William Walker and the Republic of Lower California

Though Willam Walker has made the transition from the hottest news personality in America during the years preceding the Civil War, to a virtual unknown, he still remains a controversial figure. Perhaps, due to his tremulous ambitions arrl irrational behavior which set American Latin American relations back decades, the majority of his biographers have not been able to confine themselves to writing the history of a man\u27s life and the impact it made. Their works have many times been polemics, assigning attributes to Walker, ranging from a cold, calculating, paradoxical tyrant whose religion was chivalry, to a political phenomenon personifying the ideals of Manifest Destiny. These perceptions of walker may all contain a piece of the man, but they pass over the fundamental reality that Walker was indeed a man; a driven, compulsive, angry little man. With a brief glance at Walker\u27s life, it becomes easy to understand why he was angry. He was intelligent, capable, and had a talent for convincing otherwise intelligent, rational men to follow him to the gates of hell and back. Yet, despite all this, his life was a series of unfulfilled ambitions and thwarted dreams. One aspect of Walker\u27s life that is especially ignored is his first filibustering expedition to Mexico. Perhaps this is because the whole fiasco was such a dismal failure and does not fit well into the rest of Walker\u27s life story. All of his other ventures reached their zenith before crumbling He was a physician, attorney, and newspaper editor by the time he was twenty-six, and when none of those professions satisfied him, he turned to filibustering. He was quite successful in Nicaragua, in later years, but his adventures in lower California were a comic opera from start to finish. Through compilation of contemporary newspaper accounts, eyewitness reports, memoirs and diaries, numerous secondary sources, and Walker\u27s own remarkably unbiased account, I have attempted to piece together the story of this pathetic farce that had such a tremendous impact on Mexican American relations and Walker\u27s later career as a filibuster. The conclusions reached are three-fold. First, Walker\u27s actions have been difficult for many historians to understand simply because they were not those of a sane man. He was a manic-depressive personality who drove himself to accomplish incredible feats only to discover that whatever he did was not enough. Nothing ever satisfied him. Secondly, the conquest of Lower California and Sonora was seen by Walker an an end in itself, though in the end, it simply became a transition phase for him from law abiding citizen to soldier of fortune. When Walker embarked on this escapade, he had no knowledge of military tactics. His dismal failure was due simply to ignorance on his part. The expedition was an invaluable lesson for him that played no small part in his later success in Nicaragua. Finally, it is significant that the expedition\u27s specifics were rot as important as the deteriorating effect that they had on Mexican-American relations. Already hostile towards Americans because of the Treaty of Guadalupe-Hidalgo, the Mexicans saw Walker\u27s exploits as an expression of American annexationist sentiments and for some time it became quite dangerous for Americans to travel in Lower California and Sonora

Using HVAC Systems for Providing Power Grid Ancillary Services

Real-time power supply and demand balances are critical to ensure stable power frequency and quality power services. However, the growing integration of renewable energy increasingly challenges the power infrastructure because most of the renewable resources, e.g., solar and wind energy, are intermittent and difficult to predict. To meet the stringent power frequency requirements, more fast reacting frequency regulation resources are being brought online among which grid-level batteries are the dominant ones. Although batteries can provide fast and high quality regulation services, they suffer from high initial cost, high environmental impact and round-trip efficiency loss. When providing fast frequency regulation services, battery life span could be significantly reduced, leading to even higher cost per unit of frequency regulation service. Buildings consume more than 73% of the electricity in the US, offering significant regulation reserves for the power grid. Variable-speed air-conditioning systems are taking an increasing share of the market due to the higher efficiency requirements imposed by federal agencies. In addition to efficiency benefits, variable-speed cooling/heating systems are also perfectly suited for providing ancillary services as these units can modulate their power continuously over a wide range. Compared to batteries, HVAC systems have several advantages when providing frequency regulation services: 1) in theory, they do not incur any round-trip efficiency loss; 2) the time response of an AC unit could be faster than a battery (especially compared to energy batteries with slower ramping rates and relatively larger capacities); 3) the existing regulation capacity of HVAC systems is huge and the implementation cost is much lower; 4) the environmental impact of using HVAC systems for regulation services is lower than for battery systems. This paper presents lab test results of a variable-speed heat pump for providing ancillary services. Regulation performances for both the traditional (slow) and dynamic (fast) regulation services are reported. The tested performance scores were above 0.97 and the regulation performance even beats the average battery regulation performance. Preliminary economic analysis was also performed using historical PJM prices. It was shown that the credit received for providing ancillary services could easily offset 50% of the HVAC energy cost under the tested conditions

