Intelligent Residential Air-Conditioning System With Smart-Grid Functionality

Abstract

Abstract-This paper sets forth a novel intelligent residential air-conditioning (A/C) system controller that has smart grid functionality. The qualifier "intelligent" means the A/C system has advanced computational capabilities and uses an array of environmental and occupancy parameters in order to provide optimal intertemporal comfort/cost trade-offs for the resident, conditional on anticipated retail energy prices. The term "smartgrid functionality" means that retail energy prices can depend on wholesale energy prices. Simulation studies are used to demonstrate the capabilities of the proposed A/C system controller.

Effects of price-responsive residential demand on retail and wholesale power market operations

“…For the purposes of this study, the traditional A/C systems are replaced with intelligently controlled A/C systems as modeled in [6]. The feeder load is thus divided into two parts: non price-responsive load obtained by simulating the feeder with all A/C systems in all households turned off; and the intelligently controlled A/C load, which is calculated separately.…”

“…The overall electricity power consumption depends onQ and the coefficient of performance COP (unit-free) of the A/C. The structural attributes of the ten groups of households along with their operational attributes are listed in Table II. The 65 household residents within each particular group are then allowed to have different A/C comfort-cost tradeoff preferences as captured by a "marginal utility of income" parameter α [6] varying over eight different possible settings. For simplicity, the residents' temperature "bliss points" are assumed equal.…”

“…2(c). Also on the morning of day 1, the five GenCos submit supply offers 6 to the ISO for use in the day-ahead market on day 2 that consist of their true marginal cost functions and their true capacity limits; see Table I.…”

“…6(c), it is seen that LSE 3's hourly net earnings are strongly positively correlated with hourly realtime aggregate loads. The explanation for this correlation is that, for the simulation at hand, the load forecast errors (6) and price deviations (7) are very small compared to LSE 3's mark-up earnings m · [Load …”

“…Building on prior work by the authors and their collaborators [6], this study utilizes a computational model of a household with an intelligent A/C system that responds not only to price signals but also to the household resident's preferred comfort-cost tradeoffs. The physical operations of the A/C system are represented by means of the physicsbased Equivalent Thermal Parameter (ETP) model [7], [8].…”