Whole Building Energy Performance Evaluation through. Similar Control Strategies

Similar documents
CONDENSING TEMPERATURE CONTROL THROUGH ENERGY MANAGEMENT SYSTEM SIMULATON FOR A LARGE OFFICE BUILDING

EADQUARTERS. Thesis Revised Proposal. Stephanie Kunkel Mechanical Option

A Case Study in Energy Modeling of an Energy Efficient Building with Gas Driven Absorption Heat Pump System in equest

enables to easily calculate the energy consumption of air conditioning in various conditions (MLIT). In this study, the university building is the obj

Evaluation of Energy Savings of the New Chinese Commercial Building Energy Standard

Optimisation of an HVAC system for energy saving and thermal comfort in a university classroom

UC Berkeley Indoor Environmental Quality (IEQ)

Development of New Self-Comparison Test Suites for EnergyPlus

How LEED & The Retro-Commissioning Credits Produce Energy Savings. James Vallort Vice President Environmental Systems Design, Inc.

Building Controls Strategies Conference. Retro-Commissioning with BAS Overview. 10 March Steve Brown, CAP ESD Controls Team Leader

HEATING LOAD PREDICTIONS USING THE STATIC NEURAL NETWORKS METHOD. S.Sholahudin 1, Hwataik Han 2*

Leveraging Smart Meter Data & Expanding Services BY ELLEN FRANCONI, PH.D., BEMP, MEMBER ASHRAE; DAVID JUMP, PH.D., P.E.

RETRO-COMMISSIONING OF A HEAT SOURCE SYSTEM IN A DISTRICT HEATING AND COOLING SYSTEM Eikichi Ono 1*, Harunori Yoshida 2, Fulin Wang 3 KEYWORDS

Application of a cooling tower model for optimizing energy use

Assessment of the energy demand in energy-saving office buildings from the viewpoint of variations of internal heat gains

Bryant University s Energy Guidelines for Sustainability

MODELLING AND SIMULATION OF BUILDING ENERGY SYSTEMS USING INTELLIGENT TECHNIQUES

Article Control of Thermally Activated Building System Considering Zone Load Characteristics

Secondary loop chilled water in super high-rise

MODELING AND VALIDATION OF EXISTING VAV SYSTEM COMPONENTS

Canada Published online: 28 Feb 2011.

The Creative and Performing Arts High School (CAPA) Pittsburgh, PA 9/30/2002 Andrew Tech Mechanical Option Prof. S. A. Mumma

Available online at ScienceDirect. Procedia Engineering 145 (2016 ) 18 25

Energy modeling in IDA ICE according to ASHRAE , app. G

Assessment of Climate Change Robustness of a Deep Energy Retrofit Design of an Existing Day Care Centre

Persistence Tracking in a Retro-commissioning Program

Recommissioning Energy Savings Persistence

ENERY COST AND CONSUMPTION IN A LARGE ACUTE HOSPITAL

Introduction of Energy Data Analysis Center(EDAC)

Optimization of Building Energy Management Systems

Success with MEASUREMENT & VERIFICATION

CASE STUDIES ON HVAC SYSTEM PERFORMANCE USING A WHOLE BUILDING SIMULATION BASED REAL-TIME ENERGY EVALUATION APPROACH WITH BEMS

Building Energy Analysis for a Multi-Family Residential Building (Multi V III VRF Heat-Pump System)

ENERGY RECOVERY, CALCULATION METHODS

CHILLED WATER SYSTEM OPTIMIZER

Walter Reed National Military Medical Center Bethesda, MD

Energy Efficiency. best in class

MEASUREMENT AND VERIFICATION TOOLS Spiros Metallinos Regulatory Authority for Energy, Greece

OPTIMIZATION OF ICE THERMAL STORAGE SYSTEM DESIGN FOR HVAC SYSTEMS

Performance evaluation of an actual building airconditioning

ENGINEERING UPDATE WHITE PAPER: BUILDING PERFORMANCE METRICS. price-hvac.com. May 2013 Vol. 10

Advantages of Financing Continuous Commissioning As An Energy Conservation Retrofit Measure

