50 resultados para Renewable diesels


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The Australian Government has targeted 20% of electricity generation from renewable energy sources by 2020. The 20% renewable energy target (RET) for Australia will be around 45000GWH in 2020. Renewable energy of Victoria also includes as part of support to achieve 20% RET in Australia. In Victoria wind and solar resources are abundant as compared to other sources of renewable energy. Solar radiation and wind speed data for Victoria State was collected from NASA surface meteorology and solar energy web site. A feasibility analysis has been carried out to explore the potentialities of wind and solar energy for Victoria State using hybrid optimization model of electric renewable (HOMER) software. This paper also represents the estimation analysis of RET for Victoria and describes the integrating challenges of renewable energy sources to the utility grid.

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The charging of an undivided cerium–zinc redox battery by various current waveforms some of which mimic the output of renewable energy (solar, wind, tidal, biofuel burning) to electricity transducers is considered in this work, where the battery operates through diffusion-only conditions, and is discharged galvanostatically. Under reasonable assumption, the mathematical model developed enables the observation that the performance characteristic of the cells charged with a constant power input differentiates between the various current–charge waveforms, with cell geometry and electrode kinetics playing subtle, but significant, roles; in particular, high efficiency is observed for sunlight-charged batteries which are thin and suffer no corrosion of the sacrificial electrode, and which have already experienced a charge–discharge cycle. The performance characteristics of the systems are interpreted in the light of consequences for smart grid realisation, and indicate that, for a constant power input, the most matched renewable is biofuel burning with a current output that linearly increases with time.

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In this paper, charging effect of dynamic Plug in Hybrid Electric Vehicle (PHEV) is presented in a renewable energy based electricity distribution system. For planning and designing a distribution system, PHEVs are one of the most important factor as it is going to be a spinning reserve of energy, and also a major load for distribution network. A dynamic load model of PHEVs is introduced here based on third order battery model. To determine the system adequacy, it is necessary to do a micro level analysis to know the PHEVs load impact on grid. Scope of such analysis will cover the performance of wind and solar generation with dynamic PHEVs load, as well as the stability analysis of the power grid to demonstrate that it is important to consider the dynamics of PHEVs load in a renewable energy based distribution network.

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 There is a growing interest in the use of renewable energy sources to power wireless networks in order to mitigate the detrimental effects of conventional energy production or to enable deployment in off-grid locations. However, renewable energy sources, such as solar and wind, are by nature unstable in their availability and capacity. The dynamics of energy supply hence impose new challenges for network planning and resource management. In this paper, the sustainable performance of a wireless mesh network powered by renewable energy sources is studied. To address the intermittently available capacity of the energy supply, adaptive resource management and admission control schemes are proposed. Specifically, the goal is to maximize the energy sustainability of the network, or equivalently, to minimize the failure probability that the mesh access points (APs) deplete their energy and go out of service due to the unreliable energy supply. To this end, the energy buffer of a mesh AP is modeled as a G/G/1(/N) queue with arbitrary patterns of energy charging and discharging. Diffusion approximation is applied to analyze the transient evolution of the queue length and the energy depletion duration. Based on the analysis, an adaptive resource management scheme is proposed to balance traffic loads across the mesh network according to the energy adequacy at different mesh APs. A distributed admission control strategy to guarantee high resource utilization and to improve energy sustainability is presented. By considering the first and second order statistics of the energy charging and discharging processes at each mesh AP, it is demonstrated that the proposed schemes outperform some existing state-of-the-art solutions.

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In utility power system, electricity demand is being covered largely by fossil fueled power generation, which contributes high level of GHG (greenhouse gas) emission and causes global warming worldwide. In order to reduce GHG emission level, most of the countries in the world targeting towards green energy that is power generation from RE (renewable energy) sources. In this paper, it is considered to study prospects of RE sources in particular, solar and wind in Victoria State which are abundant as compared to other sources of renewable. The wind and solar energy feasibility study and sensitivity analysis has been done for Victoria with the aid of HOMER (hybrid optimization model of electric renewable) simulation software. From the study, it has clearly evicted that wind energy combinational HPS (hybrid power system) has more contribution, and high potential than solar PV (photovoltaic) systems for a particular location. This study also investigates the influences of energy storage in the proposed HPS.

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We examine the relationship between Chinese aggregate production and consumption of three main energy commodities: coal, oil and renewable energy. Both autoregressive distributed lag (ARDL) and vector error correction modeling (VECM) show that Chinese growth is led by all three energy sources. Economic growth also causes coal, oil and renewables consumption, but with negative own-price effects for coal and oil and a strong possibility of fuel substitution through positive cross-price effects. The results further show coal consumption causing pollution, while renewable energy consumption reduces emissions. No significant causation on emissions is found for oil. Hence, making coal both absolutely and relatively expensive compared to oil and renewable energy encourages shifting from coal to oil and renewable energy, thereby improving economic and environmental sustainability.

