A phase model approach for thermostatically controlled load demand response

Abstract

A significant portion of electricity consumed worldwide is used to power thermostatically controlled loads (TCLs) such as air conditioners, refrigerators, and water heaters. Because the shortterm timing of operation of such systems is inconsequential as long as their long-run average power consumption is maintained, they are increasingly used in demand response (DR) programs to balance supply and demand on the power grid. Here, we present an ab initio phase model for general TCLs, and use the concept to develop a continuous oscillator model of a TCL and compute its phase response to changes in temperature and applied power. This yields a simple control system model that can be used to evaluate control policies for modulating the power consumption of aggregated loads with parameter heterogeneity and stochastic drift. We demonstrate this concept by comparing simulations of ensembles of heterogeneous loads using the continuous state model and an established hybrid state model. The developed phase model approach is a novel means of evaluating DR provision using TCLs, and is instrumental in estimating the capacity of ancillary services or DR on different time scales. We further propose a novel phase response based open-loop control policy that effectively modulates the aggregate power of a heterogeneous TCL population while maintaining load diversity and minimizing power overshoots. This is demonstrated by low-error tracking of a regulation signal by filtering it into frequency bands and using TCL sub-ensembles with duty cycles in corresponding ranges. Control policies that can maintain a uniform distribution of power consumption by aggregated heterogeneous loads will enable distribution system management (DSM) approaches that maintain stability as well as power quality, and further allow more integration of renewable energy sources.

Sustainability matchmaking: Linking renewable sources to electric water heating through machine learning

“…Bomela et al [72] conducted a similar study where a general thermostatically controlled loads (TCL) modelbased control was proposed to develop a continuous oscillator model of a TCL and compute its phase response to changes in temperature and applied power. In [73], Vanhoudt et al applied a model-based control algorithm to maximize the profit of a small scale district heating system heated by a combined heat and power plant (CHP).…”

Business Processes and Comfort Demand for Energy Flexibility Analysis in Buildings

“…At first, the consumption of an AC (converter) unit was correlated in real-time with the standard operation mode of a heat pump unit (compressor ON/OFF plus ventilation unit consumption). The temperature change θ(t) attributed to a thermostatically controlled load at cooling state could be used, according to Bomela et al [22], by a discrete time difference model:…”

Multi-agent reinforcement learning for modeling and control of thermostatically controlled loads

“…Furthermore, the paper benchmarks the learned model using a simulated vessel, and also investigates the reason for the efficiency gains over an entire year in much greater detail in tens of real-world households. Other model-based approaches include (26) and (27) which have focused more on using ensembles of TCLs to provide services to the grid. In doing so, the actual modelling of the TCL is simply considered as a cyclical load which has to be modulated appropriately to provide grid services.…”