scholarly journals Computational Intelligence Technologies for Occupancy Estimation and Comfort Control in Buildings

Energies ◽  
2021 ◽  
Vol 14 (16) ◽  
pp. 4971
Author(s):  
Panagiotis Korkidis ◽  
Anastasios Dounis ◽  
Panagiotis Kofinas
Keyword(s):  
Energy Consumption ◽  
Stochastic Model ◽  
Probabilistic Approach ◽  
Co2 Concentration ◽  
Comfort Index ◽  
Modelling Framework ◽  
Occupancy Estimation ◽  
Control Framework ◽  
Continuous State ◽  
Uncertainty Parameters

This paper focuses on the development of a multi agent control system (MACS), combined with a stochastic based approach for occupancy estimation. The control framework aims to maintain the comfort levels of a building in high levels and reduce the overall energy consumption. Three independent agents, each dedicated to the thermal comfort, the visual comfort, and the indoor air quality, are deployed. A stochastic model describing the CO2 concentration has been studied, focused on the occupancy estimation problem. A probabilistic approach, as well as an evolutionary algorithm, are used to provide insights on the stochastic model. Moreover, in order to induce uncertainty, parameters are treated in a fuzzy modelling framework and the results on the occupancy estimation are investigated. In the control framework, to cope with the continuous state-action space, the three agents utilise Fuzzy Q-learning. Simulation results highlight the precision of parameter and occupancy estimation, as well as the high capabilities of the control framework, when taking into account the occupancy state, as energy consumption is reduced by 55.9%, while the overall comfort index is kept in high levels, with values close to one.

A stochastic model for daily subsurface CO2 concentration and related soil respiration

2008 ◽  
Vol 31 (7) ◽  
pp. 987-994 ◽  
Author(s):  
Edoardo Daly ◽  
A. Christopher Oishi ◽  
Amilcare Porporato ◽  
Gabriel G. Katul
Keyword(s):  
Soil Respiration ◽  
Stochastic Model ◽  
Co2 Concentration

scholarly journals Quantification of potential recruitment of large woody debris in mountain catchments considering the effects of vegetation on hydraulic and geotechnical bank erosion and shallow landslides

2018 ◽  
Vol 40 ◽  
pp. 02046 ◽  
Author(s):  
Eric Gasser ◽  
Andrew Simon ◽  
Paolo Perona ◽  
Luuk Dorren ◽  
Johannes Hübl ◽  
...  
Keyword(s):  
Woody Debris ◽  
Probabilistic Approach ◽  
Temporal Distribution ◽  
Bank Erosion ◽  
Shallow Landslides ◽  
Large Woody Debris ◽  
Correction Coefficient ◽  
Model Framework ◽  
Modelling Framework ◽  
Spatio Temporal

Large woody debris (LWD) exacerbates flood damages near civil structures and in urbanized areas and the awareness of LWD as a risk is becoming more and more relevant. The recruitment of “fresh” large woody debris has been documented to play a significant role of the total amount of wood transported during flood events in mountain catchments. Predominately, LWD recruitment due to hydraulic and geotechnical bank erosion and shallow landslides contribute to high volumes of wood during floods. Quantifying the effects of vegetation on channel and slope processes is extremely complex. This manuscript therefore presents the concepts that are being implemented in a new modelling framework that aims to improve the quantification of vegetation effects on LWD recruitment processes. One of the focuses of the model framework is the implementation of the effect of spatio-temporal distribution of root reinforcement in recruitment processes such as bank erosion and shallow landslides in mountain catchments. Further, spatio-temporal precipitation patterns will be considered using a probabilistic approach to account for the spatio-temporal precipitation variability to estimate a LWD recruitment correction coefficient. Preliminary results are herein presented and discussed in form of a case study in the Swiss Prealps.

scholarly journals A Novel Theoretical Probabilistic Model for Opportunistic Routing with Applications in Energy Consumption for WSNs

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8058
Author(s):  
Christian E. Galarza ◽  
Jonathan M. Palma ◽  
Cecilia F. Morais ◽  
Jaime Utria ◽  
Leonardo P. Carvalho ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Energy Consumption ◽  
Stochastic Model ◽  
Opportunistic Networks ◽  
Opportunistic Routing ◽  
Opportunistic Network ◽  
Expected Number ◽  
Successful Transmission ◽  
Network Parameters ◽  
Proposed Model

This paper proposes a new theoretical stochastic model based on an abstraction of the opportunistic model for opportunistic networks. The model is capable of systematically computing the network parameters, such as the number of possible routes, the probability of successful transmission, the expected number of broadcast transmissions, and the expected number of receptions. The usual theoretical stochastic model explored in the methodologies available in the literature is based on Markov chains, and the main novelty of this paper is the employment of a percolation stochastic model, whose main benefit is to obtain the network parameters directly. Additionally, the proposed approach is capable to deal with values of probability specified by bounded intervals or by a density function. The model is validated via Monte Carlo simulations, and a computational toolbox (R-packet) is provided to make the reproduction of the results presented in the paper easier. The technique is illustrated through a numerical example where the proposed model is applied to compute the energy consumption when transmitting a packet via an opportunistic network.

