Power sharing control with frequency droop in a hybrid microgrid

A microgrid may contain a large number of distributed generators (DGs). These DGs can be either inertial or non-inertial, either dispatchable or non-dispatchable. Moreover, the DGs may operate in plug and play fashion. The combination of these various types of operation makes the microgrid control a challenging task, especially when the microgrid operates in an autonomous mode. In this paper, a new control algorithm for converter interfaced (dispatchable) DG is proposed which facilitates smooth operation in a hybrid microgrid containing inertial and non-inertial DGs. The control algorithm works satisfactorily even when some of the DGs operate in plug and play mode. The proposed strategy is validated through PSCAD simulation studies.

Control, operation and power sharing among parallel converter-interfaced DERs in a microgrid in the presence of unbalanced and harmonic loads

This paper demonstrates power management and control of DERs in an autonomous MG. The paper focuses on the control and performance of converter-interfaced DERs in voltage controlled mode. Several case studies are considered for a MG based on the different types of loads supplied by the MG (i.e. balanced three-phase, unbalanced, single-phase and harmonic loads). DERs are controlled by adjusting the voltage magnitude and angle in their converter output through droop control, in a decentralized concept. Based on this control method, DERs can successfully share the total demand of the MG in the presence of any type of loads. This includes proper total power sharing, unbalanced power sharing as well as harmonic power sharing, depending on the load types. The efficacy of the proposed power control, sharing and management among DERs in a microgrid is validated through extensive simulation studies using PSCAD/EMTDC.

A phase-locked-loop design for the smooth operation of a hybrid microgrid

A microgrid contains both distributed generators (DGs) and loads and can be viewed by a controllable load by utilities. The DGs can be either inertial synchronous generators or non-inertial converter interfaced. Moreover, some of them can come online or go offline in plug and play fashion. The combination of these various types of operation makes the microgrid control a challenging task, especially when the microgrid operates in an autonomous mode. In this paper, a new phase locked loop (PLL) algorithm is proposed for smooth synchronization of plug and play DGs. A frequency droop for power sharing is used and a pseudo inertia has been introduced to non-inertial DGs in order to match their response with inertial DGs. The proposed strategy is validated through PSCAD simulation studies.

Kelp detection in highly dynamic environments using texture recognition

This paper describes a texture recognition based method for segmenting kelp from images collected in highly dynamic shallow water environments by an Autonomous Underwater Vehicle (AUV). A particular challenge is image quality that is affected by uncontrolled lighting, reduced visibility, significantly varying perspective due to platform egomotion, and kelp sway from wave action. The kelp segmentation approach uses the Mahalanobis distance as a way to classify Haralick texture features from sub-regions within an image. The results illustrate the applicability of the method to classify kelp allowing construction of probability maps of kelp masses across a sequence of images.

Sensor Network Based AUV Localisation

The operation of Autonomous Underwater Vehicles (AUVs) within underwater sensor network fields provides an opportunity to reuse the network infrastructure for long baseline localisation of the AUV. Computationally efficient localisation can be accomplished using off-the-shelf hardware that is comparatively inexpensive and which could already be deployed in the environment for monitoring purposes. This paper describes the development of a particle filter based localisation system which is implemented onboard an AUV in real-time using ranging information obtained from an ad-hoc underwater sensor network. An experimental demonstration of this approach was conducted in a lake with results presented illustrating network communication and localisation performance.

The consultative process used in outreach : a narrative account

Aim The aim of this paper was to provide a narrative account of the communication skills used in an effective outreach consultation utilizing Neighbour’s consultative model. Other consultation models were considered; however, because of their overly comprehensive approach or emphasis on behaviour modification, these were deemed inappropriate. Background The nursing profession has endured significant changes of late and as a result is developing more autonomous roles in both the community and the acute health care settings. In the past, the term consultancy was used within the medical context; nowadays, there are advance nurse practitioners for whom consultancy is an integral part of their role. Although every nursing interaction is in essence a consultation, the fact that nurses are taking up on new advanced roles highlights the necessity for nurses to develop their consultation skills even further. Therefore, it makes sense to explore what aspects of that consultancy role needs special consideration in order to ensure that positive outcomes are achieved. Conclusions This paper has used a narrative account to uncover those salient skills needed to enhance the therapeutic relationship with a patient requiring the services of outreach. Furthermore, the application of a recognized consultation model was used to elucidate the underpinning knowledge of systematic history taking and assessment as well as demonstrating the communication skills and strategies needed to increase the patient’s participation and empowerment throughout the consultation. Relevance to clinical practice Effective communication skills encompassed in a consultative model are integral to the success in safeguarding the well-being of patients requiring advanced levels of care. Prejudging or pre-empting information being conveyed can be detrimental to patient safety and may prolong or complicate treatment plans.

Pulse-coupled neural network performance for real-time identification of vegetation during forced landing

Safety concerns in the operation of autonomous aerial systems require safe-landing protocols be followed during situations where the mission should be aborted due to mechanical or other failure. This article presents a pulse-coupled neural network (PCNN) to assist in the vegetation classification in a vision-based landing site detection system for an unmanned aircraft. We propose a heterogeneous computing architecture and an OpenCL implementation of a PCNN feature generator. Its performance is compared across OpenCL kernels designed for CPU, GPU, and FPGA platforms. This comparison examines the compute times required for network convergence under a variety of images to determine the plausibility for real-time feature detection.

