Description:
It is well-known that load variation and nonlinearity have detrimental impacts on the operation and performance of the conventional power systems and future smart grids (SGs) including their voltage profiles, power quality, losses and efficiency particularly during the peak load hours. This paper will perform optimal scheduling of transformer load tap changer (LTC) and switched shunt capacitors (SSCs) in smart grid with nonlinear loads and plug-in electric vehicle (PEV) charging activities to improve voltage profile, reduce grid losses and control the total harmonic distortion (THD). An established genetic algorithm (GA) for the dispatch of LTC/SSC and a recently implemented algorithm based on maximum sensitivity selections (MSS) optimization for coordination of PEVs are used to perform detailed simulations and analyses.
Description:
The future smart grid (SG) will be populated with high penetrations of plug-in electric vehicles (PEVs) that may deteriorate the quality of electric power. The consumers will also be seeking economical options to charge their vehicles. This paper proposes an overnight maximum sensitivities selection based coordination algorithm (ON-MSSCA) for inexpensive overnight PEV charging in SG. The approach is based on a recently implemented online algorithm (OL-MSSCA) that charges the vehicles as soon as they are randomly plugged-in while considering SG generation, demand and voltage constraints. In contrast to the online approach, ON-MSSCA relies on inexpensive off-peak load hours charging to reduce the cost of generating energy such that SG constraints are not violated and all vehicles are fully charged overnight. Performances of the online and overnight algorithms are compared for the modified IEEE 23kV distribution system with low voltage residential feeders populated with PEVs.
Description:
The phenomenon of deadlock in robotic cells has been long ignored by most scheduling literature. A deadlock situation arises if a part cannot change its current state indefinitely since the destination machine is occupied by another part. The probability of the deadlock occurrence is likely to be large when the processing route cannot be predicted with certainty due to inspection processes. Our focus here is on a specific robotic cell with a post-process inspection system where the inspection is performed on an independent inspection machine. Avoidance and recovery policies are applied to overcome deadlocks originated from this cell. We develop these policies to prevent deadlock or alternatively resolve it during the online implementation of cycles. The former policy minimizes the storage cost, whereas the later policy minimizes the expected cycle time. An analysis of the scheduling problem that involves timings and costs is also carried out for comparing policies.
Description:
In this study, a series of experimental shaking table tests were performed on a physical fixed based model (structure directly fixed on top of the shaking table) and a flexible base model (soil-structure system) under the influence of four scaled earthquake acceleration records (two near field and two far field records) and the results were measured. The soil- structure system includes a 15 storey structural model resting on a synthetic clayey soil mixture consisting of kaolinite, bentonite, class F fly ash, lime, and water. The selected soil model was placed into a laminar soil container, designed and constructed to realistically simulate the free field conditions in shaking table tests. Comparing the measured response of fixed base and flexible base models, it is noted that the lateral deflections of flexible base model have evidently amplified in comparison to the fixed base model. As a result, performance level of the structural model may change extensively (e.g. from life safe to near collapse level), which may be extremely dangerous and safety threatening. Thus, it is experimentally observed that dynamic soil-structure interaction plays a significant role in seismic behaviour of moment resisting building frames resting on relatively soft soils.
Description:
This study is focused on the domain of a two-machine robotic cell scheduling problem. Particularly, we propose the first analytical method for minimizing the partial cycle time of such a cell with a PC-based automatic inspection system to make the problem more realistic. It is assumed that parts must be inspected in one of the production machines, and this may result in a rework process. The stochastic nature of the rework process prevents us from applying existing deterministic solution methods for the scheduling problem. This study aims to develop an in-line inspection of identical parts using multiple contact/non-contact sensors. Initially, we present a heuristic method that converts a multiple-sensor inspection system into a single-sensor inspection system. Then, the expected sequence times of two different cycles are derived based on a geometric distribution, and finally the maximum expected throughput is pursued for each individual case.
Description:
This paper introduces a new fault location algorithm for radial MV distribution networks employing distributed travelling wave observers. Incipient fault location may reduce the risk of wild or bush fire ignition by faulty MV overhead lines. Some faults can develop over time and may exist for an extended period before the right weather conditions result in a fire. Developing faults will produce travelling voltage waves. The distributed observers are synchronized by global positioning system and use the arrival time differences to locate faults. Modal and wavelet transformation is used to detect and time stamp the travelling wave arrival time by observers. The paper first provides a brief review of fault location technology then describes the Floyd-Warshell algorithm to calculate point to point distance matrix. A travelling wave detection methods and finally the fault location algorithm will be described. Simulation model is developed in EMTP-RV software to illustrate the performance of proposed algorithm based on real network data.
