Future Distribution Network Planning With Demand Response Applications

The philosophy in distribution network planning is continuously evolving to ensure an efficient, reliable and cost-effective network design. This is particularly important with the increasing presence of Distributed Generation (DG) and Demand Response (DR) integration at the distribution network. Thus, there is a need to develop distribution network modelling tool so that the associated impacts and benefits of such integration can be properly assessed and quantified. In light of this, this thesis presents a fractal-based approach to generate a large number of consumer settlements for low voltage distribution networks. Subsequently, branching rate and minimum spanning tree concepts have been applied to connect the load points and create the network for low voltage and medium voltage, respectively. The Particle Swarm Optimization (PSO) technique was then utilized to determine the optimum rating and placement of transformers, DG and capacitors. The developed simulation tool allows the modelling and planning of distribution network to be carried out in a systematic way. In addition, a total of 10,000 network case studies have been performed to assess the network performance under the influence of demand response and solar PV penetration levels. Three different demand response strategies have been considered in this work, namely, consumer response to their own demand profile, consumer response to PV generation profile and the consumer optimized demand response facilitated by smart grid application. Methodology for generating optimum DR pattern for 2,000 individual consumers have also been proposed and implemented with the aim to improve network load factor. These comprehensive analysis of the benefits of DR would enable a more meaningful and robust conclusion to be made. The findings show that DR application at consumer level can greatly facilitate the integration of solar PV systems. The DR benefits include reduced network losses and increased network asset utilization levels. Last but not least, this research work has filed a patent for the invention of Internet-of-Things based remote demand response and energy monitoring system that could be used as an enabler for demand response application in the actual environment

Automated Unit Testing of Evolving Software

As software programs evolve, developers need to ensure that new changes do not affect the originally intended functionality of the program. To increase their confidence, developers commonly write unit tests along with the program, and execute them after a change is made. However, manually writing these unit-tests is difficult and time-consuming, and as their number increases, so does the cost of executing and maintaining them. Automated test generation techniques have been proposed in the literature to assist developers in the endeavour of writing these tests. However, it remains an open question how well these tools can help with fault finding in practice, and maintaining these automatically generated tests may require extra effort compared to human written ones. This thesis evaluates the effectiveness of a number of existing automatic unit test generation techniques at detecting real faults, and explores how these techniques can be improved. In particular, we present a novel multi-objective search-based approach for generating tests that reveal changes across two versions of a program. We then investigate whether these tests can be used such that no maintenance effort is necessary. Our results show that overall, state-of-the-art test generation tools can indeed be effective at detecting real faults: collectively, the tools revealed more than half of the bugs we studied. We also show that our proposed alternative technique that is better suited to the problem of revealing changes, can detect more faults, and does so more frequently. However, we also find that for a majority of object-oriented programs, even a random search can achieve good results. Finally, we show that such change-revealing tests can be generated on demand in practice, without requiring them to be maintained over time

Exploring GPS Data for Operational Analysis of Farm Machinery.

Global Positioning System (GPS) has made a great evolution in different aspects of modern agriculturalsectors. Today, a growing number of crop producers are using GPS and other modern electronic and computer equipments to practice Site Specific Management (SSM) and precision agriculture. This technology has the potentialin agricultural mechanization by providing farmers with a sophisticated tool to measure yield on much smaller scales as well as precisely determination and automatic storing of variables such as field time, working area,machine travel distance and speed, fuel consumption and yield information. This study focuses on how to interpretand process raw GPS data for operational analysis of farm machinery. Exact determinations of field activities usingGPS data along with accurate measurements and records of yield provide an integrated tool to calculate field efficiency and field machine index which in turn increases machine productivity and labor saving. The results canalso provide graphical tools for visualizing machine operator’s performance as well as making decision on field and machine size and selection

A comprehensive comparison between wave propagation and heat distribution via analytical solutions and computer simulations

Wave propagation and heat distribution are both governed by second order linear constant coefficient partial differential equations, however their solutions yields very different properties. This study presents a comprehensive comparison between hyperbolic wave equation and parabolic heat equation. Issues such as conservation of wave profile versus averaging, transporting information, finite versus infinite speed propagation, time reversibility versus irreversibility and propagation of singularities versus instantaneous smoothing have been addressed and followed by examples and graphical evidences from computer simulations to support the arguments

Design and Simulation of Control Systems for Field Survey Mobile Robot Platform.

