scholarly journals Simulation Based Energy Control and Comfort Management in Buildings Using Multi-Objective Optimization Routine

2020 ◽  
Vol 5 (6) ◽  
pp. 1324-1332
Author(s):  
V. S. K. V. Harish ◽  
Arun Kumar
Keyword(s):  
Energy Consumption ◽  
Hybrid Genetic Algorithm ◽  
Building Energy ◽  
Comfort Level ◽  
Large Set ◽  
Multi Objective Optimization ◽  
Energy Control ◽  
Multi Objective ◽  
Automation Systems ◽  
Optimization Routine

Building energy management systems with high-level of sophistication have to control and manage a large set of actuators and other equipment and evaluate performance of each and every-subsystem on periodic basis. In the present study, a control algorithm has been developed as an engineered solution for intelligent energy control and comfort management in buildings. A hybrid genetic algorithm - particle swarm optimization based multi-objective optimization routine is developed to compute the optimal set-point level of heating, ventilation, and air conditioning and lighting systems with a view to balancing energy consumption and occupants' comfort. Occupants' comfort is evaluated for indoor air quality as CO2 concentration, thermal and visual comfort. Case studies with a different set of optimal parameters have been worked out to calculate the amount of energy consumed as well as comfort level achieved. Overall occupants' comfort was improved by 17% and daily, weekly and monthly building energy consumption was reduced by 2.5%, 7.7%, and 17.9%, respectively. The developed intelligent control strategy can be integrated with building automation systems to achieve finely tuned real-time optimized comfort management

Methodology for Preliminary Design of Buildings Using Multi-Objective Optimization Based on Performance Simulation

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Bruno Ramos Zemero ◽  
Maria Emília de Lima Tostes ◽  
Ubiratan Holanda Bezerra ◽  
Vitor dos Santos Batista ◽  
Carminda Célia M. M. Carvalho
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Optimization Model ◽  
Building Design ◽  
Building Energy ◽  
Design Guidelines ◽  
Building Envelope ◽  
Design Stage ◽  
Multi Objective Optimization ◽  
Multi Objective

Buildings' energy consumption has a great energetic and environmental impact worldwide. The architectural design has great potential to solve this problem because the building envelope exerts influence on the overall system performance, but this is a task that involves many objectives and constraints. In the last two decades, optimization studies applied to energy efficiency of buildings have helped specialists to choose the best design options. However, there is still a lack of optimization approaches applied to the design stage, which is the most influential stage for building energy efficiency over its entire life cycle. Therefore, this article presents a multi-objective optimization model to assist designers in the schematic building design, by means of the Pareto archived evolutionary strategies (PAES) algorithm with the EnergyPlus simulator coupled to evaluate the solutions. The search process is executed by a binary array where the array components evolve over the generations, together with the other building components. The methodology aims to find optimal solutions (OSs) with the lowest constructive cost associated with greater energy efficiency. In the case study, it was possible to simulate the process of using the optimization model and analyze the results in relation to: a standard building; energy consumption classification levels; passive design guidelines; usability and accuracy, proving that the tool serves as support in building design. The OSs reached an average of 50% energy savings over typical consumption, 50% reduction in CO2 operating emissions, and investment return less than 3 years in the four different weathers.

Virtual Machines Scheduling Algorithm Based on Multi-Objective Optimization in Cloud Computing

2014 ◽  
Vol 1046 ◽  
pp. 508-511
Author(s):  
Jian Rong Zhu ◽  
Yi Zhuang ◽  
Jing Li ◽  
Wei Zhu
Keyword(s):  
Cloud Computing ◽  
Energy Consumption ◽  
Virtual Machine ◽  
Virtual Machines ◽  
Scheduling Algorithm ◽  
Machine Scheduling ◽  
Multi Objective Optimization ◽  
Multi Objective ◽  
Virtual Machine Scheduling ◽  
Set Up

How to reduce energy consumption while improving utility of datacenter is one of the key technologies in the cloud computing environment. In this paper, we use energy consumption and utility of data center as objective functions to set up a virtual machine scheduling model based on multi-objective optimization VMSA-MOP, and design a virtual machine scheduling algorithm based on NSGA-2 to solve the model. Experimental results show that compared with other virtual machine scheduling algorithms, our algorithm can obtain relatively optimal scheduling results.

scholarly journals Application of Urban Scale Energy Modelling and Multi-Objective Optimization Techniques for Building Energy Renovation at District Scale

2021 ◽  
Vol 13 (20) ◽  
pp. 11554
Author(s):  
Fahad Haneef ◽  
Giovanni Pernigotto ◽  
Andrea Gasparella ◽  
Jérôme Henri Kämpf
Keyword(s):  
Energy Efficiency ◽  
Building Energy ◽  
Energy Performance ◽  
Building Envelope ◽  
Optimization Techniques ◽  
Multi Objective Optimization ◽  
Building Stock ◽  
Energy Efficiency Measures ◽  
Multi Objective ◽  
Efficiency Measures

Nearly-zero energy buildings are now a standard for new constructions. However, the real challenge for a decarbonized society relies in the renovation of the existing building stock, selecting energy efficiency measures considering not only the energy performance but also the economic and sustainability ones. Even if the literature is full of examples coupling building energy simulation with multi-objective optimization for the identification of the best measures, the adoption of such approaches is still limited for district and urban scale simulation, often because of lack of complete data inputs and high computational requirements. In this research, a new methodology is proposed, combining the detailed geometric characterization of urban simulation tools with the simplification provided by “building archetype” modeling, in order to ensure the development of robust models for the multi-objective optimization of retrofit interventions at district scale. Using CitySim as an urban scale energy modeling tool, a residential district built in the 1990s in Bolzano, Italy, was studied. Different sets of renovation measures for the building envelope and three objectives —i.e., energy, economic and sustainability performances, were compared. Despite energy savings from 29 to 46%, energy efficiency measures applied just to the building envelope were found insufficient to meet the carbon neutrality goals without interventions to the system, in particular considering mechanical ventilation with heat recovery. Furthermore, public subsidization has been revealed to be necessary, since none of the proposed measures is able to pay back the initial investment for this case study.

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