Pipeline renewal decision support : a case study using LinEAR in a water pipeline network

This paper presents a case study for the application of a Linear Engineering Asset Renewal decision support software tool (LinEAR) at a water distribution network in Australia. This case study examines how the LinEAR can assist water utilities to minimise their total pipeline management cost, to make a long-term budget based on mathematically predicted expenditure, and to present calculated evidence for supporting their expenditure requirements. The outcomes from the study on pipeline renewal decision support demonstrate that LinEAR can help water utilities to improve the decision process and save renewal costs over a long-term by providing an optimum renewal schedules. This software can help organisation to accumulate technical knowledge and prediction future impact of the decision using what-if analysis.

Identification of pre-spike network in patients with mesial temporal lobe epilepsy

Background: Seizures and interictal spikes in mesial temporal lobe epilepsy (MTLE) affect a network of brain regions rather than a single epileptic focus. Simultaneous electroencephalography and functional magnetic resonance imaging (EEG-fMRI) studies have demonstrated a functional network in which hemodynamic changes are time-locked to spikes. However, whether this reflects the propagation of neuronal activity from a focus, or conversely the activation of a network linked to spike generation remains unknown. The functional connectivity (FC) changes prior to spikes may provide information about the connectivity changes that lead to the generation of spikes. We used EEG-fMRI to investigate FC changes immediately prior to the appearance of interictal spikes on EEG in patients with MTLE. Methods/principal findings: Fifteen patients with MTLE underwent continuous EEG-fMRI during rest. Spikes were identified on EEG and three 10 s epochs were defined relative to spike onset: spike (0–10 s), pre-spike (−10 to 0 s), and rest (−20 to −10 s, with no previous spikes in the preceding 45s). Significant spike-related activation in the hippocampus ipsilateral to the seizure focus was found compared to the pre-spike and rest epochs. The peak voxel within the hippocampus ipsilateral to the seizure focus was used as a seed region for FC analysis in the three conditions. A significant change in FC patterns was observed before the appearance of electrographic spikes. Specifically, there was significant loss of coherence between both hippocampi during the pre-spike period compared to spike and rest states. Conclusion/significance: In keeping with previous findings of abnormal inter-hemispheric hippocampal connectivity in MTLE, our findings specifically link reduced connectivity to the period immediately before spikes. This brief decoupling is consistent with a deficit in mutual (inter-hemispheric) hippocampal inhibition that may predispose to spike generation.

Integrating PV systems into distribution networks with battery energy storage systems

Integrating Photovoltaic (PV) systems with battery energy storage in the distribution network will be essential to allow for continued uptake of domestic PV system installations. With increasing concerns regarding environmental and climate change issues, incorporating sources of renewable energy into power networks across the world will be key for a sustainable future. Australia is well placed to utilise solar energy as a significant component of its future energy generation and within the last 5 years there has been a rapid growth in the penetration levels seen by the grid. This growth of PV systems is causing a number of issues including intermittency of supply, negative power flow and voltage rises. Using the simulator tool GridLAB-D with a model of a typical South-East Queensland (SEQ) 11 kV distribution feeder, the effect of various configurations of PV systems have been offset with Battery Energy Storage Systems (BESS). From this, combinations of PV and storage that are most effective at mitigating the issues were explored.

Utilizing reactive capability of PV inverters and battery systems to improve voltage profile of a residential distribution feeder

Significant increase in installation of rooftop Photovoltaic (PV) in the Low-Voltage (LV) residential distribution network has resulted in over voltage problems. Moreover, increasing peak demand creates voltage dip problems and make voltage profile even worse. Utilizing the reactive power capability of PV inverter (RCPVI) can improve the voltage profile to some extent. Resistive caharcteristic (higher R/X ratio) limits the effectiveness of reactive power to provide voltage support in distribution network. Battery Energy Storage (BES), whereas, can store the excess PV generation during high solar insolation time and supply the stored energy back to the grid during peak demand. A coordinated algorithm is developed in this paper to use the reactive capability of PV inverter and BES with droop control. Proposed algorithm is capable to cater the severe voltage violation problem using RCPVI and BES. A signal flow is also mentioned in this research work to ensure smooth communication between all the equipments. Finally the developed algorithm is validated in a test distribution network.

Impact of high PV penetration on distribution transformer life time

Integration of rooftop photovoltaics (PVs) in residential networks at moderate penetration levels is becoming a reality in many countries including Australia. Despite the technical challenges in properly accommodating PV units, one of the major benefits is the ability of PV units to extend useful life time of distribution transformers. This effect is not quantified in the existing literature. This paper carries out an analysis into the impacts of rooftop PVs at different penetration levels on the performance of distribution transformers and residential networks. This paper presents a methodology to quantify the benefit of the distribution transformer life extension brought about by customer-owned rooftop PV units. The proposed methodology is applied to a real distribution system with various scenarios, including different penetration levels. The results show the distribution transformer loss-of-life function, as a function of the rooftop PV penetration level, is monotonically decreasing function which saturates after a certain penetration level. The best life improvements occur with transformers that are highly loaded and the presence of a significant PV installation may support the deferral of transformer upgrades.

Multi-agent systems for modeling high penetration photovoltaic system impacts in distribution networks

This paper reviews the use of multi-agent systems to model the impacts of high levels of photovoltaic (PV) system penetration in distribution networks and presents some preliminary data obtained from the Perth Solar City high penetration PV trial. The Perth Solar City trial consists of a low voltage distribution feeder supplying 75 customers where 29 consumers have roof top photovoltaic systems. Data is collected from smart meters at each consumer premises, from data loggers at the transformer low voltage (LV) side and from a nearby distribution network SCADA measurement point on the high voltage side (HV) side of the transformer. The data will be used to progressively develop MAS models.

