Date of Award
Daniel Felix Ritchie School of Engineering and Computer Science, Electrical and Computer Engineering
Amin Khodaei, Ph.D.
Andy Goetz, Ph.D.
Distributed generation, Distributed power generation, Microgrid, Power distribution economics, Power system economics, Risk
This thesis proposes a risk based price adjustment method for a day ahead scheduling of a distribution side tiered community microgrid within a transactive energy style market. The system is organized into a master controller and local controller confïguration to simulate behind meter activity that is not visible to the master controller. Conditional value at risk is used to asses the risk of distributed energy resources in each local controller and the risk for each local controller is aggregated providing each local controller a single risk value. Each device's, or local controller's, risk value is used to adjust the price of power for that device. The model both minimizes the risk for the aggregator and master controller, as well as incentivizes the participants to operate reliably. Dynamic loads, dispatchable and non-dispatchable generation, electric vehicles, battery energy storage, and conventional loads are all used within the model. Four cases are proposed to simulate the adoption of distributed energy resources where the price stability is studied in each case. The price results are found to be consistent at the master controller level for a non-risk adjusted and risk adjusted simulation, as well as with some manageable stability concerns.
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Thomas William Cashel III
Received from ProQuest
Cashel, Thomas William III, "Risk Optimized Microgrid Resource Management" (2017). Electronic Theses and Dissertations. 1476.