Virtual Power Consumption and Cooling Capacity Virtual Sensors for Rooftop Units

Implementation of advanced controls and diagnostic features in small commercial buildings typically requires real-time monitoring of the energy flows, such as the power consumption and cooling capacity of rooftop units. However, these measurements are expensive and therefore limit the application of these advanced features. In order to lower the measurement cost, virtual sensing technology for rooftop unit power consumption and cooling capacity are being developed. Power transmitters and thermocouples are installed on the rooftop units to train the virtual sensors. The idea is to recycle the power transmitters after training to save cost, and then the virtual sensors estimate hourly electrical consumption and cooling capacity using only low cost, non-invasive temperature measurements. In this paper, development and validation of the virtual sensors are presented. The virtual power consumption sensors are validated for 4 different rooftop units installed in the field, whereas the cooling capacity sensors are validated using 3 laboratory-tested rooftop units. The reliability of the sensors is also investigated by studying the uncertainty of the virtual sensor outputs under different operating conditions. A cost comparison between the virtual sensors and direct measurement methods is also conducted to evaluate the potential for widespread application of the virtual sensing technology

A Heuristic Supply Air Temperature Reset Strategy for VAV Systems Employing Variable-Capacity DX Cooling Equipment

Direct expansion (DX) cooling systems are commonly used in small to medium sized commercial buildings due to low capital investment and maintenance costs. Nowadays more DX units are equipped with variable-speed fans and capacity modulating techniques to enable higher efficiency and better comfort control. This complexity provides greater energy savings potential for control optimization compared to single stage DX units with constant air flow. This paper presents a generalized control heuristic for resetting supply air temperature setpoints for multi-stage DX units configured with variable-speed supply fans. The heuristic is shown to work well for a wide range of different DX systems with different compressor types and fan-duct combinations. Digital scroll, variable-speed and multi-cylinder reciprocating compressors are considered and modeled using curve fits to manufacturer’s data. Different evaporator and condenser characteristics are also considered using models constructed from catalog data of a representative split DX cooling system. The component models are coupled to provide an overall performance model for each DX system. Fan power is another critical portion of the total HVAC power consumption. In this study, a simple method was used to characterize the performance of a duct system based on typical relationships between pressure drop and air flow rate. Different duct characteristics were coupled to different types of supply fans to provide a set of fan power maps. Optimization was then performed for each combination to find the optimal supply air temperature that minimizes total fan and compressor power. This provided a baseline for developing and validating results of the heuristic control strategy. To assess the integrated energy savings potential of the heuristic strategy, a simulation platform was developed for a medium sized commercial building to consider different DX cooling systems and climates. Simulations were carried out for a 100-day cooling season indifferent locations of US and under different control strategies, including conventional control with a constant supply air temperature setpoint, the heuristic reset strategy and optimal supply air temperature setpoint control. It is shown that the heuristic control has performance almost as good as optimal control with significant cost savings relative to conventional control that depend on the system type and location

Efficient and Robust Training Methodology for Inverse Building Modeling and Its Application to a Multi-zone Case Study

This paper presents an efficient and robust parameter training methodology, based on a previous approach for inverse building modeling that utilizes a simplified state-space approach. One new element of this training methodology is that some seasonal effects, such as variation of window transmittance at different times of the year, are taken into consideration and captured during the training process. In addition, a mixed-mode training approach is developed that allows the use of a combination of data obtained when cooling or heating is occurring with the zone temperature under control at setpoint and when the zone temperature is floating during periods of no load. To obtain a “nearly” global optimal model, a multi-start search method was found to be robust and provide good computational efficiency and accurate results. The training methodology is implemented to model three zones of Building 101 at the Navy Ship Yard in Philadelphia, Pennsylvania

Self-learning Backlash Inverse Control of Cooling or Heating Coil Valves Having Backlash Hysteresis

Valves are widely used in HVAC systems to regulate liquid flow rate, such as hot- and chilled-water valves utilized in cooling and heating coils. These valves are typically controlled with motorized actuators where significant backlash hysteresis might exist and the backlash magnitude mostly depends on the clearance of the manufactured gearbox. Due to the hysteresis effect, unsatisfactory tracking performance results when using a conventional PI controller. This paper proposes a self-learning backlash inverse control approach to mitigate the backlash effect with moderate modifications to a conventional PI control. In the proposed approach, a self-learning procedure is carried out at the beginning of the control implementation period to estimate the backlash magnitude for a specific valve. Then a backlash inverse block is added to an existing PI controller to compensate for the hysteresis effect residing in the valve. The validity of the proposed method was verified with both simulation and experimental tests and significant improvement was observed in the control performance

Comparing Maintenance Strategies for Rooftop Units having Multiple Faults through Simulation

