Lighting Consumption Optimization in a SCADA Model of Office Building Considering User Comfort Level

Due to the high penetration of the buildings in energy consumption, the use of optimization algorithms plays a key role. Therefore, all the producers and prosumers should be equipped with the automation infrastructures as well as intelligent decision algorithms, in order to perform the management programs, like demand response. This paper proposes a multi-period optimization algorithm implemented in a multi-agent Supervisory Control and Data Acquisition system of an office building. The algorithm optimizes the lighting power consumption of the building considering the user comfort constraints. A case study is implemented in order to validate and survey the performance of the implemented optimization algorithm using real consumption data of the building. The outcomes of the case study show the great impact of the user comfort constraints in the optimization level by respect to the office user’s preferences.The present work was done and funded in the scope of the following projects: COLORS Project PTDC/EEI-EEE/28967/2017 and UID/EEA/00760/2019 funded by FEDER Funds through COMPETE program and by National Funds through FCT.info:eu-repo/semantics/publishedVersio

Consumption Optimization in an Office Building Considering Flexible Loads and User Comfort

This article belongs to the Special Issue Architectures and Platforms for Smart and Sustainable CitiesThis paper presents a multiperiod optimization algorithm that is implemented in a Supervisory Control and Data Acquisition system. The algorithm controls lights and air conditioners as flexible loads to reduce the consumption and controls a dishwasher as a deferrable load to implement the load shifting. Several parameters are considered to implement the algorithm for several successive periods in a real building operation. In the proposed methodology, optimization is done regarding user comfort, which is modeled in the objective function related to the indoor temperature in each room, and in the constraints in order to prevent excessive power reduction, according to users' preferences. Additionally, the operation cycle of a dishwasher is included, and the algorithm selects the best starting point based on the appliance weights and power availability in each period. With the proposed methodology, the building energy manager can specify the moments when the optimization is run with consideration of the operational constraints. Accordingly, the main contribution of the paper is to provide and integrate a methodology to minimize the difference between the actual and the desired temperature in each room, as a measure of comfort, respecting constraints that can be easily bounded by building users and manager. The case study considers the real consumption data of an office building which contains 20 lights, 10 ACs, and one dishwasher. Three scenarios have been designed to focus on different functionalities. The outcomes of the paper include proof of the performance of the optimization algorithm and how such a system can effectively minimize electricity consumption by implementing demand response programs and using them in smart grid contexts.The present work was done and funded in the scope of the following projects: COLORSPTDC/EEI-EEE/28967/2017 and UIDB/00760/2020 funded by FEDER Funds through COMPETE programinfo:eu-repo/semantics/publishedVersio

Sequential Tasks Shifting for Participation in Demand Response Programs

In this paper, the proposed methodology minimizes the electricity cost of a laundry room by means of load shifting. The laundry room is equipped with washing machines, dryers, and irons. Additionally, the optimization model handles demand response signals, respecting user preferences while providing the required demand reduction. The sequence of devices operation is also modeled, ensuring correct operation cycles of different types of devices which are not allowed to overlap or have sequence rules. The implemented demand response program specifies a power consumption limit in each period and offers discounts for energy prices as incentives. In addition, users can define the required number of operations for each device in specific periods, and the preferences regarding the operation of consecutive days. In the case study, results have been obtained regarding six scenarios that have been defined to survey about effects of different energy tariffs, power limitations, and incentives, in a laundry room equipped with three washing machines, two dryers, and one iron. A sensitivity analysis of the power consumption limit is presented. The results show that the proposed methodology is able to accommodate the implemented scenario, respecting user preferences and demand response program, minimizing energy costs. The final electricity price has been calculated for all scenarios to discuss the more effective schedule in each scenario.This work has received funding from Portugal 2020 under SPEAR project (NORTE-01-0247-FEDER-040224), in the scope of ITEA 3 SPEAR Project 16001 and from FEDER Funds through COMPETE program and from National Funds through (FCT) under the project UIDB/00760/2020, and CEECIND/02887/2017.info:eu-repo/semantics/publishedVersio

Information and Communications Technologies (ICTs) for energy efficiency in buildings: Review and analysis of results from EU pilot projects

Information and Communications Technologies (ICTs) can play a potential role in improving the energy performance of buildings by the implementation of effective solutions that take advantage of the energy interactions between all the elements included in a building. A revision of the 105 pilots implemented or under implementation in 18 projects in the area of ICTs for energy efficiency in buildings located in 23 European countries, through 88 cities with different types of climates, buildings and technologies have been carried out through documentary and field analysis of the energy, economic and social project results. These results have been extrapolated to assess the potential energy savings which could be expected at the EU level by implementing the solutions proposed by the projects. By the implementation of the different ICT solutions, buildings have achieved more than 20% energy savings. Pilots have demonstrated that the effectiveness of the ICT solution does not depend directly on the different climates where the solutions are implemented, but on several factors, such as the level of motivation, perceived thermal comfort, quality of social interaction and communication and ICT support

Energy Optimization and Management of Demand Response Interactions in a Smart Campus

