This article presents a distributed model predictive control methodology to manage energy resources for a set of consumer subsystems. The objective of the controller is to optimally distribute the allowable energy to the subsystems. The proposed methodology yields a distributed solution that converges to the optimum that would be obtained by a centralized controller. This optimal performance is achieved by expressing the problem in terms of slack variables and the global coupling constraint as a set of local subsystem constraints, thereby favoring the application of distributed model predictive control. Hardware-in-the-loop experiments with an air-conditioning thermal solar plant are performed to show the good performance of the proposed distributed controller.This section presents the MPC formulation for resource-constrained systems, followed by a compact formulation and its reformulation in terms of slack variables that will be handy to develop a DMPC solution.
Model predictive control formulationMPC encompasses the large class of control algorithms that make explicit use of a process model to obtain the control signal by minimizing an objective function over a given horizon [1]. Moreover, MPC strategies use a receding strategy whereby the horizon is displaced toward the future at each instant, but only the first control signal of the sequence calculated at each step is applied to the plant.
This study assesses the performance of a solid-state semiconductor-based hybrid photovoltaic-thermoelectric device that aims to harness both solar irradiance and heat dissipated from photovoltaic cells operating in Foz do Iguaçu city. Initially, the technologies involved, and the arrangement of the proposed device are presented; the modeling process of the generator operation under local operating conditions and taking into account solar energy availability is described later. The thermal energy harvesting brings out an average annual efficiency gain of 4.42% and a maximum efficiency increase of 6.05% (in the fall equinox) compared to standalone PV cell operation. The power output increase due to the utilization of the heat dissipated by the PV cells was substantial, reaching values ranging from 14.82% to 40.54%, depending on the time of year. The novelty of this research stems from the field power generation forecast, in southern hemisphere, for a new STEG device that combines photovoltaic cells and solid-state thermoelectric modules.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.