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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Performance assessment of radiant cooling system integrated with desiccant assisted DOAS with solar regeneration

The Radiant cooling system integrated with Dedicated Outdoor Air System (DOAS) is a viable substitution for conventional all air system in order to reduce primary energy consumption, as it decouples the cooling and ventilation task. In DOAS major portion of energy is consumed in cooling coil where it dehumidifies the process supply air. This study describes an alternate solution for dehumidification, with the substitution of the desiccant wheel with solar regeneration in place of a chilled water coil based dehumidifier. In this paper, simulations were carried out using EnergyPlus on a reference medium office building to investigate the contribution of solar energy towards the total energy consumption of desiccant assisted DOAS with radiant cooling system. To evaluate the system performance and energy saving potential, desiccant based DOAS is compared with cooling coil assisted DOAS integrated with Radiant cooling system. Simulations were carried out for different solar collector area to evaluate primary energy savings. Results indicate that from 7.4 % to 28.6 % energy saving (according to different collector area) can be achieved due to the solar regeneration in desiccant assisted DOAS, the impact of different solar collector area on potential of energy savings is also described.

42 ENGINEERING↗
DOE OSTI2023

Assessing thermal resilience of an assisted living facility during heat waves and cold snaps with power outages

Extreme hot and cold weather events are becoming more frequent, intense, and longer due to climate change. When these events occur coincidentally with power outages, the resulting extreme indoor temperatures pose a severe health hazard for occupants. This study conducted a holistic modeling and analysis of an assisted living facility, where senior residents live, to assess its thermal resilience performance under a six-day heat wave in 2015 and a three-day cold snap in 2021 with power outages. Impacts of 13 energy efficiency measures on thermal resilience and backup power capacity of the facility were evaluated. Three thermal resilience metrics: the SET (standard effective temperature) degree-hours, the Heat Index, and the Hours of Safety, were used and calculated from the EnergyPlus simulation models. Furthermore, major findings are: (1) the facility would suffer from extreme temperatures during the cold and hot events without a power supply, not meeting the passive survivability requirements; (2) most passive envelope measures improve thermal resilience for both hot and cold events, but making the building envelope airtight results in conflicting performance between the hot and cold events; (3) natural ventilation is an effective measure to mitigate summer indoor overheating; and (4) the energy efficiency package can reduce backup power capacity by 19% for the three-day cold snap. It is recommended that building technologies and design strategies be evaluated to consider co-benefits of energy use, thermal resilience, and backup power needs through building energy codes or policies for existing and new buildings, which are transitioning for decarbonization and climate resilience.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

An encoder–decoder LSTM-based EMPC framework applied to a building HVAC system

Numerous studies have demonstrated the benefit of economic model predictive control (EMPC) applied to building heating, ventilation, and air conditioning (HVAC) systems. However, the construction and training of predictive models for building HVAC systems are widely recognized as a key technological barrier preventing large-scale adoption of EMPC for buildings. In this work, an encoder–decoder long short-term memory-based EMPC framework is developed. The key advantage of the approach is that a model may be automatically generated from a list of inputs and outputs. From the definition of inputs and outputs, the constructed model may be trained and automatically embedded into the EMPC framework for real-time estimation and control. The overall end-to-end EMPC framework from model training to on-line estimation and control are described. To this end, the encoder–decoder model provides a natural framework for state estimation (encoder), which is required to provide an initial condition for the predictive model of EMPC (decoder). Closed-loop simulations using EnergyPlus are performed to demonstrate the approach. The simulated closed-loop system consists of a building zone from a multi-zone building, which is served by an air handling unit-variable air volume HVAC system. For the HVAC example considered, the trained encoder–decoder model can predict the indoor air temperature and HVAC sensible cooling rate of a building zone over a two-day horizon with high accuracy. Overall, we find that considering a time-of-use electric rate structure, the EMPC, which manipulates the zone temperature setpoint, can reduce the HVAC power consumption cost relative to keeping the zone temperature setpoint at its maximum value (i.e., minimum energy approach).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Evaluation of energy savings potential of variable refrigerant flow (VRF) from variable air volume (VAV) in the U.S. climate locations

