A Methodology to Forecast the Control Capacity and Control Payback of a Population of Thermostatically Controlled Appliances in a Demand-Side Management

Pegah Yazdkhasti, Chris Diduch, Ahmad Elkhateb

Research output: Contribution to journalArticle

Abstract

Integrating renewable resources such as wind and solar into the existing power system has introduced new challenges due to their rapid fluctuations which tends to decrease the reliability of the grid. One method to cope with this uncertainty and variability in generation is managing the demand side through direct load control. Thermostatically controlled appliances can play a significant role for this purpose; however, the system operator requires a reliable estimation about the magnitude of the load and how much it can be shifted. This paper presents a novel methodology to formulate and forecast the control capacity of a population of thermostatically controlled appliances. In addition to that, this methodology can provide an estimation on how long the system can follow a desired level of power consumption, and how the aggregated load would change once the controller stops (ie. the payback). The performance of the proposed method was evaluated using a numerical simulator of a population of the loads. Simulation results show that the proposed method can provide a reliable estimation about controllability of the load in terms of minimum and maximum achievable load, the time interval that it can hold the load at certain level, and how the uncontrolled load would behave after the control period.
Original languageEnglish
JournalCanadian Journal of Electrical and Computer Engineering
Publication statusAccepted - 16 Mar 2020

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