Impact of PV units in LV feeders on distribution system reliability

Re-supplying loads on outage through cross-connect from adjacent feeders in a distribution system may cause voltage drop and hence require load shedding. However, the surplus PV generated in some of the LV feeders can prevent load shedding, and improve reliability. In order to measure these effects, this paper proposes the application of Direct Load Flow method[1] in reliability evaluation of distribution systems with PV units. As part of this study, seasonal impacts on load consumption together with surplus PV output power injection to higher voltage networks are also considered. New indices are proposed to measure yearly expected energy export, from LV to MV and from MV to higher voltage network.

Power quality improvements in low voltage distribution networks containing distributed energy resources

In this thesis various schemes using custom power devices for power quality improvement in low voltage distribution network are studied. Customer operated distributed generators makes a typical network non-radial and affect the power quality. A scheme considering different algorithm of DSTATCOM is proposed for power circulation and islanded operation of the system. To compensate reactive power overflow and facilitate unity power factor, a UPQC is introduced. Stochastic analysis is carried out for different scenarios to get a comprehensive idea about a real life distribution network. Combined operation of static compensator and voltage regulator is tested for the optimum quality and stability of the system.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

Renewable energy distribution in public spaces: Analyzing the case of Ballast Point Park in Sydney, using a triple bottom line approach

As cities are rapidly developing new interventions against climate change, embedding renewable energy in public spaces is an important strategy. However, most interventions primarily include environmental sustainability while neglecting the social and economic interrelationships of electricity production. Although there is a growing interest in sustainability within environmental design and landscape architecture, public spaces are still awaiting viable energy-conscious design and assessment interventions. The purpose of this paper is to investigate this issue in a renowned public space—Ballast Point Park in Sydney—using a triple bottom line (TBL) case study approach. The emerging factors and relationships of each component of TBL, within the context of public open space, are identified and discussed. With specific focus on renewable energy distribution in and around Ballast Point Park, the paper concludes with a general design framework, which conceptualizes an optimal distribution of onsite electricity produced from renewable sources embedded in public open spaces.

An efficient DSE using conditional multivariate complex Gaussian distribution

This paper presents an efficient noniterative method for distribution state estimation using conditional multivariate complex Gaussian distribution (CMCGD). In the proposed method, the mean and standard deviation (SD) of the state variables is obtained in one step considering load uncertainties, measurement errors, and load correlations. In this method, first the bus voltages, branch currents, and injection currents are represented by MCGD using direct load flow and a linear transformation. Then, the mean and SD of bus voltages, or other states, are calculated using CMCGD and estimation of variance method. The mean and SD of pseudo measurements, as well as spatial correlations between pseudo measurements, are modeled based on the historical data for different levels of load duration curve. The proposed method can handle load uncertainties without using time-consuming approaches such as Monte Carlo. Simulation results of two case studies, six-bus, and a realistic 747-bus distribution network show the effectiveness of the proposed method in terms of speed, accuracy, and quality against the conventional approach.

A coordinated voltage control approach for coordination of OLTC, voltage regulator, and DG to regulate voltage in a distribution feeder

Integration of small-scale electricity generators, known as distributed generation (DG), into the distribution networks has become increasingly popular at the present. This tendency together with the falling price of the synchronous-type generator has potential to give DG a better chance at participating in the voltage regulation process together with other devices already available in the system. The voltage control issue turns out to be a very challenging problem for the distribution engineers since existing control coordination schemes would need to be reconsidered to take into account the DG operation. In this paper, we propose a control coordination technique, which is able to utilize the ability of DG as a voltage regulator and, at the same time, minimize interaction with other active devices, such as an on-load tap changing transformer and a voltage regulator. The technique has been developed based on the concept of control zone, line drop compensation, dead band, as well as the choice of controllers' parameters. Simulations carried out on an Australian system show that the technique is suitable and flexible for any system with multiple regulating devices including DG.

Voltage balance improvement in urban low voltage distribution networks

This project is a step forward in developing effective methods to mitigate voltage unbalance in urban residential networks. The method is proposed to reduce energy losses and improve quality of service in strongly unbalanced low-voltage networks. The method is based on phase swapping as well as optimal placement and sizing of Distribution Static Synchronous Compensator (D-STATCOM) using a Particle Swarm Optimisation method.

Fractal and complex network analyses of protein molecular dynamics

Based on protein molecular dynamics, we investigate the fractal properties of energy, pressure and volume time series using the multifractal detrended fluctuation analysis (MF-DFA) and the topological and fractal properties of their converted horizontal visibility graphs (HVGs). The energy parameters of protein dynamics we considered are bonded potential, angle potential, dihedral potential, improper potential, kinetic energy, Van der Waals potential, electrostatic potential, total energy and potential energy. The shape of the h(q)h(q) curves from MF-DFA indicates that these time series are multifractal. The numerical values of the exponent h(2)h(2) of MF-DFA show that the series of total energy and potential energy are non-stationary and anti-persistent; the other time series are stationary and persistent apart from series of pressure (with H≈0.5H≈0.5 indicating the absence of long-range correlation). The degree distributions of their converted HVGs show that these networks are exponential. The results of fractal analysis show that fractality exists in these converted HVGs. For each energy, pressure or volume parameter, it is found that the values of h(2)h(2) of MF-DFA on the time series, exponent λλ of the exponential degree distribution and fractal dimension dBdB of their converted HVGs do not change much for different proteins (indicating some universality). We also found that after taking average over all proteins, there is a linear relationship between 〈h(2)〉〈h(2)〉 (from MF-DFA on time series) and 〈dB〉〈dB〉 of the converted HVGs for different energy, pressure and volume.