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نتیجه جستجو - Energy loss

تعداد مقالات یافته شده: 11
ردیف عنوان نوع
1 Boosting solar steam generation by structure enhanced energy management
افزایش تولید بخار خورشیدی توسط ساختار پیشرفته مدیریت انرژی -2020
Interfacial solar-steam generation is a promising and cost-effective technology for both desalination and wastewater treatment. This process uses a photothermal evaporator to absorb sunlight and convert it into heat for water evaporation. However solar-steam generation can be somewhat inefficient due to energy losses via conduction, convection and radiation. Thus, efficient energy management is crucial for optimizing the performance of solar-steam generation. Here, via elaborate design of the configuration of photothermal materials, as well as warm and cold evaporation surfaces, performance in solar evaporation was significantly enhanced. This was achieved via a simultaneous reduction in energy loss with a net increase in energy gain from the environment, and recycling of the latent heat released from vapor condensation, diffusive reflectance, thermal radiation and convection from the evaporation surface. Overall, by using the new strategy, an evaporation rate of 2.94 kg m−2 h−1, with a corresponding energy efficiency of solar-steam generation beyond theoretical limit was achieved.
Keywords: Solar-steam generation | photothermal | energy management | latent heat recycling | reduced graphene oxide | desalination
مقاله انگلیسی
2 Scaling laws of Mullins effect in nitrile butadiene rubber nanocomposites
مقیاس بندی قوانین اثر مولین در نانوکامپوزیت های لاستیکی بوتادین نیتریل-2020
Rubber nanocomposites experiencing cyclic deformation undoubtedly exhibit Mullins effect whose underlining mechanisms are not yet clear. Herein this effect in nitrile butadiene rubber nanocomposites is systematically investigated for revealing the influences of pre-strain interval, loading and unloading velocities, temperature, filler type and content, as well as crosslinking agent. The results show that the recovery hysteresis energy and accumulative softening energy of the nanocomposites can be superposed onto master curves as a function of microscopic strain of the rubber phase, revealing that both involving the viscoelastic deformation of the rubber phase. Especially the recovery hysteresis highly depending on temperature and loading and unloading velocities is connected to the viscoelasticity of nonideally crosslinked rubber network in the nanocomposites. On the other hand, the accumulative softening energy loss comes from recovery retardation of rubber chains and is somewhat sensitive to the filler, temperature and crosslinking agent. The investigation would be instructive to clarify the physical origin of Mullins effect to produce low dissipation rubber nanocomposites.
Keywords: Mullins effect | Energy loss | Nanocomposites
مقاله انگلیسی
3 Prediction and management of solar energy to power electrochemical processes for the treatment of wastewater effluents
پیش بینی و مدیریت انرژی خورشیدی به قدرت فرآیندهای الکتروشیمیایی برای تصفیه پساب فاضلاب-2020
A highly versatile software tool able to predict and manage the solar power coming from photovoltaic panels and to assess the environmental remediation of wastewater effluents has been developed. The prediction software tool is made up of four modules. The first one predicts the solar radiation by a phenomenological model. Secondly, an energy optimization algorithm manages the solar power towards the third and fourth modules, an environmental remediation treatment (electrooxidation) and an energy storage system (redox flow battery), respectively. The software tool is aimed to the best solar power management to obtain the highest remediation treatment. Results shows a daily solar radiation prediction with a high accuracy, attaining correlation coefficients of 0.89. Furthermore, the prediction of the removal of an organochlorinated compound from a wastewater effluent at different time of the year was studied. Different percentages of the total solar power are sent directly to the electrooxidation reactor and to the redox flow battery. At non-solar production hours, the electrooxidation reactor is powered by the redox flow battery in order to exploit the total solar power produced. The results show that, the higher the solar radiation, the higher the power percentage that must be directly sent to the electrooxidation treatment in order to attain the best energy management and the higher remediation. Thus, an 82.5% of the total solar power must be sent to the electrooxidation treatment in summer days in contrast to the 25% that have to be powered in winter days to attain the highest removal of pollutant. Consequently, it is important to evaluate the connection between devices to get the best green energy management and the lower energy losses.
Keywords: Energy management | Solar power | Green sources | Electrolysis | Redox flow batteries | Forecasting
مقاله انگلیسی
4 Optimum management of power and energy in low voltage microgrids using evolutionary algorithms and energy storage
مدیریت بهینه انرژی و برق در ریز شبکه های ولتاژ کم با استفاده از الگوریتم های تکاملی و ذخیره انرژی-2020
Microgrids are subsystems in which some loads and distributed energy resources are controlled in a coordinated manner. In recent years, microgrids have been proposed as a solution to enhance critical infrastructures’ resilience and the integration of distributed energy resources. There are many solutions on microgrid planning, as well as some practical experience on microgrids’ implementation. However, choosing microgrid optimal control strategy is strongly related to the individual structure, components and configuration of microgrid. Among others, the advantages of microgrids include improved energy efficiencies, minimized operating costs and improved environmental impacts. Achieving these targets necessitates optimal control of all energy components in the microgrid. Main contribution of this paper are two control strategies of power and energy management for synchronous microgrid operation, which have been analyzed for a specific low voltage microgrid configuration. The first strategy reduces power and energy losses, thus improving the entire microgrid system’s efficiency. The second minimizes operating costs. An evolutionary algorithm was developed to control the components of the microgrid, including e.g. micro-sources and energy storage. The method of technical and economic energy storage system sizing for microgrid optimal operation is also proposed.