Variable refrigerant flow (VRF) systems are known for their high energy performance and thus can improve energy efficiency both in residential and commercial buildings. The energy savings potential of this system has been demonstrated in several studies by comparing the system performance with conventional HVAC systems such as rooftop variable air volume systems (RTU-VAV) and central chiller and boiler systems. This paper evaluates the performance of VRF and RTU-VAV systems in a simulation environment using widely-accepted whole building energy modeling software, EnergyPlus. A medium office prototype building model, developed by the U.S. Department of Energy (DOE), is used to assess the performance of VRF and RTU-VAV systems. Each system is placed in 16 different locations, representing all U.S. climate zones, to evaluate the performance variations. Both models are compliant with the minimum energy code requirements prescribed in ASHRAE standard 90.1-2010 — energy standard for buildings except low-rise residential buildings. Finally, a comparison study between the simulation results of VRF and RTU-VAV models is made to demonstrate energy savings potential of VRF systems. The simulation results show that the VRF systems would save around 15–42% and 18–33% for HVAC site and source energy uses compared to the RTU-VAV systems. In addition, calculated results for annual HVAC cost savings point out that hot and mild climates show higher percentage cost savings for the VRF systems than cold climates mainly due to the differences in electricity and gas use for heating sources.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Angular selective window systems: Assessment of technical potential for energy savings

Static angular selective shading systems block direct sunlight and admit daylight within a specific range of incident solar angles. The objective of this study is to quantify their potential to reduce energy use and peak demand in commercial buildings using state-of-the art whole-building computer simulation software that allows accurate modeling of the behavior of optically-complex fenestration systems such as angular selective systems. Three commercial systems were evaluated: a micro-perforated screen, a tubular shading structure, and an expanded metal mesh. This evaluation was performed through computer simulation for multiple climates (Chicago, Illinois and Houston, Texas), window-to-wall ratios (0.15-0.60), building codes (ASHRAE 90.1-2004 and 2010) and lighting control configurations (with and without). The modeling of the optical complexity of the systems took advantage of the development of state-of-the-art versions of the EnergyPlus, Radiance and Window simulation tools. Results show significant reductions in perimeter zone energy use; the best system reached 28% and 47% savings, respectively without and with daylighting controls (ASHRAE 90.1-2004, south facade, Chicago,WWR=0.45). As a result, angular selectivity and thermal conductance of the angle-selective layer, as well as spectral selectivity of low-emissivity coatings, were identified as factors with significant impact on performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2014

Occupancy schedules learning process through a data mining framework

Building occupancy is a paramount factor in building energy simulations. Specifically, lighting, plug loads, HVAC equipment utilization, fresh air requirements and internal heat gain or loss greatly depends on the level of occupancy within a building. Developing the appropriate methodologies to describe and reproduce the intricate network responsible for human-building interactions are needed. Extrapolation of patterns from big data streams is a powerful analysis technique which will allow for a better understanding of energy usage in buildings. A three-step data mining framework is applied to discover occupancy patterns in office spaces. First, a data set of 16 offices with 10 minute interval occupancy data, over a two year period is mined through a decision tree model which predicts the occupancy presence. Then a rule induction algorithm is used to learn a pruned set of rules on the results from the decision tree model. Finally, a cluster analysis is employed in order to obtain consistent patterns of occupancy schedules. Furthermore, the identified occupancy rules and schedules are representative as four archetypal working profiles that can be used as input to current building energy modeling programs, such as EnergyPlus or IDA-ICE, to investigate impact of occupant presence on design, operation and energy use in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Comparison of software models for energy savings from cool roofs

