Demand Response Based on the Power Factor Considering Polynomial and Induction Motor loads

Valinejad, Jaber, Marzband, Mousa, Ansari, Meisam and Labonne, Antoine (2020) Demand Response Based on the Power Factor Considering Polynomial and Induction Motor loads. In: 2020 IEEE Texas Power and Energy Conference (TPEC): 6-7 February 2020, College Station, TX, USA. IEEE, Piscataway, NJ, pp. 402-408. ISBN 9781728144375, 9781728144368, 9781728144351

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Abstract

Demand Side Management (DSM) can bring numerous benefits to power systems, such as decreasing peak load demand, reshaping demand and enhancing system security. In order to achieve these goals, this paper proposes a two-stage model for DSM considering polynomial and induction motor loads. Induction motor includes refrigerator (RFER), dishwasher (DWSH), clothes washing machine (CWSH) and dryer style motor (DRYR) loads. The polynomial and RFER loads follow a continuous DSM while the DWSH, CWSH and DRYR loads follow a selective DSM. Considering both the active and the reactive demand response, this paper provides a new DR based on the power factor. Electrical appliances are further classified as responsive/controllable and non-responsive/uncontrollable devices on the basis of their distinct power consumption constraints. Here, all appliances' operation patterns are modeled through their functions in real systems; as a result, the polynomial load model and induction motor type loads are adopted to represent consumers' behavior. A stochastic Multi-Objective Optimal Network Operation (SMONO) framework is further proposed to solve the aforementioned DSM problem. The simulations conducted in a generic distribution network reveals that the proposed method can successfully reach an optimal trade-off between four objectives, namely, voltage security, power losses, customer costs, and peak demand.

Item Type:	Book Section
Uncontrolled Keywords:	Demand side management, Reactive demand response, Load Modelling, Security, Polynomial load, Induction Motor
Subjects:	H800 Chemical, Process and Energy Engineering
Department:	Faculties > Engineering and Environment > Mathematics, Physics and Electrical Engineering
Depositing User:	Elena Carlaw
Date Deposited:	08 Apr 2020 08:42
Last Modified:	20 Apr 2020 12:20
URI:	http://nrl.northumbria.ac.uk/id/eprint/42742

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