Smart buildings are the need of the day with increasing demand-supply ratios and deficiency to generate considerably. In any modern non-industrial infrastructure, these demands mainly comprise of thermostatically controlled loads (TCLs), which can be manoeuvred. TCL loads like air-conditioner, heater, refrigerator, are ubiquitous, and their operating times can be controlled to achieve desired aggregate power. This power aggregation, in turn, helps achieve load management targets and thereby serve as ancillary service (AS) to the power grid. In this work, a distributed averaging protocol is used to achieve the desired power aggregate set by the utility using steady-state desynchronization. The results are verified using a computer program for a homogeneous and heterogeneous population of TCLs. Further, load following scenario has been implemented using the utility as a reference. Apart from providing a significant AS to the power grid, the proposed idea also helps reduce the amplitude of power system oscillations imparted by the TCLs. Hardware-based results are obtained to verify its implementation feasibility in real-time. Additionally, we extend this idea to data-driven paradigm and provide comparisons therein.

Smart buildings are the need of the day with increasing demand-supply ratios and considerable deficiency to generate them. In any modern nonindustrial infrastructure, these demands mainly comprise thermostatically controlled loads (TCLs), which can be maneuvered. TCLs, such as air-conditioners, heaters, and refrigerators, are ubiquitous and their operating times can be controlled to achieve desired aggregate power. This power aggregation, in turn, helps achieve load management targets and thereby serves as an ancillary service (AS) to the power grid. In this work, a distributed averaging protocol is used to achieve the desired power aggregate set by the utility using steady-state desynchronization. The results are verified using a computer program for a homogeneous and heterogeneous population of TCLs. Furthermore, a load following scenario has been implemented using the utility as a reference. Apart from providing a significant AS to the power grid, the proposed idea also helps reduce the amplitude of power system oscillations imparted by the TCLs. Hardware-based results are obtained to verify its implementation feasibility in real-time.

This paper proposes a novel second order mathematical model in the Kuramoto framework to simulate and study low frequency oscillations in power systems. This model facilitates better understanding of the complex dynamics of a power network. A standard four generator power system with all-to-all connectivity is considered and results obtained from the proposed model are verified. It is shown, that the model simulates various properties related to low frequency oscillations in power systems which presently are obtained through small-signal analysis. Further, we provide analogy to blackouts in a power grid, by emulating chimera behavior and thereby discuss bifurcation analysis of the proposed model.