The proposed framework enables innovative power management in smart campuses, integrating local renewable energy sources, battery banks and controllable loads and supporting Demand Response interactions with the electricity grid operators. The paper describes each system component: the Energy Management System responsible for power usage scheduling, the telecommunication infrastructure in charge of data exchanging and the integrated data repository devoted to information storage. We also discuss the relevant use cases and validate the framework in a few deployed demonstrators

Sequential Tasks Shifting for Participation in Demand Response Programs

In this paper, the proposed methodology minimizes the electricity cost of a laundry room by means of load shifting. The laundry room is equipped with washing machines, dryers, and irons. Additionally, the optimization model handles demand response signals, respecting user preferences while providing the required demand reduction. The sequence of devices operation is also modeled, ensuring correct operation cycles of different types of devices which are not allowed to overlap or have sequence rules. The implemented demand response program specifies a power consumption limit in each period and offers discounts for energy prices as incentives. In addition, users can define the required number of operations for each device in specific periods, and the preferences regarding the operation of consecutive days. In the case study, results have been obtained regarding six scenarios that have been defined to survey about effects of different energy tariffs, power limitations, and incentives, in a laundry room equipped with three washing machines, two dryers, and one iron. A sensitivity analysis of the power consumption limit is presented. The results show that the proposed methodology is able to accommodate the implemented scenario, respecting user preferences and demand response program, minimizing energy costs. The final electricity price has been calculated for all scenarios to discuss the more effective schedule in each scenario.This work has received funding from Portugal 2020 under SPEAR project (NORTE-01-0247-FEDER-040224), in the scope of ITEA 3 SPEAR Project 16001 and from FEDER Funds through COMPETE program and from National Funds through (FCT) under the project UIDB/00760/2020, and CEECIND/02887/2017.info:eu-repo/semantics/publishedVersio

BRICKS: Building’s reasoning for intelligent control knowledge-based system

Building energy management systems have been largely implemented, focusing on specific domains. When installed together, they lack interoperability to make them work correctly and to achieve a centralized user interface. The Building's Reasoning for Intelligent Control Knowledge-based System (BRICKS) overcomes these issues by developing an interoperable building management system able to aggregate different interest domains. It is a context-aware semantic rule-based system for intelligent management of buildings' energy and security. Its output can be a set of alarms, notifications, or control actions to take. BRICKS itself, and its features are the innovative contribution of the present paper. It is very important for buildings' energy management, namely in the scope of demand response programs. In this paper, it is shown how semantics is used to enable the knowledge exchange between different devices, algorithms, and models, without the need for reprogramming the system. A scenario is deployed in a real building for demonstration.This work has received funding from the European Union’s Horizon 2020 research and innovation programme under project DOMINOES (grant agreement No 771066) and from FEDER Funds through COMPETE program and from National Funds through FCT under the projects UID/EEA/00760/2019, PTDC/EEI-EEE/28954/2017 (MAS-Society), and SFRH/BD/118487/2016.info:eu-repo/semantics/publishedVersio

Case based reasoning with expert system and swarm intelligence to determine energy reduction in buildings energy management

This paper proposes a novel Case Based Reasoning (CBR) application for intelligent management of energy resources in residential buildings. The proposed CBR approach enables analyzing the history of previous cases of energy reduction in buildings, and using them to provide a suggestion on the ideal level of energy reduction that should be applied in the consumption of houses. The innovations of the proposed CBR model are the application of the k-Nearest Neighbors algorithm (k-NN) clustering algorithm to identify similar past cases, the adaptation of Particle Swarm Optimization (PSO) meta-heuristic optimization method to optimize the choice of the variables that characterize each case, and the development of expert systems to adapt and refine the final solution. A case study is presented, which considers a knowledge base containing a set of scenarios obtained from the consumption of a residential building. In order to provide a response for a new case, the proposed CBR application selects the most similar cases and elaborates a response, which is provided to the SCADA House Intelligent Management (SHIM) system as input data. SHIM uses this specification to determine the loads that should be reduced in order to fulfill the reduction suggested by the CBR approach. Results show that the proposed approach is capable of suggesting the most adequate levels of reduction for the considered house, without compromising the comfort of the users.This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 641794 (project DREAMGO) and a grant agreement No 703689 (project ADAPT); 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

Design, simulation and analysis of a passive house and its renewable energy system for Newfoundland

A large amount of energy produced is directly consumed in the form of electricity. This need for energy is continuously growing and leading to new ways to make efficient use of it. When we talk about using energy efficiently, the idea of a passive house system kicks in, which essentially focuses on reducing energy use for space heating or cooling in a house. The main idea is to reduce the energy consumption of the house as well as reducing its impact on the environment when the occupants are using the house. The first phase of the research shows the dynamic modelling of an energy-efficient home that works on the principles and guidelines of a passive house using the EnergyPlus simulation engine. A renewable energy system has been developed for the passive house, which is located at Flat Rock, St John’s, NL Canada. The overall design has been simulated using MATLAB/Simulink environment packages. The dynamic simulation indicates that the system gives promising results. In the second phase, a detailed simulation of a renewable energy system using various software and efficient energy management techniques are presented. Finally, for experimental validation, an open-source IoT platform named Ubidots smart home automation is used as Human Machine Interface (HMI) server, an ESP32 Thing microcontroller board as a Master Logic Controller (MLC) where all sensors and output devices such as power meter, relays are connected for data acquisition and control