Description:
In Australia, employers are allowed to become accredited training providers and award qualifications to their own workers. This is not unique to Australia – there is provision for this to happen in the UK as well, although it is rarely taken up – but it is not known how widespread the practice is among countries. There are around 250 employers in Australia who have become what is known as ‘Enterprise Registered Training Organisations’ (RTOs, the Australian term for nationally-accredited training providers), and they are drawn from both public and private sectors. They become enterprise RTOs because they want more customisation of training and more control over delivery (Enterprise RTO Association, 2009a); and because they want to improve quality in their production and service processes, and to develop their workforces (Smith & Smith, 2009a). The phenomenon of enterprise RTOs has been little explored, and a major national research project, funded by the Australia Research Council, set out to map the current terrain, examine how enterprise RTOs operate, and to explore questions of training quality and comparability with qualifications delivered through institutional training providers. A partnership was set up with the Enterprise Training Organisation Association and eight enterprise RTOs, in a project with qualitative and quantitative phases including longitudinal case studies in the enterprise RTOs and two surveys of all enterprise RTOs, which gained response rates of one-third and one-quarter respectively. This paper uses findings from the project to explore the institutional infrastructure associated with employer decisions to become enterprise RTOs and maintain that status. Three aspects are examined. Firstly, the paper reports how enterprise RTOs interact with the national vocational education and training (VET) system, in terms of compliance with national quality and reporting requirements. Secondly, it examines the internal infrastructures set up within the companies to operate the enterprise RTO itself and to carry out training that results in a national qualification. Thirdly it explores the impact upon workers (who are also learners) of this way of delivering training. The project found that the processes required to operate as an enterprise RTO were very complex and demanding, and that the enterprise RTO was regularly required to prove its worth to the broader company. In an unanticipated finding, it emerged that during the project’s life, changes in the economic and business environment affected the companies within which enterprise RTOs operated, affecting the operations and structure of the RTOs.
Description:
Doubly Fed Induction Generators (DFIGs) are currently extensively used in variable speed wind power plants due to their superior advantages that include reduced converter rating, low cost, reduced losses, easy implementation of power factor correction schemes, variable speed operation and four quadrants active and reactive power control capabilities. On the other hand, DFIG sensitivity to grid disturbances, especially for voltage sags represents the main disadvantage of the equipment. In this paper, a coil is proposed to be integrated within the DFIG converters to improve the overall performance of a DFIG-based wind energy conversion system (WECS). A proportional integral (PI) controller to control the charging and discharging of the coil is introduced. Simulation results reveal the effectiveness of the proposed topology in improving the overall performance of the WECS under study.
Description:
One of the factors hindering the large scale integration of wind power is the post contingency congestion of a network due to limited availability of network capacity and auxiliary constraints. Under such conditions, the network operators can potentially request a curtailment of wind farm output if the remedial strategies fail. The paper investigates this problem in detail and proposes a mathematical framework to capture the post contingency spare capacity of network assets that is required to limit the wind curtailment. The proposed approach incorporates stochastic variation in asset thermal rating; models network congestion, and quantifies the risk of congestion using an extended version of conic-quadratic programming based optimization. The uniqueness of the proposed mathematical model is that it converts conventional thermal constraints to dynamic constraints by using a discretized stochastic penalty function with quadratic approximation of constraint relaxation penalty. The results suggest that the wind utilization can be maximized if the networks are operated 30-50% less than the nominal rating of the assets.
Description:
Reliable data transfer for underwater acoustic sensor networks (UASNs) is a major research challenge in applications such as pollution monitoring, oceanic data collection, and surveillance due to the long propagation delay and high error rate of the acoustic channel. To address this issue, an opportunistic data forwarding protocol was proposed which achieves high packet delivery success ratio with less routing overhead and energy consumption by selecting the next hop forwarder among a set of candidates based on its link reliability and data transfer reach ability. However, the protocol relies on fixed data hold time approach, i.e., Each node holds data packets for a fixed amount of time before a forwarder discovery process is initiated. Depending on the value of the fixed hold time and deployment contextual scenario, this may incur large end-to-end delay. Moreover, lack of consideration of network condition in hold time limits its performance. In this paper, we propose an adaptive technique to improve its performance. The adaptive approach calculates data hold time at each node dynamically considering a number of 'node and network' metrics including current buffer occupancy, delay experienced by stored data packets, arrival and service rate, neighbors' data transmissions and reach ability. Simulation results show that compared with fixed hold time approach, our adaptive technique reduces end-to-end delay significantly, achieves considerably higher data delivery and less energy consumption per successful packet delivery.
Description:
Reliable data transfer for underwater acoustic sensor networks (UASNs) is a major research challenge in applications such as pollution monitoring, oceanic data collection, and surveillance due to the long propagation delay and high error rate of the acoustic channel. To address this issue, an opportunistic data forwarding protocol was proposed which achieves high packet delivery success ratio with less routing overhead and energy consumption by selecting the next hop forwarder among a set of candidates based on its link reliability and data transfer reach ability. However, the protocol relies on fixed data hold time approach, i.e., Each node holds data packets for a fixed amount of time before a forwarder discovery process is initiated. Depending on the value of the fixed hold time and deployment contextual scenario, this may incur large end-to-end delay. Moreover, lack of consideration of network condition in hold time limits its performance. In this paper, we propose an adaptive technique to improve its performance. The adaptive approach calculates data hold time at each node dynamically considering a number of 'node and network' metrics including current buffer occupancy, delay experienced by stored data packets, arrival and service rate, neighbors' data transmissions and reach ability. Simulation results show that compared with fixed hold time approach, our adaptive technique reduces end-to-end delay significantly, achieves considerably higher data delivery and less energy consumption per successful packet delivery.