Use of Simplified System Models to Measure Retrofit Energy Savings

1993 ◽  
Vol 115 (2) ◽  
pp. 57-68 ◽  
Author(s):  
S. Katipamula ◽  
D. E. Claridge
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Daily Consumption ◽  
Variable Air Volume ◽  
System Models ◽  
Consumption Data ◽  
Central Texas ◽  
The Difference ◽  
June July

The retrofit of dual-duct constant volume systems (DDCV) with energy-efficient variable air volume systems (VAV) has become common in recent years. In general, the energy savings from such retrofits are estimated by developing a temperature-dependent regression model using whole building preretrofit energy consumption data. Model predictions are then compared with measured post retrofit consumption, to determine the savings. In cases where the preretrofit energy consumption is not available such a method cannot be implemented. This paper describes a method that can be used to calculate savings in such cases. The method is based on use of simplified calibrated system models. A VAV model was developed based on the ASHRAE TC 4.7 Simplified Energy Analysis Procedure (SEAP) (Knebel, 1983) and calibrated with the postretrofit energy consumption of a large engineering center in Central Texas. The loads from the calibrated VAV model were then used with the DDCV model to estimate the preretrofit energy use, also based on TC 4.7 SEAP, and apparent savings were determined as the difference between the DDCV predicted consumption and measured energy consumption for the postretrofit VAV system. The simulated hourly cooling energy consumption from the VAV model was within ±1GJ (±20 percent) of the measured consumption. The simulated daily consumption (the sum of 24 hours of consumption) compared better with the measured daily consumption (within ±7 percent). The apparent saving from the retrofit of the DDCV system with VAV was about 684 GJ in cooling energy and 324 GJ in heating energy for a three-week period June–July 1991.

A Four-Parameter Change-Point Model for Predicting Energy Consumption in Commercial Buildings

1992 ◽  
Vol 114 (2) ◽  
pp. 77-83 ◽  
Author(s):  
David Ruch ◽  
David E. Claridge
Keyword(s):  
Energy Consumption ◽  
Change Point ◽  
Energy Use ◽  
Energy Savings ◽  
Grocery Store ◽  
Parameter Change ◽  
Point Model ◽  
Linear Change ◽  
Consumption Data ◽  
Change Point Model

This paper develops a four-parameter change-point model of energy consumption as a function of dry-bulb temperature, along with accompanying error diagnostics for the model’s parameters. The model is a generalization of the widely used three-parameter, or variable-base degree-day method. The model is applied to data from a case study grocery store, is compared to the three-parameter PRISM CO model of the store data, and is shown to provide a statistically better fit to consumption data below about 15°C. This model appears to be useful for diagnosing unexpected energy use in some buildings and should be useful for determining retrofit energy savings from monitored pre-retrofit and post-retrofit data for the class of buildings whose pre-retrofit consumption is fit by a four-parameter linear change-point model.

scholarly journals Towards Sustainable Energy Retrofitting, a Simulation for Potential Energy Use Reduction in Residential Buildings in Palestine

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3876
Author(s):  
Sameh Monna ◽  
Adel Juaidi ◽  
Ramez Abdallah ◽  
Aiman Albatayneh ◽  
Patrick Dutournie ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Residential Building ◽  
Simulation Models ◽  
Water Heating ◽  
Heating And Cooling ◽  
Space Cooling ◽  
Cooling Loads

Since buildings are one of the major contributors to global warming, efforts should be intensified to make them more energy-efficient, particularly existing buildings. This research intends to analyze the energy savings from a suggested retrofitting program using energy simulation for typical existing residential buildings. For the assessment of the energy retrofitting program using computer simulation, the most commonly utilized residential building types were selected. The energy consumption of those selected residential buildings was assessed, and a baseline for evaluating energy retrofitting was established. Three levels of retrofitting programs were implemented. These levels were ordered by cost, with the first level being the least costly and the third level is the most expensive. The simulation models were created for two different types of buildings in three different climatic zones in Palestine. The findings suggest that water heating, space heating, space cooling, and electric lighting are the highest energy consumers in ordinary houses. Level one measures resulted in a 19–24 percent decrease in energy consumption due to reduced heating and cooling loads. The use of a combination of levels one and two resulted in a decrease of energy consumption for heating, cooling, and lighting by 50–57%. The use of the three levels resulted in a decrease of 71–80% in total energy usage for heating, cooling, lighting, water heating, and air conditioning.

People or Systems: Does Productivity Enhancement Matter More than Energy Management in LEED Certified Buildings?

