Parameter identification of aggregated thermostatically controlled loads for smart grids using PDE techniques

References

• Andersen, P., Pedersen, T.S., & Nielsen, K.M. (2012, October). Observer based model identification of heat pumps in a smart grid. Proceedings of Multiconference on Systems and Control, Dubrovnik. doi:10.1109/CCA.2012.6402428.
   Google Scholar
• Banakar, H., Luo, C., & Ooi, B.T. (2008). Impacts of wind power minute-to-minute variations on power system operation. IEEE Transactions on Power Systems, 23, 150–160.
   Web of Science ®Google Scholar
• Bashash, S., & Fathy, H. (2013). Modeling and control of aggregate air conditioning loads for robust renewable power management. IEEE Transactions on Control Systems Technology, 21, 1318–1327.
   Web of Science ®Google Scholar
• Bompard, E., Carpaneto, E., Chicco, G., & Napoli, R. (1996). Analysis and modelling of thermostatically-controlled loads. In Proceedings of 8th Mediterranean Electrotechnical Conference(Vol. 2, pp. 730–734). Bari: IEEE.
   Google Scholar
• Callaway, D. (2009). Tapping the energy storage potential in electric loads to deliver load following and regulation, with application to wind energy. Energy Conversion and Management, 50, 1389–1400.
   Web of Science ®Google Scholar
• Callaway, D., & Hiskens, I. (2011). Achieving controllability of electric loads. Proceedings of the IEEE, 99, 184–199.
   Web of Science ®Google Scholar
• Crank, J., & Nicolson, P. (1947). A practical method for numerical evaluation of solutions of partial differential equations of the heat conduction type. Proceedings of the Cambridge Philosophical Society, 43, 50–67.
   Web of Science ®Google Scholar
• International Energy Agency. (2006). World energy outlook 2006 (Technical report). Paris: Organisation for Economic Co-operation and Development.
   Google Scholar
• Ioannou, P., & Sun, J. (1996). Robust adaptive control. Upper Saddle River, NJ: Prentice-Hall.
   Google Scholar
• Klobasa, M. (2010). Analysis of demand response and wind integration in Germany’s electricity market. IET Renewable Power Generation, 4, 55–63.
   Web of Science ®Google Scholar
• Krstic, M., Kanellakopoulos, I., & Kokotovic, P. (1995). Nonlinear and adaptive control design. New York, NY: Wiley.
   Google Scholar
• Kundu, S., & Sinitsyn, N. (2012, June). Safe protocol for controlling power consumption by a heterogeneous population of loads. Proceedings of 2012 American Control Conference, Montreal, QC.
   Google Scholar
• Lu, N., Chassin, D.P., & Widergren, S.E. (2005). Modeling uncertainties in aggregated thermostatically controlled loads using a state queueing model. IEEE Transactions on Power Systems, 20, 725–733.
   Web of Science ®Google Scholar
• MacCormack, R.W. (2003). The effect of viscosity in hypervelocity impact cratering. Journal of Spacecraft and Rockets, 40, 757–763.
   Web of Science ®Google Scholar
• Malhame, R., & Chong, C. (1985). Electric load model synthesis by diffusion approximation of a higher-order hybrid-state stochastic system. IEEE Transactions on Automatic Control, 30, 854–860.
   Web of Science ®Google Scholar
• Mathieu, J.L., Koch, S., & Callaway, D.S. (2013). State estimation and control of electric loads to manage real-time energy imbalance. IEEE Transactions on Power Systems, 28, 430–440.
   Web of Science ®Google Scholar
• McDonald, H. (2008). Adaptive intelligent power systems: Active distribution networks. Energy Policy, 36, 4346–4351. doi:10.1016/j.enpol.2008.09.038.
   Web of Science ®Google Scholar
• Mets, K., Verschueren, T., Haerick, W., Develder, C., & Turck, F.D. (2010). Optimizing smart energy control strategies for plug-in hybrid electric vehicle charging. In Network Operations and Management Symposium Workshops (pp. 293–299). Osaka: IEEE. doi:10.1109/NOMSW.2010.5486561.
   Google Scholar
• Mohsenian-Rad, A., Wong, V.W.S., Jatskevich, J., Schober, R., & Leon-Garcia, A. (2010). Autonomous demand-side management based on game-theoretic energy consumption scheduling for the future smart grid. IEEE Transactions on Smart Grid, 1, 320–331.
   Web of Science ®Google Scholar
• Moslehi, K., & Kumar, R. (2010). A reliability perspective of the smart grid. IEEE Transactions on Smart Grid, 1, 57–64.
   Web of Science ®Google Scholar
• Moura, S.J., Ruiz, V., & Bendsten, J. (2013, December). Observer design for boundary coupled PDEs: Application to thermostatically controlled loads in smart grids. 52nd IEEE Conference on Decision and Control, Florence.
   Google Scholar
• Perfumo, C., Kofman, E., Braslavsky, J., & Ward, J. (2012). Load management: Model-based control of aggregate power for populations of thermostatically controlled loads. Energy Conversion and Management, 55, 36–48.
   Web of Science ®Google Scholar
• Petersen, M., Bendtsen, J., & Stoustrup, J. (2012, June). Optimal dispatch strategy for the agile virtual power plant imbalance compensation problem. Proceedings of American Control Conference, Montreal.
   Google Scholar
• Short, J., Infield, D.G., & Freris, L.L. (2007). Stabilization of grid frequency through dynamic demand control. IEEE Transactions on Power Systems, 22, 1284–1293.
   Web of Science ®Google Scholar
• Smyshlyaev, A., & Krstic, M. (2010). Adaptive control of parabolic PDEs. Philadelphia, PA: Princeton University Press.
   Google Scholar
• Strbac, G. (2008). Demand side management: Benefits and challenges. Energy Policy, 36, 4419–4426.
   Web of Science ®Google Scholar
• Walawalkar, R., Blumsack, S., Apt, J., & Fernands, S. (2008). An economic welfare analysis of demand response in the PJM electricity market. Energy Policy, 36, 3692–3702.
   Web of Science ®Google Scholar
• Zhang, W., Lian, J., Chang, C.Y., Kalsi, K., & Sun, Y. (2012, December). Reduced-order modeling of aggregated thermostatic loads with demand response. Proceedings of 51st IEEE Conference on Decision and Control, Maui, HI.
   Google Scholar