Manual pumping test method for characterizing the productivity of drilled wells equipped with rope pumps

Since the introduction of the rope-pump in Nicaragua in the 1990s, the dependence on wells in rural areas has grown steadily. However, little or no attention is paid to rope-pump well performance after installation. Due to financial restraints, groundwater resource monitoring using conventional testing methods is too costly and out of reach of rural municipalities. Nonetheless, there is widespread agreement that without a way to quantify the changes in well performance over time, prioritizing regulatory actions is impossible. A manual pumping test method is presented, which at a fraction of the cost of a conventional pumping test, measures the specific capacity of rope-pump wells. The method requires only sight modifcations to the well and reasonable limitations on well useage prior to testing. The pumping test was performed a minimum of 33 times in three wells over an eight-month period in a small rural community in Chontales, Nicaragua. Data was used to measure seasonal variations in specific well capacity for three rope-pump wells completed in fractured crystalline basalt. Data collected from the tests were analyzed using four methods (equilibrium approximation, time-drawdown during pumping, time-drawdown during recovery, and time-drawdown during late-time recovery) to determine the best data-analyzing method. One conventional pumping test was performed to aid in evaluating the manual method. The equilibrim approximation can be performed while in the field with only a calculator and is the most technologically appropriate method for analyzing data. Results from this method overestimate specific capacity by 41% when compared to results from the conventional pumping test. The other analyes methods, requiring more sophisticated tools and higher-level interpretation skills, yielded results that agree to within 14% (pumping phase), 31% (recovery phase) and 133% (late-time recovery) of the conventional test productivity value. The wide variability in accuracy results principally from difficulties in achieving equilibrated pumping level and casing storage effects in the puping/recovery data. Decreases in well productivity resulting from naturally occuring seasonal water-table drops varied from insignificant in two wells to 80% in the third. Despite practical and theoretical limitations on the method, the collected data may be useful for municipal institutions to track changes in well behavior, eventually developing a database for planning future ground water development projects. Furthermore, the data could improve well-users’ abilities to self regulate well usage without expensive aquifer characterization.

DESIGN AND IMPLEMENT DYNAMIC PROGRAMMING BASED DISCRETE POWER LEVEL SMART HOME SCHEDULING USING FPGA

With the development and capabilities of the Smart Home system, people today are entering an era in which household appliances are no longer just controlled by people, but also operated by a Smart System. This results in a more efficient, convenient, comfortable, and environmentally friendly living environment. A critical part of the Smart Home system is Home Automation, which means that there is a Micro-Controller Unit (MCU) to control all the household appliances and schedule their operating times. This reduces electricity bills by shifting amounts of power consumption from the on-peak hour consumption to the off-peak hour consumption, in terms of different “hour price”. In this paper, we propose an algorithm for scheduling multi-user power consumption and implement it on an FPGA board, using it as the MCU. This algorithm for discrete power level tasks scheduling is based on dynamic programming, which could find a scheduling solution close to the optimal one. We chose FPGA as our system’s controller because FPGA has low complexity, parallel processing capability, a large amount of I/O interface for further development and is programmable on both software and hardware. In conclusion, it costs little time running on FPGA board and the solution obtained is good enough for the consumers.

DESIGN AND IMPLEMENTATION OF HOME USE PORTABLE SMART ELECTRONICS

The widespread of low cost embedded electronics makes it easier to implement the smart devices that can understand either the environment or the user behaviors. The main object of this project is to design and implement home use portable smart electronics, including the portable monitoring device for home and office security and the portable 3D mouse for convenient use. Both devices in this project use the MPU6050 which contains a 3 axis accelerometer and a 3 axis gyroscope to sense the inertial motion of the door or the human hands movement. For the portable monitoring device for home and office security, MPU6050 is used to sense the door (either home front door or cabinet door) movement through the gyroscope, and Raspberry Pi is then used to process the data it receives from MPU6050, if the data value exceeds the preset threshold, Raspberry Pi would control the USB Webcam to take a picture and then send out an alert email with the picture to the user. The advantage of this device is that it is a small size portable stand-alone device with its own power source, it is easy to implement, really cheap for residential use, and energy efficient with instantaneous alert. For the 3D mouse, the MPU6050 would use both the accelerometer and gyroscope to sense user hands movement, the data are processed by MSP430G2553 through a digital smooth filter and a complementary filter, and then the filtered data will pass to the personal computer through the serial COM port. By applying the cursor movement equation in the PC driver, this device can work great as a mouse with acceptable accuracy. Compared to the normal optical mouse we are using, this mouse does not need any working surface, with the use of the smooth and complementary filter, it has certain accuracy for normal use, and it is easy to be extended to a portable mouse as small as a finger ring.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.