26.97±0.76 mL, fish = 89.70±1.25 mL, vegetable = 42.00±1.76 mL, mixed = 108.90±1.42 mL). A comparative study of acclimatized (the different food waste substrates were mixed with anaerobic sewage sludge and incubated at 37°C for 31days) and non-acclimatized food waste substrate (food waste that was not incubated with anaerobic sewage sludge) showed that acclimatized food waste substrate enhanced bio-hydrogen production by 90 - 100%.

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Modern power systems have become more complex due to the growth in load demand, the installation of Flexible AC Transmission Systems (FACTS) devices and the integration of new HVDC links into existing AC grids. On the other hand, the introduction of the deregulated and unbundled power market operational mechanism, together with present changes in generation sources including connections of large renewable energy generation with intermittent feature in nature, have further increased the complexity and uncertainty for power system operation and control. System operators and engineers have to confront a series of technical challenges from the operation of currently interconnected power systems. Among the many challenges, how to evaluate the steady state and dynamic behaviors of existing interconnected power systems effectively and accurately using more powerful computational analysis models and approaches becomes one of the key issues in power engineering. The traditional computing techniques have been widely used in various fields for power system analysis with varying degrees of success. The rapid development of computational intelligence, such as neural networks, fuzzy systems and evolutionary computation, provides tools and opportunities to solve the complex technical problems in power system planning, operation and control.

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Despite tough economic times, the uptake of photovoltaic (PV) technology has seen tremendous growth over the past decade. More than 21 GW of rooftop PV systems were installed globally in the year 2012 alone. This is fueled by various incentives offered by policy makers around the world with a goal of enhancing renewable energy integration and reducing the dependence on fossil fuels. For instance, the goal of achieving 20% energy consumption from renewable resources by 2020 has been unanimously accepted by numerous countries in Europe, North America, and Australia. Uptake of PVs by residential and small businesses has been augmented by generous rebates offered by government on installations and on the amount of energy injected into the grid. Furthermore, the global market outlook report published by EPIA predicts that the rooftop PV installations will continue to grow for the foreseeable future.

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Due to the increasing recognition of global climate change, the building and construction industry is under pressure to reduce carbon emissions. A central issue in striving towards reduced carbon emissions is the need for a practicable and meaningful yardstick for assessing and communicating greenhouse gas (GHG) results. ISO 14067 was published by the International Organization for Standardization in May 2013. By providing specific requirements in the life cycle assessment (LCA) approach, the standard clarifies the GHG assessment in the aspects of choosing system boundaries and simulating use and end-of-life phases when quantifying carbon footprint of products (CFPs). More importantly, the standard, for the first time, provides step-to-step guidance and standardized template for communicating CFPs in the form of CFP external communication report, CFP performance tracking report, CFP declaration and CFP label. ISO 14067 therefore makes a valuable contribution to GHG quantification and transparent communication and comparison of CFPs. In addition, as cradle-to-grave should be used as the system boundary if use and end-of-life phases can be simulated, ISO 14067 will hopefully promote the development and implementation of simulation technologies, with Building Information Modelling (BIM) in particular, in the building and construction industry.

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This paper presents simulation results for future electricity grids using an agent-based model developed with MODAM (MODular Agent-based Model). MODAM is introduced and its use demonstrated through four simulations based on a scenario that expects a rise of on-site renewable generators and electric vehicles (EV) usage. The simulations were run over many years, for two areas in Townsville, Australia, capturing variability in space of the technology uptake, and for two charging methods for EV, capturing people's behaviours and their impact on the time of the peak load. Impact analyses of these technologies were performed over the areas, down to the distribution transformer level, where greater variability of their contribution to the assets peak load was observed. The MODAM models can be used for different purposes such as impact of renewables on grid sizing, or on greenhouse gas emissions. The insights gained from using MODAM for technology assessment are discussed.

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Non-thermal plasma (NTP) has been introduced over the past several years as a promising method for nitrogen oxide (NOx) removal. The intent, when using NTP, is to selectively transfer input electrical energy to the electrons, and to not expend this in heating the entire gas stream, which generates free radicals through collisions, and promotes the desired chemical changes in the exhaust gases. The generated active species react with the pollutant molecules and decompose them. This paper reviews and summarizes relevant literature regarding various aspects of the application of {NTP} technology on {NOx} removal from exhaust gases. A comprehensive description of available scientific literature on {NOx} removal using {NTP} technology is presented, including various types of NTP, e.g. dielectric barrier discharge, corona discharge and electron beam. Furthermore, the combination of {NTP} with catalyst and adsorbent for better {NOx} removal efficiency is presented in detail. The removal of {NOx} from both simulated gases and real diesel engines is also considered in this review paper. As {NTP} is a new technique and is not yet commercialized, there is a need for more studies to be performed in this field.

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This work explores the potential of Australian native plants as a source of second-generation biodiesel for internal combustion engines application. Biodiesels were evaluated from a number of non-edible oil seeds which are grow naturally in Queensland, Australia. The quality of the produced biodiesels has been investigated by several experimental and numerical methods. The research methodology and numerical model developed in this study can be used for a broad range of biodiesel feedstocks and for the future development of renewable native biodiesel in Australia.

