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

Air conditioner consumption optimization in an office building considering user comfort

The rapid growth of energy consumption and its consequences in the last decades, made the world persuaded to energy optimization and energy management. Therefore, producers and prosumers should be equipped with the automation infrastructures to perform the management programs, such as demand response programs. Office buildings are considering as a proper case for implementing energy consumption minimization since they are responsible for a huge portion of total energy consumption in the world. This paper proposes a multi-period optimization algorithm implemented in Supervisory Control and Data Acquisition system of an office building. The developed optimization algorithm is an efficient solution considered for minimizing the power consumption of air conditioners by considering the user comfort constraints. Two determinative parameters are defined to prevent over-power reduction from certain devices. In order to respect to user preferences, priority numbers are dedicated to each air conditioner to present the importance of each device. A case study with several scenarios is implemented to verify the performance of the proposed algorithm in real life using real data of the building. The obtained results show the impacts of proposed parameters and different comfort constraints of algorithm while the main target of the optimization has been reached.The present work was done and funded in the scope of the following projects: MAS-Society Project PTDC/EEI-EEE/28954/2017 and UID/EEA/00760/2019 funded by FEDER, Spain Funds through COMPETE program and byNational Funds through FCT, Portugal.info:eu-repo/semantics/publishedVersio