Real-time power line extraction from unmanned aerial system video images

In this paper a real-time vision based power line extraction solution is investigated for active UAV guidance. The line extraction algorithm starts from ridge points detected by steerable filters. A collinear line segments fitting algorithm is followed up by considering global and local information together with multiple collinear measurements. GPU boosted algorithm implementation is also investigated in the experiment. The experimental result shows that the proposed algorithm outperforms two baseline line detection algorithms and is able to fitting long collinear line segments. The low computational cost of the algorithm make suitable for real-time applications.

Physical access control administration using building information models

Physical access control systems play a central role in the protection of critical infrastructures, where both the provision of timely access and preserving the security of sensitive areas are paramount. In this paper we discuss the shortcomings of existing approaches to the administration of physical access control in complex environments. At the heart of the problem is the current dependency on human administrators to reason about the implications of the provision or the revocation of staff access to an area within these facilities. We demonstrate how utilising Building Information Models (BIMs) and the capabilities they provide, including 3D representation of a facility and path-finding can reduce possible intentional or accidental errors made by security administrators.

An investigation on the accuracy of regional ocean models through field trials

Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Although these models provide information at a unprecedented resolutions and have proven to increase accuracy and effectiveness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles. For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current velocity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.

Reducing actuator switchings for motion control of autonomous underwater vehicles

A priority when designing control strategies for autonomous underwater vehicles is to emphasize their cost of implementation on a real vehicle and at the same time to minimize a prescribed criterion such as time, energy, payload or combination of those. Indeed, the major issue is that due to the vehicles' design and the actuation modes usually under consideration for underwater platforms the number of actuator switchings must be kept to a small value to ensure feasibility and precision. This constraint is typically not verified by optimal trajectories which might not even be piecewise constants. Our goal is to provide a feasible trajectory that minimizes the number of switchings while maintaining some qualities of the desired trajectory, such as optimality with respect to a given criterion. The one-sided Lipschitz constant is used to derive theoretical estimates. The theory is illustrated on two examples, one is a fully actuated underwater vehicle capable of motion in six degrees-of-freedom and one is minimally actuated with control motions constrained to the vertical plane.

Wind-energy based path planning for unmanned aerial vehicles using Markov decision processes

Exploiting wind-energy is one possible way to extend flight duration for Unmanned Arial Vehicles. Wind-energy can also be used to minimise energy consumption for a planned path. In this paper, we consider uncertain time-varying wind fields and plan a path through them. A Gaussian distribution is used to determine uncertainty in the Time-varying wind fields. We use Markov Decision Process to plan a path based upon the uncertainty of Gaussian distribution. Simulation results that compare the direct line of flight between start and target point and our planned path for energy consumption and time of travel are presented. The result is a robust path using the most visited cell while sampling the Gaussian distribution of the wind field in each cell.

A human-simulated immune evolutionary computation approach

Premature convergence to local optimal solutions is one of the main difficulties when using evolutionary algorithms in real-world optimization problems. To prevent premature convergence and degeneration phenomenon, this paper proposes a new optimization computation approach, human-simulated immune evolutionary algorithm (HSIEA). Considering that the premature convergence problem is due to the lack of diversity in the population, the HSIEA employs the clonal selection principle of artificial immune system theory to preserve the diversity of solutions for the search process. Mathematical descriptions and procedures of the HSIEA are given, and four new evolutionary operators are formulated which are clone, variation, recombination, and selection. Two benchmark optimization functions are investigated to demonstrate the effectiveness of the proposed HSIEA.

Coordinated tuning of DFIG-based wind turbines and batteries using bacteria foraging technique for maintaining constant grid power output

This paper proposes the use of battery energy storage (BES) system for the grid-connected doubly fed induction generator (DFIG). The BES would help in storing/releasing additional power in case of higher/lower wind speed to maintain constant grid power. The DC link capacitor is replaced with the BES system in a DFIG-based wind turbine to achieve the above-mentioned goal. The control scheme is modified and the co-ordinated tuning of the associated controllers to enhance the damping of the oscillatory modes is presented using bacterial foraging technique. The results from eigenvalue analysis and the time domain simulation studies are presented to elucidate the effectiveness of the BES systems in maintaining the grid stability under normal operation.

