66 resultados para POWER GENERATION
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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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This paper details a system dynamics model developed to simulate proposed changes to water governance through the integration of supply, demand and asset management processes. To effectively accomplish this, interconnected feedback loops in tariff structures, demand levels and financing capacity are included in the model design, representing the first comprehensive life-cycle modelling of potable water systems. A number of scenarios were applied to Australia's populated South-east Queensland region, demonstrating that introducing temporary drought pricing (i.e. progressive water prices set inverse with availability), in conjunction with supply augmentation through rain-independent sources, is capable of efficiently providing water security in the future. Modelling demonstrated that this alternative tariff structure reduced demand in scarcity periods thereby preserving supply, whilst revenues are maintained to build new water supply infrastructure. In addition to exploring alternative tariffs, the potential benefits of using adaptive pressure-retarded osmosis desalination plants for both potable water and power generation was explored. This operation of these plants for power production, when they would otherwise be idle, shows promise in reducing their net energy and carbon footprints. Stakeholders in industry, government and academia were engaged in model development and validation. The constructed model displays how water resource systems can be reorganised to cope with systemic change and uncertainty.
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The phenomenal growth in economy experienced in developed countries throughout the 20th century has largely been driven by the availability of conventional energy sources for electricity generation. However, increased concern about fossil fuels and adverse effect of carbon dioxide emission in to atmosphere changed the conventional power system to a viable one by integrating renewable energy sources into the existing system. Among the Renewable Energy (RE) sources, wind energy is one of the fastest growing technologies in reducing the Green House Gas (GHG) emissions in to the atmosphere due to its continuous availability throughout a period. Hence, this paper discusses the performance of a wind-grid connected system in a semi-arid region by conducting a case study. Wilson promontory, one of the best locations for wind generation in Victoria is considered as a case study. Hybrid Optimization Model for Electric Renewable (HOMER) is used as a simulating tool for this analysis. This study also presents the influences of storage system in the proposed Hybrid Power System (HPS) allowing energy to be stored during higher generations or lower load demands. In addition this paper also discusses the major integration issues to facilitate the large scale wind energy into the grid for reliable power generation and distribution.
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Type reduction (TR) is one of the key components of interval type-2 fuzzy logic systems (IT2FLSs). Minimizing the computational requirements has been one of the key design criteria for developing TR algorithms. Often researchers give more rewards to computationally less expensive TR algorithms. This paper evaluates and compares five frequently used TR algorithms based on their contribution to the forecasting performance of IT2FLS models. Algorithms are judged based on the generalization power of IT2FLS models developed using them. Synthetic and real world case studies with different levels of uncertainty are considered to examine effects of TR algorithms on forecasts' accuracies. As per obtained results, Coupland-Jonh TR algorithm leads to models with a higher and more stable forecasting performance. However, there is no obvious and consistent relationship between the widths of the type reduced set and the TR algorithm. © 2013 Elsevier B.V.
Uncertainty handling using neural network-based prediction intervals for electrical load forecasting
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The complexity and level of uncertainty present in operation of power systems have significantly grown due to penetration of renewable resources. These complexities warrant the need for advanced methods for load forecasting and quantifying uncertainties associated with forecasts. The objective of this study is to develop a framework for probabilistic forecasting of electricity load demands. The proposed probabilistic framework allows the analyst to construct PIs (prediction intervals) for uncertainty quantification. A newly introduced method, called LUBE (lower upper bound estimation), is applied and extended to develop PIs using NN (neural network) models. The primary problem for construction of intervals is firstly formulated as a constrained single-objective problem. The sharpness of PIs is treated as the key objective and their calibration is considered as the constraint. PSO (particle swarm optimization) enhanced by the mutation operator is then used to optimally tune NN parameters subject to constraints set on the quality of PIs. Historical load datasets from Singapore, Ottawa (Canada) and Texas (USA) are used to examine performance of the proposed PSO-based LUBE method. According to obtained results, the proposed probabilistic forecasting method generates well-calibrated and informative PIs. Furthermore, comparative results demonstrate that the proposed PI construction method greatly outperforms three widely used benchmark methods. © 2014 Elsevier Ltd.
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Abstract Mg
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A freestanding conducting polymer plate with one side forming a Schottky contact and the other side an Ohmic contact with two different metal electrodes can generate a DC voltage with an output current density as high as 218.6 μA cm(-2) upon mechanical deformation.
