Investigate the Potential Peak Energy Reduction of Integrated M-Cycle Evaporative Cooling With HVAC in Hot and Dry Climate

2019 ◽  
Author(s):  
Fahad Almehmadi ◽  
Ahmad Aljabr
Keyword(s):  
Energy Consumption ◽  
Thermal Model ◽  
Control Strategies ◽  
Evaporative Cooling ◽  
Space Environment ◽  
Cooling Load ◽  
Hourly Temperature ◽  
Peak Energy ◽  
Cooling Loads ◽  
The Impact

Abstract The purpose of the study is to investigate the potential energy saving of integrated M-Cycle evaporative cooling with HVAC. The model consists of three sub-systems which are thermal model of the typical house in Saudi Arabia, HVAC, and M-Cycle evaporative cooling. A thermal model of the typical house is performed to estimate the cooling load and then an integration between these sub-systems were built in MATLAB Simulink where the dynamic behavior of the whole system is examined. The house was simulated based on the actual hourly outdoor temperature and the physical properties of the house to estimate the cooling loads. To facilitate the simulation, the average hourly temperature is used. The results of the simulation show that energy consumption during peak hours can be reduced by up to 6%. It was found that the control system has a tremendous impact on controlling house temperature and cooling load. The impact of two different control strategies is investigated and their influence on house temperature and cooling loads are determined. It was found that PID control has advantage over On/Off control, in which the temperature in the space environment is kept uniform, and energy consumption is reduced by 20%.

A Thermal Model of a Fiber Optic Bundle for a Hybrid Solar Lighting System

2005 ◽  
Author(s):  
Michael J. Cheadle ◽  
Gregory F. Nellis ◽  
Sanford A. Klein ◽  
William A. Beckman
Keyword(s):  
Energy Consumption ◽  
Thermal Model ◽  
Fiber Optic ◽  
Management Strategies ◽  
Design Tool ◽  
Lighting Energy ◽  
Solar Lighting ◽  
Reduce Energy Consumption ◽  
Lighting Systems ◽  
Cooling Loads

Hybrid solar lighting (HSL) systems distribute natural sunlight to luminaires located in office or retail buildings in order to reduce energy consumption associated with conventional lighting systems. HSL systems reduce energy consumption directly by reducing the lighting energy and indirectly by reducing the associated cooling loads. A key component of the HSL system is the fiber optic bundle (FOB) that transmits the light from the collector to the luminaire. The observed thermal failure of the FOB when exposed to concentrated sunlight has motivated the development of a thermal model of this component. This paper describes the development of a predictive thermal model of the heat transfer in an FOB for an HSL system. The model is verified experimentally against temperature measurements obtained in the lab under controlled conditions and provides a powerful design tool that can be used to evaluate alternative thermal management strategies.

scholarly journals Forecasting peak energy demand for smart buildings

2020 ◽  
Author(s):  
Mona A. Alduailij ◽  
Ioan Petri ◽  
Omer Rana ◽  
Mai A. Alduailij ◽  
Abdulrahman S. Aldawood
Keyword(s):  
Neural Network ◽  
Time Series ◽  
Energy Consumption ◽  
Energy Demand ◽  
Arima Model ◽  
Demand Forecasting ◽  
User Preferences ◽  
Machine Learning Techniques ◽  
Peak Energy ◽  
The Impact

AbstractPredicting energy consumption in buildings plays an important part in the process of digital transformation of the built environment, and for understanding the potential for energy savings. This also contributes to reducing the impact of climate change, where buildings need to increase their adaptability and resilience while reducing energy consumption and maintain user comfort. The use of Internet of Things devices for monitoring and control of energy consumption in buildings can take into account user preferences, event monitoring and building optimization. Detecting peak energy demand from historical building data can enable users to manage their energy use more efficiently, while also enabling real-time response strategies (including control and actuation) to known or future scenarios. Several statistical, time series, and machine learning techniques are proposed in this work to predict electricity consumption for five different building types, by using peak demand forecasting to achieve energy efficiency. We have used several indigenous and exogenous variables with a view to test different energy forecasting scenarios. The suggested techniques are evaluated for creating predictive models, including linear Regression, dynamic regression, ARIMA time series, exponential smoothing time series, artificial neural network, and deep neural network. We conduct the analysis on an energy consumption dataset of five buildings from 2014 until 2019. Our results show that for a day ahead prediction, the ARIMA model outperforms the other approaches with an accuracy of 98.91% when executed over a 168 h (1 week) of uninterrupted data for five government buildings.

