کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6680293 | 1428071 | 2018 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Multi-objective active distribution networks expansion planning by scenario-based stochastic programming considering uncertain and random weight of network
ترجمه فارسی عنوان
برنامه ریزی گسترش گسترده شبکه های فعال چند هدفه با برنامه ریزی تصادفی مبتنی بر سناریوی با توجه به وزن نامطلوب و تصادفی شبکه
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کلمات کلیدی
برنامه ریزی چند هدفه شبکه توزیع فعال مدیریت انرژی، شبکه تصادفی نامشخص حداقل درخت درختی برنامه ریزی تصادفی،
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
مهندسی انرژی و فناوری های برق
چکیده انگلیسی
This paper presents a novel multi-objective model of active distribution network planning based on stochastic programming and uncertain random network (URN) theory. The planning model is proposed to find the final scheme with optimal alternative, location, size and operational strategy for the candidate distribution lines, transformer substations (TSs), distribution generations (DGs), static var compensators (SVCs) and on-load tap changers (OLTCs). Firstly, a scenario-based approach is developed to analyse the uncertainties in network system, such as the demand and intermittency of renewable sources. Since the impact of multiple uncertain factors on network cannot be ignored, a network frame is then modelled by uncertain and random weights of spanning tree (ST) instead of fixed value. In order to achieve the minimization of total cost, and further the selection of a minimum spanning tree (MST) with the uncertain and random weight, a 3-dimensional uncertain space is constructed based on the combination of the previous two targets. In addition, a second-order cone programming (SOCP) is applied to cope with the multi-objective, mixed-integer nonlinear nature of the proposed planning model. Simulation is performed on a modified Pacific Gas and Electric Company (PG&E) 69-bus distribution system, and the results demonstrate the effectiveness of the proposed model.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Applied Energy - Volume 219, 1 June 2018, Pages 207-225
Journal: Applied Energy - Volume 219, 1 June 2018, Pages 207-225
نویسندگان
Shiwei Xie, Zhijian Hu, Daming Zhou, Yan Li, Shunfei Kong, Weiwei Lin, Yunfei Zheng,