Chilled Water Plant Redesign

An energy-saving control strategy for VRF and VAV combined air conditioning system in heating mode

Promoting Building Energy Efficiency through Performancebased Standards: Is it a Challenge? By Priyantha Bandara

Comparative Heating Performances of Ground Source and Air Source Heat. Pump Systems for Residential Buildings in Shanghai

Available online at ScienceDirect. Procedia Engineering 121 (2015 )

Principles of Ventilation and Air Conditioning Design & Installation

THERMAL CHARACTERISTICS AND ENERGY CONSERVATION MEASURES IN AN INDOOR SPEED-SKATING ARENA

The optimization of the mechanical night cooling system in the office building

Ventilation. Demand-controlled ventilation (DCV) Demand-Controlled. With ASHRAE Standard Based

The Effects of Set-Points and Dead-Bands of the HVAC System on the Energy Consumption and Occupant Thermal Comfort

LIBRARY ENERGY WALK- THROUGH. Andy Robinson, Training and Education, SEDAC

Secondary loop chilled water in super high-rise

Expand the Modeling Capabilities of DOE s EnergyPlus TM Building Energy Simulation Program. Final Technical Report for DOE Project # DE-FC26-04NT42330

COMFORT-PRODUCTIVITY Building costs COMFORT-PERFORMANCE. Radiant Heating and Cooling Systems for Better Comfort and Energy Efficiency INDOOR - OUTDOOR

Incorporating Uncertainty Analysis into a Building Retrofit Analysis Using OpenStudio and EnergyPlus

The impact of Building Automation on Energy Efficiency. Siemens with DESIGO and Synco best in class. Siemens AG, 2009 All Rights Reserved

Chilled Beams. The new system of choice?

Building Energy Modeling Using Artificial Neural Networks

Impact of HVAC Systems on Building Peak Electricity Load

Using Annual Building Energy Analysis for the Sizing of Cooling Tower for Optimal Chiller-Cooling Tower Energy Performance

A Comparative Study of Energy Consumption for Residential HVAC Systems Using EnergyPlus

Great Ocean Rd Ice Creamery

CASE STUDY HOW COULD WE OPTIMIZE THE ENERGY-EFFICIENT DESIGN FOR AN EXTRA-LARGE RAILWAY STATION WITH A COMPREHENSIVE SIMULATION?

Air Conditioning Inspections for Buildings Assessing Equipment Sizing

Retro-Commissioning for Existing Facilities

Technical Retro-Commissioning of Existing Buildings

EVALUATION OF BUILDING ENERGY CONSUMPTION BASED ON FUZZY LOGIC AND NEURAL NETWORKS APPLICATIONS

Model Based Building Chilled Water Loop Delta-T Fault Diagnosis

OPERATION AND CONTROL OF THERMALLY ACTIVATED SLAB HEATING AND COOLING SYSTEMS

Energy Conservation for Office Buildings. Major points, measures, and successful cases of energy conservation for office buildings

Using a Whole Building Approach to Energy Efficiency

Fraunhofer CSE: Applied R&D to Drive Clean Energy Technology Commercialization & Economic Development June 2014

DesignTools Software Energy Analyzer User Manual

Development of Design Guidance for K-12 Schools: From 30% to 50% Energy Savings

Building Management System to support building renovation

SorTech package solution description

A STUDY OF PREDICTED ENERGY SAVINGS AND SENSITIVITY ANALYSIS. A Thesis YING YANG

Thesis Proposal. Park. Findlay 12/10/2010. Connor Blood

The impact of Building Automation on Energy Efficiency. Siemens with DESIGO and Synco best in class. Siemens AG, plc, All Rights Reserved

Thermal Energy Storage

DOE Best Practice Software Tools. Joseph Chappell Adam Roget

Field Performance Measurements of VRF System with Subcooling Heat Exchanger

Trane eflex. For Ton Light Commercial Applications

AHU Models Using Whole Building Cooling and Heating Energy Consumption Data

NEW FEATURES IN THE CARRIER HOURLY ANALYSIS PROGRAM v4.40

THE NEW WAY TO PROVIDE COMFORT IN 4 PIPES SYSTEMS APPLICATIONS

Hourly Analysis Program v.4.1 Page 1 of 1

NZEB: The new challenge of HVAC Manufacturers. ASTRO Tower (Archi Urbain)