scholarly journals Performance Evaluation of Two Machine Learning Techniques in Heating and Cooling Loads Forecasting of Residential Buildings

2020 ◽  
Vol 10 (11) ◽  
pp. 3829 ◽  
Author(s):  
Arash Moradzadeh ◽  
Amin Mansour-Saatloo ◽  
Behnam Mohammadi-Ivatloo ◽  
Amjad Anvari-Moghaddam
Keyword(s):  
Machine Learning ◽  
Energy Consumption ◽  
Residential Buildings ◽  
Load Forecasting ◽  
Training Data ◽  
Support Vector ◽  
Cooling Load ◽  
Heating And Cooling ◽  
Cooling Loads ◽  
Heating And Cooling Load

Nowadays, since energy management of buildings contributes to the operation cost, many efforts are made to optimize the energy consumption of buildings. In addition, the most consumed energy in the buildings is assigned to the indoor heating and cooling comforts. In this regard, this paper proposes a heating and cooling load forecasting methodology, which by taking this methodology into the account energy consumption of the buildings can be optimized. Multilayer perceptron (MLP) and support vector regression (SVR) for the heating and cooling load forecasting of residential buildings are employed. MLP and SVR are the applications of artificial neural networks and machine learning, respectively. These methods commonly are used for modeling and regression and produce a linear mapping between input and output variables. Proposed methods are taught using training data pertaining to the characteristics of each sample in the dataset. To apply the proposed methods, a simulated dataset will be used, in which the technical parameters of the building are used as input variables and heating and cooling loads are selected as output variables for each network. Finally, the simulation and numerical results illustrates the effectiveness of the proposed methodologies.

Solar Panel Orientation Based on Building Power Consumption

2014 ◽  
Author(s):  
Mesut Cabuk ◽  
Mohammad H. Naraghi
Keyword(s):  
Energy Consumption ◽  
Energy Production ◽  
Present Model ◽  
Electric Energy ◽  
Solar Panel ◽  
Cooling Load ◽  
Electric Energy Consumption ◽  
Index Model ◽  
Peak Energy ◽  
June July

In the present work electric energy consumption of a typical building based on its cooling load for summers of five consecutive years were evaluated. The cooling load hourly variations were evaluated based on the eQuest software. It was determined that the peak electric energy consumption of the building occurs around 4:00PM during months of June, July and August. Then the clear sky model was used to determine the solar panel orientation to best match peak energy consumption. The best solar panel orientation to meet building’s peak demand is about 50 degrees tilt angle with azimuth angle of about between fifty and sixty degrees westward. The clearness index model is then used to evaluate the annual energy production of solar panel. It was determined that the annual energy production of the panel based on the present model is approximately 22–23% less than a southward orientation. The present model however, produces twice more electric power during peak demanding hours, when it is needed most.

scholarly journals Improving Building Energy Performance Using Dual VAV Configuration Integrated with Dedicated Outdoor Air System

Buildings ◽  
2021 ◽  
Vol 11 (10) ◽  
pp. 466
Author(s):  
Nabil Nassif ◽  
Iffat Ridwana
Keyword(s):  
Energy Consumption ◽  
Air Temperature ◽  
Energy Savings ◽  
Energy Performance ◽  
Office Building ◽  
Effective Control ◽  
Cooling Load ◽  
Outdoor Air ◽  
System A ◽  
Cooling Loads

As building systems account for almost half of the total energy consumed by the building sector to provide space heating, cooling, and ventilation, efficiently designing these systems can be the key to energy conservation in buildings. Dual VAV systems with an effective control strategy can substantially reduce the energy consumption in buildings, providing a significant scope of further research on this system configuration. This paper proposes to utilize the warm air duct of the dual VAV system as a dedicated outdoor air (DOA) unit when no heating is required, which allows the cooling load to be effectively distributed between two ducts. A specific control sequence is proposed with different supply air temperature reset strategies to estimate the heating, cooling loads, and fan power energy consumption of the proposed system. A simple two-zone office building is taken as a preliminary case study to simulate the airflow rates and fan power of a single duct VAV and proposed dual VAV systems to illustrate the concept. Finally, a larger multi-zone office building is simulated to measure the annual heating, cooling loads, and fan power energy and compare the energy savings among the systems. The results show significant fan power reduction ranging from 1.7 to 9% and notable heating energy reduction up to 76.5% with a small amount of cooling load reduction varying from 0.76 to 2.56% depending on the different locations for the proposed dual VAV systems. Further energy savings from different supply air temperature reset strategies demonstrate the opportunity of employing them according to climates and case studies. The proposed dual VAV system proves to have the potential to be adapted in buildings for the purpose of sustainability and energy savings.