2021 ◽  
Vol 13 (24) ◽  
pp. 13863
Author(s):  
Yana Akhtyrska ◽  
Franz Fuerst
Keyword(s):  
Energy Consumption ◽  
Energy Management ◽  
Energy Use ◽  
Management Practices ◽  
Energy Savings ◽  
Occupant Comfort ◽  
Energy Use Intensity ◽  
Using Data ◽  
Advanced Metering ◽  
The Impact

This study examines the impact of energy management and productivity-enhancing measures, implemented as part of LEED Existing Buildings Operations and Management (EBOM) certification, on source energy use intensity and rental premiums of office spaces using data on four major US markets. Energy management practices, comprised of commissioning and advanced metering, may reduce energy usage. Conversely, improving air quality and occupant comfort in an effort to increase worker productivity may in turn lead to higher overall energy consumption. The willingness to pay for these features in rental office buildings is hypothesised to depend not only on the extent to which productivity gains enhance the profits of a commercial tenant but also on the lease arrangements for passing any energy savings to the tenant. We apply a difference-in-differences method at a LEED EBOM certification group level and a multi-level modelling approach with a panel data structure. The results indicate that energy management and indoor environment practices have the expected effect on energy consumption as described above. However, the magnitude of the achieved rental premiums appears to be independent of the lease type.

scholarly journals Humidity-Sensitive Demand-Controlled Ventilation Applied to Multi-Unit Residential Building – Performance and Energy Consumption in Dfb Continental Climate

2020 ◽  
Author(s):  
Jerzy Sowa ◽  
Maciej Mijakowski
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Residential Buildings ◽  
Ventilation System ◽  
Residential Building ◽  
Primary Energy ◽  
Controlled Ventilation ◽  
Demand Controlled Ventilation ◽  
Continental Climate

A humidity-sensitive demand-controlled ventilation system is known for many years. It has been developed and commonly applied in regions with an oceanic climate. Some attempts were made to introduce this solution in Poland in a much severe continental climate. The article evaluates this system's performance and energy consumption applied in an 8-floor multi-unit residential building, virtual reference building described by the National Energy Conservation Agency NAPE, Poland. The simulations using the computer program CONTAM were performed for the whole hating season for Warsaw's climate. Besides passive stack ventilation that worked as a reference, two versions of humidity-sensitive demand-controlled ventilation were checked. The difference between them lies in applying the additional roof fans that convert the system to hybrid. The study confirmed that the application of demand-controlled ventilation in multi-unit residential buildings in a continental climate with warm summer (Dfb) leads to significant energy savings. However, the efforts to ensure acceptable indoor air quality require hybrid ventilation, which reduces the energy benefits. It is especially visible when primary energy use is analyzed.

Modelling of energy consumption in sociotechnical systems with intelligent equipment

2021 ◽  
pp. 4-19
Author(s):  
Владимир Борисович Барахнин ◽  
Светлана Валентиновна Мальцева ◽  
Константин Владимирович Данилов ◽  
Василий Вячеславович Корнилов
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Electricity Consumption ◽  
Feedback Mechanism ◽  
Smart Devices ◽  
Consumption Function ◽  
Management Processes ◽  
Consumption Data ◽  
The Times ◽  
Dynamic Time

Современные социотехнические системы в различных областях характеризуются наличием в их составе большого количества интеллектуального оборудования, которое может самостоятельно регулировать собственное потребление энергии, а также взаимодействовать с другими потребителями в процессах принятия решений и управления. Одна из таких отраслей - энергетика, где самоорганизация и системы коллективного потребления являются наиболее перспективными с точки зрения обеспечения эффективности использования энергоресурсов. Рассмотрены подходы к установлению статических и динамических тарифов на электроэнергию. Проведено сравнение двух моделей энергопотребления - статического двухтарифного и динамического, учитывающих рациональное поведение умных устройств, способных выбирать лучшие режимы для потребления электроэнергии. Показано влияние количества таких устройств на возможность достижения равномерного потребления при использовании второй модели. Modern socio-technical systems in various fields include a large number of smart equipment that can independently regulate its own energy consumption, as well as interact with other consumers in decision-making and management processes. Energy is one of these areas. Self-organization and collective self-consumption are the most promising in terms of ensuring the efficiency of energy use. Existing and prospective approaches to using static and dynamic time-based tariffs are under consideration. The paper presents a mathematical description of two models of energy consumption: a static model based on the allocation of two zones with a fixed duration and tariffs for each one and a dynamic model of two-tariff accounting with feedback, which assumes tariffs changing based on the results of the analysis of current electricity consumption. A pilot study of both models was conducted by using energy consumption data and taking into account the rational behavior of smart devices as consumers who can choose the best periods for electricity consumption. During the experiments it was investigated how an increase in the share of smart devices in the composition of electricity consumers as well as options for establishing zones and tariffs, affect the possibility of achieving uniform consumption during the day. Experiments have shown that with a small proportion of smart devices, acceptable results that reduce the variation in the consumption function can favor usage of the model without feedback. An increase in the number of actors in the system inevitably requires including a feedback mechanism into the system that allows the resource supplier to prevent excessive concentration of smart devices during the period of the cheaper tariff. However, when the share of smart devices exceeds a certain critical value, a pronounced inversion of the times of cheap and expensive tariffs occurs in two successive iterations. In this case, in order to ensure a quite even distribution of electricity consumption, it is advisable for the supplier to return to the single tariff rate. Thus, an excessive increase in the number of actors in the system can neutralize the effect of their use

