Planning and operational energy optimization solutions for smart buildings

Abstract

The incremented popularity of Internet of Things (IoT), thanks to improvements both in hardware and software of sensors over the last years, enables the possibility to monitor and gather any kind of data. Additionally, the arrangement of heterogeneous sensors, capable of perceiving information about their surroundings, into a rich Wireless Sensor Network (WSN), allows the appearance of complex systems in which resources are managed more efficiently. Smart cities, buildings, parkings, emergency services are appearing, where control over energy consumption and better sustainability are coupled with an improvement of the comfort of occupants. In this paper, we address the problem of energy optimization in smart buildings, considering both the planning and operational aspects. Specifically, the first aim is to propose an optimal deployment of the WSN inside a building. For this, we present a model able to identify the optimal locations for different types of sensors and gateways, by optimizing energy consumption while fulfilling connectivity, resource, protection, and clustering coverage constraints. Once the IoT system is deployed, we address the problem of how the building actually functions, according to the behaviour of the occupants. In particular, we propose a Building Management System (BMS) capable of efficiently and automatically manage the building elements using human behavioural models, thus lowering the overall building energy consumption whilst maintaining acceptable levels of comfort.

Dynamic User Preference Parameters Selection and Energy Consumption Optimization for Smart Homes Using Deep Extreme Learning Machine and Bat Algorithm

“…For the management of IoT systems and energy efficiency, authors in [37] presented a smart building template. The planning and identification of the best suitable locations to install sensors and gateways reduce the energy consumption in smart buildings [38]. The fuzzy logic controller based model has been successful in the hydroponics environment for the optimization of humidity and water level [39].…”

“…Equation (37) can be used to calculate the frequency for Bat (i). The values of xi and vi updates when the iterations proceed further, while for the calculation of new solutions, let's say x t i and velocities v t i at step t we can use (38) and (39) respectively. = + ( − ) (37)…”

“…Where β in (37) represents a random vector determined from a uniform distribution of the range [0,1]. In (38), x * has been calculated as the current best global solution among all the possible solutions available in the Bat population n [31]. The velocity increment has been represented as ki or fi, and both can be used to adjust the change in velocity at the time of fixation of other factor ki or fi based on the type of problem.…”

Cool Roof Impact on Building Energy Need: The Role of Thermal Insulation with Varying Climate Conditions

“…Optimization techniques are getting more popular for designing and evaluating renewable and sustainable building and energy systems [44]. In a considerable number of studies in the area of smart and sustainable buildings, both single-objective and multi-objective optimization methods have been used for optimization of buildings envelopes [45][46][47]. In this paper, the generic optimization software GenOpt v3.1.1 (Lawrence Berkeley National Laboratory, CA, USA) [36] was used for single-objective optimization.…”

A GRASP Meta-Heuristic for Evaluating the Latency and Lifetime Impact of Critical Nodes in Large Wireless Sensor Networks

“…Smart cities [2,3], smart buildings [4], health-care systems [5], industrial production, and many more fields are taking advantage of the data collection easiness that modern WSN offer to behave more efficiently. By collecting environmental data, smart buildings, for instance, can improve light and temperature control systems to save energy when possible, or even automate building actions by gathering people's movements in order to increase their comfort [6].…”