مدیریت انرژی مشارکتی جامعه ای با ساختمانهای هوشمند
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مدیریت انرژی مشارکتی جامعه ای با ساختمانهای هوشمند

عنوان فارسی مقاله: مدیریت انرژی مشارکتی جامعه ای با ساختمانهای هوشمند: یک رویکرد بلاک چین
عنوان انگلیسی مقاله: Cooperative energy management of a community of smart-buildings: A Blockchain approach
مجله/کنفرانس: مجله بین المللی سیستم های انرژی و برق - International Journal Of Electrical Power & Energy Systems
رشته های تحصیلی مرتبط: برق، فناوری اطلاعات
گرایش های تحصیلی مرتبط: الکترونیک، مدیریت سیستم های اطلاعات، سامانه های شبکه ای
کلمات کلیدی فارسی: مدیریت انرژی مشارکتی، ساختمانهای هوشمند، جامعه هوشمند، بلاک چین، پاسخ تقاضا، قرارداد هوشمند، بهینه سازی خطی، الگوریتم غیر متمرکز
کلمات کلیدی انگلیسی: Cooperative energy management، Smart-buildings، Smart-community، Blockchain، Demand response، Smart-contract، Linear optimization، Decentralized algorithm
نوع نگارش مقاله: مقاله پژوهشی (Research Article)
نمایه: Scopus - Master Journals List - JCR
شناسه دیجیتال (DOI): https://doi.org/10.1016/j.ijepes.2019.105643
دانشگاه: Department of Electrical Engineering (STI), Ecole Polytechnique Fédérale de Lausanne, Lausanne 1005, Switzerland
ناشر: الزویر - Elsevier
نوع ارائه مقاله: ژورنال
نوع مقاله: ISI
سال انتشار مقاله: 2020
ایمپکت فاکتور: 5/627 در سال 2019
شاخص H_index: 100 در سال 2020
شاخص SJR: 1/260 در سال 2019
شناسه ISSN: 0142-0615
شاخص Quartile (چارک): Q1 در سال 2019
فرمت مقاله انگلیسی: PDF
تعداد صفحات مقاله انگلیسی: 11
وضعیت ترجمه: ترجمه نشده است
قیمت مقاله انگلیسی: رایگان
آیا این مقاله بیس است: بله
آیا این مقاله مدل مفهومی دارد: دارد
آیا این مقاله پرسشنامه دارد: ندارد
آیا این مقاله متغیر دارد: دارد
کد محصول: E14474
رفرنس: دارای رفرنس در داخل متن و انتهای مقاله
فهرست انگلیسی مطالب

Abstract


1- Introduction


2- Smart-building model


3- Smart-buildings community framework


4- Case study and discussion


5- Conclusion


References

نمونه متن انگلیسی مقاله

Abstract


Demand Response (DR) is progressively moving from a centralized, unidirectional structure to a set of advanced decentralized mechanisms that better balance distributed supply and demand. This paper presents a decentralized cooperative DR framework to manage the daily energy exchanges within a community of Smart-Buildings, in the presence of local Renewable Energy Sources (RES). The proposed algorithm taps into the flexibility of the participants to let them decide of a day-ahead community power profile, and subsequently ensures the forecast tracking during the next day. In practice, the algorithm is fully decentralized by the Blockchain technology, that enables a trusted communication medium among the participants and enforces autonomous monitoring and billing via Smart-Contracts. With such an energy management framework, participating Smart-Buildings can together aim at a common objective, such as carbon-free resources usage or aggregated grid services, without depending on a centralized aggregator/utility. Simulations on realistic Swiss building models demonstrate that nearly all the renewable production resources could be harnessed locally through the presented framework, compared to selfish individual optimization. Under a quadratic cost of grid electricity, the considered community profile could dramatically be flattened, hence avoiding costly peaks at the grid interface. A scalability analysis shows that, considering the current public Ethereum Blockchain, the framework could handle a community size of up to 100 Smart-Buildings.


Introduction


The increasing world demand in electricity is envisioned to be entirely supplied by sustainable Renewable Energy Source (RES) in order to counteract the global climate change. However, intrinsic volatility and uncontrollably of decentralized RES production pose severe challenges to the current electrical grid, that must ensure stability at any time. Progressively, the centralized grid sees a change in paradigms, transitioning from a system dispatching a production portfolio following the electrical demand to a Smart-Grid that handles a portfolio of controllable demand to match an uncontrollable supply [1]. To assist this transition, Smart-Buildings have recently emerged as a solution to leverage the flexibility offered by the various entities commonly found in buildings. Equipped with the right hardware and Information and Communication Technology (ICT) they can provide active Demand Response (DR) to the electrical grid [2,3]. DR regroups a set of mechanisms divided into incentive and price-based programs, that specify various signals to be exchanged between the grid and the consumers in order to shape the power profile of the latter. Many works have tackled the problem at individual building level, demonstrating their capability to adapt their power consumption to grid signals while ensuring occupant comfort [4–7]. Beyond individual building optimization, there is a need of handling the problem at the community level. By doing so, local resources such as Photovoltaic (PV) production can optimally be harnessed while reducing the overall peak power demand. Many optimization frameworks have emerged to collectively manage the energy of multiple users [8–12]. Nevertheless, these solutions require a central agent that collects user information to subsequently dispatch optimal set points to each of them. Even though generic simplified models can be used to represent buildings flexibility [9,12], centralized solutions still face issues of privacy, single point of failure, scalability, and market entry of small prosumers.

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