For this study, a web-based Roof Savings Calculator (RSC) has been deployed for the United States Department of Energy as an industry-consensus tool to help building owners, manufacturers, distributors, contractors and researchers easily run complex roof and attic simulations. RSC simulates multiple roof and attic technologies for side-by-side comparison including reflective roofs, different roof slopes, above sheathing ventilation, radiant barriers, low-emittance roof surfaces, duct location, duct leakage rates, multiple substrate types, and insulation levels. Annual simulations of hour-by-hour, whole-building performance are used to provide estimated annual energy and cost savings from reduced HVAC use. While RSC reported similar cooling savings to other simulation engines, heating penalty varied significantly. RSC results show reduced cool roofing cost-effectiveness, thus mitigating expected economic incentives for this countermeasure to the urban heat island effect. This paper consolidates comparison of RSC's projected energy savings to other simulation engines including DOE-2.1E, AtticSim, Micropas, and EnergyPlus. Also included are comparisons to previous simulation-based studies, analysis of RSC cooling savings and heating penalties, the role of radiative heat exchange in an attic assembly, and changes made for increased accuracy of the duct model. Finally, radiant heat transfer and duct interaction not previously modeled is considered a major contributor to heating penalties.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2016

A simulation approach to estimate energy savings potential of occupant behavior measures

Occupant behavior in buildings is a leading factor influencing energy use in buildings. Low-cost behavioral solutions have demonstrated significant potential energy savings. Estimating the behavioral savings potential is important for a more effective design of behavior change interventions, which in turn will support more effective energy-efficiency policies. This study introduces a simulation approach to estimate the energy savings potential of occupant behavior measures. First it defines five typical occupant behavior measures in office buildings, then simulates and analyzes their individual and integrated impact on energy use in buildings. The energy performance of the five behavior measures was evaluated using EnergyPlus simulation for a real office building across four typical U.S. climates and two vintages. The Occupancy Simulator was used to simulate the occupant movement in each zone with inputs from the site survey of the case building. Based on the simulation results, the occupant behavior measures can achieve overall site energy savings as high as 22.9% for individual measures and up to 41.0% for integrated measures. Although energy savings of behavior measures would vary depending upon many factors, the presented simulation approach is robust and can be adopted for other studies aiming to quantify occupant behavior impact on building performance.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

A novel Variable Refrigerant Flow (VRF) heat recovery system model: Development and validation

As one of the latest emerging HVAC technologies, the Variable Refrigerant Flow (VRF) system with heat recovery (HR) configurations has obtained extensive attention from both the academia and industry. Compared with the conventional VRF systems with heat pump (HP) configurations, VRF-HR is capable of recovering heat from cooling zones to heating zones and providing simultaneous cooling and heating operations. Moreover, this could lead to substantial energy saving potential and more flexible zonal control. In this paper, a novel model is developed to simulate the energy performance of VRF-HR systems. It adheres to a more physics-based development with the ability to simulate the refrigerant loop performance and consider the dynamics of more operational parameters, which is crucial for representing more advanced control logics. Another key feature of the model is the introduction of component-level curves for indoor units and outdoor units instead of overall performance curves for the entire system, and thus it requires much fewer user-specified performance curves as model inputs. The validation study reflects good agreements between the simulated energy use from the new VRF-HR model and the laboratory measurement data across all operational modes at sub-hourly time steps. The model has been adopted in the official release of the EnergyPlus simulation program since Version 8.6, which enables more accurate and robust assessments of VRF-HR systems to support their applications in energy retrofit of existing buildings or design of zero-net-energy buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Potential benefits of cool walls on residential and commercial buildings across California and the United States: Conserving energy, saving money, and reducing emission of greenhouse gases and air pollutants

