Operation and control of a hybrid microgrid containing unbalanced and nonlinear loads

This paper shows how the power quality can be improved in a microgrid that is supplying a nonlinear and unbalanced load. The microgrid contains a hybrid combination of inertial and converter interfaced distributed generation units where a decentralized power sharing algorithm is used to control its power management. One of the distributed generators in the microgrid is used as a power quality compensator for the unbalanced and harmonic load. The current reference generation for power quality improvement takes into account the active and reactive power to be supplied by the micro source which is connected to the compensator. Depending on the power requirement of the nonlinear load, the proposed control scheme can change modes of operation without any external communication interfaces. The compensator can operate in two modes depending on the entire power demand of the unbalanced nonlinear load. The proposed control scheme can even compensate system unbalance caused by the single-phase micro sources and load changes. The efficacy of the proposed power quality improvement control and method in such a microgrid is validated through extensive simulation studies using PSCAD/EMTDC software with detailed dynamic models of the micro sources and power electronic converters

Power management and power flow control with back-to-back converters in a utility connected microgrid

This paper proposes a method for power flow control between utility and microgrid through back-to-back converters, which facilitates desired real and reactive power flow between utility and microgrid. In the proposed control strategy, the system can run in two different modes depending on the power requirement in the microgrid. In mode-1, specified amount of real and reactive power are shared between the utility and the microgrid through the back-to-back converters. Mode-2 is invoked when the power that can be supplied by the DGs in the microgrid reaches its maximum limit. In such a case, the rest of the power demand of the microgrid has to be supplied by the utility. An arrangement between DGs in the microgrid is proposed to achieve load sharing in both grid connected and islanded modes. The back-to-back converters also provide total frequency isolation between the utility and the microgrid. It is shown that the voltage or frequency fluctuation in the utility side has no impact on voltage or power in microgrid side. Proper relay-breaker operation coordination is proposed during fault along with the blocking of the back-to-back converters for seamless resynchronization. Both impedance and motor type loads are considered to verify the system stability. The impact of dc side voltage fluctuation of the DGs and DG tripping on power sharing is also investigated. The efficacy of the proposed control ar-rangement has been validated through simulation for various operating conditions. The model of the microgrid power system is simulated in PSCAD.

Improvement of stability and load sharing in an autonomous microgrid using supplementary droop control loop

This paper investigates the problem of appropriate load sharing in an autonomous microgrid. High gain angle droop control ensures proper load sharing, especially under weak system conditions. However it has a negative impact on overall stability. Frequency domain modeling, eigenvalue analysis and time domain simulations are used to demonstrate this conflict. A supplementary loop is proposed around a conventional droop control of each DG converter to stabilize the system while using high angle droop gains. Control loops are based on local power measurement and modulation of the d-axis voltage reference of each converter. Coordinated design of supplementary control loops for each DG is formulated as a parameter optimization problem and solved using an evolutionary technique. The sup-plementary droop control loop is shown to stabilize the system for a range of operating conditions while ensuring satisfactory load sharing.

Load sharing and power quality enhanced operation of a distributed microgrid

This paper describes control methods for proper load sharing between parallel converters connected in a microgrid and supplied by distributed generators (DGs). It is assumed that the microgrid spans a large area and it supplies loads in both in grid connected and islanded modes. A control strategy is proposed to improve power quality and proper load sharing in both islanded and grid connected modes. It is assumed that each of the DGs has a local load connected to it which can be unbalanced and/or nonlinear. The DGs compensate the effects of unbalance and nonlinearity of the local loads. Common loads are also connected to the microgrid, which are supplied by the utility grid under normal conditions. However during islanding, each of the DGs supplies its local load and shares the common load through droop characteristics. Both impedance and motor loads are considered to verify the system response. The efficacy of the controller has been validated through simulation for various operating conditions using PSCAD. It has been found through simulation that the total Harmonic Distortion (THD) of the of the microgrid voltage is about 10% and the negative and zero sequence component are around 20% of the positive sequence component before compensation. After compensation, the THD remain below 0.5%, whereas, negative and zero sequence components of the voltages remain below 0.02% of the positive sequence component.

Hybrid cascade converter topology with series connected symmetrical and asymmetrical diode-clamped H-Bridge cells

A novel H-bridge multilevel PWM converter topology based on a series connection of a high voltage (HV) diode-clamped inverter and a low voltage (LV) conventional inverter is proposed. A DC link voltage arrangement for the new hybrid and asymmetric solution is presented to have a maximum number of output voltage levels by preserving the adjacent switching vectors between voltage levels. Hence, a fifteen-level hybrid converter can be attained with a minimum number of power components. A comparative study has been carried out to present high performance of the proposed configuration to approach a very low THD of voltage and current, which leads to the possible elimination of output filter. Regarding the proposed configuration, a new cascade inverter is verified by cascading an asymmetrical diode-clamped inverter, in which nineteen levels can be synthesized in output voltage with the same number of components. To balance the DC link capacitor voltages for the maximum output voltage resolution as well as synthesise asymmetrical DC link combination, a new Multi-output Boost (MOB) converter is utilised at the DC link voltage of a seven-level H-bridge diode-clamped inverter. Simulation and hardware results based on different modulations are presented to confirm the validity of the proposed approach to achieve a high quality output voltage.

Detection and Estimation of Nonstationary Power Transients

This chapter looks at issues of non-stationarity in determining when a transient has occurred and when it is possible to fit a linear model to a non-linear response. The first issue is associated with the detection of loss of damping of power system modes. When some control device such as an SVC fails, the operator needs to know whether the damping of key power system oscillation modes has deteriorated significantly. This question is posed here as an alarm detection problem rather than an identification problem to get a fast detection of a change. The second issue concerns when a significant disturbance has occurred and the operator is seeking to characterize the system oscillation. The disturbance initially is large giving a nonlinear response; this then decays and can then be smaller than the noise level ofnormal customer load changes. The difficulty is one of determining when a linear response can be reliably identified between the non-linear phase and the large noise phase of thesignal. The solution proposed in this chapter uses “Time-Frequency” analysis tools to assistthe extraction of the linear model.

Genshanmen Urban Centre and Transport Interchange

This project is the result of a collaborative design process involving QUT School of Design, and AREN Consulting and ZIAD (Zheijiang Provincial Institute of Architectural Design and Research). This project is the submission prepared by the above partnership for an invited international design competition, promoted by Hangzhou City, China. ---------- This major urban design and architecture project is for a large transport oriented development on the new Hangzhou Subway system. The development, covering several city blocks, includes the provision of residential, retail, education, commercial, and transport infrastructure; integrated with rail, bus and ferry systems. ---------- The design strategies are based on the development or artificial land forms; the cutting of new canals, raising of the ground plane, and metaphoric reference to the Yellow Mountains (explored in the detail of the central ‘ridge’ of built form). Further to this, the project explores the integration of sustainable technologies and philosophies with large scale building projects in a subtropical context.

Transaction mining for fraud detection in ERP Systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour, and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

Driver behaviour and decision making at railway level crossings : An exploratory on-road case study

Crashes at rail level crossings represent a significant problem, both in Australia and worldwide. Advances in driving assessment methods, such as the provision of on-road instrumented test vehicles, now provide researchers with the opportunity to further understand driver behaviour at rail level crossings in ways not previously possible. This paper gives an overview of a recent on-road pilot study of driver behaviour at rail level crossings in which 25 participants drove a pre-determined route, incorporating 4 rail level crossings, using MUARC's instrumented On-Road Test Vehicle (ORTeV). Drivers provided verbal commentary whilst driving the route, and a range of other data were collected, including eye fixations, forward, cockpit and driver video, and vehicle data (speed, braking, steering wheel angle, lane tracking etc). Participants also completed a post trial cognitive task analysis interview. Extracts from the wider analyses are used to examine in depth driver behaviour at one of the rail level crossings encountered during the study. The analysis presented, along with the overall analysis undertaken, gives insight into the driver and wider systems factors that shape behaviour at rail level crossings, and highlights the utility of using a multi-method, instrumented vehicle approach for gathering data regarding driver behaviour in different contexts.

GPS fault detection with IMU and aircraft dynamics

Approaches with Vertical Guidance (APV) can provide greater safety and cost savings to general aviation through accurate GPS horizontal and vertical navigation. However, GPS needs augmentation to achieve APV fault detection requirements. Aircraft Based Augmentation Systems (ABAS) fuse GPS with additional sensors at the aircraft. Typical ABAS designs assume high-quality inertial sensors with Kalman filters but these are too expensive for general aviation. Instead of using high-quality (and expensive) sensors, the purpose of this paper is to investigate augmenting GPS with a low-quality MEMS IMU and Aircraft Dynamic Model (ADM). The IMU and ADM are fused together using a multiple model fusion strategy in a bank of Extended Kalman Filters (EKF) with the Normalized Solution Separation (NSS) fault detection scheme. A tightly-coupled configuration with GPS is used and frequent GPS updates are applied to the IMU and ADM to compensate for their errors. Based upon a simulated APV approach, the performance of this architecture in detecting a GPS ramp fault is investigated showing a performance improvement over a GPS-only “snapshot” implementation of the NSS method. The effect of fusing the IMU with the ADM is evaluated by comparing a GPS-IMU-ADM EKF with a GPS-IMU EKF where a small improvement in protection levels is shown.

An introduction to inertial and visual sensing

In this paper we present a tutorial introduction to two important senses for biological and robotic systems — inertial and visual perception. We discuss the fundamentals of these two sensing modalities from a biological and an engineering perspective. Digital camera chips and micro-machined accelerometers and gyroscopes are now commodities, and when combined with today's available computing can provide robust estimates of self-motion as well 3D scene structure, without external infrastructure. We discuss the complementarity of these sensors, describe some fundamental approaches to fusing their outputs and survey the field.

Green energy : sustainable energy sources and alternative technologies

Despite the general evolution and broadening of the scope of the concept of infrastructure in many other sectors, the energy sector has maintained the same narrow boundaries for over 80 years. Energy infrastructure is still generally restricted in meaning to the transmission and distribution networks of electricity and, to some extent, gas. This is especially true in the urban development context. This early 20th century system is struggling to meet community expectations that the industry itself created and fostered for many decades. The relentless growth in demand and changing political, economic and environmental challenges require a shift from the traditional ‘predict and provide’ approach to infrastructure which is no longer economically or environmentally viable. Market deregulation and a raft of demand and supply side management strategies have failed to curb society’s addiction to the commodity of electricity. None of these responses has addressed the fundamental problem. This chapter presents an argument for the need for a new paradigm. Going beyond peripheral energy efficiency measures and the substitution of fossil fuels with renewables, it outlines a new approach to the provision of energy services in the context of 21st century urban environments.

A new method for improving reliability and line loss in distribution networks

In this paper, both Distributed Generators (DG) and capacitors are allocated and sized optimally for improving line loss and reliability. The objective function is composed of the investment cost of DGs and capacitors along with loss and reliability which are converted to the genuine dollar. The bus voltage and line current are considered as constraints which should be satisfied during the optimization procedure. Hybrid Particle Swarm Optimization as a heuristic based technique is used as the optimization method. The IEEE 69-bus test system is modified and employed to evaluate the proposed algorithm. The results illustrate that the lowest cost planning is found by optimizing both DGs and capacitors in distribution networks.

QoS-oriented sesource allocation and scheduling of multiple composite web services in a hybrid cloud using a random-key genetic algorithm

In cloud computing resource allocation and scheduling of multiple composite web services is an important challenge. This is especially so in a hybrid cloud where there may be some free resources available from private clouds but some fee-paying resources from public clouds. Meeting this challenge involves two classical computational problems. One is assigning resources to each of the tasks in the composite web service. The other is scheduling the allocated resources when each resource may be used by more than one task and may be needed at different points of time. In addition, we must consider Quality-of-Service issues, such as execution time and running costs. Existing approaches to resource allocation and scheduling in public clouds and grid computing are not applicable to this new problem. This paper presents a random-key genetic algorithm that solves new resource allocation and scheduling problem. Experimental results demonstrate the effectiveness and scalability of the algorithm.