This paper presents an economic analysis of stationary and dual-axis tracking photovoltaic (PV) systems installed in the US Upper Midwest in terms of life-cycle costs, payback period, internal rate of return, and the incremental cost of solar energy. The first-year performance and energy savings were experimentally found along with documented initial cost. Future PV performance, savings, and operating and maintenance costs were estimated over 25-year assumed life. Under the given assumptions and discount rates, the life-cycle savings were found to be negative. Neither system was found to have payback periods less than the assumed system life. The lifetime average incremental costs of energy generated by the stationary and dual-axis tracking systems were estimated to be $0.31 and $0.37 per kWh generated, respectively. Economic analyses of different scenarios, each having a unique set of assumptions for costs and metering, showed a potential for economic feasibility under certain conditions when compared to alternative investments with assumed yields.

A grid-connected dual-axis tracking photovoltaic (PV) system was installed in the Upper Midwest of the U.S., defined as a cold region, and then evaluated and monitored for a 1 year period. This system serves as a real-world application of PV for electricity generation in a region long overlooked for PV research studies. Additionally, the system provides an opportunity for research, demonstration, and education of dual-axis tracking PV, again not commonly studied in cold regions. In this regard, experimental data for the system were collected and analyzed over a 1year period. During the year of operation, the PV system collected a total of 2173 kWh/m(2), which equates to 5.95 kWh/m(2) on average per day, of solar insolation and generated a total of 1815 kWh, which equates to an energy to rated power ratio of 1779 kWh/kW(p) of usable AC electrical energy. The system operated at an annual average conversion efficiency and performance ratio of 11% and 0.82%, respectively, while the annual-average conversion efficiency of the inverter was 92%. The tracking system performance is also compared to a stationary PV system, which is located in close proximity to the tracking PV system. The tracking system's conversion efficiency was 0.3% higher than the stationary system while the energy generation per capacity was 40% higher although the PV module conversion efficiencies were not significantly different for the two systems.

This paper presents the heat transfer characteristics of a stationary PV system and a dual-axis tracking PV system installed in the Upper Midwest, U.S. Because past solar research has focused on the warmer, sunnier Southwest, a need exists for solar research that focuses on this more-populated and colder Upper Midwest region. Meteorological and PV experimental data were collected and analyzed for the two systems over a one-year period. At solar irradiance levels larger than 120 W/m2, the array temperatures of the dual-axis tracking PV system were found to be lower than those of the stationary system by 1.8 °C, which is a strong evidence of the different heat transfer trends for both systems. The hourly averaged heat transfer coefficients for the experiment year were found to be 20.8 and 29.4 W/m2 °C for the stationary and tracking systems, respectively. The larger heat transfer coefficient of the dual-axis tracking system can be explained by the larger area per unit PV module exposed to the ambient compared to the stationary system. The experimental temperature coefficients for power at a solar irradiance level of 1000 W/m2 were −0.30% and −0.38%/ °C for the stationary and dual-axis tracking systems, respectively. These values are lower than the manufacturer's specified value −0.5/ °C. Simulations suggest that annual conversion efficiencies could potentially be increased by approximately 4.3% and 4.6%, respectively, if they were operated at lower temperatures.