The aim of this study was to design automatic and accurate control systems for wheel speed and steering of an agricultural mobile robot. Three controllers, including lead-lag compensator, Proportional-Integral-Derivative (PID) and fuzzy logic controller were designed and simulated in this study to control the angular rate of the shaft of a DC motor actuator for a field survey mobile robot that moves between plants rows to perform image acquisition task through a digital camera mounted on a two link arm attached on the robot base. The response of the actuator model for each controller were determined and compared for a sinusoidal and a step input that simulated robot speed and positioning references respectively. Performance analysis showed the effectiveness of the PID and lead-lag compensator response for the wheel steering task, while the fuzzy logic controller design had a better performance in wheel speed control. The output of this analysis was a proved satisfaction of the proposed design criteria which results enhanced mobility of the robot in terms of fast response, speed control accuracy and smooth steering at row-end turnings

A review of Greenhouse Climate Control and Automation Systems in Tropical Regions.

Design and development of automation system for a tropical greenhouse involves different phases, including studying of environmental factors and crop responses, control algorithm, instrumentation and software/hardware interface. In contrast to cold arid climates, a tropical greenhouse is not to provide a warm and humid environment for crop, but to create an ideal condition in which plants can be protected against heavy rainfalls, direct sun radiation, disease, insects and birds. High relative humidity and ambient temperature climate in a tropical greenhouse creates a complicated dynamic system that is influenced by changes of external conditions, making it a challenging environmental control task. This paper reviews and addresses issues involved in the design procedure of automation control system in tropical greenhouses

Data acquisition for Monitoring Vapor Pressure deficit in a tropical lowland shelter-house plant production

The objective of this study was to monitor air Vapor Pressure Deficit (VPD) in a tropical lowland shelter-house plant production. A custom-designed real-time Data Acquisition (DAQ) system with three independent microcontroller boards and sensors for monitoring aerial parameters was developed, calibrated and tested. Sample temperature and Relative Humidity (RH) data for VPD calculations were continuously collected every 60 sec, for 6 days, inside a 40 m2 shelter-house located at the Universiti Putra Malaysia agricultural experimental field. Preliminary results showed that VPD values varied from 0.16 to 2.51 kPa, with a mean of 0.83 kPa and standard deviation (Std) of 0.6 kPa. Different regression models were used to describe the nonlinear correlation that existed between temperature and VPD data. Results showed that squared polynomial model produced the maximum coefficient of determination (R2) equal to 0.976. This model was successfully used for VPD prediction based on temperature inputs. The hypotheses that collected data follow normal distribution and have different means in the 6 days of experiment were rejected at any significant level. The result of this study can be used in decision support systems’ database for controlling tropical lowland plant production environments

Design and Analysis of Full-state Feedback Controller for a Tractor Active Suspension: Implications for Crop Yield.

Vehicle suspension systems are needed in modern tractors to improve ride comfort by insulating driver’s cabin from road disturbances. Active suspension (AS) systems have the potential to improve both ride quality and handling vibration performance upon use of feedback to control its hydraulic actuator. This gives a capability to the vehicle to continuously adjust itself and response to the varying road conditions. The main objective of this study was to use a full-state feedback approach to design and analysis of AS control system for Kubota M110X tractor to eliminate the transmitted vibrations to the driver’s cabin caused by field roughness. The inputs of the system were determined as the control force generated from the hydraulic actuator of the AS and the road disturbances caused by holes and uneven surface. A simulation model was developed to analyze the behavior of the system to disturbances with 0.25 m amplitude. Results are included to show the dynamic performance and robustness of the proposed controller in dissipating the corresponding disturbance vibrations for a comfort ride with an instant overshoot of about 12% of the inputs disturbance and a settling time (ST) of 4.36 sec