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At least 1,711 records · Page 95

Peak load reduction and load shaping in HVAC and refrigeration systems in commercial buildings by using a novel lightweight dynamic priority-based control strategy

Reducing peak power demand in a building can reduce electricity expenses for the building owner and contribute to the efficiency and reliability of the electrical power grid. For the building owner, reduced expenses come from the reduction or elimination of peak power charges on electricity bills. For the power system operator, reducing peak power demand leads to a more predictable load profile and reduces stress on the electric grid system. Herein we present a computationally inexpensive, dynamic, and retrofit-deployable control strategy to effect peak load reduction and load shaping. The effectiveness of the control strategy is examined in a simulation with 80 air-conditioning units and 40 refrigeration units. The results show that a peak demand reduction of 60 kW can be achieved relative to peak demand in a typical set point–based approach. The proposed strategy was deployed in a gymnasium building with four rooftop HVAC units, where it showed over 15% peak demand (kW) reduction savings while maintaining or lowering energy consumption (in kilowatt-hours) relative to the set point–based thermostat controls.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Utilizing commercial heating, ventilating, and air conditioning systems to provide grid services: A review

The modern power grid faces multiple challenges due to an increase in the adoption of renewable generation, such as dynamically balancing supply and demand at different time scales. Demand side management in buildings plays a vital role in achieving this balance because buildings can provide grid services through a variety of building assets. However, the development of grid-interactive, efficient buildings is still in its infancy, and a systematic and holistic understanding of grid service delivery strategies in terms of energy efficiency, load shifting, load shedding and load modulating is still limited. This paper is a comprehensive review of the development and application of building-level control strategies for utilizing heating, ventilating, and air conditioning systems to provide grid services. These strategies have been investigated through numerical and experimental studies. Control algorithms, such as heuristic rule-based control and model-based control, have been used to enable the automatic control delivery of grid services. The advantages and disadvantages of the strategies are summarized and discussed. Finally, research trends are also identified, which include considering predicted mean vote-based and occupant-based thermal comfort, modeling of occupant behavior, integrating power grid operations with building control, and combining different demand flexibility modes in the control design.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Stochastic scheduling for commercial building cooling systems: considering uncertainty in zone temperature prediction

Here, this paper presents the first attempt to address the uncertainty in zone temperature prediction with stochastic optimization. The uncertain zone temperature is a process uncertainty and has not been considered in the existing stochastic optimization for building control. To fill this gap, we proposed a novel formulation of stochastic optimization to handle process uncertainty in building control. Specifically, we first examined the accuracy of a typical linear model for predicting zone temperature. We then formulated the scheduling of the building cooling system as a stochastic optimization problem over a 24-hour look-ahead period to minimize the electricity cost of the studied building cooling system. After that, we applied the proposed stochastic load scheduling (SLS) to a direct expansion (DX) cooling system that serves a medium office building. Through simulation with a detailed building energy simulation software, EnergyPlus, we evaluated the operational cost and the thermal comfort compared with a deterministic load scheduling. The operation cost of scheduling was found to vary with the level of zone temperature prediction uncertainty. The proposed SLS can mitigate the impacts of uncertain zone temperature predictions on both operational cost and thermal comfort. The evaluation results indicate that the proposed SLS works better when the uncertainty level is more significant.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Intra-catalyst CH 4 oxidation pathways on a Pd/Al 2 O 3 /CeZrO x -based commercial catalyst and implications on NO x conversion profiles for a natural gas vehicle exhaust under lambda modulation

The performance of a three-way catalyst (TWC) in natural gas-powered vehicles is enhanced by periodic changes in air-to-fuel ratio (λ-modulation). The reaction networks and sequences inside the catalyst that facilitate such enhanced performance have not been extensively investigated. Here, this work applied intra-catalyst measurements (SpaciMS) to analyze the transient spatiotemporal gas concentrations inside a Pd-based TWC to establish relationships between CH 4 , NO x , CO and H 2 conversion pathways. Steam reforming and partial oxidation were revealed to be the main CH 4 conversion routes. The cyclic rich-lean conditions combined with the oxygen storage capacity (OSC) of the TWC generate reduced and oxidized zones that are constantly moving within the catalyst, changing the dominant chemical reactions occurring on the surface. In the reduced zones, OSC is depleted while CH 4 is converted through steam reforming and NO x is converted through reactions with H 2 , CO, and other surface-bound reducing fragments formed by CH 4 conversion. In the oxidized zones, OSC is replenished, CH 4 is converted by partial oxidation, and H 2 , CO, and NH 3 are oxidized. The length of lean-rich phases impacts the catalyst performance significantly; too short or too long of a rich or lean phase can lower the overall conversion of reactive species. An inhibition of CH 4 conversion was observed during the rich phase possibly due to CO-poisoning of active sites. The intra-catalyst measurements revealed that the catalyst consists of three distinct reaction zones and their lengths vary with modulation conditions. Various modulation frequencies, amplitudes, λ-centers, and temperatures were investigated which allowed an understanding of how these parameters affect the reaction zones and catalyst utilization. Understandings from this work can enable adaptive λ-control strategies to optimize the overall TWC performance over a range of vehicle operating conditions.