scholarly journals Artificial Intelligence Assisted Heating Ventilation and Air Conditioning Control and the Unmet Demand for Sensors: Part 2. Prior Information Notice (PIN) Sensor Design and Simulation Results

Sensors ◽  
2019 ◽  
Vol 19 (15) ◽  
pp. 3440 ◽  
Author(s):  
Chin-Chi Cheng ◽  
Dasheng Lee
Keyword(s):  
Artificial Intelligence ◽  
Energy Consumption ◽  
Air Conditioning ◽  
Prior Information ◽  
Energy Savings ◽  
Theoretical Derivation ◽  
Consumption Data ◽  
Temperature And Humidity ◽  
Hvac Control ◽  
Comparative Results

The study continues the theoretical derivation from Part 1, and the experiment is carried out at a bus station equipped with six water-cooled chillers. Between 2012 and 2017, historical data collected from temperature and humidity sensors, as well as the energy consumption data, were used to build artificial intelligence (AI) assisted heating ventilation and air conditioning (HVAC) control models. The AI control system, in conjunction with a specifically designed prior information notice (PIN) sensor, was used to improve the prediction accuracy. This data collected between 2012 and 2016 was used for AI training and PIN sensor testing. During the hottest week of 2017 in Taiwan, the PIN sensor was used to conduct temperature and humidity data predictions. A model-based predictive control was developed to obtain air conditioning energy consumption data. The comparative results between the predictive and actual data showed that the temperature and humidity prediction accuracies were between 95.5 and 96.6%, respectively. Additionally, energy savings amounting to 39.8% were achieved compared to the theoretical estimates of 44.6%, a difference of less than 5%. These results show that the experimental model supports the theoretical estimations. In the future, a PIN sensor will be installed in a chiller to further verify the energy savings of the AI assisted HVAC control.

scholarly journals Comparison Evaluations of VRF and RTU Systems Performance on Flexible Research Platform

2018 ◽  
Vol 2018 ◽  
pp. 1-16 ◽  
Author(s):  
Je-hyeon Lee ◽  
Piljae Im ◽  
Jeffrey D. Munk ◽  
Mini Malhotra ◽  
Min-seok Kim ◽  
...  
Keyword(s):  
Energy Use ◽  
Energy Savings ◽  
Thermal Conditions ◽  
The United States ◽  
Energy Performance ◽  
Coefficient Of Performance ◽  
Part Load ◽  
Variable Air Volume ◽  
Heating And Cooling ◽  
Load Conditions

The energy performance of a variable refrigerant flow (VRF) system was evaluated using an occupancy-emulated research building in the southeastern region of the United States. Full- and part-load performance of the VRF system in heating and cooling seasons was compared with a conventional rooftop unit (RTU) variable-air-volume system with electric resistance heating. During both the heating and cooling seasons, full- and part-load conditions (i.e., 100%, 75%, and 50% thermal loads) were maintained alternately for 2 to 3 days each, and the energy use, thermal conditions, and coefficient of performance (COP) for the RTU and VRF system were measured. During the cooling season, the VRF system had an average COP of 4.2, 3.9, and 3.7 compared with 3.1, 3.0, and 2.5 for the RTU system under 100%, 75%, and 50% load conditions and resulted in estimated energy savings of 30%, 37%, and 47%, respectively. During the heating season, the VRF system had an average COP ranging from 1.2 to 2.0, substantially higher than the COPs of the RTU system, and resulted in estimated energy savings of 51%, 47%, and 27% under the three load conditions, respectively.

scholarly journals Design and Application of Cellular Concrete on a Mexican Residential Building and Its Influence on Energy Savings in Hot Climates: Projections to 2050