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Electrical power systems are undergoing highly significant changes in their structures. The emergence of renewable energy units in the power generation sector, the use of high-voltage DC in the power transmission sector, and the prevalence of islanded or integrated microgrids in the distribution sector are the strongest evidence supporting this claim. These changes are mostly the consequences of the increasing energy demand rate, climate change, and environmental challenges, as well as the high investment and maintenance cost of the previous structures. Considering these new conditions and according to the recent development in DC/DC conversion topologies and control techniques, different studies have been conducted on how and why DC microgrids outperform AC microgrids. This study discusses the feasibility of the DC microgrid system according to recent developments in power systems. The efficiency and power loss reduction in DC distribution systems are then analyzed, some of the common strategies and devices for protection systems in such networks are reviewed, and the possible and existing challenges in developing the DC microgrids are highlighted. The mathematical calculations and theories for this evaluation are presented to determine the reliable justification for selecting the appropriate microgrid systems.
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Nowadays, there is growing interest towards the area of building integrated photovoltaic (BIPV) systems and PV microgrids (MGs) in the field of power generation and distribution systems. This is mainly due to the higher adaptability and compatibility of these systems with preplanned sustainable development strategies in the most urban areas. The quiet operating process and movement free characteristic of photovoltaic systems brought them to the roof tops of the buildings in urban and rural areas and made them the most demanded means of renewable energy systems. This study highlights the problems affecting the performance and efficiency of BIPV systems and presents miscellaneous solutions and recommendations to solve these problems.
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Thermoelectrochemical cells are increasingly promising devices for harvesting waste heat, offering an alternative to the traditional semiconductor-based design. Advancement of these devices relies on new redox couple/electrolyte systems and an understanding of the interplay between the different factors that dictate device performance. The Seebeck coefficient (Se) of the redox couple in the electrolyte gives the potential difference achievable for a given temperature gradient across the device. Prior work has shown that a cobalt bipyridyl redox couple in ionic liquids (ILs) displays high Seebeck coefficients, but the thermoelectrochemical cell performance was limited by mass transport. Here we present the Se and thermoelectrochemical power generation performance of the cobalt couple in novel mixed IL/molecular solvent electrolyte systems. The highest power density of 880 mW m-2, at a ΔT of 70 °C, was achieved with a 31 (v/v) MPN-[C2mim][B(CN)4] electrolyte combination. The significant power enhancement compared to the single solvent or IL systems results from a combination of superior ionic conductivity and higher diffusion coefficients, shown by electrochemical analysis of the different electrolytes. This is the highest power output achieved to-date for a thermoelectrochemical cell utilising a high boiling point redox electrolyte.
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Over the past decade, the growing demand of Grid-connected photo voltaic (GCPV) system has been increasing due to an extensive use of renewable energy technologies for sustainable power generation and distribution. High-penetrated GCPV systems enhance the operation of the network by improving the voltage levels and reducing the active power losses along the length of the feeder. This paper aims to investigate the voltage variations and Total Harmonic Distortion (THD) of a typical GCPV system modelled in Power system simulator, PSS SINCAL with the change of level of PV integrations in a Low Voltage (LV) distribution network. Five different case studies are considered to investigate the impact of PV integrations on LV nodes and the corresponding voltage variations and harmonics. In addition, this paper also explores and benchmarks the voltage improvement techniques by implementing On Load Tap Changer (OLTC) with respective to the main transformer and addition of Shunt Capacitor (SC) at appropriate node points in LV network,
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Given the considerable recent attention to distributed power generation and interest in sustainable energy, the integration of photovoltaic (PV) systems to grid-connected or isolated microgrids has become widespread. In order to maximize power output of PV system extensive research into control strategies for maximum power point tracking (MPPT) methods has been conducted. According to the robust, reliable, and fast performance of artificial intelligence-based MPPT methods, these approaches have been applied recently to various systems under different conditions. Given the diversity of recent advances to MPPT approaches a review focusing on the performance and reliability of these methods under diverse conditions is required. This paper reviews AI-based techniques proven to be effective and feasible to implement and very common in literature for MPPT, including their limitations and advantages. In order to support researchers in application of the reviewed techniques this study is not limited to reviewing the performance of recently adopted methods, rather discusses the background theory, application to MPPT systems, and important references relating to each method. It is envisioned that this review can be a valuable resource for researchers and engineers working with PV-based power systems to be able to access the basic theory behind each method, select the appropriate method according to project requirements, and implement MPPT systems to fulfill project objectives.