Keywords: Battery energy storage unit | Distributed generation | Evolutionary algorithm | Microgrid optimization | Power and energy management
مقاله انگلیسی
5 Thermal management of the waste energy of a stand-alone hybrid PV-windbattery power system in Hong Kong
مدیریت حرارتی انرژی زائد یک سیستم قدرتمند هیبریدی PV-بادگیر مستقل در هنگ کنگ-2020
This paper firstly investigated the thermal management of wasted energy from a stand-alone hybrid solar-windbattery power system. The total dump load or waste power can be up to 50% of total system power yield, and therefore waste energy management is urgent with high necessity. A new phase change material (PCM: Ba (OH)2·8H2O) with high storage capacity is introduced for the thermal management of hybrid power system. Different renewable energy configurations with different battery storage capacities are simulated and investigated. For different scenarios, the ratio of the captured thermal energy from waste energy to total solar/ wind power output ranges from 24.45% to 72.48% regarding all system losses. The cases without battery bank are featured by high thermal energy amount/ percentage (waste energy) and high power supply failure. Typical results show that, the total yearly renewable power output is 173,877 kWh with only 51.99% directly for demand load, and 57,672 kWh with 33.17% can be effectively stored in the thermal storage tank as heat, which can supply about 136 people’ heat demand per year. Compared with the water tank, the PCM thermal storage tank can save much space and land because of its high energy density. Appropriate thermal management of standalone hybrid solar-wind-battery power systems is necessary and feasible.
Keywords: Solar-wind-battery system | Dump load | Thermal energy | Heat | Energy losses
مقاله انگلیسی
6 A hierarchical energy management strategy for hybrid energy storage via vehicle-to-cloud connectivity
یک استراتژی مدیریت انرژی سلسله مراتبی برای ذخیره انرژی هیبریدی از طریق اتصال وسیله نقلیه به ابر-2020
In order to enhance energy efficiency and improve system performance, the road mobility system requires more preview information and advanced methods. This paper proposes a novel hierarchical optimal energy management strategy for electric buses with a battery/ultracapacitor hybrid energy storage system, to optimal split the power and reduce the battery life degradation. This method is based on vehicle-to-cloud connectivity. In the cloud platform, an optimal energy management strategy is developed using dynamic programming, where the battery degradation cost and the electric cost are taken into consideration. In the vehicle level, a model predictive control is developed to deal with the uncertainties, reduce the energy losses, and handle the system constraints. The cost function of the model predictive control includes the ultracapacitor state of charge planning and energy losses. In order to evaluate the effectiveness of the proposed method, a rule-based energy management strategy is developed as the baseline approach. The China bus driving cycle and other six real bus driving cycles recorded in China are used to validate the robustness of the proposed method. To be more realistic, the random uncertainties up to 20% are included in all driving cycles. Furthermore, the time delay and packet losses in communication are also considered. Simulation results show that the proposed method significantly outperforms the rule-based method, and the average improvement could be over 40% in the studied driving cycles.
Keywords: Vehicle-to-cloud connectivity | Energy management | Model predictive control | Real-time optimization | Hybrid energy storage
مقاله انگلیسی
7 Efficiency in electromechanical drive motors and energy performance indicators for implementing a management system in balanced animal feed manufacturing
بهره وری در راندن موتورهای الکترومکانیکی و شاخص های عملکرد انرژی برای اجرای یک سیستم مدیریت در تولید متعادل خوراک دام-2020
Energy management for manufacturing animal feed requires efficiency in the electric motors that actuate electro mechanisms consisting in chain conveyors (3548 kWh/day), elevators of buckets (2626 kWh/ day), types axis non-end screw (298 kWh/day) and conveyor bands (434 kWh/day); all with different types of mechanical transmissions mainly reducers, chains and straps that as major consumers of electric energy represent the greatest potential savings. On the other hand, energy performance indicators are needed for assessing the production of feed and implementing an energy management system. In this paper a methodology is applied to determine the operating efficiencies of the electrical motors to the current load factors and adjusted to the actual operating conditions. The case study is a balanced animal feed manufacturing plant. The energy base line of the processes of higher energy consumption was obtained as well as energy performance indicators of 10 kWh/t for the same productive levels (500 t/ day), representing a reduction of 364 000 kWh/year and, consequently, 15% of the entry recorded of energy costs. This result is equivalent to generation costs at 120 t of oil/year, which means a saving of 6000 USD/year and 140.14 t of CO2 equivalent that is no longer emitted.