scholarly journals ANALYSIS OF ENERGY-EFFICIENT HOUSE LAYOUT DESIGN IN TROPICAL CLIMATE

2021 ◽  
Vol 47 (1) ◽  
pp. 11-18
Author(s):  
Aisyah Zakiah
Keyword(s):  
Energy Consumption ◽  
Energy Efficient ◽  
Residential Buildings ◽  
Weather Data ◽  
Cooling Load ◽  
City Development ◽  
Total Energy Consumption ◽  
Wall Area ◽  
Consumption Energy ◽  
Cooling Loads

Energy-efficient residential provision is an essential concern for the present and future city development. Currently, the residential buildings contribute approximately 37.5% to significant energy consumption and carbon emissions, which mainly used for cooling. This research aims to study the house layout arrangement to minimise cooling loads and further reduce energy consumption. Energy efficiency analysis is performed by comparing the cooling load and total energy consumption from variations of the hypothetical design of detached or semi-detached housing layouts commonly built in Indonesia. The calculation of cooling loads and energy consumption is performed by simulation in Energy Plus 8.4 with Jakarta weather data. The results show that the arrangement of the house layout may reduce the cooling load up to 24%. The total conditioned wall area that varies due to the variations of house layouts are found to affect the cooling loads.

scholarly journals Impact of Rise in Atmosphere Temperature on an Official Building’s Energy Consumption in Kathmandu

2018 ◽  
Vol 13 (1) ◽  
pp. 102-107
Author(s):  
Sameer Pandit ◽  
Nawraj Bhattarai
Keyword(s):  
Energy Consumption ◽  
Energy Resource ◽  
Resource Assessment ◽  
Mineral Wool ◽  
Weather Data ◽  
Consumption Pattern ◽  
Insulation Material ◽  
Total Energy Consumption ◽  
Hourly Temperature ◽  
The Impact

 The objective of this research is to study the impact of rise in atmospheric temperature, in buildings energy consumption in the future. An existing Typical Meteorological Year (TMY) weather file of time span 1973-1996 composed of weather data by Solar and Wind Energy Resource Assessment (SWERA) project is assumed as the baseline climate in this study. Monthly average temperature of future years in business as usual scenario predicted by Meteonorm is downscaled to hourly temperature data using downscaling method, morphing. This showed that annual average air temperature of the atmosphere will increase by 1.64¬0C, 2.12¬0C, 2.52¬0C and 2.28¬0C from baseline year in the years 2010, 2020, 2030, and 2040 respectively. Building energy simulation tool eQUEST is used to analyze the energy consumption pattern of a selected building located in Kathmandu. Study has shown that total energy consumption of the building for heating, cooling, lighting and miscellanies equipment will increase by 4.9%, 6.2%, 7.3% and 8.3% for the years 2010, 2020, 2030 and 2040 respectively from baseline year whereas cooling load will increase by 19%, 23%, 27% and 31%. The study also has shown that insulating a building will decrease the energy consumption. There will be decrease in the cooling energy consumption by 2.29%, 2.98%, 4.06% and 4.78% in the years 2010, 2020, 2030 and 2040 respectively after addition of insulation material mineral wool/fiber.Journal of the Institute of Engineering, 2017, 13(1): 102-107

scholarly journals Simplified Building Thermal Model Used for Optimal Control of Radiant Cooling System

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Lei He ◽  
Bo Lei ◽  
Haiquan Bi ◽  
Tao Yu
Keyword(s):  
Supervisory Control ◽  
Thermal Model ◽  
Thermal Environment ◽  
Cooling System ◽  
Hvac Systems ◽  
Cooling Load ◽  
System Operation ◽  
Cooling Systems ◽  
Radiant Cooling ◽  
Cooling Loads

