دانلود رایگان ترجمه مقاله شبیه ساز بار مسکونی هوشمند برای مدیریت انرژی در شبکه های هوشمند (نشریه IEEE 2018) (ترجمه رایگان – برنزی ⭐️)
این مقاله انگلیسی ISI در نشریه IEEE در ۱۱ صفحه در سال ۲۰۱۸ منتشر شده و ترجمه آن ۲۲ صفحه میباشد. کیفیت ترجمه این مقاله رایگان – برنزی ⭐️ بوده و به صورت کامل ترجمه شده است.
دانلود رایگان مقاله انگلیسی + خرید ترجمه فارسی | |
عنوان فارسی مقاله: |
شبیه ساز بار مسکونی هوشمند برای مدیریت انرژی در شبکه های هوشمند |
عنوان انگلیسی مقاله: |
Smart Residential Load Simulator for Energy Management in Smart Grids |
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مشخصات مقاله انگلیسی | |
فرمت مقاله انگلیسی | |
سال انتشار | ۲۰۱۸ |
تعداد صفحات مقاله انگلیسی | ۱۱ صفحه با فرمت pdf |
نوع مقاله | ISI |
نوع ارائه مقاله | ژورنال |
رشته های مرتبط با این مقاله | مهندسی برق، مهندسی انرژی |
گرایش های مرتبط با این مقاله | مهندسی کنترل، انرژی های تجدیدپذیر، مهندسی الکترونیک |
چاپ شده در مجله (ژورنال) | نتایج بدست آمده در حوزه الکترونیک صنعتی – Transactions on Industrial Electronics |
کلمات کلیدی | مدل سازی وسایل خانگی، مدیریت انرژی، مصرف انرژی، شبکه هوشمند، بار های هوشمند، خانه های هوشمند |
کلمات کلیدی انگلیسی | Appliance modeling – home energy management – household energy consumption – smart grid – smart loads – smart houses |
ارائه شده از دانشگاه | دانشکده مهندسی الکترومکانیکی در دانشگاه کولیما، مکزیک |
نمایه (index) | Scopus – Master Journals – JCR |
شناسه شاپا یا ISSN | ۰۲۷۸-۰۰۴۶ |
شناسه دیجیتال – doi | https://doi.org/10.1109/TIE.2018.2818666 |
ایمپکت فاکتور(IF) مجله | ۸٫۶۹۹ در سال ۲۰۱۹ |
شاخص H_index مجله | ۲۳۶ در سال ۲۰۲۰ |
شاخص SJR مجله | ۲٫۴۰۰ در سال ۲۰۱۹ |
شاخص Q یا Quartile (چارک) | Q1 در سال ۲۰۱۹ |
بیس | نیست ☓ |
مدل مفهومی | ندارد ☓ |
پرسشنامه | ندارد ☓ |
متغیر | ندارد ☓ |
رفرنس | دارای رفرنس در داخل متن و انتهای مقاله ✓ |
کد محصول | F1715 |
نشریه | آی تریپل ای – IEEE |
مشخصات و وضعیت ترجمه فارسی این مقاله | |
فرمت ترجمه مقاله | pdf و ورد تایپ شده با قابلیت ویرایش |
وضعیت ترجمه | انجام شده و آماده دانلود |
کیفیت ترجمه | ترجمه رایگان – برنزی ⭐️ |
تعداد صفحات ترجمه تایپ شده با فرمت ورد با قابلیت ویرایش | ۲۲ صفحه (۱ صفحه رفرنس انگلیسی) با فونت ۱۴ B Nazanin |
ترجمه عناوین تصاویر | ترجمه شده است ✓ |
ترجمه متون داخل تصاویر | ترجمه نشده است ☓ |
ترجمه ضمیمه | ندارد ☓ |
ترجمه پاورقی | ندارد ☓ |
درج تصاویر در فایل ترجمه | درج شده است ✓ |
درج فرمولها و محاسبات در فایل ترجمه | به صورت عکس درج شده است ✓ |
منابع داخل متن | به صورت عدد درج شده است✓ |
منابع انتهای متن | به صورت انگلیسی درج شده است ✓ |
کیفیت ترجمه | کیفیت ترجمه این مقاله پایین میباشد. |
فهرست مطالب |
چکیده |
بخشی از ترجمه |
چکیده |
بخشی از مقاله انگلیسی |
Abstract This paper describes the development of a freeware smart residential load simulator to facilitate the study of residential energy management systems in smart grids. The proposed tool is based on MATLAB-Simulink-GUIDE toolboxes and provides a complete set of user-friendly graphical interfaces to properly model and study smart thermostats, air conditioners, furnaces, water heaters, stoves, dishwashers, cloth washers, dryers, lights, pool pumps, and refrigerators, whose models are validated with actual measurements. Wind and solar power generation as well as battery sources are also modeled, and the impact of different variables, such as ambient temperature and household activity levels, which considerably contribute to energy consumption, are considered. The proposed simulator allows modeling of appliances to obtain their power demand profiles, thus helping to determine their contribution to peak demand, and allowing the calculation of their individual and total energy consumption and costs. In addition, the value and impact of generated power by residential sources can be determined for a 24-h horizon. This freeware platform is a useful tool for researchers and educators to validate and demonstrate models for energy management and optimization, and can also be used by residential customers to model and understand energy consumption profiles in households. Some simulation results are presented to demonstrate the performance and application of