Intelligent multi-objective optimization for building energy and comfort management

An Embedded Platform for Testbed Implementation of Multi-Agent System in Building Energy Management System

“…The main objectives of the energy management systems [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26][27] are usually to minimize the energy cost and/or maximize user comfort. In addition to these two optimization objectives, the objective function of maximizing the energy usage from the local renewable energy source is also employed [28,29].…”

“…The MAS-based BEMS could be classified into three groups, i.e., based-on: the number of criteria to be optimized, the optimization algorithm, and the implementation platform. In the first group, they are divided into single-objective optimization [10][11][12][13][14][15][16][17] and multi-objectives optimization [18][19][20][21][22][23]. Based on the optimization algorithm, they are divided into the conventional-based optimization techniques [10,11,13,15,17,21,23] and the artificial intelligent (AI)-based optimization techniques [12,14,16,[18][19][20]22].…”

“…A system to predict the energy demand of the building using the Artificial Neural Network (ANN) is proposed in [5]. The ANN model is trained using the dataset of monthly historical energy consumption of the building.Due to the distributed components (sensors, actuators, generators, loads) of the HEMS/BEMS, an intelligent multi-agent system (MAS) is widely adopted [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23]. The MAS is a distributed control system where each agent works autonomously and coordinates with each other to achieve the global goal.…”

Demand side flexibility coordination in office buildings: A framework and case study application

“…Specifically, thermal comfort, indoor air quality (IAQ), comfort recovery periods, availability periods, comfort response systems, power demand, power demand reduction or increase and energy delivered or energy used during DSF episodes are all considered. Consideration of identified building performance characteristics is instrumental in balancing local demand and power grid support requirements (Shaikh et al, 2016). This is an improvement from the trend whereby DSF coordination frameworks emphasize power grid performance at the expense of building performance as evident in Rajeev and Ashok (2015), Abdisalaam et al (2012), and Puchegger (2015).…”

Model Calibration Methodology to Assess the Actual Lighting Conditions of a Road Infrastructure

“…These energy reduction approaches are aligned with the Lighting Europe's Strategy Roadmap 2025, focused on enhancing the lighting quality through LEDification, intelligent lighting systems, and human centric lighting based on a circular economy. Many studies have been dedicated to the study of indoor building lighting systems [6][7][8][9][10][11][12] to design energy saving measures. However, one of the main energy consumers is road lighting, representing around 1.3% of the global electricity use [2].…”