Bibliography

1

ANSI, “ANSI C84.1-2016; American National Standard for Electric Power Systems and Equipment—Voltage Ratings (60 Hz),” ed, 2016.

2

IEEE, “IEEE Guide for Electric Power Distribution Reliability Indices,” *IEEE Std 1366-2012 (Revision of IEEE Std 1366-2003),* pp. 1-43, 2012.

3

IEEE, “IEEE Guide for Collecting, Categorizing, and Utilizing Information Related to Electric Power DistributionInterruption Events,” *IEEE Std 1782-2014,* pp. 1-98, 2014.

4

ASHRAE, “ANSI/ASHRAE standard 55-2010 : thermal environmental conditions for human occupancy,” 2010.

5

H. Hao, C. D. Corbin, K. Kalsi, and R. G. Pratt, “Transactive Control of Commercial Buildings for Demand Response,” *IEEE Transactions on Power Systems,* vol. PP, pp. 1-1, 2016.

6

J. K. Kok, C. J. Warmer, and I. G. Kamphuis, “PowerMatcher: multiagent control in the electricity infrastructure,” presented at the Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems, The Netherlands, 2005.

7

TeMix Inc. (2017). *TeMix*. Available: http://www.temix.net.

8

NIST. (2017). *NIST Transactive Energy Challenge*. Available: https://pages.nist.gov/TEChallenge/.

9

IEEE, “IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA)– Federate Interface Specification,” *IEEE Std 1516.1-2010 (Revision of IEEE Std 1516.1-2000),* pp. 1-378, 2010.

10

IEEE, “IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA)– Framework and Rules,” *IEEE Std 1516-2010 (Revision of IEEE Std 1516-2000),* pp. 1-38, 2010.

11

IEEE, “IEEE Standard for Modeling and Simulation (M&S) High Level Architecture (HLA)– Object Model Template (OMT) Specification,” *IEEE Std 1516.2-2010 (Revision of IEEE Std 1516.2-2000),* pp. 1-110, 2010.

12

D. G. Holmberg, D. Hardin, R. Melton, R. Cunningham, and S. Widergren, “Transactive Energy Application Landscape Scenarios,” Smart Grid Interoperability Panel2016.

13

K. P. Schneider, Y. Chen, D. Engle, and D. Chassin, “A Taxonomy of North American radial distribution feeders,” in *2009 IEEE Power & Energy Society General Meeting*, 2009, pp. 1-6.

14

R. Lincoln. (2017). *PYPOWER*. Available: https://pypi.python.org/pypi/PYPOWER.

15

H. Li and L. Tesfatsion, “The AMES wholesale power market test bed: A computational laboratory for research, teaching, and training,” in *2009 IEEE Power & Energy Society General Meeting*, 2009, pp. 1-8.

16

D. J. Hammerstrom, C. D. Corbin, N. Fernandez, J. S. Homer, A. Makhmalbaf, R. G. Pratt *, et al.* (2016). *Valuation of Transactive Systems Final Report, PNNL-25323*. Available: http://bgintegration.pnnl.gov/pdf/ValuationTransactiveFinalReportPNNL25323.pdf.

17

D. P. Chassin, J. C. Fuller, and N. Djilali, “GridLAB-D: An agent-based simulation framework for smart grids,” *Journal of Applied Mathematics,* vol. 2014, pp. 1-12, 2014.

18

R. D. Zimmerman, C. E. Murillo-Sanchez, and R. J. Thomas, “MATPOWER: Steady-State Operations, Planning, and Analysis Tools for Power Systems Research and Education,” *IEEE Transactions on Power Systems,* vol. 26, pp. 12-19, 2011.

19

S. Ciraci, J. Daily, J. Fuller, A. Fisher, L. Marinovici, and K. Agarwal, “FNCS: a framework for power system and communication networks co-simulation,” presented at the Proceedings of the Symposium on Theory of Modeling & Simulation - DEVS Integrative, Tampa, Florida, 2014.

20

J. C. Fuller, K. P. Schneider, and D. Chassin, “Analysis of Residential Demand Response and double-auction markets,” in *2011 IEEE Power and Energy Society General Meeting*, 2011, pp. 1-7.

21

J. Arlow and I. Neustadt, *UML 2.0 and the Unified Process: Practical Object-Oriented Analysis and Design (2nd Edition)*: Addison-Wesley Professional, 2005.

22

H. Zhang, Y. Vorobeychik, J. Letchford, and K. Lakkaraju, “Data-Driven Agent-Based Modeling, with Application to Rooftop Solar Adoption,” presented at the Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems, Istanbul, Turkey, 2015.

23

V. Sultan, B. Alsamani, N. Alharbi, Y. Alsuhaibany, and M. Alzahrani, “A predictive model to forecast customer adoption of rooftop solar,” in *2016 4th International Symposium on Computational and Business Intelligence (ISCBI)*, 2016, pp. 33-44.