Generation following with thermostatically controlled loads via alternating direction method of multipliers sharing algorithm

Abstract

Abstract-A fundamental requirement of the electric power system is to maintain a continuous and instantaneous balance between generation and load. The intermittency and uncertainty introduced by renewable energy generation requires expanded ancillary services to maintain this balance. In this paper, we examine the potential of thermostatically controlled loads (TCLs), such as refrigerators and electric water heaters, to provide generation following services in real-time energy markets (1 to 5 minutes). To control the non-linear dynamics of hysteretic dead-band systems in a manner suitable for convex optimization, we introduce an alternative control trajectory representation of the TCLs and their discrete input signals. To perform distributed optimization across large populations of TCLs, we apply a variation of the alternating direction method of multipliers (ADMM) algorithm. We numerically demonstrate the algorithm's potential for controlling a TCL population's total power demand within an error tolerance of 10 kW.

ARX Model of a Residential Heating System With Backpropagation Parameter Estimation Algorithm

“…usage by up to 30% [2]. Such intelligent systems can improve the efficiency of building operations, better regulate indoor conditions to improve air quality and occupant comfort, and enable buildings to participate in demand response services to improve power grid stability and reduce energy related carbon emissions [3][4][5][6][7][8].…”

Recursive parameter estimation of thermostatically controlled loads via unscented Kalman filter

“…The sign conventions in (1) assume that the TCL is providing a cooling load and that P (and thus θ 2 ) is negative.…”

“…The advantages of responsive TCLs over large storage technologies include: (i) they are already wellestablished technologies; (ii) they are spatially distributed around the power system; (iii) they employ simple and fast local actuation; (iv) they are unimpaired by the outage of individuals in the population; and (v) they -on the aggregate -can produce a quasi-continuous response despite the discrete nature of the individual controls [1][2] [3].…”

“…Recent trends in the field of convex optimization, in particular the introduction of the alternating direction method of multipliers (ADMM), have enabled researchers to pursue distributed methods of load control [1][12] [13][14] [15]. Therefore, rather than using an aggregation model with centralized control, individual TCLs can coordinate amongst each other to drive the population towards a shared global objective.…”

Blockchains for decentralized optimization of energy resources in microgrid networks

“…Power withdrawals due to uncontrollable loads (lights, plug loads) are considered deterministic, inflexible, and inelastic. We do not model thermostatically controlled loads or smart inverters, though those can be added to the formulation using the approaches in [39] and [26] respectively.…”