Solar-reflective “cool” walls reduce absorption of sunlight by the building envelope, which may decrease cooling load in warm weather and increase heating load in cool weather. Changes to annual heating, ventilation, and air conditioning (HVAC) energy use depend on climate, wall construction, wall orientation, building geometry, HVAC efficiency, and operating schedule. Changes to annual energy cost and energy-related emissions further vary with local energy prices and emission factors. In this work, we used EnergyPlus to perform over 100,000 whole-building energy simulations, spanning 10 different building categories, three building vintages, 16 California climate zones, and 15 United States (U.S.) climate zones. We find that cool walls yielded annual source energy, energy cost, and emission savings in all California climate zones and in warm U.S. (ASHRAE) climate zones. In California, annual whole-building HVAC energy cost savings were 4.0–27% in single-family homes, 0.5–3.8% in medium office buildings, and 0.0–8.5% in stand-alone retail stores. In warm U.S. climates—zones 1A (Miami, FL) through 4B (Albuquerque, NM)—annual HVAC energy cost savings were 1.8–8.3% in single-family homes, 0.3–4.6% in medium office buildings, and 0.5–11% in stand-alone retail stores. California and U.S. fractional source energy and emission savings were comparable to fractional energy cost savings. Per unit surface area modified, cool-wall savings often exceeded cool-roof savings because building codes typically prescribe much less wall insulation than roof insulation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Energy savings with outdoor temperature-based smart ventilation control strategies in advanced California homes

We simulated the energy performance of smart ventilation controls based on outdoor temperature in homes located in California climate regions, designed to comply with the 2016 Title 24, Part 6 California Energy Code prescriptive requirements. The smart controls shift ventilation rates in time, but ensure an annual occupant pollutant exposure equal to, or less than, what would be experienced in a home with a constant ventilation rate equal to the whole house target airflow in the ASHRAE Standard 62.2-2016. Annual simulations of previously developed prototype homes with validated ventilation models were conducted via co-simulation of EnergyPlus with CONTAM. Controller performance varied substantially by climate zone, airtightness and house prototype. Smart controls were generally ineffective in Climate Zone 1 (Arcata) due to its lack of a cooling season and low diurnal temperature swings. The most successful smart controls used parameters pre-calculated using an optimization routine. In order to better inform state energy policy, we also determined savings weighted by the amount of new home construction in each climate. The best controls averaged about one-third of ventilation-related energy savings that increased to about 48–55% when weighted. Annual average savings were about 650–700 kWh/year for the best controllers. The vast majority of site energy savings were for heating end-uses (>90% of total savings). Whole house ventilation rates increased between 0% and 42%, with typical increases in the 15–20% range. Finally, the best-performing control strategies shifted ventilation rates seasonally and modulated flows within each season. Peak concentrations during low ventilation times were kept below an exposure level of 3, well below the maximum of 5 required to avoid acute exposure issues.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2019

Validation on Aggregate Flexibility from Residential Air Conditioning Systems for Building-to-Grid Integration

To facilitate the integration of buildings to the power grid, battery-equivalent models have been proposed to characterize and quantify aggregate flexibility from building loads. An analytical method has been proposed to construct such a flexibility model for thermostatically controlled loads. Since this analytical method is derived from a simplified representation of building thermal dynamics, it is necessary to evaluate the resulting flexibility model in a more realistic context. This paper focuses on the validation of this analytical method for estimating aggregate flexibility from residential air conditioning (ACs) systems. A high-fidelity model is first developed to mimic thermal behaviors of a residential AC system through a co-simulation between Modelica and EnergyPlus. A population of virtual residential AC systems is then generated by randomizing parameters of the high-fidelity model. Finally, an aggregate flexibility model is constructed for the residential AC population using the analytical method and validated using results from simulation of the high-fidelity model. It is found that the flexibility estimated using the analytical method is with reasonable accuracy, but can be improved by explicitly incorporating heat gains into the method.

Huang, Sen↗
DOE OSTI2019

Roof-integrated radiative air-cooling system to achieve cooler attic for building energy saving