Improving stability of a DFIG-based wind power system with tuned damping controller

This paper focuses on the implementation of a damping controller for the doubly fed induction generator (DFIG) system. Coordinated tuning of the damping controller to enhance the damping of the oscillatory modes is presented using bacterial foraging technique. The effect of the tuned damping controller on converter ratings of the DFIG system is also investigated. The results of both eigenvalue analysis and the time-domain simulation studies are presented to elucidate the effectiveness of the tuned damping controller in the DFIG system. The improvement of the fault ride-through capability of the system is also demonstrated.

Rough fuzzy control of SVC for power system stability enhancement

This paper presents a new approach to the design of a rough fuzzy controller for the control loop of the SVC (static VAR system) in a two area power system for stability enhancement with particular emphasis on providing effective damping for oscillatory instabilities. The performances of the rough fuzzy and the conventional fuzzy controller are compared with that of the conventional PI controller for a variety of transient disturbances, highlighting the effectiveness of the rough fuzzy controller in damping the inter-area oscillations. The effect of the rough fuzzy controller in improving the CCT (critical clearing time) of the two area system is elaborated in this paper as well.

Impact of wind power development on transmission planning at Midwest ISO

The Midwest Independent Transmission System Operator (MISO) has experienced significant amounts of wind power development within the last decade. The MISO footprint spans the majority of the upper Midwest region of the country, from the Dakotas to Indiana and as far east as Michigan. These areas have a rich wind energy resource. States in the MISO footprint have passed laws or set goals that require load serving entities to supply a portion of their load using renewable energy. In order to meet these requirements, significant investments are needed to build the transmission infrastructure necessary to deliver the power from these often remote wind energy resources to the load centers. This paper presents some of the transmission planning related work done at MISO which was largely influenced by current and future needs for increased wind power generation in the footprint. Specifically, topics covered are generator interconnection, long-term planning coordination, and cost-allocation for new transmission lines.

Generator interconnection procedures at the Midwest ISO

The Midwestern US is a wind-rich resource and wind power is being developed in this region at a very brisk pace. Transporting this energy resource to load centers invariably requires massive transmission lines. This issue of developing additional transmission to support reliable integration of wind on to the power grid provides a multitude of interesting challenges spanning various areas of power systems such as transmission planning, real-time operations and cost-allocation for new transmission. The Midwest ISO as a regional transmission provider is responsible for processing requests to interconnect proposed generation on to the transmission grid under its purview. This paper provides information about some of the issues faced in performing interconnection planning studies and Midwest ISO's efforts to improve its generator interconnection procedures. Related cost-allocation efforts currently ongoing at the Midwest ISO to streamline integration of bulk quantities of wind power in to the transmission grid are also presented.

Sufficiently informative measurements for stability of approximate conditional mean estimates

This paper establishes sufficient conditions to bound the error in perturbed conditional mean estimates derived from a perturbed model (only the scalar case is shown in this paper but a similar result is expected to hold for the vector case). The results established here extend recent stability results on approximating information state filter recursions to stability results on the approximate conditional mean estimates. The presented filter stability results provide bounds for a wide variety of model error situations.

Long term transmission planning to meet renewable energy targets in Australia

Australia is rich in renewable energy resources such as wind, solar and geothermal. Geographical diversity of these renewable resources combined with developing climate change policies poses a great challenge for the long term interconnection planning. Intermittency of wind and solar potentially driving the development of new transmission lines bring additional complexity to power system operations and planning. This paper provides an overview of generation and transmission planning studies in Australia to meet 20% renewable energy target by 2020. Appraisal of the effectiveness of dispersed energy storage, non schedulable peaking plants, wide area controls and demand management techniques to aid the penetration of renewables is presented in this paper

Probability analysis of machine angle stability with non-gaussian wind power input

The security of power transfer across a given transmission link is typically a steady state assessment. This paper develops tools to assess machine angle stability as affected by a combination of faults and uncertainty of wind power using probability analysis. The paper elaborates on the development of the theoretical assessment tool and demonstrates its efficacy using single machine infinite bus system.

Collaborative efforts to enhance power engineering education in Australia

A review of the issues for supporting learning of power engineering in Australia is presented in this paper. The learning needs of students and the support available in blended learning and through distance educations are explored in this review. Specific software tools to assist the learning environment are appraised and the relevance for the next generation of power engineers assessed.