Italcementi Center for Research and Innovation

COMPUTER MODEL OF A UNIVERSITY BUILDING USING THE ENERGYPLUS PROGRAM

Building Automation Systems

ARCH-MEDES (I) CONSULTANTS PVT. LTD. Green Park Delhi

! #! %%%%&%%% &( &% )) + # +,% #.!. # 0! 1 2! ,%,% 0 # 0! 1 2! ,4&,) 5,%

Case Study of Implementation of Web-Based Energy Management and Control System onto Campus Buildings

Infosys. Driven by Values

Normal Children's Discovery Museum, LEED Silver:

ENERGY MODELING FOR MEASUREMENT AND VERIFICATION

BUILDING DESIGN FOR HOT AND HUMID CLIMATES IMPLICATIONS ON THERMAL COMFORT AND ENERGY EFFICIENCY. Dr Mirek Piechowski 1, Adrian Rowe 1

Transcription:

Whole Building Energy Performance Evaluation through Similar Control Strategies S.H. Cheon 1, Y.H. Kwak 1, C.Y. Jang 2, and J.H. Huh 1* 1 Department of Architectural Engineering, University of Seoul, Seoul 130-743, Republic of Korea 2 Building Energy Research Center, Korea Institute of Energy Research, Daejeon 305-343, Republic of Korea ABSTRACT The energy consumption of architectural environment system accounts for the most proportion in life cycle cost, and it can be efficiently reduced through Building Automation System(BAS) based on Building Energy Management System(BEMS). There are similar controls among the BAS control strategies. However, there are almost no studies that compare the building energy performance of such similar controls. Accordingly, this study compares and analyzes the building energy performance of similar controls and then decides which control strategy appears to derive the most benefit during cooling season. The real target building model is modelled by using EnergyPlus and verified through comparing the actual energy consumption with the simulated energy consumption. After that, temperature control and enthalpy control which are to manipulate the outdoor air flow rate by comparing the thermal properties of return air are applied to verified model. In addition, the zero energy band and duty cycling are performed to determine the operational status of AHU by measuring indoor temperature. Results shows that the enthalpy control is more beneficial than the temperature control, and the duty cycling is more reliable than the zero energy band. According to the result of this study, it is found that it is better to apply the control that is good building energy performance in the similar control strategies. In the design phase, the control that is good building energy performance in the similar control strategies can be preferentially selected, and, furthermore, they can be integrated into one. KEYWORDS Building Automation System, Temperature Control, Enthalpy Control, Zero Energy Band, Duty Cycling * Corresponding author email: huhj0715@uos.ac.kr

INTRODUCTION In life cycle cost(lcc), the energy cost and facility management cost during the operational phase is five to six times higher than the initial investment cost. Because the energy consumption during the operational phase of the building accounts for a large proportion, its importance, related to the efficient use of energy in building operation and management aspect, increases. Studies related to building energy management system(bems) that includes building energy management functions have been internationally conducted with building automation system(bas) that includes control facilities to use energy efficiently. Kim et al.(2010) studied the change of cooling load through applying temperature control and enthalpy control to the office building located in Seoul. The enthalpy control caused the cooling load to reduce. However, the temperature control increased the cooling load due to the excessive increase of latent heat load based on the characteristics of Korean summer climate. Huang et al.(2006) applied optimum start/stop, night purge, and enthalpy control to virtual zone developed on the VAV system and reported energy saving of 17%. Canbay et al.(2006) applied optimum start/stop, night purge, and enthalpy control to shopping centre buildings in Turkey and reported energy saving of 22%. There are similar controls among the BAS control strategies. However, there have been almost no studies comparing the building energy performance of such similar controls. In the design phase, the control that is good building energy performance in the similar control strategies can be preferentially selected, and, furthermore, they can be integrated into one. This study compares and analyzes the building energy performance of temperature control and enthalpy control as outdoor air control strategies, and zero energy band and duty cycling as AHU control strategies during cooling season. METHOD This study is performed by using the following procedure, and uses EnergyPlus as an energy simulation tool. (1) Modelling through the energy audit of the target building. (2) Completion of the baseline model through comparing the simulated energy consumption with the actual energy consumption. (3) Application of outdoor air control strategies(e.g., temperature control and enthalpy control) and AHU control strategies(e.g., zero energy band and duty cycling) to the baseline model. (4) Comparing and analyzing the building energy performance of the similar control strategies. MODELING AND CALIBRATION The office building, G Building, located in Daejeon, Republic of Korea, is composed of five floors. It uses the VAV system for air conditioning, and operates four air handling units(ahus). The operational status of its AHUs is shown in Table 1. Table 1.Operational status of AHUs

