Direct Load Control Demand Response Program for Air Conditioners

According to importance of demand response programs in last decades, many efforts have been made to change the consumption patterns of the users, and the use of renewable resources has also increased. Significant part of energy consumption belongs to the entire kinds of the buildings such as residential, commercial, and office buildings. In this context, the air conditioners can play an important role in demand response programs. Air conditioners can be as thermostatically controllable appliances for direct load control demand response program. In this paper, an optimization algorithm is developed to optimize the power consumption of air conditioners based on the user preferences to maintain the user comfort. The methodology of this work is proposed as a linear optimization problem that consider the generation of a renewable energy resource, which supplies a part of the energy consumption of the building. For the case study, the amount of the renewable energy generation, total consumption of building, and the consumption of the air conditioners in a real research building are considered and the optimization has been done based on the realistic data.This work has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAMGO) and from FEDER Funds through COMPETE program and from National Funds through FCT, under the project UID/EEA/00760/2013.info:eu-repo/semantics/publishedVersio

Optimization-Based Home Energy Management System Under Different Electricity Pricing Schemes

This paper presents an optimization-based home energy management system, by taking advantages of renewable resources and energy storage system for optimally managing the energy consumption and generation of the house. The surplus of renewable generation will be stored in energy storage system or will be injected into the main grid. An optimization algorithm is developed for this system in order to minimize the electricity bill of the house considering electricity tariffs. Four home appliances are considered to be controlled by this system for reducing the consumption in critical periods. The outcomes of optimization problem are the optimal scheduling of the resources including renewable generation, energy storage system, consumption reduction, and power transactions with the grid. In the case study, the developed model will be employed in three different scenarios, which considers simple electricity prices and time-of- use tariffs in order to test and validate the performance of the developed model.The present work was done and funded in the scope of the following projects: H2020 DREAM-GO Project (Marie Sklodowska-Curie grant agreement No 641794); Project GREEDI (ANI|P2020 17822); and UID/EEA/00760/2013 funded by FEDER Funds through COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio