A peak-load reduction computing tool sensitive to commercial building environmental preferences
Introduction
Demand Response (DR), as an option for electric utility peak load management, has gained significant attention in the recent past which can decrease both energy and power consumptions [1], [2]. Most large commercial buildings (100,000 sq. ft. or more) are equipped with Energy Management Systems (EMS) which provide opportunities for peak load reduction [3], [4]. The use of EMS is not widespread in small and medium-sized commercial buildings (<100,000 sq. ft.) [3]. Due to limited availability of DR methods and tools, building owners typically miss building specific DR opportunities [5]. They do not approach DR strategy development systematically and are unable to correctly estimate DR effectiveness [6], [7]. The best DR strategies for any building should take into account potential for peak load reduction, electrical energy savings, customer comfort and economics [8]. Overly stringent Heating, Ventilation and Air Conditioning (HVAC)-based DR requirements not only affect occupant comfort and convenience but also create a new peak at off-peak times when DR events end [8]. This new peak also needs to be taken into account for any DR planning. However, building owners usually perform minimal analysis of their load data and adapt DR strategies as described in [8].
In this study, a particular attention is given to the HVAC load. Authors in [9] identify that commercial buildings in the U.S. are usually overcooled and it is a cultural practice to purposely set a low temperature. Authors in [8] discuss HVAC-based DR strategies including global temperature adjustment of zones and systemic adjustments to the air distribution and cooling systems. Findings in [10], [11], [12] indicate that among HVAC based DR strategies, global temperature adjustment of zones, where entire facility cooling set points are raised to some absolute values, best achieves DR goal. Authors in [13] summarize energy savings results from different case studies involving global summer set point temperature increase. However, authors in [14] show that applying global set point changes during peak hours with pre-cooling efforts to a large multi zone commercial building results in poor distribution of HVAC capacity across zones and an uneven distribution of occupant satisfaction across the building. Authors in [14] design a HVAC control strategy to adapt a building’s DR on a zone-by-zone basis for planning in advance HVAC operation to balance energy costs, greenhouse gas emissions and occupant thermal comfort.
A recent study indicates that building occupants rank thermal comfort to be of similar importance to visual and acoustic comfort and indoor air quality [15]. Authors in [16] present a review of human thermal comfort in the built environment and identify a gap in thermal comfort studies in relation to interdisciplinary research. Studies [17], [18], [19] propose thermostat strategies to understand the trade-off between energy consumption and thermal comfort. Authors in [20] investigate the relationship between building insulation and air conditioning unit supply air temperature to provide better comfort. Authors in [21] identify various factors affecting building thermal comfort and building material to improve it. Authors in [22] investigate energy saving potential of PMV based control in glass façade buildings and suggest careful design of components of glass facade can achieve thermal comfort and energy savings. Authors in [23] control the indoor air velocity to maintain the PMV index within thermal comfort range to achieve energy savings. Authors in [24] perform thermal comfort simulation by integrating building thermal behavior analysis with PMV thermal comfort model to identify appropriate low-energy cooling opportunities which achieve better thermal comfort. Authors in [25] assess summer comfort of a modeled building which depends upon thermal performance of the building envelope with external climate and internal gains and losses which intervene with comfort criteria. Authors in [26] develop a living space thermal-comfort regulator which maintains PMV index within specified limits.
Literature review reveals that an optimal control of each thermal zone’s cooling load is needed since all thermal zones do not behave the same, they may not be able to evenly share the DR shed burden. Higher increase in the cooling set points for zones with high solar gains drastically effects occupant thermal comfort. To address the above knowledge gaps the authors propose to design a peak load reduction computing tool for commercial building DR which provides optimal control of each thermal zone’s cooling load in a medium-sized office building and an insight into how thermal comfort is related to peak load and energy consumption. The tool maximizes building’s economic benefits while being sensitive to occupant needs. Following the DR event, HVAC systems use extra energy to remove the heat gained during reduced service levels of DR event to bring back the system to normal conditions and hence experience rebound. This rebound is investigated and a means to mitigate this impact is suggested.