the proposed simulator. ۱٫ Introduction S MART grids coupled with renewable energy resources can yield significant economic and environmental benefits. The smart grid’s ability to improve efficiency, make better use of existing assets, enhance reliability and power quality, reduce dependence on imported energy, and minimize environmental impacts is a market force that has substantial economic value [1]. These grids are growing fast, but if this growth is to be sustained, their value must become more clear to all stakeholders, especially residential consumers. The latter are an important part of electricity demand, since for example, the residential sector accounted near 20% of the electrical energy demand in Ontario, Canada in 2016 [2]; also, residential energy consumption in the US was 22% of the total consumed energy in 2015 [3], and similar values were reported for the European Union in 2016 [4]. Space heating/cooling systems, water heaters, refrigerators, dishwashers, cloth washers, dryers, lighting, and cooking ranges are the most common appliances in the residential sector [2]–[۴]. Heating, ventilation, and air conditioning (HVAC) and water heaters are major energy consumption devices. Therefore, controlling the residential end-use electricity demand can have a significant impact on reducing the peak demand and optimize energy consumption, which can be accomplished in smart or intelligent homes with automation systems to control residential loads [5], [6]. Several studies have been reported in the literature on the prediction of load-shape and optimization methods for energy management, since some appliances can be easily scheduled to reduce energy cost and consumption without affecting customer comfort. For instance, a model to minimize the peak load by scheduling pool pumps, air conditioner and water heaters (WH) is proposed in [7]; a mixed integer linear programming model is developed to minimize the energy cost and maximize customers’ comfort while taking into account the influence of price signals on the household. Some projects focus on scheduling the HVAC and/or water heater by making use of wireless thermostat technology to optimize costs and thermal comfort, as in [8]. References [9]–[۱۵] explore different ways of creating appliance-level load models for load management purposes, based on statistical data to predict the load-shape of the demand. Several models and simulators have been developed to model HVAC systems and buildings. For example, the EnergyPlus software [16], which models thermal energy in buildings, allows analyzing the impact of HVAC and lighting systems in buildings from a thermal perspective, but it has not been designed for determining electrical load profiles of households, including the impact of appliances and other building loads and local sources on its electricity demand. The Commercial HVAC (CHVAC) software calculates the maximum heating and cooling loads for commercial buildings [17]. The Applications Program for Air-Conditioning and Heating Engineers (APACHE) is a graphical user interface to analyze thermal performance and energy use of buildings [18]. None of the existing modeling tools take into account other appliances and some are not easy to use. Hence, there is a need for user-friendly simulators to understand how appliances interact with each other with respect to energy consumption, as well as facilitate the study and application of mathematical models for home EMSs, which is the main purpose of the work presented here. The presented simulator allows computing load profiles of buildings that could be used by other simulators such as Homer [19], where electric load is used as an input for the design of hybrid diesel-renewable microgrids. |
دانلود رایگان مقاله انگلیسی + خرید ترجمه فارسی | |
عنوان فارسی مقاله: |
شبیه ساز بار مسکونی هوشمند برای مدیریت انرژی در شبکه های هوشمند |
عنوان انگلیسی مقاله: |
Smart Residential Load Simulator for Energy Management in Smart Grids |
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