مشخصات مقاله | |
ترجمه عنوان مقاله | تبادل نظیر به نظیر برق در یک سایت صنعتی: ارزش انعطاف پذیری ساختمان ها در کاهش بار پیک |
عنوان انگلیسی مقاله | Peer-to-peer electricity trading in an industrial site: Value of buildings flexibility on peak load reduction |
انتشار | مقاله سال 2021 |
تعداد صفحات مقاله انگلیسی | 14 صفحه |
هزینه | دانلود مقاله انگلیسی رایگان میباشد. |
پایگاه داده | نشریه الزویر |
نوع نگارش مقاله |
مقاله پژوهشی (Research Article) |
مقاله بیس | این مقاله بیس نمیباشد |
نمایه (index) | Scopus – Master Journals List – JCR |
نوع مقاله | ISI |
فرمت مقاله انگلیسی | |
ایمپکت فاکتور(IF) |
4.867 در سال 2019 |
شاخص H_index | 166 در سال 2019 |
شاخص SJR | 2.061 در سال 2019 |
شناسه ISSN | 0378-7788 |
شاخص Quartile (چارک) | Q1 در سال 2019 |
مدل مفهومی | دارد |
پرسشنامه | ندارد |
متغیر | دارد |
رفرنس | دارد |
رشته های مرتبط | عمران |
گرایش های مرتبط | سازه |
نوع ارائه مقاله |
ژورنال |
مجله | انرژی و ساختمان ها – Energy and Buildings |
دانشگاه | Norwegian University of Science and Technology |
کلمات کلیدی | تجارت نظیر به نظیر، ذخیره باتری، ساختمانهای صنعتی، بازار برق محلی، تعرفه سودمندی، اوج تراشیدن جمعی، فضای ذخیره سازی مشترک |
کلمات کلیدی انگلیسی | Peer-to-peer trade، Battery storage، Industrial buildings، Local electricity market، Utility tariff، Collective peak shaving، Shared storage |
شناسه دیجیتال – doi |
https://doi.org/10.1016/j.enbuild.2021.110737 |
کد محصول | E15271 |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
فهرست مطالب مقاله: |
Abstract Graphical abstract Keywords 1. Introduction 2. Related literature 3. Modelling buildings in an industrial site 4. A Norwegian industrial site: model implementation and data 5. Results 6. Conclusions Declaration of Competing Interest Acknowledgments Appendix References |
بخشی از متن مقاله: |
AbstractLocal electricity markets and peer-to-peer (P2P) trading schemes in buildings have recently gained importance as an efficient way to incentivize energy flexibility (e.g. consumer demand response or storage) and to share local energy resources (e.g. solar PV). This paper proposes local electricity markets for a complex of industrial buildings. We study P2P electricity trading and analyze the role of sharing local flexibility, e.g. a large battery, to maximise the use of distributed energy resource (DER) technologies. The objective is to investigate the value of P2P electricity trading in combination with on-site flexibility resources for a Norwegian industrial site. As the industrial consumers are exposed to a substantial peak power charge for grid usage, the study analyses how a local market affect the peak power demand management. To analyze it, we developed a linear programming model that represents the local power system characteristics of the buildings and simulate one year in operations. Results indicate potential savings on reducing electricity costs in the range of 6.8% to 11.0% based on P2P trading features. The total cost of peak power is reduced up to 25%, making peak shaving the largest contributor to the net cost savings. Moreover, the industrial site consumes more distributed generation locally, with no DER power curtailment and reduced grid feed-in. Introduction Local energy systems, such as rooftop solar photovoltaic (PV) systems, end-use energy storages, small-scale wind farms, and distributed energy resources (DERs) in general, are rapidly entering the power market. This is being further accelerated by technology development of batteries, smart grid technologies, deregulation, and the raise of prosumers and energy communities. Hence, as future power systems might move from producer-centric to more consumer-centric, the adoption and management of DERs will require new market designs tailored to local energy systems and buildings. An emerging approach is to create smaller entities and gather them as communities, cells or microgrids. There, using (and sharing) DERs at a local (building) level is more attractive than feeding into the grid, due to the differences in electricity selling and buying prices, losses and the stress of the distribution grid. |