Architecture Study of an Energy Microgrid

被引:0
作者
Patel, Ravi [1 ]
Paleari, Walter [1 ]
Selva, Daniel [1 ]
机构
[1] Cornell Univ, Syst Engn Program, Ithaca, NY 14850 USA
来源
2016 11TH SYSTEMS OF SYSTEM ENGINEERING CONFERENCE (SOSE), IEEE | 2016年
关键词
system architecture; microgrid; evolutionary optimization; knowledge discovery; TECHNOLOGIES;
D O I
暂无
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
In the last decade, there has been a push to achieve regional energy independence by developing small, self-sufficient microgrids that complement, and in some cases, replace the main centralized grid. This sort of distributed energy system has numerous advantages. One of them is the ability to disengage and function independently from the main grid in the event of a catastrophic failure. Additionally, they allow for a far greater penetration of renewable energy sources, thus allowing for a much cleaner energy system with a diverse set of energy sources, and limited dependence on fossil fuels. Lastly, the proximity of the energy production and end user allows for the excess energy, generally dissipated, produced during the power generation process to be leveraged into a parallel heating/cooling cycle, thus increasing the energy efficiency of the entire process. While the concept of a distributed energy system and its merits are easy to see, industry experience shows that effectively designing such a system is a far more complicated task. Most such systems fail to generate at their potential due to the lack of appropriate configuration. The architecture design of a microgrid is complex due its dependence on a number of project-specific parameters such as stakeholder needs, resource availability, existing legacy infrastructure, and demand among others. The purpose of this paper is to study the use of a System Architecture approach to designing a microgrid for Ithaca NY. Such an approach involves examining the needs of the stakeholders, determining system goals, selecting a concept, and developing an architectural model, a mathematical construct that is used to generate alternative architectures and evaluate their cost, performance, and risk. The space of alternative architectures is explored by means of a multi-objective evolutionary optimization algorithm. Data mining and sensitivity analysis algorithms are used to determine design features that are common in good architectures. Finally, a small set of promising architectures is selected.
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页数:8
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