Items Heat Source of Coils Etc. AHU 1 AHU 2 Using plant with EHP AHU 3 Using electricity - AHU 4 Using plant Disuse The simulated energy consumption is compared with the actual energy consumption of the chillers, cooling tower, EHP, fans, pumps, lighting, and plug that is measured to calculated monthly error. Since this study analyzes the building energy performance of similar controls during cooling season, the energy consumptions from July to December are considered. Input values are adjusted after analyzing causes when error occurs greatly. The calibration process of model is shown in Figure 1. Collect information about the Building Adjust Input Values Create Input File Identify Possible Reasons for The Mismatch Between Simulated Results and Measured Data Obtain Results from Simulation Models Collect Measured Data Determine If Simulated Results and Measured Data Match Calibration is Complete Figure 1. Calibration process of Model The error is calculated by using the Mean Bias Error (MBE) Eq. (1), Root Mean Square Error (RMSE) Eq. (2), and Coefficient of the Variation of RMSE (Cv(RMSE)) Eq. (3). ( S M ) MBE (%) 100 (1) M RMSE ( S M ) N 2 (2)

RMSE Cv ( RMSE ) 100 (3) A where S, M, N, and A are the simulated energy consumption[kwh], measured energy consumption[kwh], number of data, and mean of the measured energy consumption[kwh], respectively. Each MBE and Cv(RMSE) value in the results is shown in Table 2. The MBE and Cv(RMSE) values of the target building model are satisfied with the recommended error standard(ashrae 2002, M&V 2008). The completed baseline model is shown in Figure 2. Table 2. MBE and Cv(RMSE) values Items MBE Cv(RMSE) Items MBE Cv(RMSE) Chiller -2.32 5.43 Pump 0.44 13.53 Cooling tower 1.89 9.86 Lighting -3.23 12.19 EHP 4.07 12.31 Plug -1.35 7.71 Fan -4.79 10.80 Total -1.75 4.84 OA EA M/B C/C Ice Storage Chiller C/T H/C Zone Zone Boiler CONTROL STRATEGIES Figure 2.Whole building simulation modeling (1) Outdoor Air Control Strategies Temperature control and enthalpy control compare the thermal properties of return air and outdoor air. The outdoor air flow rate is increased if the thermal property of outdoor air is more beneficial to air conditioning than return air, or the outdoor air flow rate is minimized if it is not. Therefore, the thermal property of mixed air that is beneficial to air conditioning is induced to reduce the load of coils and facility. Temperature control considers only sensible heat of air, while enthalpy control considers both sensible heat and latent heat of air. This study applies temperature control and enthalpy control by using Erl(EnergyPlus runtime language). The composed algorithms are shown in Figure 3 and 4 respectively.

Current Time (t i ) Current Time (t i ) T RA < T OA Calculate OA Fraction h RA < h OA Calculate OA Fraction Minimize Increase Minimize Increase Figure 3. Temperature control Figure 4. Enthalpy control (2) AHU Control Strategies Zero energy band is a dead band where neither heating nor cooling energy is used within the time of air conditioning. The main purpose is to minimize the energy consumption of AHU by stopping air conditioning when the indoor temperature is within the zero energy band. This study excludes winter season, and the permitted maximum temperature is set as 28 that is the set point of the target building. The algorithm is composed by using Erl. The composed algorithm is shown in Figure 5. Current Time (t i ) Current Time (t i ) Minute = 15 ~ 45 Minute = 45 ~ 60 T Zone > T Set T Zone > T Set Turn On Turn On Figure 5. Zero energy band Figure 6. Duty cycling Duty cycling is very similar to zero energy band. However, there is a difference due to the fact that the stop time is determined to meet the indoor condition of each specific cycle. The actual stop time is adjusted by using the feedback of the indoor

Energy Consumption [kwh] temperature between the pre-set minimum and maximum stop time to maintain the comfortable indoor condition. This study sets that the feedback period is from 15minute to 45 minute and minimum stop time is 15minutes 45minute to 60 minute within a cycle per hour. The algorithm is composed by using Erl, and shown in Figure 6. RESULTS AND DISCUSSION In this study, the total electric energy consumption(cooling energy) of the chillers, cooling tower, EHP, and DX coil that is used to remove cooling load is considered during cooling season(from July 1 to September 18). The cooling energy of each case is shown in Figure 7. 65000 60000 55000 50000 45000 40000 35000 Baseline Model Temp. Control Enthalpy Control Zero Energy Band Figure 7. Cooling energy of each cases Duty Cycling (1) Outdoor Air Control Strategies Cooling energy saving is 6,473 kwh(10.2%) in the temperature control, and 7,302 kwh(11.5%) in the enthalpy control in comparison to the baseline model. The cooling energy is reduced in both controls by increasing the outdoor air flow rate when it is beneficial to air conditioning, and it is analyzed that the cooling energy saving of the enthalpy control is greater than the temperature control due to the characteristics of the Korean summer humid climate. (2) AHU Control Strategies Cooling energy saving is 7,741 kwh(12.2%) in the zero energy band, and 9,264 kwh(14.6%) in the duty cycling in comparison to the baseline model. Both controls usually stop AHUs for 15 minutes to 30 minutes within an hourly cycle. However, the zero energy band sometimes keeps operating AHUs without stop while the duty cycling stops AHUs for at least 15 minutes, thus, it is analyzed that the cooling energy saving of the duty cycling is greater than the zero energy band. CONCULSION This study develops the baseline model of the target building through comparing the simulated energy consumption with the actual energy consumption by using the

energy simulation tool to apply control strategies. As similar control strategies, the building energy performance between temperature control and enthalpy control, and between zero energy band and duty cycling are comparatively analyzed. The results show that all controls cause the cooling energy to reduce in comparison to the baseline model. It is analyzed that the cooling energy saving of the enthalpy control is greater than the temperature control, and the cooling energy saving of the duty cycling is greater than the zero energy band. This study is expected to be used as basic data, in the selection of a control strategy, which is good building energy performance in the design phase, and in the use of the integration of similar controls as a single control mechanism. However, advanced study should be conducted to apply to actual buildings since this study conducts by using only the energy simulation tool. ACKNOWLEDGEMENT This work was partially supported by grant Smart green building from the Korea Institute of Energy Research in 2012. REFERENCES ASHRAE. 2002. ASHRAE's GUIDELINE 14-2002 for MEASUREMENT OF ENERGY AND DEMAND SAVING. Canbay C. S. et al. 2006. Evaluating performance indices of shopping centre and implementing HVAC control principle to minimize energy usage, Energy and Buildings. Cheon S. H. et al. 2012. Feasibility Study Energy Saving of Cooling System using Outdoor Air Control Strategies, The Society of Air-conditioning and Refrigerating Engineers of Korea. Elis P. G et al. 2007, Simulation of Energy Management System in EnergyPlus, 10th International IBPSA Conference. Huang W. Z. et al. 2006. Dynamic simulation of energy management control function for HVAC system in buildings, Energy Conversion and Management. Kim M. Y. et al. 2010. Energy Saving Characteristics of Enthalpy Control Outdoor Air Cooling using Dynamic Simulation, The Society of Air-conditioning and Refrigerating Engineers of Korea. Kwak Y. H. et al. 2010. Simulation-based Application of Energy Management System that Integrates Blind and Dimming Control Strategies, 8th International Symposium on Architectural Interchanges in Asia. Krarti M. ENERGY AUDIT OF BUILDINGS An Engineering Approach, CRC Press. U.S Department of Energy. 2008. M&V Guidelines: Measurement and Verification for Federal Energy Project, Version 3.0.