The building attic usually subjects to substantial solar heat gain and has much higher temperature compared to the conditioned living space during the day, especially in summer and in hot areas. Reducing attic temperature can reduce cooling energy consumption in buildings. However, conventional techniques such as cool roof or attic ventilation, suffer from either heating penalty in winter or limited attic temperature reduction. In this work, a new roof-integrated radiative air-cooling system is introduced, which couples radiative sky cooling with attic ventilation to reduce attic temperature. A radiative air cooler with 1.08 m 2 surface area is constructed using a recently developed daytime radiative sky cooling metamaterial [Zhai et al., Science 355, pp. 1062–1066, 2017]. Experimental tests show that sub-ambient air cooling is achieved throughout 24-h day-and-night cycle in a summer day with clear sky conditions. Depending on air flow rates, measured sub-ambient temperature reductions of air are 5–8°C at night and 3–5°C at noon under direct sunlight, respectively. An in-house model is first developed for the radiative air-cooling system, the model is then coupled with EnergyPlus to study annual energy saving of buildings. The performance of the radiative air-cooling system is compared with three reference systems: shingle roof, attic ventilation, and cool roof. Results show that for a single-family house, attic temperature can be substantially reduced by 15.5–21.0°C, varying with attic insulation level, compared to shingle roof on typical summer days. Compared to a shingle roof (solar reflectance 0.25, thermal emittance 0.9) residential building with attic insulations of R-30 (RSI-5.28), R-10 (RSI-1.76), and R-0.8 (RSI-0.14), the roof-integrated radiative air-cooling system can achieve annual cooling energy savings of 0.4–1.5 kWh/m 2 (4.6–18.8%), 1.2–3.6 kWh/m 2 (10.2–41.4%), and 3.7–11.8 kWh/m 2 (26.5–76.1%) respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Assessment of peak power demand reduction available via modulation of building ventilation systems.

Peak power demand strains electrical grids and increases cost of electricity generation, transmission and distribution infrastructure. Many studies have examined ways of reducing peak power demand, including modification of room air temperature setpoints or reduction of lighting levels. However, very few or no studies have examined the peak power reduction resource offered by temporary curtailment of building ventilation systems. For this reason, we conducted a simulation campaign in which we examined the resource offered by temporary ventilation curtailment in commercial buildings of different use types across the United States and in residences in the state of California, with the essential constraint that any changes resulted in air quality acceptable to occupants through additional ventilation to compensate for the curtailment. To do this, we employed previously validated building models implemented in the airflow and contaminant transport tool CONTAM and building thermal and systems modeling tool EnergyPlus, in some cases co-simulated. Overall, results show savings are highly dependent on building type and climate but range from 0–2 W/ft 2 and up to 40% of total peak building power demand. Depending on building type, this power shed can be conducted for 1.5–8 h before acute exposure or odor concerns are expected, assuming a safety factor of 2. This reduction is of the same magnitude as that offered by thermal control strategies such as setpoint increase, or from lighting reduction strategies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Robustness of energy performance of Zero-Net-Energy (ZNE) homes

Zero-net-energy (ZNE) homes produce an adequate amount of energy on-site to meet their energy demand based on source energy for an entire year. California building energy efficiency standards require new residential buildings started in 2020 to be ZNE. For various reasons, a home designed as ZNE may not achieve ZNE performance in real operation. Here we aimed to quantify the robustness of the energy performance of ZNE homes due to weather variability, climate change, and the uncertainty of occupant behavior. A single-family ZNE house, based on the optimal cost-effective design in three California climate zones, was used to develop the EnergyPlus simulation models. Weather variations were considered from a combination of the historical 30 years’ actual meteorological year (AMY) weather data, typical year weather data in TMY3, and future weather data based on Intergovernmental Panel on Climate Change scenarios. Three scenarios of occupant behavior from the energy perspective were defined to represent the uncertainty about occupants’ activities, comfort requirements, and their adaptive interactions with buildings and systems. In terms of annual source energy, the simulation results of the ZNE homes showed: (1) a decrease of 23–38 percent for occupants with energy austerity behavior and an increase of 120–130 percent for occupants with energy wasteful behavior, compared with the baseline assumption of normal occupants; (2) a variation range of –15 percent to +14 percent for the results using 30-year AMY weather data compared with the baseline results using TMY3 weather data; (3) an increase of 10–13 percent with future weather in Fresno and Riverside and a decrease of 15 percent with San Francisco; and (4) climate change can reduce the gap between the austerity and wasteful consumption. These findings provide insights into how ZNE homes may perform in reality and inform architects, engineers, occupants, and policymakers to pay more attention to occupant behavior on design, operation, and regulations of ZNE homes to ensure energy performance robustness.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

