A scalable architecture for the interconnection of microgrids

Electrification is a global challenge that is especially acute in India, where about one fifth of the population has no access to electricity. Solar powered microgrid technology is a viable central grid alternative in the electrification of India, especially in remote areas where grid extension is cost prohibitive. However, the upfront costs of microgrid development, coupled with inadequate financing, have led to the implementation of small scale, stand alone systems. Thus, the costs of local generation and storage are a substantial barrier to acquisition of the technology. Furthermore, the issues of uncertainty, intermittency, and variability of renewable generation are daunting in small microgrids due to lack of aggregation. In this work, a methodology is provided that maximizes system-wide reliability through the design of a computationally scalable communication and control architecture for the interconnection of microgrids. An optimization based control system is proposed that finds optimal load scheduling and energy sharing decisions subject to system dynamics, power balance constraints, and congestion constraints, while maximizing network-wide reliability. The model is first formulated as a centralized optimization problem, and the value of interconnection is assessed using supply and demand data gathered in India. The model is then formulated as a layered decomposition, in which local scheduling optimization occurs at each microgrid, requiring only nearest neighbor communication to ensure feasibility of the solutions. Finally, a methodology is proposed to generate distributed optimal policies for a network of Linear Quadratic Regulators that are each making decisions coupled by network flow constraints. The LQR solution is combined with network flow dual decomposition to generate a fully decomposed algorithm for finding the dynamic programming solution of the LQR subject to network flow constraints.

Department dc:contributor.department

Massachusetts Institute of Technology. Engineering Systems Division

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Fero, Allison

Advisor dc:contributor.advisor

• Munther Dahleh and Mardavij Roozbehani.

• Institute for Data, Systems, and Society.
• Engineering Systems Division.
• Technology and Policy Program.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/115007

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/115007