Demand Side Management Strategy for Distribution Networks Volt/Var Control: A FCS-Model Predictive Control Approach
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Demand Side Management Strategy for Distribution Networks Volt/Var Control: A FCS-Model Predictive Control Approach Rafael A. Fuhrmann1 · Raul V. A. Monteiro1 · Surya C. Dhulipala2 · Arturo Bretas2 Received: 17 January 2020 / Revised: 20 June 2020 / Accepted: 3 August 2020 © Brazilian Society for Automatics–SBA 2020
Abstract Due to the advent of distributed energy resources at distribution level, utility companies face new challenges in terms of voltage control. Existing works in the literature have proposed the use of demand side management (DSM) to provide ancillary services to the grid. Some works explored the use of thermal inertia of buildings to tackle the frequency regulation problem. Existing DSM strategies ignore the potential service loads can provide for the Volt/Var control (VVC) problem. The ability of smart buildings to provide reactive power support to the grid has not been exploited to date. In this paper, we present a finite control state model predictive control strategy for VVC in distribution networks. The robustness of this strategy is validated on a modified IEEE 13 bus system. Keywords Demand side management · FCS-MPC · Smart grids
1 Introduction Demand side management (DSM) is a strategy in which the consumer side, i.e. residential, industrial and commercial loads, is modulated to provide ancillary services to the grid, to maintain the voltage magnitude and frequency levels in allowable operational region (Palensky and Dietrich 2011). At distribution level, some common DSM strategies range from load shifting (flattening action over the grid’s load profile) to direct load control (DLC)—an approach in which the operator is able to curtail (load shedding) or modulate individual loads’ consumption (DSM) to meet the grid’s needs at the time (Palensky and Dietrich 2011). In this work, we present a DLC method which modulates power consumption of thermostatically controlled loads (TCLs)—heating, ventilation and air conditioning systems
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Raul V. A. Monteiro [email protected] Rafael A. Fuhrmann [email protected] Surya C. Dhulipala [email protected] Arturo Bretas [email protected]
1
Federal University of Mato Grosso, Cuiabá, Brazil
2
University of Florida, Gainesville, USA
(HVAC) in this case. HVACs are suitable candidates for DSM due to their inherent thermal energy storage capabilities. DLC for Volt/Var control (VVC) was explored in our previous work of Dhulipala et al. (2018) which uses the priority stack controller, where an agent changes the state of operation (ON/OFF) of an optimal number of HVAC systems in order to restore the distribution network (DN) voltage profile to nominal levels. HVACs are also suitable for load balancing services, as demonstrated by Lu (2012). Other successful examples can be found in the works of Lampropoulos et al. (2013), Bomela et al. (2018) and Mahdavi et al. (2017). There is a need for proper control technique to completely tackle the DLC problem. One such method is the model predictive control (MPC), a methodology where an online op
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