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Optimum selection of renewable energy power generating units for a green home.

机译:为绿色家庭最佳选择可再生能源发电设备。

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摘要

This dissertation focuses on the selection of renewable energy power generating units for a household to meet the power demand. As the appliances increase, the power consumption increases and power generation needs to increase correspondingly. If the homes are powered by renewable energy sources such as wind and solar energy, the carbon content in the atmosphere released from fossil fuels can be significantly reduced. Utilizing these renewable sources reduces the impact on the environment and saves energy bills. By not releasing any carbon into the air and saving the building material and water, the environment will be clean and thus the home can be called green home. This dissertation is divided into three parts to investigate the supply of power through selected renewable energy power generation units using an optimization algorithm. The first part is the selection of units for a grid-connected household to meet the average power demand. The second part is the economic analysis study on the selection of units for a household, where feasible and economical solutions are proposed for a green home. The third part is the selection of units for an off-grid home which uses a diesel generator as a reserve unit for power generation, based on power demand through user input. Genetic Algorithm (GA) is used to solve the problems given the weather data available from NASA meteorology data tables.
机译:本文的重点是为家庭选择满足电力需求的可再生能源发电机组。随着设备的增加,功耗增加,并且发电量也相应增加。如果房屋由可再生能源(例如风能和太阳能)提供动力,则可以大大减少化石燃料释放的大气中的碳含量。利用这些可再生资源可减少对环境的影响并节省能源费用。通过不向空气中释放任何碳并节省建筑材料和水,环境将变得干净,因此该房屋可以称为绿色房屋。本论文分为三个部分,利用优化算法研究可再生能源发电单元的电力供应。第一部分是为满足平均用电需求的并网家庭选择设备。第二部分是对家庭单位选择的经济分析研究,其中提出了针对绿色家庭的可行且经济的解决方案。第三部分是基于用户输入的电力需求,选择离网房屋的单位,该房屋使用柴油发电机作为发电的备用单位。鉴于来自NASA气象数据表的天气数据,遗传算法(GA)用于解决问题。

著录项

  • 作者单位

    Lamar University - Beaumont.;

  • 授予单位 Lamar University - Beaumont.;
  • 学科 Alternative Energy.;Engineering Industrial.;Engineering Architectural.
  • 学位 D.E.
  • 年度 2013
  • 页码 99 p.
  • 总页数 99
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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