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Reliability Modeling for Power Systems Incorporating Renewable Power

Graduate Researcher(s): 
Weixuan Gao
Faculty Advisor/PI: 
Mike Lepech
Collaborators: 
Dimitry Gorinevsky
Project Sponsor: 
Bits & Watts

The research develops probabilistic analysis approach to ensure generating capacity is sufficient to balance load (electricity demand) in power grid. In the future grid, most generation will come from variable sources, such as solar and wind. This means the grid can be only balanced probabilistically. Variability of renewable generation requires using storage, which must be a part of the analysis. Further, mandated reliability of the power systems is very high. This means the probabilistic analysis must carefully consider the combined impact of several random factors and model extreme events. The paper presents probabilistic methodology addressing the mentioned issues. It is demonstrated using actual ISO data.

Publications: 

Probabilistic Balancing of Grid with Renewables and Storage, Weixuan Gao, Dimitry Gorinevsky, 2018 IEEE International Conference on Probabilistic Methods Applied to Power Systems (PMAPS)