MPC has the ability to optimize the system operation parameters for energy conservation. Recently, it has been used in HVAC systems for saving energy, but there are very few applications in radiant cooling systems. To implement MPC in buildings with radiant terminals, the predictions of cooling load and thermal environment are indispensable. In this paper, a simplified thermal model is proposed for predicting cooling load and thermal environment in buildings with radiant floor. In this thermal model, the black-box model is introduced to derive the incident solar radiation, while the genetic algorithm is utilized to identify the parameters of the thermal model. In order to further validate this simplified thermal model, simulated results from TRNSYS are compared with those from this model and the deviation is evaluated based on coefficient of variation of root mean square (CV). The results show that the simplified model can predict the operative temperature with a CV lower than 1% and predict cooling loads with a CV lower than 10%. For the purpose of supervisory control in HVAC systems, this simplified RC thermal model has an acceptable accuracy and can be used for further MPC in buildings with radiation terminals.

Comparison of static and dynamic shading systems for office building energy consumption and cooling load assessment

2018 ◽  
Vol 29 (5) ◽  
pp. 978-998 ◽  
Author(s):  
Francesco De Luca ◽  
Hendrik Voll ◽  
Martin Thalfeldt
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Control Algorithm ◽  
Office Buildings ◽  
Office Building ◽  
Cooling Load ◽  
Content Type ◽  
Improve Energy Efficiency ◽  
Shading Devices ◽  
Cooling Loads

PurposeExterior shading devices and dynamic shading systems constitute an efficient way to improve energy efficiency and occupants’ comfort in buildings through the reduction of direct solar heat gains and disturbing glare. The purpose of this paper is to analyse the performance of different types of shading systems, fixed and dynamic, and their influence on the energy consumption and cooling loads for an office building located in Tallinn, Estonia. The scope is to determine the most performative configuration for energy consumption and cooling load reduction for office buildings and to provide designers and developers with the necessary knowledge to increase the performance of their buildings.Design/methodology/approachThere are many types of fixed shading devices, most of which use rectangular planar elements, the orientation and layout of which depends on the building location and façade orientation. The dynamic shading systems vary on the base of the building occupancy schedules and occupants’ preferences. The paper presents a method to determine the most efficient type and size of fixed shading devices in relation to different windows’ size and orientation, and the quantity of windows panes. At the same time the dynamic shading system using a control algorithm developed by the authors is compared.FindingsThe results show that solar shading is an efficient way to control the energy consumption of office buildings, though with different efficacy by the static systems depending on orientation, window and shading type. Evidence shows that dynamic blind systems have more uniform performance and usually outperform static shading.Originality/valueThe paper compares the performances of different static and dynamic shading devices and systems for the location in Tallinn. The dynamic shading system tested uses a control algorithm developed by the authors. The indications for the energy reduction and cooling loads are a valuable resource for designers and developers to increase the energy efficiency of their buildings.

Impact of Construction Materials in the Energy Consumption in Homes in the Caribbean

Solar Energy ◽  
2005 ◽  
Author(s):  
Luis H. Alva ◽  
Jorge E. Gonza´lez ◽  
John B. Hertz
Keyword(s):  
Puerto Rico ◽  
Energy Consumption ◽  
Energy Saving ◽  
Energy Efficient ◽  
Air Conditioning ◽  
Natural Ventilation ◽  
Construction Materials ◽  
Hot Water ◽  
Cooling Load ◽  
The Impact

This investigation presents the thermal analysis of an experimental, low energy consuming home for low-income families, located in Puerto Rico, where the prevailing climate is hot and humid. The objective of this analysis is to aid in the design of energy efficient homes, which in turn will reduce energy consumption in the Island. This investigation compares the analysis of this experimental house, specifically designed for the tropics, to a similarly sized, conventionally built low-cost home. Different construction materials are evaluated in conjunction with the use of either natural ventilation or air conditioning. The impact of natural ventilation is analyzed, with results for the inside temperature and interior heat removal presented and compared. Additional energy saving strategies are evaluated, including solar thermal energy for domestic hot water production, daylighting and the use of energy efficient lights. The annual energy consumption of the proposed experimental home is calculated and compared with the energy consumption of the conventional house. The thermal load of the house is calculated through the use of mathematical simulations of the dynamic annual cooling load using well-known software such as Energy-Plus for a TMY for San Juan, Puerto Rico. Results for the inside temperature of the experimental house, the heat loss due to natural ventilation, the cooling load when air conditioning is used, and energy consumption are presented and compared with the conventional house. Results indicate that the experimental house is 30% more energy efficient when all the energy saving strategies are considered.

Sign in / Sign up

Export Citation Format

Share Document