An improved method for direct incident solar radiation calculation from hourly solar insolation data in building energy simulation

Solar radiation considerably influences the energy consumption of buildings and the power production of building integrated photovoltaic (BIPV) systems. Hourly solar insolation (Wh/m 2 ), represented as the amount of solar irradiance collected on the ground during a 1-h period, is the most common solar radiation data available and widely used in weather files applied in building energy modeling programs (BEMPs). Because the solar beam and position vary over time, the use of hourly insolation data as the input might result in errors in the estimation of the direct incident solar radiation on a particular surface. In this study, methods used in BEMPs for direct incident solar radiation calculations are first analyzed, and an improved method adopting a new algorithm for estimating the solar irradiance is proposed. Furthermore, the algorithm assumes that the solar irradiance changes linearly within a 1-h period and can be estimated based on the solar irradiance at the half clock and slope. The collected direct normal solar irradiance data of 2016 from eight solar radiation stations in China were used to demonstrate the proposed method and evaluate its performance by comparing the results with those from three conventional methods used in BEMPs along with the ground truth measurements. In addition, in this study, factors affecting the accuracy of the calculation results are explored. The results of the estimated direct incident solar radiation show that the proposed method achieves the best accuracy, followed by the methods used in DOE-2, EnergyPlus, and DeST. The proposed method guarantees that the hourly direct solar insolation will remain the same and reflects the variation in the direct solar irradiance across a 1-h time frame. The proposed method can be adopted in BEMPs to improve the accuracy of the solar radiation calculation, thereby improving the accuracy of the simulated building performance and the BIPV production.

14 SOLAR ENERGY↗
DOE OSTI2020

Automated fault detection of residential air-conditioning systems using thermostat drive cycles

Residential air conditioning equipment comprises a significant portion of the total energy consumption of a home. Unfortunately, air-conditioning systems can be susceptible to faulty operation either from installation errors or faults that accrue over the equipment’s lifetime. This paper presents a novel automated fault detection algorithm for residential air-conditioning systems that can alert the homeowner of the presence of these faults. The proposed algorithm utilizes only the home’s thermostat and outside air temperature to perform automated fault detection over the course of the equipment’s lifetime, including immediately after installation. The algorithm uses an extended Kalman filter approach to identify a three-resistor, two-capacitor (3R2C) electrical equivalent thermodynamic model. The identified 3R2C model is used to predict cooling times during a testing period comprising of a series of thermostat drive-cycle experiments. We tested the algorithm on an EnergyPlus™ model of a typical residential building in Orlando, Florida. Duct faults, indoor airflow faults, and refrigerant undercharge faults were introduced into the building model one at a time. The algorithm was able to accurately determine duct-leak faults, 40% airflow faults, 40% undercharge faults, and no-fault cases with an accuracy of 70%, 77%, 82%, and 87%, respectively.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Data-driven building energy modeling with feature selection and active learning for data predictive control

Three gaps impede the development of cost-effective and accurate data-driven building energy modeling/models (DBEM) for energy forecasting and predictive control strategies. Gap 1: data bias is common in building operation data, but this topic is hardly studied in DBEM; Gap 2: high data dimensionality is common in DBEM, but a systematic and scalable methodology is lacking to solve the problem; Gap 3: the interactions between data bias and high dimensionality have not been systematically studied for DBEM and predictive control in buildings. In this work, to address the three gaps mentioned above, we develop a framework that integrates active learning and feature selection for DBEM used for whole building data predictive control (or DPC, which is a branch of model predictive control). The framework provides a systematic methodology and automatic workflow that starts with raw data from building automation systems to the establishment of data-driven energy models for DPC controllers. The developed strategies and framework are evaluated in a virtual testbed based on EnergyPlus and BCVTB. Improved performance and reduced computational complexity are observed from the DBEM built with the developed framework, as well as the DPC controller based on that DBEM, indicating the effectiveness of the developed framework.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