Keywords: Balanced animal feed | Energy efficiency | Energy losses | Energy management systems | Energy performance indicators | Load factor
مقاله انگلیسی
8 Multi-agent microgrid energy management based on deep learning forecaster
مدیریت انرژی میکروگیدر چند عامل مبتنی بر پیشگویی یادگیری عمیق-2019
This paper presents a multi-agent day-ahead microgrid energy management framework. The objective is to minimize energy loss and operation cost of agents, including conventional distributed generators, wind turbines, photovoltaics, demands, battery storage systems, and microgrids aggregator agent. To forecast market prices, wind generation, solar generation, and load demand, a deep learning-based approach is designed based on a combination of convolutional neural networks and gated recurrent unit. Each agent utilizes the designed learning approach and its own historical data to forecast its required parameters/data for scheduling purposes. To preserve the information privacy of agents, the alternating direction method of multipliers (ADMM) is utilized to find the optimal operating point of microgrid distributedly. To enhance the convergence performance of the distributed algorithm, an accelerated ADMM is presented based on the concept of over-relaxation. In the proposed framework, the agents do not need to share with other parties either their historical data for forecasting purposes or commercially sensitive information for scheduling purposes. The proposed framework is tested on a realistic test system. The forecast values obtained by the proposed forecasting method are compared with several other methods and the accelerated distributed algorithm is compared with the standard ADMM and analytical target cascading.
Keywords: Microgrid energy management system | Short-term forecasting | Deep learning | Convolutional neural networks | Gated recurrent unit | Alternating direction method of multipliers
مقاله انگلیسی
9 الگوریتم Krill herd برای محل بهینه تولید توزیع شده در سیستم توزیع شعاعی
سال انتشار: 2016 - تعداد صفحات فایل pdf انگلیسی: 14 - تعداد صفحات فایل doc فارسی: 48
تولید پراکنده (DG) به عنوان یک راه حل مناسب برای کنترل تلفات خط، ولتاژ گذر، ثبات ولتاژ و غیره به رسمیت شناخته شده و نشان دهنده یک عصر جدید برای سیستم های توزیع است. این مقاله در حال توسعه رویکردی برای قرار دادن DG به منظور به حداقل رساندن از دست دادن قدرت و انرژی فعال خطوط توزیع است، در حالی که ولتاژ باس و شاخص پایداری ولتاژ را در محدوده مشخص یک سیستم قدرت معین حفظ می کند. بهینه سازی بر اساس محل مطلوب و اندازه بهینه از DG انجام شده است. این مقاله یک روش الگوریتم کریل گله جدید، کارآمد (KHA) را برای حل مشکل تخصیص بهینه DG شبکه های توزیع توسعه داده است. برای تست امکان سنجی و اثربخشی، الگوریتم KH ارائه شده بر روی 33 باس، 69-باس و 118 باس شبکه های توزیع شعاعی استاندارد تست شده است. نتایج شبیه سازی نشان می دهد که نصب DG در محل مطلوب به طور قابل توجهی می تواند سبب کاهش از دست دادن قدرت سیستم برق توزیع شده شود. علاوه بر این، نتایج عددی، در مقایسه با دیگر الگوریتم های جستجوی تصادفی مانند الگوریتم ژنتیک (GA)، بهینه سازی ازدحام ذرات (PSO)، همراه GA و PSO (GA / PSO و عامل حساسیت از دست دادن شبیه سازی آنیلینگ (LSFSA)، نشان می دهد که KHA می تواند راه حل هایی با کیفیت بهتر را پیدا کند.
کلمات کلیدی: سیستم توزیع شعاعی | ژنراتور توزیع | کاهش تلفات | الگوریتم های تکاملی | الگوریتم کریل هرد | تکامل تفاضلی
مقاله ترجمه شده
10 Optimal allocation of stochastically dependent renewable energy based distributed generators in unbalanced distribution networks
تخصیص بهینه بر اساس ژنراتور انرژی های تجدید پذیر تصادفی وابسته به توزیع در شبکه های توزیع نامتعادل-2015
This paper proposes an algorithm for modeling stochastically dependent renewable energy based dis tributed generators for the purpose ofproper planning ofunbalanced distribution networks. The proposed algorithm integrate the diagonal band Copula and sequential Monte Carlo method in order to accurately consider the multivariate stochastic dependence between wind power, photovoltaic power and the sys tem demand. Secondly, an efficient algorithm based on modification ofthe traditional Big Bang-Big crunch method is proposed for optimal placement ofrenewable energy based distributed generators in the pres ence of dispatchable distributed generation. The proposed optimization algorithm aims to minimize the energy loss in unbalanced distribution systems by determining the optimal locations ofnon-dispatchable distributed generators and the optimal hourly power schedule ofdispatchable distributed generators. The proposed algorithms are implemented in MATLAB environment and tested on the IEEE 37-node feeder. Several case studies are done and the subsequent discussions show the effectiveness of the proposed algorithms. Keywords: Big Bang-Big crunch Copula Monte Carlo Renewable energy Stochastic Distributed Generation
مقاله انگلیسی
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