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Multi-generation Modeling and Building Energy use optimization based on a Natural Gas driven Internal Combustion Engine

机译:基于天然气驱动的内燃机的多代建模和建筑能耗优化

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Science and technological advancement, environmental pollution, government policies and rising energy costs have long since begun redefining the way power is generated, distributed and utilized. Considering the much higher standards relative to common practices, distributed energy power generation has proven to be a viable alternative to centralized power generation due to the many advantages such as energy generation and control independence, lower greenhouse emissions and significant reduction in transmission losses. This research considers a natural gas-powered internal combustion engine (ICE) with heat recovery and trigeneration capabilities or combined cooling heating and power (CCHP) as well as renewable energy incorporation including solar panels and possibly solar thermal. Research objective is to create an accurate working numerical model that in future can be compared with an experimental model for verification and optimization. TRNSYS software is used to create a numerical model by assembling the components as it would be in real life and running a simulation. In modeling the building, Sketchup and OpenStudio will be used to create thermal zones as in a single-family two story detached house with conventional floor plans. The model will then be imported into the TRNSYS environment for further analysis. Optimization of the system would be primary, and with a targeted energy utilization factor of 95%, this research will seek to provide substantial and convincing data for future installations.
机译:自从开始重新定义电力的产生,分配和利用的方式以来,科学技术的进步,环境污染,政府政策和不断上升的能源成本就已经很久了。考虑到相对于常规做法更高的标准,分布式能源发电已被证明是集中式发电的可行替代方案,因为它具有许多优势,例如能源发电和控制独立性,较低的温室气体排放量以及显着减少的传输损耗。这项研究考虑了具有热回收和三代发电功能或结合了冷热电联产(CCHP)的天然气动力内燃机(ICE)以及可再生能源,包括太阳能电池板和可能的太阳能热能。研究目标是创建一个准确的工作数值模型,以后可以与实验模型进行比较以进行验证和优化。 TRNSYS软件用于通过组装组件来创建数值模型,就像在现实生活中一样,并运行模拟。在建筑物建模中,Sketchup和OpenStudio将用于创建热区,就像在具有常规平面图的单户两层独立式住宅中一样。然后将模型导入TRNSYS环境中以进行进一步分析。系统的优化将是首要的,目标能源利用率为95%,这项研究将寻求为未来的安装提供实质性和令人信服的数据。

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