1,593 research outputs found

    A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments

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    In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing the energy optimization problem. The goal of each technique was to maintain a balance between user comfort and energy requirements such that the user can achieve the desired comfort level with the minimum amount of energy consumption. Researchers have addressed the issue with the help of different optimization algorithms and variations in the parameters to reduce energy consumption. To the best of our knowledge, this problem is not solved yet due to its challenging nature. The gap in the literature is due to the advancements in the technology and drawbacks of the optimization algorithms and the introduction of different new optimization algorithms. Further, many newly proposed optimization algorithms which have produced better accuracy on the benchmark instances but have not been applied yet for the optimization of energy consumption in smart homes. In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes. The detailed discussion has been carried out on different factors contributing towards thermal comfort, visual comfort, and air quality comfort. We have also reviewed the fog and edge computing techniques used in smart homes

    Personalized Ambience: An Integration of Learning Model and Intelligent Lighting Control

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    The number of households and offices adopting automation system is on the rise. Although devices and actuators can be controlled through wireless transmission, they are mostly static with preset schedules, or at different times it requires human intervention. This paper presents a smart ambience system that analyzes the user’s lighting habits, taking into account different environmental context variables and user needs in order to automatically learn about the user’s preferences and automate the room ambience dynamically. Context information is obtained from Yahoo Weather and environmental data pertaining to the room is collected via Cubesensors to study the user’s lighting habits. We employs a learning model known as the Reduced Error Prune Tree (REPTree) to analyze the users’ preferences, and subsequently predicts the preferred lighting condition to be actuated in real time through Philips Hue. The system is able to ensure the user’s comfort at all time by performing a closed feedback control loop which checks and maintains a suitable lighting ambience at optimal level

    Demand Response Strategy Based on Reinforcement Learning and Fuzzy Reasoning for Home Energy Management

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    As energy demand continues to increase, demand response (DR) programs in the electricity distribution grid are gaining momentum and their adoption is set to grow gradually over the years ahead. Demand response schemes seek to incentivise consumers to use green energy and reduce their electricity usage during peak periods which helps support grid balancing of supply-demand and generate revenue by selling surplus of energy back to the grid. This paper proposes an effective energy management system for residential demand response using Reinforcement Learning (RL) and Fuzzy Reasoning (FR). RL is considered as a model-free control strategy which learns from the interaction with its environment by performing actions and evaluating the results. The proposed algorithm considers human preference by directly integrating user feedback into its control logic using fuzzy reasoning as reward functions. Q-learning, a RL strategy based on a reward mechanism, is used to make optimal decisions to schedule the operation of smart home appliances by shifting controllable appliances from peak periods, when electricity prices are high, to off-peak hours, when electricity prices are lower without affecting the customer’s preferences. The proposed approach works with a single agent to control 14 household appliances and uses a reduced number of state-action pairs and fuzzy logic for rewards functions to evaluate an action taken for a certain state. The simulation results show that the proposed appliances scheduling approach can smooth the power consumption profile and minimise the electricity cost while considering user’s preferences, user’s feedbacks on each action taken and his/her preference settings. A user-interface is developed in MATLAB/Simulink for the Home Energy Management System (HEMS) to demonstrate the proposed DR scheme. The simulation tool includes features such as smart appliances, electricity pricing signals, smart meters, solar photovoltaic generation, battery energy storage, electric vehicle and grid supply.Peer reviewe

    Functions of fuzzy logic based controllers used in smart building

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    The main aim of this study is to support design and development processes of advanced fuzzy-logic-based controller for smart buildings e.g., heating, ventilation and air conditioning, heating, ventilation and air conditioning (HVAC) and indoor lighting control systems. Moreover, the proposed methodology can be used to assess systems energy and environmental performances, also compare energy usages of fuzzy control systems with the performances of conventional on/off and proportional integral derivative controller (PID). The main objective and purpose of using fuzzy-logic-based model and control is to precisely control indoor thermal comfort e.g., temperature, humidity, air quality, air velocity, thermal comfort, and energy balance. Moreover, this article present and highlight mathematical models of indoor temperature and humidity transfer matrix, uncertainties of users’ comfort preference set-points and a fuzzy algorithm