Maintenance strategies currently used for commercial building rooftop units (RTU) can be classified into two categories: reactive strategies and proactive strategies. In reactive strategies, maintenance and service is performed only when needed, e.g. when a system is unable to maintain setpoint. In proactive strategies, maintenance is scheduled at routine intervals to avoid service interruptions regardless of whether the system actually needs it. While these strategies could not be more different, it is unclear which strategy is more optimal. Moreover, whether one strategy is more optimal than the other more than likely depends on the application – contributing to much uncertainty. A third category of maintenance has been enabled by automated fault detection and diagnostics (AFDD) technologies that aims to provide building operators and service providers more detailed information about the actual state of equipment in the field. This third strategy, called condition-based maintenance, aims to optimize service and maintenance decisions throughout the life of equipment based on updated measurements of performance and service costs. In this work, these three types of maintenance strategies are compared using a commercial building simulation model utilizing a fault impact equipment model. Along with comparing different strategies under the same fault scenario, ambient conditions, and loads, optimal maintenance schedules are generated using dynamic programming. Benefits of a condition-based maintenance approach utilizing a suite of AFDD methodologies are highlighted with respect to reducing operating costs

Artificial Neural Networks for Fast Rooftop Unit Fault Impact Modeling and Simulation

Like any electromechanical system, direct-expansion (DX) air conditioners and heat pumps often develop faults over time that contribute to reduced operating efficiency, more frequent comfort violations, or even premature failure. Automated fault detection and diagnosis (AFDD) methods have been developed for these systems and much experimental effort has been undertaken for their evaluation. In order to reduce development costs required for AFDD technologies, additional research related to modeling DX equipment subject to faults has been undertaken. Investigation of AFDD methods in a virtual environment typically requires relatively detailed equipment models based in some part on thermodynamic principles. Because of these embedded constraints, simulation of faulty equipment operating performance can be time consuming and computationally intensive. In this work, meta-models based on previously developed greybox fault impact models for DX equipment have been developed using artificial neural networks. After tuning these neural network meta-models for different equipment, AFDD performance and fault impacts were simulated using a simple building load model. Significant computational speedups were realized over the original greybox equipment models without loss of significant accuracy. Ultimately through careful meta-model training, it is believed that using neural networks to approximate detailed, computationally-intensive equipment or building models may be useful in applications that require frequent model evaluations

Development of an Embedded RTU FDD using Open-Source Monitoring and Control Platform

Previous research on automated fault detection and diagnostics (FDD) for HVAC systems has shown promising benefits like earlier detection and more accurate isolation of different faults. While most researchers, equipment manufacturers, and policymakers agree that HVAC system FDD is important and has the potential to reduce significant energy waste due to faulty system operation, widespread adoption of these tools has been slow. An automated fault detection and diagnosis system has been developed for packaged (rooftop) air conditioners based on the VOLTTRONTM monitoring and controls framework developed by the Department of Energy. The system implements a virtual-sensor-based FDD methodology capable of isolating common rooftop unit faults such as improper refrigerant charge level, heat exchanger fouling, liquid-line restrictions, and compressor valve leakage. A fault impact evaluation component has also been implemented in order to determine the relative impact that faults have on system performance. This is accomplished using virtual sensor outputs and manufacturers’ performance map reference models for performance indices such as cooling capacity and COP. This system has been implemented using low-cost electronics components and was be tested using a 5-ton RTU in a laboratory environment. In this work, a high-level overview of the automated rooftop unit (RTU) FDD system structure will be presented detailing how individual software agents interact along with a description of the computational and network requirements of the system. Alternative system architectures will also be discussed in comparison to the hybrid system presented. A review of the FDD algorithms is also presented that details the virtual sensors implementations along with the methodology to detect, diagnose, and evaluate different faults.  Finally, the performance of the FDD system will be demonstrated using laboratory test data collected for a 4-ton RTU with micro-channel condenser. The goal of this research is to produce a field ready FDD tool for RTUs that can be used to show the benefits of FDD in real systems. Ultimately, the software implementation (using Python) and hardware designs of all the systems components will be released under an open source license in an effort to reduce the engineering effort required by equipment manufacturers interested in a complete AFDD solution

Development of Economic Impact Models for RTU Economizer Faults

Stuck outdoor-air dampers can lead to significant energy waste when undiagnosed for extended periods of time. This is especially true for packaged (rooftop) air conditioners where preventative maintenance may not be frequent or only reserved for emergencies. Automated fault detection and diagnosis (AFDD) tools for outdoor-air dampers and economizers have been proposed in the past to reduce the effort and cost for this kind of maintenance and are even required by some new building standards (CA - Title 24 2013). While qualitatively, the effects of stuck damper faults are understood, much less has been written about these faults’ impacts on cooling cycle performance and actual operating costs. An investigation of incorrect outdoor-air fraction on cooling capacity, efficiency, sensible heat ratio (SHR), and run-time is presented. An evaluation of the commanded damper position based on economizer controller logic is used to capture impacts of stuck damper faults at the full range of position and under different ambient conditions. Using experimental data, these models are validated for a 4-ton rooftop air-conditioner (RTU) with integrated economizer. The combined effect of these impacts are analyzed based on air-side virtual sensors outputs and modified version of an economic performance degradation index (EPDI) first proposed by Li and Braun (2006). This performance index estimates fault impacts on operation costs as well as the added equipment costs due to the need to operate the air-conditioner longer. These economic performance impact outputs can be used in an optimal maintenance scheduling tool in future work