scholarly journals An Occupancy Based Cyber-Physical System Design for Intelligent Building Automation

2015 ◽  
Vol 2015 ◽  
pp. 1-15 ◽  
Author(s):  
Kottarathil Eashy Mary Reena ◽  
Abraham Theckethil Mathew ◽  
Lillykutty Jacob
Keyword(s):  
Energy Consumption ◽  
Physical System ◽  
Wireless Channel ◽  
Sensor Nodes ◽  
Automation System ◽  
Cyber Physical System ◽  
Building Automation ◽  
Total Energy Consumption ◽  
Intelligent Building ◽  
Nsga Ii

Cyber-physical system (CPS) includes the class of Intelligent Building Automation System (IBAS) which increasingly utilizes advanced technologies for long term stability, economy, longevity, and user comfort. However, there are diverse issues associated with wireless interconnection of the sensors, controllers, and power consuming physical end devices. In this paper, a novel architecture of CPS for wireless networked IBAS with priority-based access mechanism is proposed for zones in a large building with dynamically varying occupancy. Priority status of zones based on occupancy is determined using fuzzy inference engine. Nondominated Sorting Genetic Algorithm-II (NSGA-II) is used to solve the optimization problem involving conflicting demands of minimizing total energy consumption and maximizing occupant comfort levels in building. An algorithm is proposed for power scheduling in sensor nodes to reduce their energy consumption. Wi-Fi with Elimination-Yield Nonpreemptive Multiple Access (EY-NPMA) scheme is used for assigning priority among nodes for wireless channel access. Controller design techniques are also proposed for ensuring the stability of the closed loop control of IBAS in the presence of packet dropouts due to unreliable network links.

scholarly journals Lighting Control Including Daylight and Energy Efficiency Improvements Analysis

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2166 ◽  
Author(s):  
Aniela Kaminska ◽  
Andrzej Ożadowicz
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Energy Savings ◽  
Residential Buildings ◽  
Experimental Tests ◽  
Experimental Results ◽  
Automation System ◽  
Building Automation ◽  
Total Energy Consumption ◽  
Lighting Control

Energy used for lighting is one of the major components of total energy consumption in buildings. Nowadays, buildings have a great potential to reduce their energy consumption, but to achieve this purpose additional efforts are indispensable. In this study, the need for energy savings evaluation before the implementation of lighting control algorithms for a specified building is highlighted. Therefore, experimental tests have been carried out in a university building with laboratories and other rooms, equipped with KNX building automation system. A dimmable control strategy has been investigated, dependent on daylight illuminance. Moreover, a relationship between external and internal daylight illuminance levels has been evaluated as well. Based on the experimental results, the authors proposed a method for the rough estimation of electrical energy savings. Since, according to the EN 15232 standard, Building Automation and Control Systems (BACS) play an important role in buildings’ energy efficiency improvements, the BACS efficiency factors from this standard have been used to verify the experimental results presented in the paper. The potential to reduce energy consumption from lighting in non-residential buildings by 28% for offices and 24% for educational buildings has been confirmed, but its dependence on specific building parameters has been discussed as well.

scholarly journals A Smart Home System based on Microcontroller using Android Application and MySQL Database

2020 ◽  
Vol 3 (1) ◽  
pp. 455-464
Author(s):  
Ömer Gül ◽  
Uğur Bayrak
Keyword(s):  
Energy Efficient ◽  
Smart Home ◽  
Smart Devices ◽  
Automation System ◽  
Building Automation ◽  
Android Application ◽  
Intelligent Building ◽  
Internet Connection ◽  
Remote Server ◽  
Building Automation System

In recent years, people may disremember to turn off various devices or not be sure open or closed. Predefined scenarios for these people, home comfort and efficiency in the workplace will help a lot. Most people spend time with mobile phones throughout the day. Therefore, the control of smart devices by phones would be an appropriate solution. In this study, it is designed with microcontroller based intelligent building automation system hardware and software to provide energy efficient, security and comfort. The programming of the microcontroller, writing the android application program for the mobile phone and MySQL database software were realized. Microcontroller with GSM shield, it is possible to control the devices connected to the system by an android application automatically and manually by means of the internet connection by the MySQL database on the remote server. It is ensured that all devices are adjusted with a single touch according to predefined scenarios.

scholarly journals A University Building Test Case for Occupancy-Based Building Automation

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3145 ◽  
Author(s):  
Siva Swaminathan ◽  
Ximan Wang ◽  
Bingyu Zhou ◽  
Simone Baldi
Keyword(s):  
Energy Consumption ◽  
Thermal Model ◽  
Current Control ◽  
Automation System ◽  
Test Case ◽  
Building Automation ◽  
Set Point ◽  
Low Level ◽  
Point Control ◽  
Set Point Control