    Entrepreneurship Through Start-ups in Hill Areas Using Photovoltaic Systems

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    There is large potential for generating solar power in Uttarakhand (India) endowed with natural resources. The extensive use of solar energy through solar PV panels in Distributed and Renewable Electricity Generation is significant to utilize multi climatic zones of hilly areas. In this regard, UREDA (Uttarakhand Renewable Energy Development Agency) targets to achieve a huge boost of solar PV battery backup with approved subsidy budget of INR 6 billion to 50 billion by 2019/20 under JNNSM (Jawaharlal Nehru National Solar Mission). This investment will increase productivity, enhance employment opportunities and improve quality of education. However, maximization of power output from panels used for same is achieved through use of MPPT (Maximum Power Point Trackers). The commercially installed solar power systems can be made to accomplish higher efficiency by implementing MPPT systems in start ups. In this paper, the effort is made to use MPPT system designed by intelligent controller for implementation in PV based utility systems. The regulated voltage output from MPPT system is obtained irrespective of fluctuations in environment. These variations are tested for changing temperature and irradiance due to shading or partial unavailability of sun. The results of same have been optimized through MATLAB/SIMULINK. The model designed is intended to be a beneficial source for PV engineers and researchers to provide high efficiency with the use of MPPT

    Entrepreneurship Through Start-ups in Hill Areas Using Photovoltaic Systems

    Get PDF
    There is large potential for generating solar power in Uttarakhand (India) endowed with natural resources. The extensive use of solar energy through solar PV panels in Distributed and Renewable Electricity Generation is significant to utilize multi climatic zones of hilly areas. In this regard, UREDA (Uttarakhand Renewable Energy Development Agency) targets to achieve a huge boost of solar PV battery backup with approved subsidy budget of INR 6 billion to 50 billion by 2019/20 under JNNSM (Jawaharlal Nehru National Solar Mission). This investment will increase productivity, enhance employment opportunities and improve quality of education. However, maximization of power output from panels used for same is achieved through use of MPPT (Maximum Power Point Trackers). The commercially installed solar power systems can be made to accomplish higher efficiency by implementing MPPT systems in start ups. In this paper, the effort is made to use MPPT system designed by intelligent controller for implementation in PV based utility systems. The regulated voltage output from MPPT system is obtained irrespective of fluctuations in environment. These variations are tested for changing temperature and irradiance due to shading or partial unavailability of sun. The results of same have been optimized through MATLAB/SIMULINK. The model designed is intended to be a beneficial source for PV engineers and researchers to provide high efficiency with the use of MPPT

    Günəş panellərindən əldə edilən elektrik enerjisinin qeyri-səlis məntiq ilə idarə edilməsi və ağıllı ev sistemlərində tətbiqi.

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    In this thesis, application of Fuzzy Logic controller to the building energy management system using solar power system energy as a renewable energy source has been put into practice in smart home automation buildings. Solar panels with 2 photovoltaic system with 150 Watt force value and 2 accumulators with 12 V 200 Ah values were used in this hybride power system. The aim of this study is to provide the created system both work autonomous and grid connected. According to this purpose, including the grid connection failure providing energy permanence on managed loads is aimed. This process done by Fuzzy logic controllable building energy managament system. Energy which is produced by hybrid system, firstly charges accumulators and then is transfered to grid or loads. If the hybrid system doesn’t produce energy and batteries are empty, continuity of autonomous loads are compensated from city grid. Additionally before the connecting to the city grid, the controller can analyze home distribution system for supply to the life safety and most importance loads such as , fire alarm control system, access door system, wifi network and extar low voltage power supply. The most important factor here is to ensure the stability of the energy supply of important loads. Second issueis that, energy saving by opening unnecessary loads and also reducing unnecessary energy consumption in smart home systems through specially applied lighting, brightness, movement and precense sensors has been studied

    An Adaptive Intelligent Integrated Lighting Control Approach for High-Performance Office Buildings

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    abstract: An acute and crucial societal problem is the energy consumed in existing commercial buildings. There are 1.5 million commercial buildings in the U.S. with only about 3% being built each year. Hence, existing buildings need to be properly operated and maintained for several decades. Application of integrated centralized control systems in buildings could lead to more than 50% energy savings. This research work demonstrates an innovative adaptive integrated lighting control approach which could achieve significant energy savings and increase indoor comfort in high performance office buildings. In the first phase of the study, a predictive algorithm was developed and validated through experiments in an actual test room. The objective was to regulate daylight on a specified work plane by controlling the blind slat angles. Furthermore, a sensor-based integrated adaptive lighting controller was designed in Simulink which included an innovative sensor optimization approach based on genetic algorithm to minimize the number of sensors and efficiently place them in the office. The controller was designed based on simple integral controllers. The objective of developed control algorithm was to improve the illuminance situation in the office through controlling the daylight and electrical lighting. To evaluate the performance of the system, the controller was applied on experimental office model in Lee et al.’s research study in 1998. The result of the developed control approach indicate a significantly improvement in lighting situation and 1-23% and 50-78% monthly electrical energy savings in the office model, compared to two static strategies when the blinds were left open and closed during the whole year respectively.Dissertation/ThesisDoctoral Dissertation Architecture 201
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