Energy-efficient building design, especially in residential construction, strongly relies on thermophysical properties of the building envelope and its materials. With increasing insulation values in construction practice, the focus turns to the prevention of thermal bridging as well as airtight construction to reduce unwanted heat transfer through the envelope. The building envelope serves multiple functions apart from heat retention that are tied to structure, safety, and visual appeal or aesthetics; and the stakeholders in the design and construction process all have different decision criteria. Supported by disciplinary education separating engineering and architecture and based on the dogma of Modern Architecture, most contemporary architects consider slender details and clear separation of architectural elements to be intrinsic to good architectural design thinking. The engineer involved in the design of the HVAC systems considers the envelope as the basis for the load calculation, whereas the construction engineer and project manager prioritize cost, maintenance, and constructability. Tradeoffs have to be considered and possibly a new proportional relationship has to be found for a building envelope between the increased need for insulation, seals and gaskets, structural necessities, and exterior appearance; and ideally without penetrating elements that could conduct heat from hot to cold. Considering current construction techniques, conceptual design thinking, proportional relationships, and building science, this paper analyzes energy efficient envelope construction methods and details strategies of the U.S. DOE 2009 Solar Decathlon homes. The paper will evaluate the influence that envelope construction methods which prevent thermal bridges have on the potential to develop a coherent exterior and interior appearance, thermal performance, and constructability to develop a balance between materials and thermodynamics. Different value systems exist within the design team related to the building envelope and lead to a trade-off pentagram. For architects, the envelope carries aesthetic, symbolic, and sometimes even cultural meaning, while it is just one of many parameters for the load calculation of the HVAC engineer and a means to protect the structural elements of a building and to protect against water and fire for the construction engineer. The paper thus concludes with a design recommendation of how to reduce thermal bridging in the building envelope and still maintain aesthetic values pertinent to architectural pedagogy.

A huge barrier to wider adoption of building automation systems (BAS) in commercial buildings is their complex, time-consuming, and often proprietary installation, configuration, and commissioning process. A framework for plug-and-play HVAC air-handling unit (AHU) control systems is proposed in this study. This is the foundation and the first step toward a plug-and-play HVAC control system that will eventually lead to self-configuring HVAC control systems for automatic BAS setup, configuration, commissioning, and possible automatic detection and repair of potential controls problems. This framework is built on commercially available smart transducers that are compatible with the IEEE 1451 family of standards. To solve the critical issue of resolving system ambiguity, a structural pattern recognition algorithm is developed to automatically recognize temperature sensor locations in an AHU. The algorithm can be a critical part of a plug-and-play or self-configuring HVAC control system in establishing a binding list of control system input/output and automated assignment and verification of the binding list.This work consists of two parts. Part I, the present paper, reviews existing technologies and discusses technology gaps for incorporating plug-and-play and self-configuring concepts into HVAC control systems. A plug-and-play framework for an AHU is then proposed. Part II (Zhou and Nelson 2011), a companion paper, develops a structural pattern recognition algorithm to automatically identify AHU temperature sensor locations and a scheme to resolve AHU system ambiguity. A prototype of the plug-and-play framework for an AHU was built and tested in an experimental facility. Tests are conducted at various initial conditions, environmental temperatures, and chilled-water system configurations to demonstrate the feasibility of the framework and the robustness of the pattern recognition algorithm.

Experiments conducted on two identical real heating, ventilation and air-conditioning (HVAC) systems were used to compare the performance of an adaptive fuzzy logic controller (AFLC) to that of a conventional proportional, integral and derivative (PID) controller. Two types of experiments were conducted, one with changing set point for supply air temperature and the second with changing supply air flow rate. To remove bias between the testing systems, the controllers were switched from one system to the other.The experimental results indicated that genetic algorithms and evolutionary strategies can be successfully used to develop an adaptive fuzzy logic controller for HVAC applications, potentially saving energy and reducing deviations in the supply air temperature from its set point, but with higher actuator travel distance. (C) 2011 Elsevier B.V. All rights reserved.

A plug-and-play framework for an HVAC air-handling unit (AHU) control system is proposed in Part I of this work (Zhou and Nelson 2011). In Part II, a structural pattern recognition algorithm to automatically recognize temperature sensors is developed. A prototype of the framework was built and used in experiments designed to test the validity of the method for automatically recognizing the locations of temperature sensors in an AHU. The experiments demonstrated the ability of the prototype to successfully identify the location of each of eleven temperature sensors located at various positions in an AHU running under diverse conditions.

