Mechanical ventilation systems are commonly utilized in livestock housing to counter indoor pollution and control the indoor thermal environment. During their operation, the systems must be ...appropriately controlled according to the changes in the indoor/outdoor thermal environments (conventionally handled by the facility manager based on their experience). In this study, a 24 h optimal ventilation system control strategy was developed using weather forecasting data to control the temperature in livestock housing. A building energy system model for livestock housing was developed based on measurement data. The optimal control strategy was derived by conducting simulation analysis using the model and optimizing four control variables of the ventilation system. The developed optimal ventilation system control strategy showed better indoor air temperature maintenance performance (energy-saving performance (ESP) of 20.50%) compared to the conventional control method. Furthermore, the ESP achievement increased as the prediction performance of the weather forecasting data increased. The optimal ventilation fan control strategy developed in this study, an intelligent control method based on an energy model and weather forecasting data, is expected to be introduced as an advanced technology to the field of livestock housing wherein research on the development of such strategies in the operation stage is still insufficient.
•Optimal control of livestock mechanical ventilation systems via weather forecasting.•Proposed strategy demonstrates sufficient indoor temperature maintenance performance.•Proposed strategy exhibited high energy efficiency compared to conventional method.•Enhanced energy savings through accurate weather forecasts.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
•A thermal model for the dynamic analysis of an indoor fish farm was developed.•On-site measurements of indoor fish farm validated thermal model feasibility.•Activity factor of fish farms increases ...evaporative loss and relative humidity.•Air changes affect temperatures, relative humidity, and evaporative loss.•Model can be used for energy-consumption prediction and optimal environment control.
Since energy consumption in buildings relies primarily on their purpose as opposed to the type of occupants, relatively high energy is also consumed in the indoor fish farms where people do not live. In particular, energy consumption of indoor fish farms has been increasing for the high productivity and economic efficiency. Therefore, a feasibility study of dynamic thermal modeling development for indoor fish farms is critical to analyze energy consumption. In this study, an indoor fish farm thermal model was developed, and the feasibility of the model was analyzed using onsite indoor temperature, relative humidity, and water temperature data. Further, the major sensitive variables in model development and their effects were investigated. The errors between measured and predicted results obtained using the developed thermal model were within hourly acceptable limits, which means the developed thermal model was valid. The activity factor (AF) and air change per hour (ACH), which are the major sensitive variables, significantly affected thermal performance such as evaporation loss, indoor temperature, relative humidity and water temperature. The average indoor relative humidity increased by approximately 16% when AF increased from 0 to 2. The average evaporation loss of the fish farm increased by 20.9 kW to 49 kW when ACH was 10. Therefore, similar to an indoor fish farm, the effects of aeration, opening/closing of windows and doors must be considered for simulations during energy-model development and future improvements. The results suggest that the proposed thermal model for indoor fish farms can be used to develop an energy model and expanded to various fields for predicting energy consumption and optimal control.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Energy scarcity and environmental damage necessitates efficient design, which requires significant information from different sources. As decisions affecting energy performance are made at early ...stages based on minimal information, support tools for the energy-efficient design of buildings are necessary during this period. Energy efficiency is a critical initial planning stage factor when designing smart farms. This study developed early design tool using building performance simulation (BPS) model for indoor fish farms which was validated with on-site measurement data for 120 days. The average MBE and the Cv(RMSE) values of the BPS model satisfied the error rate within the hourly criteria ranges for the entire measurement period. Design parameters for an early design tool were determined through a Morris sensitivity analysis. An early design tool was developed using the MATLAB graphical user interface, facilitating the search for variables that increased energy efficiency and enabling energy consumption comparisons of different alternatives.
•Propose a method for utilizing building performance simulation in aquaculture building.•Validated the simulation results by comparison with on-site measurement data.•Selected early-stage design parameters for indoor fish farm using Morris sensitivity analysis.•Development of design tools for critical decisions from the early design stage.•Tool can be used to evaluate parametric and alternative designs suitable for the indoor fish farm.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Digital twins, an emerging technology, are widely used in various industries. It builds a virtual space by mirroring a physical space and performs different simulations to solve problems that are ...complicated or impossible to solve in the physical space. Livestock farming in agriculture is evolving rapidly with the introduction of various information and communication technologies for digital farming. However, only few studies have examined the digital twin in terms of HVAC systems directly related to productivity in livestock farming. Here, we propose a novel digital twin framework for livestock farming focusing on pig houses. Livestock farming is one of perspective areas where digital twins can provide benefits for the growth of livestock and their operation in an efficient manner. To validate effect of the proposed digital twin framework for a pig house, we perform various simulations using a real-world dataset of a pig house. As a result of analyzing the energy demands for heating in pigsty based on the digital twin framework, the fan-coil unit was found to be the most energy efficient. In addition, when the optimal control of the HVAC system was applied, it was found to be more energy efficient than the conventional control method. The results obtained in this study show that our approach is superior to existing operational conventions, particularly in terms of energy efficiency.