Heating, ventilation and air-conditioning (HVAC) units in buildings form a system-of-subsystems entity that must be accurately integrated and controlled by the building automation system to ensure the occupants’ comfort with reduced energy consumption. As control of HVACs involves a standardized hierarchy of high-level set-point control and low-level Proportional-Integral-Derivative (PID) controls, there is a need for overcoming current control fragmentation without disrupting the standard hierarchy. In this work, we propose a model-based approach to achieve these goals. In particular: the set-point control is based on a predictive HVAC thermal model, and aims at optimizing thermal comfort with reduced energy consumption; the standard low-level PID controllers are auto-tuned based on simulations of the HVAC thermal model, and aims at good tracking of the set points. One benefit of such control structure is that the PID dynamics are included in the predictive optimization: in this way, we are able to account for tracking transients, which are particularly useful if the HVAC is switched on and off depending on occupancy patterns. Experimental and simulation validation via a three-room test case at the Delft University of Technology shows the potential for a high degree of comfort while also reducing energy consumption.

scholarly journals Development of a New Green Indicator and Its Implementation in a Cyber–Physical System for a Green Supply Chain

2020 ◽  
Vol 12 (20) ◽  
pp. 8629 ◽  
Author(s):  
Paula Morella ◽  
María Pilar Lambán ◽  
Jesús Royo ◽  
Juan Carlos Sánchez ◽  
Lisbeth del Carmen Ng Corrales
Keyword(s):  
Supply Chain ◽  
Energy Consumption ◽  
Real Time ◽  
Physical System ◽  
Machine Tools ◽  
Industry 4.0 ◽  
Performance Indicator ◽  
Green Supply Chain ◽  
Cyber Physical System ◽  
Key Performance Indicator

This work investigates Industry 4.0 technologies by developing a new key performance indicator that can determine the energy consumption of machine tools for a more sustainable supply chain. To achieve this, we integrated the machine tool indicator into a cyber–physical system for easy and real-time capturing of data. We also developed software that can turn these data into relevant information (using Python): Using this software, we were able to view machine tool activities and energy consumption in real time, which allowed us to determine the activities with greater energy burdens. As such, we were able to improve the application of Industry 4.0 in machine tools by allowing informed real-time decisions that can reduce energy consumption. In this research, a new Key Performance Indicator (KPI) was been developed and calculated in real time. This KPI can be monitored, can measure the sustainability of machining processes in a green supply chain (GSC) using Nakajima’s six big losses from the perspective of energy consumption, and is able to detect what the biggest energy loss is. This research was implemented in a cyber–physical system typical of Industry 4.0 to demonstrate its applicability in real processes. Other productivity KPIs were implemented in order to compare efficiency and sustainability, highlighting the importance of paying attention to both terms at the same time, given that the improvement of one does not imply the improvement of the other, as our results show.

scholarly journals Energy Consumption Analysis and Optimization of the Deep-Sea Self-Sustaining Profile Buoy

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2316 ◽  
Author(s):  
Mingcong Liu ◽  
Shaobo Yang ◽  
Hongyu Li ◽  
Jiayi Xu ◽  
Xingfei Li
Keyword(s):  
Energy Consumption ◽  
Optimization Model ◽  
Deep Sea ◽  
Kinematic Model ◽  
Control Mode ◽  
Total Energy Consumption ◽  
Nsga Ii ◽  
Energy Consumption Model ◽  
Energy Consumption Optimization ◽  
Static Energy

In order to reduce the energy consumption of deep-sea self-sustaining profile buoy (DSPB) and extend its running time, a stage quantitative oil draining control mode has been proposed in this paper. System parameters have been investigated including oil discharge resolution (ODR), judgment threshold of the floating speed and frequency of oil draining on the energy consumption of the system. The single-objective optimization model with the total energy consumption of DSPB’s ascent stage as the objective function has been established by combining the DSPB’s floating kinematic model. At the same time, as the static working current of the DSPB can be further optimized, a multi-objective energy consumption optimization model with the floating time and the energy consumption of the oil pump motor as objective functions has been established. The non-dominated sorted genetic algorithm-II (NSGA-II) has been employed to optimized the energy consumption model in the ascent stage of the DSPB. The results showed that the NSGA-II method has a good performance in the energy consumption optimization of the DSPB, and can reduce the dynamic energy consumption in the floating process by 28.9% within 2 h considering the increase in static energy consumption.

scholarly journals A Bi-Objective Approach to Minimize Makespan and Energy Consumption in Flow Shops with Peak Demand Constraint

