scholarly journals Home Energy Monitoring System Towards Smart Control of Energy Consumption

2019 ◽  
pp. 40-53 ◽  
Author(s):  
Zakariae Jebroni ◽  
Jose A. Afonso ◽  
Belkassem Tidhaf
Keyword(s):  
Energy Consumption ◽  
Monitoring System ◽  
Energy Monitoring ◽  
Smart Control

scholarly journals Energy Monitoring System for Existing Buildings in Indonesia

2018 ◽  
Vol 42 ◽  
pp. 01003
Author(s):  
Sentagi Sesotya Utami ◽  
Faridah ◽  
Na’im A. Azizi ◽  
Erlin Kencanawati ◽  
M. Akbar Tanjung ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Monitoring System ◽  
Local Governments ◽  
Energy Savings ◽  
Performance Testing ◽  
Cost Effective ◽  
Existing Buildings ◽  
Energy Monitoring ◽  
Building Permit ◽  
Significant Difference

Current studies conducted by JICA, AMPRI and IFC-World Bank, reported that large commercial buildings in Indonesia are not energy and water efficient. One of the cause is the lack of regulation. Meanwhile, effective regulations to reduce energy and water consumption are the concern mostly in a new building to obtain a building permit. This strategy is understandable as retrofitting existing buildings are often more difficult to be implemented, and enforcement is still a major issue in Indonesia. Local governments are currently working on streamlining building permit process as well as developing an online monitoring system for existing buildings. By applying a Building Energy Management System (BEMS) enables to reduce energy consumption up to 15%. An energy monitoring system was designed and installed through this research for Department of Nuclear Engineering and Engineering Physics (DNEEP) building, Faculty of Engineering, Universitas Gadjah Mada. It is a 20 years old two-story building used for educational activities, which consist of classrooms, laboratories, offices and storage spaces. An audit energy was done recently in 2015 where an energy consumption of 261.299,636 kWh/year.m2 was reported. In the existing condition, a power meter is inaccessible and therefore, the only feedback of occupancy behavior in the energy consumption is through the electricity bill. The previous study has shown that building occupants would behave more efficiently if the amount of energy used is notified, and the amount of energy savings are recorded. However, these energy monitoring systems are considered expensive and uniquely tailored for every building. This research aims to design and install a cost effective BEMS based on occupant’s satisfactory assessment of the lighting, acoustics, and air conditioning quality. The data will be used as a decision supporting system (DSS) by building management through the use of a GUI. The design of the interface was based on a survey result from the prospective users. Installed energy monitoring system uses a current sensor with an accuracy of 98% and a precision of 0.04 A while the voltage sensor with an accuracy of 98% and a precision of 0.58 V. The performance testing shows that the number of web clients influences delay of data transmission. The result of the survey shows that GUI is categorized as fair in design without a significant difference between the perceptions of users with and without survey supervision.

scholarly journals The methodical issues of industrial energy monitoring systems implementation

2020 ◽  
pp. 47-56
Author(s):  
V. Nakhodov ◽  
O. Borychenko ◽  
A. Cherniavskyi
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Monitoring System ◽  
Energy Management ◽  
Specific Energy ◽  
Management System ◽  
Specific Energy Consumption ◽  
Monitoring Systems ◽  
Energy Management System ◽  
Energy Monitoring

Statistics show that energy is one of the highest operating costs in a manufacturing enterprise. So, improving energy efficiency can lead to a significant increase in profits and reduce the impact of the enterprise on the environment. To increase the performance of energy efficiency activities, it is necessary to implement an energy management system. One of the components of this system is energy monitoring, which, in turn, is based on the periodic collection and analysis of data to assess the state of the monitoring objects in terms of energy efficiency. In this paper, the role and place of energy monitoring in the energy management system of an industrial enterprise are noted. The paper proposes the concept of creating energy monitoring system in industrial companies, which is based on the combination of a monitoring system based on specific energy consumption, and usage of group energy characteristics of production facilities. Implementing such energy monitoring systems will allow to conduct operational control of energy efficiency of production facilities by creating individual systems for monitoring energy efficiency, as well as successfully carry out such monitoring at the enterprise and its subdivisions over longer periods of time using specific energy consumption indicators. It also provides general guidelines for conducting energy monitoring. These guidelines were formed based on the results of studying various methods and scientific publications in the field of energy monitoring, as well as on the basis of practical experience in the development and implementation of energy management systems. Particular attention is paid to the issues of processing and analysis of information about the objects of energy monitoring of industrial enterprises. The practical application of the concept of creating energy monitoring systems envisages gradual improvement of the existing monitoring system based on the specific energy consumption, which will be further completely replaced with individual energy efficiency monitoring systems.

Retrofitting for Energy Management

2021 ◽  
pp. 96-119
Author(s):  
Michael Christian Krutwig
Keyword(s):  
Energy Consumption ◽  
Monitoring System ◽  
Energy Management ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Cyber Physical Systems ◽  
Radio Networks ◽  
Energy Monitoring ◽  
Energy Management Systems ◽  
Measurement Infrastructure

According to ISO 50001, energy management systems are increasingly being implemented in companies, with the continuous measurement of energy consumption playing an important role. At the same time, energy meters are increasingly becoming cyber-physical systems (CPS) in the IoT age. LPWAN radio networks and IoT clouds open up new possibilities for retrofitting meters and industrial components. By using these technologies, the measurement infrastructure of an energy monitoring system can be cost-effectively expanded. This section presents the technologies relevant for energy management and shows their application using selected use cases for LoRaWAN, OPC UA, and the combination of optical character recognition (OCR) and IoT Cloud.