In general, for livestock building, a simple system for controlling the HVAC system that is based only on the indoor air temperature is applied. This study evaluated the applicability of temperature ...humidity index (THI)-based ventilation systems installed in livestock buildings using a building energy simulation model. Based on the monitoring data of an actual pig house, the integrated predictive performance of the indoor temperature and humidity of the building energy simulation model was calibrated. Additionally, the indoor environment of the existing temperature-based control and THI-controlled ventilation systems was compared through simulations. The average THI and the section exceeding the THI threshold were both lower compared to the existing system. This was because the part load ratio of the fans of the THI-controlled ventilation system was higher than that of the existing system, indicating better ventilation. These results suggest that THI-based ventilation systems can overcome the limitations of existing temperature-based systems and effectively improve the thermal stress management of livestock buildings. This study portrays that the indoor environment can be improved by simply changing control variables, while presenting the field applicability and research value of THI-based control systems in the management of livestock environments.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Abstract A long short‐term memory (LSTM) model is introduced to predict missing datapoints of dissolved oxygen (DO) in an eel ( Anguilla japonica ) recirculating aquaculture system. Field experiments ...allow to determine periodic patterns in DO data corresponding to day–night cycles and a DO decrease after feeding. To improve the accuracy of DO prediction by using a training‐to‐test data ratio of 5:1, training with data in sequential and reverse orders is performed and evaluated. The LSTM model used to predict DO levels in the fish tank has an error of approximately 3.25%. The proposed LSTM model trained on DO data has a high applicability and may support water quality control in aquaculture farms.
South Korea has potential in developing large-scale pig-farming practices. However, poorly designed facilities and ventilation structures lead to production losses and energy inefficiency. This study ...examines energy efficiency in pig houses by establishing a heating, ventilation, and air-conditioning (HVAC) system. Using the current ventilation system of the baseline energy model, case studies were conducted. Compared with baseline case 1, energy consumption of remaining cases were lower. This suggests that the pig house is currently energy inefficient. Photovoltaic (PV) generation, contributing toward 35% of the annual energy consumption, for a sustainable pig house was investigated. This energy model shows energy efficiency potential. Therefore, expanding research into energy management is essential for optimal facility design and operation using the energy model.
•Sustainability of a pig house was analyzed using energy model.•Efficient and improved system saved approximately 33.8% more energy.•Annual PV generation was equal to 35% of the pig house's annual energy consumption.•The study aims to expand research to energy management using design and scenario.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Carbon dioxide (CO2) emissions from the livestock industry are expected to increase. A response strategy for CO2 emission regulations is required for pig production as this industry comprises a large ...proportion of the livestock industry and it is projected that per capita pork consumption will rise. A CO2 emission response strategy can be established by accurately measuring the CO2 concentrations in pig facilities. Here, we compared and evaluated the performance of three different machine learning (ML) models (ElasticNet, random forest regression (RFR), and support vector regression (SVR)) designed to predict CO2 concentration and internal air temperature (Ti) values in the pig house used to regulate a heating, ventilation, and air conditioning (HVAC) control system. For each ML model, the hyperparameter was optimised and the predictive accuracy was evaluated. The order of predictive accuracy for the ML models was ElasticNet < SVR < RFR. Hence, random forest regression provided superior prediction performance. Based on the test dataset, for Ti prediction by RFR, R2 ≥ 0.848 and the root mean square error (RMSE) and mean absolute error (MAE) were 0.235 °C and 0.160 °C, respectively, whilst for CO2 concentration prediction by RFR, R2 ≥ 0.885 and the RMSE and MAE were 64.39 ppm and ≤ 46.17 ppm, respectively.
Novel Packet Switching for Green IP Networks Jo, Seng‐Kyoun; Kim, Young‐Min; Lee, Hyun‐Woo ...
ETRI journal,
April 2017, 2017-04-00, 2017-04, Volume:
39, Issue:
2
Journal Article
Peer reviewed
Open access
A green technology for reducing energy consumption has become a critical factor in ICT industries. However, for the telecommunications sector in particular, most network elements are not usually ...optimized for power efficiency. Here, we propose a novel energy‐efficient packet switching method for use in an IP network for reducing unnecessary energy consumption. As a green networking approach, we first classify the network nodes into either header or member nodes. The member nodes then put the routing‐related module at layer 3 to sleep under the assumption that the layer in the OSI model can operate independently. The entire set of network nodes is then partitioned into clusters consisting of one header node and multiple member nodes. Then, only the header node in a cluster conducts IP routing and its member nodes conduct packet switching using a specially designed identifier, a tag. To investigate the impact of the proposed scheme, we conducted a number of simulations using well‐known real network topologies and achieved a more energy‐ efficient performance than that achieved in previous studies.
While communication technologies are evolving rapidly, there is still the nontrivial matter of a communication systems being green. Although some energy-aware solutions have been proposed for the ...telecommunications sector, they are not designed with the ultimate goal of being environment-friendly. In this paper, we investigate the problem of achieving energy efficiency in IP networks by taking into account not only the energy consumption of the network but also the impact of various energy sources, e.g., renewable energies. We propose a new green networking approach in which we classify network nodes into clusters and select one header node in each cluster according to the generation cost and the carbon emission per unit of energy. We develop a routing scheme using IP routing only on header nodes and conducting packet forwarding using a carefully designed identifier on other nodes to achieve a greener communication system. We validate our solution with a variety of simulations using real-world renewable energy statistics, and the results show that our approach is superior to other existing solutions, particularly in terms of energy and cost efficiency.
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