Herbert A. Ingley

Zone-level control algorithms based on occupancy information for energy efficient buildings

We examine the problem of how to use occupancy information of various fidelity to reduce the energy consumed in maintaining desired levels of thermal comfort and indoor air quality (IAQ) in commercial buildings. We focus on the zone-level control, where the control inputs to be decided are the supply air (SA) flow rate and the amount of reheat. We propose three control algorithms with varying information requirements: (i) POBOC, that requires long-horizon accurate prediction of occupancy and a model of the hygrothermal dynamics of the zone, (ii) OMBOC, that requires only occupancy measurement and a dynamic model, and (iii) Z-DCV, that requires only occupancy measurement. The first two strategies use a model predictive control framework to compute the optimal control inputs, while the third one is a pure feedback-based control strategy. Simulations with a calibrated model show that significant energy savings over a baseline controller, the kind usually used in existing buildings, is possible with the last two strategies, that is, even without occupancy prediction. Trade-offs between complexity and performance of the control algorithms are discussed.

Effect of various uncertainties on the performance of occupancy-based optimal control of HVAC zones

Model Predictive Control (MPC) has emerged as a potential control architecture for operating buildings in a more energy efficient manner. We study through simulations the effect of several sources of uncertainty that arise in the implementation of MPC on the energy consumption, thermal comfort, and indoor air quality (IAQ). These include occupancy profile, measurement errors and mismatch between the plant and its model that the control algorithm uses. Simulations are carried out for two extreme cases: a winter day with no solar load and a summer day with high solar load. The study shows that increasing fluctuations in occupancy, errors in measuring occupancy, and model mismatch have the strongest impact on the energy consumption. However, measurement errors in outside temperature and solar load does not have significant impact. Therefore, it is possible to improve the controller performance by using more accurate occupancy sensors. Furthermore, implementation cost can also be reduced by eliminating the sensors and prediction algorithms for predicting outside temperature and thermal loads without compromising the controller performance. Even with these uncertainties, MPC delivers 12-37% reduction of energy use over conventional control methods without affecting thermal comfort and IAQ.

A Review of Hydrogen Production Technologies

This paper describes an overview of the present status of the conventional hydrogen production technologies and some of the recent developments in the production of hydrogen using solar energy resources. It was found that conversion of fossil fuels and biomass, electrolysis of water using solar and wind energy, and direct solar conversion by thermochemical means are some of the most significant methods of H2 production. The technological status and economic analysis for commercial and near commercial technologies using renewable energy sources such as electrolysis using PV and solar thermal power, photochemical and photoelectrochemical hydrogen production, direct thermal decomposition of water, thermochemical cycles, and biological hydrogen production are outlined. Although fossil fuels are currently the least expensive and most widely used sources of hydrogen production, it is argued from an economic analysis that renewable sources of hydrogen are the most promising options for the future. Further, solar hydrogen becomes a storable fuel that is produced from this non-storable and intermittent source of energy.Copyright

Experimental evaluation of occupancy-based energy-efficient climate control of VAV terminal units

Results are presented from a nearly week-long experimental evaluation of a scalable control algorithm for a commercial building HVAC system based on real-time measurements of occupancy obtained from motion detectors. The control algorithm decides air flow rate and amount of reheat for each variable air volume terminal box based on real-time measurements of occupancy and space temperature. It is a rule-based controller, so the control computations are simple. The experiments showed that the proposed controller resulted in 37% energy savings over baseline on average without sacrificing indoor climate. In contrast to prior work that reports energy savings without a careful measure of the effect on indoor climate, it is verified that the controller indeed maintains indoor climate as well as the buildings baseline controller does. This verification is performed from measurements of a host of environmental variables and analysis of before/after occupant survey results. A complete system required to retrofit existing buildings with the controller is presented, which includes a wireless sensor network and a software execution platform. Two useful observations from this work are: (i) considerable energy savings—along with compliance with ASHRAE ventilation standards—are possible with simple occupancy-based control algorithms that are easy to retrofit; and (ii) these savings are attained with binary occupancy measurements from motion detectors that do not provide occupancy-count measurements. Results also show that there is a large variation in energy savings from zone to zone and from day to day.

A Kinetic Model for Ammonia Adsorption on a Titanium Nitride Surface

Recent developments aiming to microsensors based on floating gate field effect transistors (FGFET) were investigated for application in a rodent cage monitoring. Given that these sensors were on the forefront of technology, a theoretical model was developed for the ammonia sensor to further understand the chemical reaction taking place on its surface. The sensors were tested in a controlled environment, where the air quality was known. The magnitude and time of the response to different levels of ammonia were determined in the 50-100 ppm range. The reaction mechanism selected for the model which was best supported by the literature and the experiments was molecular adsorption of ammonia on a titanium nitride surface. The experimental results were fitted to the model to obtain the adsorption and desorption rate constants, the equilibrium concentration constant, equilibrium constant, and Gibbs free energy, which were 6.28 L/mol · s, 6.43 × 10-3 s-1, 976.7 L/mol, 39.04, and -9.25 kJ/mol, respectively. Based on these values, it was determined that the forward reaction, or adsorption, occurs spontaneously. There was good correlation between the theoretical model and the experimental results, indicating that the theoretical model was sufficient for this application.

Cumulative Exergy and Life Cycle Assessment of Ethanol Fuel Production From Corn via Dry Milling

This study represents a cumulative exergy and life cycle assessment of corn ethanol production via dry milling. The process under consideration includes the agricultural process for production of corn, transportation of corn and industrial process of ethanol production. The secondary process of production of pesticides and fertilizers is also taken into consideration. It is seen that the exergy content of ethanol produced from this process is 23.3 MJ per liter of ethanol produced. The non-renewable input was 7.5 MJ per liter. The overall production efficiency of the industrial process was found to be 49%. The life cycle assessment results showed that both the global warming potential and acidification potential are positive which means that the production of corn ethanol via dry milling contributes to the increase of greenhouse gases and acidification.Copyright