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Continuous usage of fossil fuels and other conventional resources to meet the growing demand has resulted in in-creased energy crisis and greenhouse gas emissions. Hence, it is essential to use renewable energy sources for more reliable, effective, sustainable and pollution free transmission and distribution networks. Therefore, to facilitate large-scale integration of renewable energy in particular wind and solar photovoltaic (PV) energy, this paper presents the feasibility analysis for semi-arid climate and finds the most suitable places in North East region of Victoria for re-newable energy generation. For economic and environmental analysis, Hybrid Optimization Model for Electric Re-newables (HOMER) has used to investigate the prospects of wind and solar energy considering the Net Present Cost (NPC), Cost of Energy (COE) and Renewable fraction (RF). Six locations are selected from North East region of Victo-ria and simulations are performed. From the feasibility analysis, it can be concluded that Mount Hotham is one of the most suitable locations for wind energy generation while Wangaratta is the most suitable location for solar energy generation. Mount Hotham is also the best suitable locations in North East region for hybrid power systems i.e., com-bination of both wind and solar energy generation.

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This paper presents a new distributed multi-agent scheme for reactive power management in smart coordinated distribution networks with renewable energy sources (RESs) to enhance the dynamic voltage stability, which is mainly based on controlling distributed static synchronous compensators (DSTATCOMs). The proposed control scheme is incorporated in a multi-agent framework where the intelligent agents simultaneously coordinate with each other and represent various physical models to provide information and energy flow among different physical processes. The reactive power is estimated from the topology of distribution networks and with this information, necessary control actions are performed through the proposed proportional integral (PI) controller. The performance of the proposed scheme is evaluated on a 8-bus distribution network under various operating conditions. The performance of the proposed scheme is validated through simulation results and these results are compared to that of conventional PI-based DSTATCOM control scheme. From simulation results, it is found that the distributed MAS provides excellence performance for improving voltage profiles by managing reactive power in a smarter way.

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The penetration of intermittent renewable energy sources (IRESs) into power grids has increased in the last decade. Integration of wind farms and solar systems as the major IRESs have significantly boosted the level of uncertainty in operation of power systems. This paper proposes a comprehensive computational framework for quantification and integration of uncertainties in distributed power systems (DPSs) with IRESs. Different sources of uncertainties in DPSs such as electrical load, wind and solar power forecasts and generator outages are covered by the proposed framework. Load forecast uncertainty is assumed to follow a normal distribution. Wind and solar forecast are implemented by a list of prediction intervals (PIs) ranging from 5% to 95%. Their uncertainties are further represented as scenarios using a scenario generation method. Generator outage uncertainty is modeled as discrete scenarios. The integrated uncertainties are further incorporated into a stochastic security-constrained unit commitment (SCUC) problem and a heuristic genetic algorithm is utilized to solve this stochastic SCUC problem. To demonstrate the effectiveness of the proposed method, five deterministic and four stochastic case studies are implemented. Generation costs as well as different reserve strategies are discussed from the perspectives of system economics and reliability. Comparative results indicate that the planned generation costs and reserves are different from the realized ones. The stochastic models show better robustness than deterministic ones. Power systems run a higher level of risk during peak load hours.

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This article analyses the determinants of renewable energy consumption in six major emerging economies who are proactively accelerating the adoption of renewable energy. The long-run elasticities from both panel methods (fully modified ordinary least square and dynamic least square) and the time series method (autoregressive distributed lag) seem to be pretty consistent. For Brazil, China, India and Indonesia, in the long-run, renewable energy consumption is significantly determined by income and pollutant emission. However, for Philippines and Turkey, income seems to be the main driver for renewable energy consumption. In the short-run, for Brazil and China bi-directional causalities between renewable energy and income; and between renewable energy and pollutant emission are found. This research justifies the efforts undertaken by emerging countries to reduce the carbon intensity by increasing the energy efficiency and substantially increasing the share of renewable in the overall energy mix

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This paper presents the impact of large penetration of wind power on the transient stability through a dynamic evaluation of the critical clearing times (CCTs) by using intelligent agent-based approach. A decentralised multi-agent-based framework is developed, where agents represent a number of physical device models to form a complex infrastructure for computation and communication. They enable the dynamic flow of information and energy for the interaction between the physical processes and their activities. These agents dynamically adapt online measurements and use the CCT information for relay coordination to improve the transient stability of power systems. Simulations are carried out on a smart microgrid system for faults at increasing wind power penetration levels and the improvement in transient stability using the proposed agent-based framework is demonstrated.