In this paper, an evolutionary strategy approach is presented for tuning an AFLC to control the outlet temperature of a cooling coil. Two different methods, modifying scaling factors and modifying fuzzy membership functions, are studied. The simulation and real-time tests showed that evolutionary strategy techniques work well for evolving these AFLC parameters.

In this study, an energy balance and uncertainty analysis was performed on a standard chilled water cooling coil mounted in a commercial Air Handling Unit operating under typical conditions with a conventional PID loop control. Two different sets of relative humidity transmitters and temperature sensors (high and low accuracy) were evaluated for measuring relative humidity and temperature of the moist air entering and exiting a cooling coil. The impact of the different errors in these sensors and installation on the uncertainty in the energy calculation is presented. In addition, the affects of the transient behavior inherent in the cooling coil with respect to the energy balance was evaluated. This study gives insight to how an energy balance test coupled with an uncertainty analysis could be used to verify the cooling coil system performance and instrumentation output. Experimental results showed that the transient behavior inherent to the cooling coil had a negligible affect on the energy balance calculations and that by employing high accuracy instrumentation and careful installation, expected energy balance results could be attained.

An adaptive approach to control a water valve for a cooling coil, called an adaptive fuzzy logic controller (AFLC), is developed and validated in this study. The AFLC calculates the error between the supply air temperature and the supply air temperature set point for air in an air handling unit (AHU) of a heating, ventilating, and air conditioning (HVAC) system and continues to improve the fuzzy controller parameters to minimize the error. The AFLC uses genetic algorithms (GAs) to improve the fuzzy rule matrix and fuzzy membership functions for the AHU in HVAC systems. In this paper, the application of genetic algorithms for developing the AFLC is presented. After a brief background on fuzzy logic controllers and GA theory, the use of GAs is explained. Three methods of modifying the fuzzy rule matrix using the GAs are presented along with simulation and real-time experimental results. Experimental results indicate that GAs can be successfully applied to modify an AFLC rule matrix to achieve a better controller.

Relative humidity sensors are common components in building heating, ventilating, and air-conditioning (HVAC) systems, and their performance can significantly impact energy use in these systems. Therefore, a study was undertaken to test and evaluate the most commonly used relative humidity sensors in HVAC systems, namely, the capacitive and resistive types. The procedures presented here provide a methodology to test and evaluate duct-mounted relative humidity sensors for accuracy, linearity, hysteresis, and repeatability.The test and evaluation procedures presented in this paper are all inclusive in that they range from procuring the humidity sensors to comparing the accuracy of humidity sensors. Specifically, a procedure is presented to both procure humidity sensors from the manufacturers and to maintain quality control by controlling the storage, handling, and movement of the sensor while documenting time and date at each step. Further it describes the apparatus and instrumentation, along with test conditions, used to perform experiments on humidity sensors. Additionally, it outlines a detailed experimental procedure to evaluate the accuracy of humidity sensors. Finally, a discussion is presented on analyzing and comparing the accuracy of humidity sensors by using test data. The results of the accuracy test and evaluation of the humidity sensors and the results of the linearity, repeatability, and hysteresis evaluation will be presented later.

This is the final paper of a three-part series reporting on the test and evaluation of typical duct-mounted relative humidity sensors used in building HVAC applications. In this paper three duct-mounted humidity sensors from each of six different manufacturers (i.e., models A to F) were tested and evaluated to determine the sensor repeatability, hysteresis, and linearity. The experimental database of the accuracy study, as described in the Part 2 paper (Joshi et al. 2004b), was used to evaluate the repeatability, hysteresis, and linearity of sensors. The results show that at 50% RH, the sensors are repeatable within 1.5% RH for temperatures of 15 degrees C, 25 degrees C, and 35 degrees C. The maximum hysteresis for all sensors is less than 3.2% for all humidities and temperatures. The hysteresis is positive for all temperatures, humidities, and sensor models. For most of the humidity range, Model B has the largest nonlinearity of -3.8% RH while Model C has the least nonlinearity of 0.0% RH. Finally, the magnitude of the errors in repeatability for all sensor models at 25 degrees C and 50% RH is smaller than the magnitudes of both hysteresis and linearity.

