在地下配电馈线上集成沼气、光伏和小型风力可再生分布式发电的潮流模拟

IF 2.2 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Data Pub Date : 2023-10-07 DOI:10.3390/data8100150
Welson Bassi, Igor Cordeiro, Ildo Luis Sauer
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引用次数: 0

摘要

分布式发电的迅速发展导致了越来越多的能源集成化。然而,将这些能源整合到配电网络中,为确保配电网络能够有效地容纳相关的分布式能源和电力,提出了具体的挑战。因此,评估沿导体、元件和负载的电力效应是至关重要的。潮流分析是一种成熟的数值方法,用于评估电力系统在稳态运行时的参数和数量。巴西圣保罗大学Cidade Universitária“Armando de Salles Oliveira”(CUASO)校区位于巴西圣保罗,其特色是地下配电系统。能源与环境研究所(IEE)领导了几个分布式发电(DG)来源的整合,包括沼气厂,光伏装置和小型风力涡轮机,进入CUASO的一个馈线,称为“USP-105”。考虑到这些源的互连,使用PowerWorldTM Simulator v.23进行负载流模拟。该数据集提供了模拟中使用的综合信息和计算文件。它是重新分析、教学目的和传播与DG实施相关的技术见解的宝贵资源。
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Power-Flow Simulations for Integrating Renewable Distributed Generation from Biogas, Photovoltaic, and Small Wind Sources on an Underground Distribution Feeder
The rapid expansion of distributed generation leads to the integration of an increasing number of energy generation sources. However, integrating these sources into electrical distribution networks presents specific challenges to ensure that the distribution networks can effectively accommodate the associated distributed energy and power. Thus, it is crucial to evaluate the electrical effects of power along the conductors, components, and loads. Power-flow analysis is a well-established numerical methodology for assessing parameters and quantities within power systems during steady-state operation. The University of São Paulo’s Cidade Universitária “Armando de Salles Oliveira” (CUASO) campus in São Paulo, Brazil, features an underground power distribution system. The Institute of Energy and Environment (IEE) leads the integration of several distributed generation (DG) sources, including a biogas plant, photovoltaic installations, and a small wind turbine, into one of the CUASO’s feeders, referred to as “USP-105”. Load-flow simulations were conducted using the PowerWorldTM Simulator v.23, considering the interconnection of these sources. This dataset provides comprehensive information and computational files utilized in the simulations. It serves as a valuable resource for reanalysis, didactic purposes, and the dissemination of technical insights related to DG implementation.
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Data
Data Decision Sciences-Information Systems and Management
CiteScore
4.30
自引率
3.80%
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0
审稿时长
10 weeks
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