A Stochastic Model Predictive Control Framework for Stationary Battery Systems

2018 ◽  
Vol 33 (4) ◽  
pp. 4397-4406 ◽  
Author(s):  
Ranjeet Kumar ◽  
Michael J. Wenzel ◽  
Matthew J. Ellis ◽  
Mohammad N. ElBsat ◽  
Kirk H. Drees ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Stochastic Model ◽  
Predictive Control ◽  
Control Framework ◽  
Battery Systems ◽  
Stochastic Model Predictive Control

Discussion on the Design of Freezing Dehumidification-Based Radiant Air-Conditioning System

2012 ◽  
Vol 204-208 ◽  
pp. 4274-4279
Author(s):  
Chao Yi Tan ◽  
Han Qing Wang ◽  
Hui Zhu
Keyword(s):  
Energy Consumption ◽  
Air Conditioning ◽  
Design Method ◽  
Load Ratio ◽  
Design Parameters ◽  
Air Conditioning System ◽  
Comfort Index ◽  
Low Energy Consumption ◽  
The Mean ◽  
Approximation Calculation

For the purpose of realizing non-dewfall condition of the radiant panels, low energy consumption and nice comfort of the freezing dehumidification-based radiant air-conditioning system, the design temperature and humidity of the room were figured out according to the mean comfort index of human body during the design. And in order to lower the energy consumption, the necessity of the reasonable load allocation between the dehumidification unit and the radiant unit was discussed by means of the calculation with the quasi heat-humidity-ratio line. As a result, much more precise design parameters were acquired through the approximation calculation. And it was proven to be a good design method by applying these parameters to the design of the reading rooms of the library. In the design example of the reading room, the load ratio between the dehumidification unit and the radiant unit was 48 to 52, and the recirculation air flow rate of the dehumidification unit was not less than 36.8% of the total air rate of the room.

scholarly journals Projection of Carbon Dioxide (CO2) Emissions in Coming Decades in Indian Context

2012 ◽  
Vol 9 (1) ◽  
pp. 17-22
Author(s):  
I. Nawaz
Keyword(s):  
Energy Consumption ◽  
Population Growth ◽  
Energy Demand ◽  
Electricity Generation ◽  
Fossil Fuels ◽  
Co2 Concentration ◽  
Indian Context ◽  
Oil And Natural Gas ◽  
Per Capita ◽  
Carbon Dioxide Co2

Every observable movement involves energy. Hence, energy is obviously an important determinant in the development of a nation. To be specific, the standard of living is directly related to the per capita energy consumption in the region. The per capita energy consumption is mostly due to consumption of electricity. Therefore, electric power is one of the key factors in development of a country. The combined effect of population growth and increase in industrial, domestic and agricultural activities are inevitable and the basic reason for the increase in the worldwide energy demand. Particularly in the Indian context, the power demand is likely to increase by 7% per annum in the next few decades; assuming a GDP growth of 9%. The major resources of electricity generation are the conventional fossil fuels: coal, oil and natural gas. At present, 55% of electricity generated in India is from coal. However, use of coal for electricity generation results in increase of CO2 concentration in atmosphere. In this study, an attempt has been made to estimate the increase in CO2 emission on the basis of statistical analysis using the available data of power production and projected population growth.

scholarly journals Adaptive Path Following and Locomotion Optimization of Snake-Like Robot Controlled by the Central Pattern Generator

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Zhengcai Cao ◽  
Dong Zhang ◽  
Biao Hu ◽  
Jinguo Liu
Keyword(s):  
Energy Consumption ◽  
Central Pattern Generator ◽  
Optimization Algorithm ◽  
Path Following ◽  
Cuckoo Search ◽  
Optimization Method ◽  
Pattern Generator ◽  
Complex Environment ◽  
Efficiency Optimization ◽  
Control Framework

