Big Data for SMART Sensor and Intelligent Electronic Devices – Building Application

Zand, Mohammad; Nasab, Morteza Azimi; Padmanaban, Sanjeevikumar; Khoobani, Mohammad

doi:10.1201/9781003201069-2

Cited by 8 publications

(5 citation statements)

References 0 publications

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“…Among the benefits of integrating MGs into power systems are enhanced economic and environmental benefits, as well as improved dependability of traditional power systems. The utilization of renewable energy sources in MGs can mitigate global warming and boost the viability of power industry entry in designated areas [3].…”

Section: Literature Review and Research Gapmentioning

confidence: 99%

Providing an Intelligent Frequency Control Method in a Microgrid Network in the Presence of Electric Vehicles

Alizadeh,

Tightiz,

Azimi Nasab

2024

WEVJ

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Due to the reduction in fossil fuel abundance and the harmful environmental effects of burning them, the renewable resource potentials of microgrid (MG) structures have become highly highly. However, the uncertainty and variability of MGs leads to system frequency deviations in islanded or stand-alone mode. Usually, battery energy storage systems (BESSs) reduce this frequency deviation, despite limitations such as reducing efficiency in the long term and increasing expenses. A suitable solution is to use electric vehicles (EVs) besides BESSs in systems with different energy sources in the microgrid structure. In this field, due to the fast charging and discharging of EVs and the fluctuating character of renewable energy sources, controllers based on the traditional model cannot ensure the stability of MGs. For this purpose, in this research, an ultra-local model (ULM) controller with an extended state observer (ESO) for load frequency control (LFC) of a multi-microgrid (MMG) has been systematically developed. Specifically, a compensating controller based on the single-input interval type fuzzy logic controller (FLC) was used to remove the ESO error and improve the LFC performance. Since the performance of the ULM controller based on SIT2-FLC depends on specific parameters, all of these coefficients were adjusted by an improved harmony search algorithm (IHSA). Simulation and statistical analysis results show that the proposed controller performs well in reducing the frequency fluctuations and power of the system load line and offers a higher level of resistance than conventional controllers in different MG scenarios.

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Section: Literature Review and Research Gapmentioning

confidence: 99%

Providing an Intelligent Frequency Control Method in a Microgrid Network in the Presence of Electric Vehicles

Alizadeh,

Tightiz,

Azimi Nasab

2024

WEVJ

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“…Though the technology grows faster, smart building applications face new challenges compared to those faced previously. Apart from the above classifications, smart buildings can be broadly divided into three systems associated with management solutions: (a) The information system gathers data from different devices and makes decisions [7], (b) the analysis system analyzes the set data to find insights for fault detection and diagnostics (FDD) and takes measurements to verify abilities [8], and (c) control systems connect and control the assets installed in the smart building, maintain the lighting systems, and manage ventilation, air-conditioning, and other related activities [9].…”

Section: Smart Environment By Integrating Smart Buildingmentioning

confidence: 99%

Analyzing and Managing Various Energy-Related Environmental Factors for Providing Personalized IoT Services for Smart Buildings in Smart Environment

Krishnan

Prabu

Loganathan³

et al. 2023

Sustainability

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More energy is consumed by domestic appliances all over the world. By reducing energy consumption, sustainability can be improved in domestic contexts. Several earlier approaches to this problem have provided a conceptual overview of green and smart buildings. This paper aims to provide a better solution for reducing energy consumption by identifying the fields of abnormal energy consumption. It creates a better environment-friendly smart building to adopt the various lifestyles of people. This paper’s main objective is to monitor and control the energy efficiency of smart buildings by integrating IoT sensors. This paper mainly analyzes various prime factors that can help to improve energy efficiency in smart buildings. Factors impacting energy consumption are analyzed, and outliers of energy consumption are predicted and optimized to save energy. Various parameters are derived from IoT devices to improve energy efficiency in lighting and HVAC controls, energy monitoring, building envelope and automation systems, and renewable energy. The parameters used in water, network convergence, and electrical and environmental monitoring are also used for improving energy efficiency. This paper uses various IoT devices for monitoring and generating data in and around a smart building and analyzes it by implementing an intelligent Information Communication Technology (ICT) model called the Dynamic Semantic Behavior Data Analysis (DSBDA) Model to analyze data concerning dynamic changes in the environment and user behavior to improve energy efficiency and provide better sustainable lifestyle-based smart buildings. From the analyzed output, the outliers of the power consumption and other abnormalities are identified and controlled manually or automatically to improve sustainability regarding energy use in smart buildings.

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“…Zand et al [9] divided the smart building work into two folds: artificial intelligence methods and classification mathematical models. The essential part of their work covers rules based on intelligent smart homes and challenges related to deployment to form a prototype using sensors and actuators.…”

Section: Intelligent Building In Context Of Big Datamentioning

confidence: 99%

Real-Time Approach for Smart Building Operations Prediction Using Rule-Based Complex Event Processing and SPARQL Query

KUMAR,

Chandra,

Agarwal

2023

Preprint

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Due to intelligent, adaptive nature towards various operations and their ability to provide maximum comfort to the occupants residing in them, smart buildings are becoming a pioneering area of research. Since these architectures leverage the Internet of Things (IoT), there is a need for monitoring different operations (Occupancy, Humidity, Temperature, CO2 , etc.) to provide sustainable comfort to the occupants. This paper proposes a novel approach for intelligent building operations monitoring using rule-based complex event processing and query-based approaches for dynamically monitoring the different operations. Siddhi is a complex event processing engine designed for handling multiple sources of event data in real time and processing it according to predefined rules using a decision tree. Since streaming data is dynamic in nature, to keep track of different operations, we have converted the IoT data into an RDF dataset. The RDF dataset is ingested to Apache Kafka for streaming purposes and for stored data we have used the GraphDB tool that extracts information with the help of SPARQL query. Consequently, the proposed approach is also evaluated by deploying the large number of events through the Siddhi CEP engine and how efficiently they are processed in terms of time. Apart from that, a risk estimation scenario is also designed to generate alerts for end users in case any of the smart building operations need immediate attention. The output is visualized and monitored for the end user through a tableau dashboard.

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Big Data for SMART Sensor and Intelligent Electronic Devices – Building Application

Cited by 8 publications

References 0 publications

Providing an Intelligent Frequency Control Method in a Microgrid Network in the Presence of Electric Vehicles

Providing an Intelligent Frequency Control Method in a Microgrid Network in the Presence of Electric Vehicles

Analyzing and Managing Various Energy-Related Environmental Factors for Providing Personalized IoT Services for Smart Buildings in Smart Environment

Real-Time Approach for Smart Building Operations Prediction Using Rule-Based Complex Event Processing and SPARQL Query

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