Date of Award


Document Type


Degree Name


Organizational Unit

Daniel Felix Ritchie School of Engineering and Computer Science, Computer Science

First Advisor

Amin Khodaei, Ph.D.


Distributed generation, Distribution markets, Grid flexibility, Microgrid optimal scheduling, Power distribution, Renewable energy resources


Distributed renewable energy resources have attracted significant attention in recent years due to the falling cost of the renewable energy technology, extensive federal and state incentives, and the application in improving load-point reliability. This growing proliferation, however, is changing the traditional consumption load curves by adding considerable levels of variability and further challenging the electricity supply-demand balance. In this dissertation, the application of microgrids in effectively capturing the distribution network net load variability, caused primarily by the prosumers, is investigated. Microgrids provide a viable and localized solution to this challenge while removing the need for costly investments by the electric utility on reinforcing the existing electricity infrastructure. A flexibility-oriented microgrid optimal scheduling model is proposed and developed to coordinate the microgrid net load with the aggregated consumers/prosumers net load in the distribution network with a focus on ramping issues and flexibility support of utility grid. The proposed coordination is performed to capture both inter-hour and intra-hour net load variabilities. Furthermore, a microgrid optimal scheduling model is developed to demonstrate microgrid's capability in offering ancillary services to the utility grid. The proposed microgrid optimal scheduling model coordinates the microgrid net load with the aggregated consumers/prosumers net load in its connected distribution feeder to capture both inter-hour and intra-hour net load variations in order to offer different ancillary services to the utility grid. The proposed models are developed through mixed-integer programming. In addition, a robust optimization model is applied to the proposed model in order to consider possible uncertainties in forecasting while supporting the utility grid. The microgrid value of ramping is further determined based on its available reserve using a cost-benefit analysis, which helps the microgrid owners for offering the flexibility support to the utility grid. In addition, a distribution market scheduling model is developed to capture and collect the ramping capability of participating microgrids in the distribution market as to offer it to the upstream network to address emerging ramping issues in the system associated with growing proliferation of variable renewable generation. Moreover, numerical simulations on a test distribution feeder with one microgrid and several consumers and prosumers exhibit the effectiveness of the proposed model.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Alireza Majzoobi


Received from ProQuest

File Format




File Size

117 p.


Electrical engineering