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The relationship between corporate and sustainability performance continues to be controversial and unclear, not withstanding numerous theoretical and empirical studies. Despite this, views on corporate responsibilities “meet where management can show how voluntary social and environmental management contributes to the competitiveness and economic success of the company.” This approach is fundamental to the business case for infrastructure sustainability. It suggests that beyond-compliance activities undertaken by companies are commercially justified if they can be shown to contribute to profitability and shareholder value. Potential public good benefits range across a wide spectrum of economic (for example employment, local purchasing, reduced demand for electricity generation), social (indigenous employment and development, equity of access), and environmental (lower greenhouse gas emission, reduced use of non-renewable resources and potable water, less waste, enhanced biodiversity). Some of these benefits have impacts that lie in more than one of the economic, social, and environmental areas of public goods. Using a sustainability rating schemes and potential business benefits from sustainability initiatives, this paper presents a brief summary of an online survey of industry that identifies how rating scheme themes and business benefits relate. This allows for a case to be built demonstrating which sustainability themes offer particular business benefits.

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Many complex aeronautical design problems can be formulated with efficient multi-objective evolutionary optimization methods and game strategies. This book describes the role of advanced innovative evolution tools in the solution, or the set of solutions of single or multi disciplinary optimization. These tools use the concept of multi-population, asynchronous parallelization and hierarchical topology which allows different models including precise, intermediate and approximate models with each node belonging to the different hierarchical layer handled by a different Evolutionary Algorithm. The efficiency of evolutionary algorithms for both single and multi-objective optimization problems are significantly improved by the coupling of EAs with games and in particular by a new dynamic methodology named “Hybridized Nash-Pareto games”. Multi objective Optimization techniques and robust design problems taking into account uncertainties are introduced and explained in detail. Several applications dealing with civil aircraft and UAV, UCAV systems are implemented numerically and discussed. Applications of increasing optimization complexity are presented as well as two hands-on test cases problems. These examples focus on aeronautical applications and will be useful to the practitioner in the laboratory or in industrial design environments. The evolutionary methods coupled with games presented in this volume can be applied to other areas including surface and marine transport, structures, biomedical engineering, renewable energy and environmental problems.

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For wind farm optimizations with lands belonging to different owners, the traditional penalty method is highly dependent on the type of wind farm land division. The application of the traditional method can be cumbersome if the divisions are complex. To overcome this disadvantage, a new method is proposed in this paper for the first time. Unlike the penalty method which requires the addition of penalizing term when evaluating the fitness function, it is achieved through repairing the infeasible solutions before fitness evaluation. To assess the effectiveness of the proposed method on the optimization of wind farm, the optimizing results of different methods are compared for three different types of wind farm division. Different wind scenarios are also incorporated during optimization which includes (i) constant wind speed and wind direction; (ii) various wind speed and wind direction, and; (iii) the more realisticWeibull distribution. Results show that the performance of the new method varies for different land plots in the tested cases. Nevertheless, it is found that optimum or at least close to optimum results can be obtained with sequential land plot study using the new method for all cases. It is concluded that satisfactory results can be achieved using the proposed method. In addition, it has the advantage of flexibility in managing the wind farm design, which not only frees users to define the penalty parameter but without limitations on the wind farm division.

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Wind energy, being the fastest growing renewable energy source in the present world, requires a large number of wind turbines to transform wind energy into electricity. One factor driving the cost of this energy is the reliable operation of these turbines. Therefore, it is a growing requirement within the wind farm community, to monitor the operation of the wind turbines on a continuous basis so that a possible fault can be detected ahead of time. As the wind turbine operates in an environment of constantly changing wind speed, it is a challenging task to design a fault detection technique which can accommodate the stochastic operational behavior of the turbines. Addressing this issue, this paper proposes a novel fault detection criterion which is robust against operational uncertainty, as well as having the ability to quantify severity level specifically of the drivetrain abnormality within an operating wind turbine. A benchmark model of wind turbine has been utilized to simulate drivetrain fault condition and effectiveness of the proposed technique has been tested accordingly. From the simulation result it can be concluded that the proposed criterion exhibits consistent performance for drivetrain faults for varying wind speed and has linear relationship with the fault severity level.

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This work is a MATLAB/Simulink model of a controller for a three-phase, four-wire, grid-interactive inverter. The model provides capacity for simulating the performance of power electroinic hardware, as well as code generation for an embedded controller. The implemented hardware topology is a three-leg bridge with a neutral connection to the centre-tap of the DC bus. An LQR-based current controller and MAF-based phase detector are implemented. The model is configured for code generation for a Texas Instruments TMS320F28335 Digital Signal Processor (DSP).

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Displacement of conventional synchronous generators by non-inertial units such as wind or solar generators will result in reduced-system inertia affecting under-frequency response. Frequency control is important to avoid equipment damage, load shedding, and possible blackouts. Wind generators along with energy storage systems can be used to improve the frequency response of low-inertia power system. This paper proposes a fuzzy-logic based frequency controller (FFC) for wind farms augmented with energy storage systems (wind-storage system) to improve the primary frequency response in future low-inertia hybrid power system. The proposed controller provides bidirectional real power injection using system frequency deviations and rate of change of frequency (RoCoF). Moreover, FFC ensures optimal use of energy from wind farms and storage units by eliminating the inflexible de-loading of wind energy and minimizing the required storage capacity. The efficacy of the proposed FFC is verified on the low-inertia hybrid power system.

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Intermittent generation from wind farms leads to fluctuating power system operating conditions pushing the stability margin to its limits. The traditional way of determining the worst case generation dispatch for a system with several semi-scheduled wind generators yields a conservative solution. This paper proposes a fast estimation of the transient stability margin (TSM) incorporating the uncertainty of wind generation. First, the Kalman filter (KF) is used to provide linear estimation of system angle and then unscented transformation (UT) is used to estimate the distribution of the TSM. The proposed method is compared with the traditional Monte Carlo (MC) method and the effectiveness of the proposed approach is verified using Single Machine Infinite Bus (SMIB) and IEEE 14 generator Australian dynamic system. This method will aid grid operators to perform fast online calculations to estimate TSM distribution of a power system with high levels of intermittent wind generation.