2020 ◽  
Vol 12 (10) ◽  
pp. 4110
Author(s):  
Weiwei Cui ◽  
Biao Lu
Keyword(s):  
Energy Consumption ◽  
Production Scheduling ◽  
Pareto Frontier ◽  
Management Problem ◽  
Energy Aware ◽  
Total Energy Consumption ◽  
Peak Demand ◽  
Nsga Ii ◽  
Flow Shops ◽  
Demand Constraint

With the growing concern of energy shortage and environment pollution, the energy aware operation management problem has emerged as a hot topic in industrial engineering recently. An integrated model consisting of production scheduling, preventive maintenance (PM) planning, and energy controlling is established for the flow shops with the PM constraint and peak demand constraint. The machine’s on/off and the speed level selection are considered to save the energy consumption in this problem. To minimize the makespan and the total energy consumption simultaneously, a multi-objective algorithm founded on NSGA-II is designed to solve the model effectively. The key decision variables are coded into the chromosome, while the others are obtained heuristically using the proposed decoding method when evaluating the chromosome. Numerical experiments were conducted to validate the effectiveness and efficiency by comparing the proposed algorithm and the traditional rules in manufacturing plant. The impacts of constraints on the Pareto frontier are also shown when analyzing the tradeoff between two objectives, which can be used to explicitly assess the energy consumption.

scholarly journals A Bi-Objective Vehicle-Routing Problem with Soft Time Windows and Multiple Depots to Minimize the Total Energy Consumption and Customer Dissatisfaction

2018 ◽  
Vol 10 (11) ◽  
pp. 4257 ◽  
Author(s):  
Shijin Wang ◽  
Xiaodong Wang ◽  
Xin Liu ◽  
Jianbo Yu
Keyword(s):  
Energy Consumption ◽  
Vehicle Routing Problem ◽  
Time Windows ◽  
Total Energy Consumption ◽  
Nsga Ii ◽  
Routing Problem ◽  
Soft Time Windows ◽  
Multiple Depots ◽  
Customer Dissatisfaction ◽  
Constraint Method

In recent years, the impact of the energy crisis and environment pollution on quality of life has forced industry to actively participate in the development of a sustainable society. Simultaneously, customer satisfaction improvement has always been a goal of businesses. It is recognized that efficient technologies and advanced methods can help transportation companies find a better balance between progress in energy saving and customer satisfaction. This paper investigates a bi-objective vehicle-routing problem with soft time windows and multiple depots, which aims to simultaneously minimize total energy consumption and customer dissatisfaction. To address the problem, we first develop mixed-integer programming. Then, an augmented ϵ -constraint method is adopted to obtain the optimal Pareto front for small problems. It is very time consuming for the augmented ϵ -constraint method to precisely solve even medium-sized problems. For medium- and large-sized problems, two Non-dominated Sorting Genetic Algorithm-II (NSGA-II)-based heuristics with different rules for generating initial solutions and offspring are designed. The performance of the proposed methods is evaluated by 100 randomly generated instances. Computational results show that the second NSGA-II-based heuristic is highly effective in finding approximate non-dominated solutions for small-size and medium-size instances, and the first one is performs better for the large-size instances.

scholarly journals Multi-Objective Casting Production Scheduling Problem by a Neighborhood Structure Enhanced Discrete NSGA-II: An Application from Real-World Workshop

2021 ◽  
Author(s):  
Weihua Tan ◽  
Xiaofang Yuan ◽  
Yuhui Yang ◽  
Lianghong Wu
Keyword(s):  
Energy Consumption ◽  
Real World ◽  
Production Scheduling ◽  
Scheduling Problem ◽  
Neighborhood Structure ◽  
Total Energy Consumption ◽  
Nsga Ii ◽  
Research Attention ◽  
Multi Objective ◽  
Casting Production

Abstract Casting production scheduling problem (CPSP) has attracted increasing research attention in recent years to facilitate the profits, efficiency, and environment issues of casting industry. Casting is often characterized by the properties of intensive energy consumption and complex process routes, which motivate the in-depth investigation on construction of practical multi-objective scheduling models and development of effective algorithms. In this paper, for the first time, the multi-objective casting production scheduling problem (MOCPSP) is constructed to simultaneously minimize objectives of defective rate, makespan, and total energy consumption. Moreover, a neighborhood structure enhanced discrete NSGA-II (N-NSGA-II) is designed to better cope with the proposed MOCPSP. In the N-NSGA-II, the advantage of selection mechanism of NSGA-II is fully utilized for selecting non-dominate solution, three neighborhood structures are elaborately designed to strengthen the ability of the local search, and a novel solution generating approach is proposed to increase the diversity of solutions for global search. Finally, a real-world case is illustrated to evaluate the performance of the N-NSGA-II. Computational results show that the proposed N-NSGA-II obtains a wider range of non-dominated solutions with better quality compared to other well-known multi-objective algorithms.

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