Section snippets
Methodology of the study
The study presents a peak load reduction computing tool for commercial building DR – validated by simulation – and investigates the impact of raising cooling set point schedule for a simulated medium-sized office building during DR event on each thermal zone’s PMV index, building peak load and energy consumption. The study has been performed for the summer season when cooling load is high during afternoon hours in an office building. In this study, EnergyPlus, a building energy simulation tool,
Simulation results and discussions
Simulations are performed for a summer day. Note that the façade design for the three floors of the simulated medium-sized office building is same; the main climatic element, solar radiation, affects the building occupant thermal comfort as it includes the amount of heat transferred to the building. The simulated medium-sized office building’s north axis is specified to true North. The 4-perimeter zones on all floors are exposed to external environment as they have exterior walls and windows,
Conclusions
Thermal zones do not behave the same; hence a global temperature adjustment will result in poor distribution of HVAC capacity across zones and an uneven distribution of occupant satisfaction across the building. The peak load reduction computing tool for commercial building DR developed in this study optimally controls cooling set points of each thermal zone in a simulated medium-sized office building while maintaining occupant thermal comfort and achieves optimized peak load savings. The PMV
Acknowledgement
This work is supported in part by the U.S. National Science Foundation under Grant# ECCS-1232076.
References (37)
- et al.
The cost of over-cooling commercial buildings in the United States
Energy Build
(2015) Thermal comfort and building energy consumption implications – a review
Appl Energy
(2014)- et al.
Literature survey on how different factors influence human comfort in indoor environments
Build Environ
(2011) A review of human thermal comfort in the built environment
Energy Build
(2015)- et al.
Optimized monthly-fixed thermostat-setting scheme for maximum energy-savings and thermal comfort in air-conditioned spaces
Appl Energy
(2008) Energy efficient fuzzy based combined variable refrigerant volume and variable air volume air conditioning system for buildings
Appl Energy
(2010)Numerical simulation of cooling energy consumption in connection with thermostat operation mode and comfort requirements for the Athens buildings
Appl Energy
(2011)Transient analysis and improvement of indoor thermal comfort for an air-conditioned room with thermal insulations
Ain Shams Eng J
(2015)Role of building material in thermal comfort in tropical climates – a review
J Build Eng
(2015)- et al.
Building envelope regulations on thermal comfort in glass facade buildings and energy-saving potential for PMV-based comfort control
Build Environ
(2011)
An approach to building energy savings using the PMV index
Build Environ
Thermal-comfort analysis and simulation for various low-energy cooling-technologies applied to an office building in a subtropical climate
Appl Energy
Design of a fuzzy system for living space thermal-comfort regulation
Appl Energy
Occupant performance and building energy consumption with different philosophies of determining acceptable thermal conditions
Build Environ
Cited by (33)
A Q-learning based optimization method of energy management for peak load control of residential areas with CCHP systems
2023, Electric Power Systems ResearchReduction and transformation of energy use data for end-user group categorization in dormitory buildings
2020, Journal of Building EngineeringCitation Excerpt :Occupant intervention aims to encourage occupants to have pro-environmental behaviors (e.g., energy use feedback, energy saving tips) [9,10]. Among the previously mentioned measures, considerable attention [7,11–13] has been given to HVAC system control because they consume almost half the energy used in buildings [14,15]. Also, energy-efficient operation of HVAC systems has proven to be the most promising way to reduce energy consumption in buildings [16,17].
Energy efficiency of end-user groups for personalized HVAC control in multi-zone buildings
2020, EnergyCitation Excerpt :A wide variety of HVAC control strategies have been proposed to reduce energy consumption in buildings [16–18]. The most common control parameters in HVAC simulation and control are the temperature setpoint [16] and operation time (i.e., on/off time) [17]. Researchers hypothesize that personalizing the operation of HVAC systems depending on thermal zone reduces energy consumption while minimizing the thermal discomfort of occupants in indoor environments [19].