Lean-Rich cycling↗

Comparative analysis of temperature dependent properties of commercial nuclear fuel pellet and surrogates undergoing cracking: A review

A variety of normal and accident scenarios can generate thermal stresses enough to cause cracking in light water reactor (LWR) fuel. To better understand this behavior, cracking experiments have been carried out to induce thermal gradients in fuel pellets via induction heating and direct resistance heating. In this study, Ceria (CeO 2 ) and yttria stabilized zirconia (YSZ) pellets were chosen as a surrogate fuel material for uranium dioxide (UO 2 ). Induction heating was done using copper coils and molybdenum susceptors which heated the surrogates to a threshold temperature that is sufficiently high for the fuel material to conduct current. Thereafter, direct resistance heating was achieved by passing current through the specimen using a DC power supply to introduce volumetric heating to replicate reactor operating conditions. Simultaneous real-time dual imaging of the ceria pellet surface has been designed using optical and infra-red camera system to capture images of cracks and full-field temperature gradients on pellet. It was observed that YSZ pellets need a much higher voltage-current for volumetric heating and do not exhibit the cracking pattern as ceria and UO 2 , hence YSZ was ruled out for further consideration. Ceria was found to be an appropriate surrogate for UO 2 . Furthermore, the experimental set up and test conditions demand the need to primarily understand the thermo-physical, mechanical and optical properties of UO 2 and the surrogates. Thus, it is essential to have an in-depth knowledge about the various temperature dependent properties of UO 2 and CeO 2 for establishing a comparative analysis between the surrogate and UO 2 for conducting experiments.

36 MATERIALS SCIENCE↗

Utilization of waste heat from a commercial GT for freshwater production, cooling and additional power: Exergoeconomic analysis and optimization

In this work, a multigeneration system is proposed for power, cooling and freshwater production. The waste heat from a SIEMENS SGT6-2000E GT is utilized to drive a supercritical CO 2 recompression Brayton cycle (SCRBC) and multi-effect desalination (MED) with thermal vapor compressor (TVC), while the waste heat from the pre-cooler of the SCRBC is utilized to drive an absorption cooling cycle. Detailed thermodynamic, exergy and exergoeconomic analyses are performed for the proposed multigeneration system using Engineering Equation Solver (EES). A sensitivity study is also performed to study the effects of the main operational parameters on the proposed system performance. Finally, multi-objective optimization using a genetic algorithm approach in EES is carried out to reach the optimal design. The proposed system can consume 34.2% less energy input and reduce CO 2 emission by 39.3% compared to the stand-alone systems for power, cooling and freshwater production. The results show that the energy utilization factor and exergy efficiency of the proposed system are improved by 33.6% and 14.3%, respectively, while the total unit product cost is reduced by 11.3% compared to the stand-alone GT cycle. Further, from exergoeconomic optimization, the proposed system can produce 132.4 MW of power, 7.09 MW of cooling and 650 kg/s of freshwater at energy utilization factor of 57.5%, exergy efficiency of 39.7% and total unit product cost of 16.3 $/GJ.

42 ENGINEERING↗

Model-based predictive control of multi-zone commercial building with a lumped building modelling approach

Here this study investigates the applicability of a lumped building modeling approach to model-based predictive control (MPC) to alleviate the complex modeling process of the grey-box multi-zone building model. Based on experimental data, two building models were estimated in this study. The detailed model as a reference case and a lumped model were estimated with decentralized and conventional approaches, respectively. Then, simulations were performed with two boundary conditions, including the comfort bound and electricity cost structure. The performances of the MPC with the detailed and lumped models were analyzed compared to the feedback control. More savings was achieved with a larger comfort bound and more aggressive electricity cost structure. The savings potential of the proposed lumped model approach was not as high as that of the detailed model. However, the proposed method yields good control performance, whose savings was approximately 8.6% over that of feedback control. These results suggest that the proposed method can be used to facilitate MPC implementation in multi-zone building applications.

42 ENGINEERING↗

Sensor cost-effectiveness analysis for data-driven fault detection and diagnostics in commercial buildings

Data-driven building fault detection and diagnostics (FDD) is heavily dependent on sensors. However, common sensors from Building Automation Systems are not optimized to maximize accuracy in FDD. Installing additional sensors that provide more detailed building system information is key to maximizing the performance of FDD solutions. Here in this paper, we present a sensor cost analysis workflow to quantify the economic implications of installing new sensors for FDD using the concept of sensor threshold marginal cost (STMC). STMC does not represent actual sensor cost. Rather, it represents a target cost based on the economic benefit that would be realized through improved FDD performance and one or more specified economic criteria. We calculate STMCs for multiple possible fault types and use fault prevalence information to aggregate STMCs into a single dollar value to determine the cost-effectiveness of a potential sensor investment. We conducted a case study using Oak Ridge National Laboratory's Flexible Research Platform (FRP) test facility as a reference. The case study demonstrates the feasibility of the analysis and highlights the key cost considerations in sensor selection for FDD. The results also indicate that identifying and installing the few key sensor(s) is critical to cost-effectively improve FDD performance.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