Novelty-based visual obstacle detection in agriculture

This paper describes a novel obstacle detection system for autonomous robots in agricultural field environments that uses a novelty detector to inform stereo matching. Stereo vision alone erroneously detects obstacles in environments with ambiguous appearance and ground plane such as in broad-acre crop fields with harvested crop residue. The novelty detector estimates the probability density in image descriptor space and incorporates image-space positional understanding to identify potential regions for obstacle detection using dense stereo matching. The results demonstrate that the system is able to detect obstacles typical to a farm at day and night. This system was successfully used as the sole means of obstacle detection for an autonomous robot performing a long term two hour coverage task travelling 8.5 km.

A bayesian approach for place recognition

This paper presents a robust place recognition algorithm for mobile robots that can be used for planning and navigation tasks. The proposed framework combines nonlinear dimensionality reduction, nonlinear regression under noise, and Bayesian learning to create consistent probabilistic representations of places from images. These generative models are incrementally learnt from very small training sets and used for multi-class place recognition. Recognition can be performed in near real-time and accounts for complexity such as changes in illumination, occlusions, blurring and moving objects. The algorithm was tested with a mobile robot in indoor and outdoor environments with sequences of 1579 and 3820 images, respectively. This framework has several potential applications such as map building, autonomous navigation, search-rescue tasks and context recognition.

Fast re-parameterisation of Gaussian mixture models for robotics applications

Autonomous navigation and picture compilation tasks require robust feature descriptions or models. Given the non Gaussian nature of sensor observations, it will be shown that Gaussian mixture models provide a general probabilistic representation allowing analytical solutions to the update and prediction operations in the general Bayesian filtering problem. Each operation in the Bayesian filter for Gaussian mixture models multiplicatively increases the number of parameters in the representation leading to the need for a re-parameterisation step. A computationally efficient re-parameterisation step will be demonstrated resulting in a compact and accurate estimate of the true distribution.

Energy-based positioning control of underactuated vehicles using manifold regulation

In this paper, we consider the problem of position regulation of a class of underactuated rigid-body vehicles that operate within a gravitational field and have fully-actuated attitude. The control objective is to regulate the vehicle position to a manifold of dimension equal to the underactuation degree. We address the problem using Port-Hamiltonian theory, and reduce the associated matching PDEs to a set of algebraic equations using a kinematic identity. The resulting method for control design is constructive. The point within the manifold to which the position is regulated is determined by the action of the potential field and the geometry of the manifold. We illustrate the performance of the controller for an unmanned aerial vehicle with underactuation degree two-a quadrotor helicopter.

Genetics and the transformation of the personal

The shared nature of genetic information presents new challenges for legal understandings of the self. Within traditional legal discourses the individual is conceptualised as separate and autonomous. In contrast, the genetic individual is understood as inherently relational. This paper analyses the transformation of our understandings of the personal. The transformative processes are assessed through discussion of the changing meanings of privacy in the context of genetic information within families; changing views over access to information about biological parentage by children conceived through assisted reproductive technology; preimplantation genetic diagnosis and the changing context of reproductive decisionmaking.

Risk-management of UAS robust autonomy for its integration into civil aviation safety frameworks

This paper discusses a model of the civil aviation reg- ulation framework and shows how the current assess- ment of reliability and risk for piloted aircraft has limited applicability for Unmanned Aircraft Systems (UAS) with high levels of autonomous decision mak- ing. Then, a new framework for risk management of robust autonomy is proposed, which arises from combining quantified measures of risk with normative decision making. The term Robust Autonomy de- scribes the ability of an autonomous system to either continue or abort its operation whilst not breaching a minimum level of acceptable safety in the presence of anomalous conditions. The decision making associ- ated with risk management requires quantifying prob- abilities associated with the measures of risk and also consequences of outcomes related to the behaviour of autonomy. The probabilities are computed from an assessment under both nominal and anomalous sce- narios described by faults, which can be associated with the aircraft’s actuators, sensors, communication link, changes in dynamics, and the presence of other aircraft in the operational space. The consequences of outcomes are characterised by a loss function which rewards the certification decision

Light of Extinction

Light of Extinction presents a diverse series of views into the complex antics of a semi-autonomous gaggle of robotic actants. Audiences initially enter into the 'backend' of the experience to be rudely confronted with the raw, messy operations of a horde of object-manipulating robotic forms. Seen through viewing apertures these ‘things’ deny any opportunity to grasp their imagined order. Audiences then flow on into the 'front end' of the work where now, seen through another aperture, the very same forms seemingly coordinate a stunning deep-field choreography, floating lusciously within inky landscapes of media, noise and embodied sound. As one series of conceptions slip into extinction, so others flow on in. The idea of the 'extinction of human experience' expresses a projected fear for that which will disappear when biodiverse worlds have descended into an era of permanent darkness. ‘Light Of Extinction' re-positions this anthropomorphic lament in order to suggest a more rounded acknowledgement of what might still remain - suggesting the previously unacknowledged power and place of autonomous, synthetic creation. Momentary disbelief gives way to a relieving celebration of the imagined birth of ‘things’ – without need for staples such as conventional light or the harmonious lullabies of long-extinguished sounds.

Evaluation of robust autonomy and implications on UAS certification and design

As the number of potential applications of Unmanned Aircraft Systems (UAS) grows in civilian operations and national security, National Airworthiness Authorities are under increasing pressure to provide a path for certification and allow UAS integration into the national airspace. The success of this integration depends on developments in improved UAS reliability and safety, regulations for certification, and technologies for operational performance and safety assessment. This paper focusses on the latter and describes the use of a framework for evaluating robust autonomy of UAS, namely, the autonomous system’s ability to either continue operation in the presence of faults or safely shut down. The paper draws parallels between the proposed evaluation framework and the evaluation of pilots during the licensing process. It also discusses how the data from the proposed evaluation can be uses as an aid for decision making in certification and UAS designs.