2020 ◽  
Vol 10 (22) ◽  
pp. 8225
Author(s):  
Ana C. Borbon-Almada ◽  
Jorge Lucero-Alvarez ◽  
Norma A. Rodriguez-Muñoz ◽  
Manuel Ramirez-Celaya ◽  
Samuel Castro-Brockman ◽  
...  
Keyword(s):  
Climate Change ◽  
Energy Consumption ◽  
Energy Use ◽  
Energy Savings ◽  
Design Stage ◽  
Second Phase ◽  
Dynamic Simulations ◽  
Conventional Concrete ◽  
The Impact ◽  
Cellular Concrete

The thermal performance of economical housing located in hot climates remains a pending subject, especially in emerging economies. A cellular concrete mixture was designed, considering its thermophysical properties, to apply the new material into building envelopes. The proposed materials have low density and thermal conductivity to be used as a nonstructural lightweight construction element. From the design stage, a series of wall systems based on cellular concrete was proposed. Whereas in the second phase, the materials were analyzed to obtain the potential energy savings using dynamic simulations. It is foreseen that the energy consumption in buildings located in these climates will continue to increase critically due to the temperature increase associated with climate change. The temperatures predicted mean vote (PMV), electric energy consumption, and CO2 emissions were calculated for three IPCC scenarios. These results will help to identify the impact of climate change on the energy use of the houses built under these weather conditions. The results show that if the conventional concrete blocks continue to be used, the air conditioning energy requirements will increase to 49% for 2030 and 61% by 2050. The proposed cellular concrete could reduce energy consumption between 15% and 28%, and these saving rates would remain in the future. The results indicate that it is necessary to drive the adoption of lightweight materials, so the impact of energy use on climate change can be reduced.

scholarly journals Systematic Simplified Simulation Methodology for Deep Energy Retrofitting Towards Nze Targets Using Life Cycle Energy Assessment

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3038 ◽  
Author(s):  
José Sánchez Ramos ◽  
MCarmen Guerrero Delgado ◽  
Servando Álvarez Domínguez ◽  
José Luis Molina Félix ◽  
Francisco José Sánchez de la Flor ◽  
...  
Keyword(s):  
Life Cycle ◽  
Energy Consumption ◽  
Energy Savings ◽  
Residential Building ◽  
Energy Performance ◽  
Simulation Tools ◽  
Energy Assessment ◽  
Energy Efficiency Improvement ◽  
The Difference ◽  
Reduction Of Energy Consumption

The reduction of energy consumption in the residential sector presents substantial potential through the implementation of energy efficiency improvement measures. Current trends involve the use of simulation tools which obtain the buildings’ energy performance to support the development of possible solutions to help reduce energy consumption. However, simulation tools demand considerable amounts of data regarding the buildings’ geometry, construction, and frequency of use. Additionally, the measured values tend to be different from the estimated values obtained with the use of energy simulation programs, an issue known as the ‘performance gap’. The proposed methodology provides a solution for both of the aforementioned problems, since the amount of data needed is considerably reduced and the results are calibrated using measured values. This new approach allows to find an optimal retrofitting project by life cycle energy assessment, in terms of cost and energy savings, for individual buildings as well as several blocks of buildings. Furthermore, the potential for implementation of the methodology is proven by obtaining a comprehensive energy rehabilitation plan for a residential building. The developed methodology provides highly accurate estimates of energy savings, directly linked to the buildings’ real energy needs, reducing the difference between the consumption measured and the predictions.

scholarly journals Using Conversational Assistants and Connected Devices to Promote a Responsible Energy Consumption at Home

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 32
Author(s):  
Jesús Fontecha ◽  
Iván González ◽  
Alberto Salas-Seguín
Keyword(s):  
Energy Consumption ◽  
Home Environment ◽  
Smart Home ◽  
Energy Use ◽  
Consumption Data ◽  
Smart Home Environment ◽  
Current Energy ◽  
Positive Results ◽  
Natural Way ◽  
At Home

Today, households worldwide are being increasingly connected. Mobile devices and embedded systems carry out many tasks supported by applications which are based on artificial intelligence algorithms with the aim of leading homes to be smarter. One of the purposes of these systems is to connect appliances to the power network, as well as to the internet to monitor consumption data among others. In addition, new interaction ways are emerging to manage all these systems. For example, conversational assistants which allow us to interact by voice with devices at home. In this work, we present GreenMoCA, a system to monitor energy consumption data from connected devices at home with the aim of improving sustainability aspects and reducing such energy consumption, supported by a conversational assistant. This system is able to interact with the user in a natural way, providing information of current energy use and feedback based on previous consumption measures in a Smart Home environment. Finally, we assessed GreenMoCA from a usability and user experience approach on a group of users with positive results.

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