1982IEEE Transactions on Power Apparatus and SystemsRequires access

Physically-Based Model of Demand with Applications to Load Management Assessment and Load Forecasting

Terry M. Calloway, Charles W. Brice

Open publisher page 42 citations

Abstract

In the analysis of various load management scenarios, it is important to recognize the effects of the particular loads being controlled on the power system. This paper presents a physically-motivated model of the demand of a group of air conditioners as a function of the outside temperature, the average building and air conditioning system parameters, and the average thermostat setting. The model shows the payback efect and the results of changing thermostat settings and building insulation levels.

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What this paper is about

In the analysis of various load management scenarios, it is important to recognize the effects of the particular loads being controlled on the power system. This paper presents a physically-motivated model of the demand of a group of air conditioners as a function of the outside temperature, the average building and air conditioning system parameters, and the average thermostat setting. The model shows the payback efect and the results of changing thermostat settings and building insulation levels.

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OpenAlex reports 42 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

In the analysis of various load management scenarios, it is important to recognize the effects of the particular loads being controlled on the power system. This paper presents a physically-motivated model of the demand of a group of air conditioners as a function of the outside temperature, the average building and air conditioning system parameters, and the average thermostat setting. The model shows the payback efect and the results of changing thermostat settings and building insulation levels.

Key concepts: Thermostat, Air conditioning, Demand response, Load management, Automotive engineering, Electric power system, Demand forecasting, Engineering

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