This is the second paper in a three-part series reporting on the test and evaluation of typical duct-mounted relative humidity sensors used in building HVAC applications. In this paper, three duct-mounted humidity sensors from each of six different manufacturers were tested and evaluated to determine the sensor accuracy and to provide a comparison with manufacturer specifications. A total of 18 sensors were tested, nine of them were capacitive-type sensors and nine were resistive-type sensors. The sensors were tested at three different temperatures (i.e., 15°C, 25°C, and 35°C) and five different relative humidity (RH) levels (i.e., 10%, 30%, 50%, 70%, and 90% RH). The experimental procedure used for testing and evaluating the accuracy of the humidity sensors was described previously in Part 1 (Joshi et al. 2004a) of this paper. The test and evaluation results show that at 25°C, two of the six humidity sensor models are within manufacturer-specified accuracy of ±3% for the entire relative humidity range of 10% to 90%. A third sensor model did not meet the manufacturer-specified accuracy of ±3% at any humidity level tested while the remaining three sensor models met the manufacturer-specified accuracy of ±3% for only part of the humidity range.

This paper presents methods and results for the prediction of energy conservation retrofits for heating, ventilating, and air-conditioning (HVAC) systems as part of the Great Building Energy Predictor Shootout II. The predictions are based on hourly whole-building electricity, motor control center electricity, lights and equipment electricity, cooling and heating energy use, and the accompanying weather data. An autoassociative neural network was used as a preprocessor to replace the missing data and a standard feed-forward artificial neural network was utilized to predict results were acceptable for the verification of the sample networks, actual building energy prediction could have benefited by including the holiday and weekend information during the network training as well as information from previous time steps.

Since commercially-available, double-effect, absorption cooling systems give relatively high performance for using solar energy or other medium-temperature sources, their performance was simulated and studied. To evaluate the cooling system performance, two objective functions were established: the system performance (COP) and the system cost. The system cost was used as the objective function to determine the optimum design of the system, while the COP was used to evaluate the effects of each variable on the system performance. The system optimization shows that there is an economic optimum heat-transfer area for each heat exchanger. Further study shows that this is a global minimum cost of the system. The best COPs that could be achieved by changing the heat-transfer areas and the inlet hot water temperature vary between 1.4 and 1.5. Higher COPs of approximately 1.6 were achieved if higher chilled water inlet temperatures or lower cooling water temperatures are used. These conditions are not desirable since higher chilled water inlet temperatures are not useful for cooling, and lower cooling water inlet temperatures are not usually available.

This article describes a knowledge-based system which allows the selection of HVAC systems for small office building in two climatic regions: cold and hot/humid. The information presented here comes from ASHRAE research project RP-642. The project assembled, developed, and verified a knowledge base for the selection of heating, ventilating, and air-conditions (HVAC) system types for small (less than 20,000 ft{sup 2} [1,858 m{sup 2}]) office buildings in two climatic regions: cold and hot/humid. The work includes the selection of the primary energy-conversion and distribution system types. A prototype knowledge-based system (KBS) was developed to demonstrate the use of this knowledge base. More details about this project are presented in papers by Habib Shams.

Educational course material is constantly being developed by professors. More and more of this course material is now on computers. It is often desirable for this material to be available through computer networks to the widest possible audience. Given a general audience, this access should be quick and simple. The National Engineering Delivery System (NEEDS) is a new courseware development and distributed system which allows faculty, students, industry and other users to easily access a large number of diverse courseware modules in an effective and efficient manner. This paper documents the design and implementation of a system that may make this idea a reality. The work includes the development of databases used to store course material information, the design of an efficient communication networking protocol for delivering courseware modules, and the development of user front‐ends for general access to the course material stored in the databases.