Retrofitting for Energy Management

2019 ◽  
pp. 196-218
Author(s):  
Michael Christian Krutwig
Keyword(s):  
Energy Consumption ◽  
Monitoring System ◽  
Energy Management ◽  
Character Recognition ◽  
Optical Character Recognition ◽  
Cyber Physical Systems ◽  
Radio Networks ◽  
Energy Monitoring ◽  
Energy Management Systems ◽  
Measurement Infrastructure

According to ISO 50001, energy management systems are increasingly being implemented in companies, with the continuous measurement of energy consumption playing an important role. At the same time, energy meters are increasingly becoming cyber-physical systems (CPS) in the IoT age. LPWAN radio networks and IoT clouds open up new possibilities for retrofitting meters and industrial components. By using these technologies, the measurement infrastructure of an energy monitoring system can be cost-effectively expanded. This section presents the technologies relevant for energy management and shows their application using selected use cases for LoRaWAN, OPC UA, and the combination of optical character recognition (OCR) and IoT Cloud.

Applying Research on Campus Energy-Saving Power Monitoring System

2014 ◽  
Vol 672-674 ◽  
pp. 499-502
Author(s):  
Li Ming Wei ◽  
Peng Xu
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Monitoring System ◽  
Specific Energy ◽  
Specific Energy Consumption ◽  
Energy Monitoring ◽  
Power Monitoring ◽  
The North ◽  
Key Technologies ◽  
Campus Energy

Campus energy consumption takes up a large proportion of the total expenses of the campus. At the same time power consumption is emphasis. In the paper design of campus energy monitoring system and key technologies are demonstrated. The above-mentioned scheme is applied in a university in the north of China. The energy-saving measures are studied combined with the characteristics of the specific energy consumption.

Smart Plant Growth Control and Monitoring System for Indoor Hydroponic Farming

2019 ◽  
Vol 1 (2) ◽  
Author(s):  
Fina Supegina
Keyword(s):  
Water Level ◽  
Monitoring System ◽  
Growth Control ◽  
Set Point ◽  
Water Solvent ◽  
Growth Room ◽  
Smart Control ◽  
Level Sensor ◽  
Planting Method ◽  
Hydroponic Growth

Hydroponics is one of planting method that use water as a medium of plants growth, in this technique, mineral solution added into the water solvent, allowing the nutrient uptake process by the plants.  Farming by hydroponic method must pay attention to the following parameters namely, temperature, humidity, the level of water needs and nutrients and also the level of sunlight need for photosynthesis process.  This research used hydroponic technique in hydroponic growth room, and  there is a LED growth light as an alternate of sunlight, due to this room is closed without sunlight.  There are outputs displayed in monitoring system namely, temperature sensor, humidity sensor, ultrasound sensor to detect height of the plant and water level sensor to measured height of the water as a medium of the plant.  Results of measured sensor in hydroponic growth room explained as the following:  fan cooler worked when temperature , and humidity  .  Water pump worked when water level is less than 50% accordance set point.  Control on LED Growth Light and LED Bulb when LDR sensor reached set point > 500 in bright condition, and < 500 in dark condition respectively. The average of Time update/received data in thing speak web is 2.4 second. Keywords: Smart Control, Hydroponic, IoT, Monitoring

A Critical Study on Campus Energy Monitoring System and Role of IoT

2021 ◽  
Author(s):  
Mopuri Deepika ◽  
Merugu Kavitha ◽  
N. S. Kalyan Chakravarthy ◽  
J. Srinivas Rao ◽  
D. Mohan Reddy ◽  
...  
Keyword(s):  
Monitoring System ◽  
Critical Study ◽  
Energy Monitoring ◽  
Campus Energy

Semi-supervised Intrusive Appliance Load Monitoring in Smart Energy Monitoring System

2021 ◽  
Vol 17 (3) ◽  
pp. 1-20
Author(s):  
Vanh Khuyen Nguyen ◽  
Wei Emma Zhang ◽  
Adnan Mahmood
Keyword(s):  
Supervised Learning ◽  
Monitoring System ◽  
End Users ◽  
Training Data ◽  
Smart Device ◽  
Energy Monitoring ◽  
Load Monitoring ◽  
Benchmark Datasets ◽  
Smart Home Environment ◽  
Smart Appliance

Intrusive Load Monitoring (ILM) is a method to measure and collect the energy consumption data of individual appliances via smart plugs or smart sockets. A major challenge of ILM is automatic appliance identification, in which the system is able to determine automatically a label of the active appliance connected to the smart device. Existing ILM techniques depend on labels input by end-users and are usually under the supervised learning scheme. However, in reality, end-users labeling is laboriously rendering insufficient training data to fit the supervised learning models. In this work, we propose a semi-supervised learning (SSL) method that leverages rich signals from the unlabeled dataset and jointly learns the classification loss for the labeled dataset and the consistency training loss for unlabeled dataset. The samples fit into consistency learning are generated by a transformation that is built upon weighted versions of DTW Barycenter Averaging algorithm. The work is inspired by two recent advanced works in SSL in computer vision and combines the advantages of the two. We evaluate our method on the dataset collected from our developed Internet-of-Things based energy monitoring system in a smart home environment. We also examine the method’s performances on 10 benchmark datasets. As a result, the proposed method outperforms other methods on our smart appliance datasets and most of the benchmarks datasets, while it shows competitive results on the rest datasets.

Sign in / Sign up

Export Citation Format

Share Document