This work investigates locomotion efficiency optimization and adaptive path following of snake-like robots in a complex environment. To optimize the locomotion efficiency, it takes energy consumption and forward velocity into account to investigate the optimal locomotion parameters of snake-like robots controlled by a central pattern generator (CPG) controller. A cuckoo search (CS) algorithm is applied to optimize locomotion parameters of the robot for environments with variable fractions and obstacle distribution. An adaptive path following method is proposed to steer the snake-like robot forward and along a desired path. The efficiency and accuracy of the proposed path following method is researched. In addition, a control framework that includes a CPG network, a locomotion efficiency optimization algorithm, and an adaptive path following method is designed to control snake-like robots move in different environments. Simulation and experimental results are presented to illustrate the performance of the proposed locomotion optimization method and adaptive path following controller for snake-like robots in complexity terrains.

scholarly journals Occupant Comfort Management Based on Energy Optimization Using an Environment Prediction Model in Smart Homes

2019 ◽  
Vol 11 (4) ◽  
pp. 997 ◽  
Author(s):  
Wenquan Jin ◽  
Israr Ullah ◽  
Shabir Ahmad ◽  
Dohyeun Kim
Keyword(s):  
Energy Consumption ◽  
Power Consumption ◽  
Prediction Model ◽  
Optimization Model ◽  
Indoor Environment ◽  
Energy Optimization ◽  
Comfort Index ◽  
Optimal Power ◽  
Temperature And Humidity ◽  
Occupant Comfort

Occupant comfort management is an important feature of a smart home, which requires achieving a high occupant comfort level as well as minimum energy consumption. Based on a large amount of data, learning models enable us to predict factors of a mathematical model for deriving the optimal result without expensive experiments. Comfort management supports high-level comfort to the occupant in the individual indoor environment, using the optimal power consumption to run home appliances. In this paper, we propose occupant comfort management based on energy optimization, using an environment prediction model. The proposed energy optimization model provides optimal power consumption based on the proposed objective function, which requires temperature and comfort index data as the input parameters. For the input requirement, temperature prediction model and humidity prediction model are presented based on a recurrent neural network with a pre-collected dataset, including indoor and outdoor temperature and humidity sensing data. Using the predicted temperature and humidity data, the comfort index model derives the predicted mean vote value to be used in the energy optimization model with the predicted temperature data. The experimental results present an 8.43% reduction of the optimized power consumption compared to the actual power consumption using mean absolute percentage error to calculate. Moreover, the emulation of an indoor environment using optimal energy consumption presents as approximately similar to the actual data.

A Novel Coal Based Cogeneration System for Substitute Natural Gas and Power With CO2 Capture and Moderate Recycle of the Chemical Unconverted Gas

2013 ◽  
Author(s):  
Sheng Li ◽  
Hongguang Jin ◽  
Lin Gao
Keyword(s):  
Energy Consumption ◽  
Natural Gas ◽  
Energy Saving ◽  
Co2 Capture ◽  
Co2 Concentration ◽  
Low Energy ◽  
The Novel ◽  
Good Efficiency ◽  
Cogeneration System ◽  
Energy Penalty

Cogeneration of substitute natural gas (SNG) and power from coal efficiently and CO2 capture with low energy penalty during coal utilization are very important technical paths to clean coal technologies for China which is rich in coal but lack of natural gas resources. This paper integrates a novel coal based cogeneration system with CO2 capture for SNG and power, and presents the energetic and exergy analysis based on the thermodynamic formulas and the use of ASPEN PLUS 11.0. In the novel system, instead of separation from the gas before synthesis traditionally, CO2 will be removed from the unconverted gas after synthesis, whose concentration can reach as high as 55% before separation and is much higher than 30% in traditional SNG production system. And by moderate recycle instead of full recycle of chemical unconverted gas back into SNG synthesis, the sharp increase in energy consumption for SNG synthesis with conversion ratios will be avoided, and by using part of the chemical unconverted gas, power is cogenerated efficiently. Thermodynamic analysis shows that the benefit from both systematic integration and high CO2 concentration makes the system have good efficiency and low energy penalty for CO2 capture. The overall efficiency of the system ranges from 53%–62% at different recycle ratios. Compared to traditional single production systems (IGCC with CO2 capture for power, traditional SNG system for SNG production), the energy saving ratio (ESR) of the novel system is 16%–21%. And compared to IGCC and traditional SNG system, the energy saving benefit from cogeneration can even offset the energy consumption for CO2 separation and realize zero energy penalties for CO2 capture systematically. Sensitivity analysis hints that an optimized recycle ratio of unconverted gas and chemicals to power output ratio (CPOR) can maximize system performance and minimize the energy penalty for CO2 capture.

Sign in / Sign up

Export Citation Format

Share Document