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.

A Change-Point Principal Component Analysis (CP/PCA) Method for Predicting Energy Usage in Commercial Buildings: The PCA Model

1993 ◽  
Vol 115 (2) ◽  
pp. 77-84 ◽  
Author(s):  
D. Ruch ◽  
Lu Chen ◽  
J. S. Haberl ◽  
D. E. Claridge
Keyword(s):  
Principal Component Analysis ◽  
Change Point ◽  
Electricity Consumption ◽  
Principal Component ◽  
Component Analysis ◽  
Commercial Buildings ◽  
Grocery Store ◽  
Commercial Building ◽  
Point Model ◽  
Change Point Model

A new method for predicting daily whole-building electricity usage in a commercial building has been developed. This method utilizes a Principal Component Analysis (PCA) of intercorrelated influencing parameters (e.g., dry-bulb temperature, solar radiation and humidity) to predict electricity consumption in conjunction with a change-point model. This paper describes the PCA procedure and presents the results of its application in conjunction with a change-point regression, to predict whole-building electricity consumption for a commercial grocery store. Comparison of the results with a traditional Multiple Linear Regression (MLR) analysis indicates that a change-point, Principal Component Analysis (CP/PCA) appears to produce a more reliable and physically plausible model than an MLR analysis and offers more insight into the environmental and operational driving forces that influence energy consumption in a commercial building. It is thought that the method will be useful for determining conservation retrofit savings from pre-retrofit and post-retrofit consumption data for commercial buildings. A companion paper presents the development of the four-parameter change-point model and a comparison to the Princeton Scorekeeping Method (PRISM) (Ruch and Claridge, 1991).

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.

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.

A Bayesian Change Point Model for Historical Time Series Analysis

2004 ◽  
Vol 12 (4) ◽  
pp. 354-374 ◽  
Author(s):  
Bruce Western ◽  
Meredith Kleykamp
Keyword(s):  
Time Series ◽  
Change Point ◽  
Regression Coefficients ◽  
Simulation Methods ◽  
Historical Time ◽  
Point Location ◽  
Point Model ◽  
Political Relationships ◽  
Standard Models ◽  
Change Point Model

Political relationships often vary over time, but standard models ignore temporal variation in regression relationships. We describe a Bayesian model that treats the change point in a time series as a parameter to be estimated. In this model, inference for the regression coefficients reflects prior uncertainty about the location of the change point. Inferences about regression coefficients, unconditional on the change-point location, can be obtained by simulation methods. The model is illustrated in an analysis of real wage growth in 18 OECD countries from 1965–1992.

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.

scholarly journals Discriminating between Long Memory and Volatility Shifts

2016 ◽  
Vol 36 (4) ◽  
Author(s):  
Aonan Zhang ◽  
Robertas Gabrys ◽  
Piotr Kokoszka
Keyword(s):  
Long Memory ◽  
Change Point ◽  
Kernel Estimator ◽  
Practical Implementation ◽  
Point Model ◽  
Variance Estimators ◽  
Long Run ◽  
The Us ◽  
Change Point Model ◽  
Stock Indexes

We develop a practical implementation of the test proposed in Berkes, Horv´ath, Kokoszka, and Shao (2006) designed to distinguish between a change-point model and a long memory model. Our implementation is calibrated to distinguish between a shift in volatility of returns and long memory in squared returns. It uses a kernel estimator of the long-run variance of squared returns with the maximal lag selected by a data driven procedure which depends on the sample size, the location of the estimated change point and the direction of the apparent volatility shift (increase versus decrease). In a simulations study, we also consider other long-run variance estimators, including the VARHAC estimator, but we find that they lead to tests with inferior performance. Applied to returns on indexes and individual stocks, our test indicates that even for the same asset, a change-point model may be preferable for a certain period of time, whereas there is evidence of long memory in another period of time. Generally there is stronger evidence for long memory in the eight years ending June 2006 than in the eight years starting January 1992. This pattern is most pronounced for US stock indexes and shares in the US financial sector.

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