Impact Assessment of High-Power Domestic EV Charging Proliferation of a Distribution Network

Transport electrification is becoming the mainstream as a means to improve efficiency, performance, andsustainability of transportation systems. Electrical vehicles (EVs) can help to de-carbonise the environment, but a downside isthe technical issues presented to the low-voltage distribution network. To quantify the stochastic nature of transport-affectedelectrification, probabilistic load flow is employed. Monte Carlo-based simulation is applied to accommodate the probabilisticuncertainties associated with variable EV charging patterns. This study considers high-power charging (up to 11 kW) at thedomestic level while monitoring power quality variations (voltage drop, voltage unbalance factor, voltage sag) standards. Thiswork focuses on the Irish and UK, distribution system operator\u27s–transmission system operator\u27s perspectives, as it will help toidentify the likely impacts due to high-EV charger proliferation at household locations. The results indicate that if a 3.68 kWcharger is used at the domestic level, it is possible for 40% of total household consumers to connect EVs directly to thedistribution network without any power quality breaches. Furthermore, the proliferation of EV can be increased up to 100% ifconstrained to the start, and middle portions of the network (relative to the feeder substation transformer). For higher chargercapacities (up to 11 kW), a bottleneck is presented regarding a resultant voltage unbalance factor

Estimating the Wind Resource in an Urban Area: a Case Study of Micro Wind Generation Potential in Dublin, Ireland

The micro-turbine wind market in cities faces significant challenges due to the complexities associated with the urban terrain but, if a renewable solution to increasing energy demand is to be achieved, energy conversion systems where populations are concentrated, that is cities, must be considered. This research evaluates the urban wind resource by employing a physically-based empirical model to link wind observations at a conventional meteorological site to those acquired at urban sites. The approach is based on urban climate research that has examined the effects of varying surface roughness on the wind-field between and above buildings. Here, this is applied to link observations at Dublin Airport, outside the urban area, to those made at an urban and sub-urban site in Dublin where instruments were placed near roof-level and well above roof height. The log model to describe the vertical wind profile is tested against observations made over the course of a year. It is shown to have sufficient accuracy to assess the potential for micro–turbine energy generation in cities and illustrates that the urban wind resource can be evaluated from measurements made at a nearby site, adjusted for the urban site location

Surgical management of posterior fossa metastases

The diagnosis of brain metastases is associated with a poor prognosis reflecting uncontrolled primary disease that has spread to the relative sanctuary of the central nervous system. 20 % of brain metastases occur in the posterior fossa and are associated with significant morbidity. The risk of acute hydrocephalus and potential for sudden death means these metastases are often dealt with as emergency cases. This approach means a full pre-operative assessment and staging of underlying disease may be neglected and a proportion of patients undergo comparatively high risk surgery with little or no survival benefit. This study aimed to assess outcomes in patients to identify factors that may assist in case selection. We report a retrospective case series of 92 consecutive patients operated for posterior fossa metastases between 2007 and 2012. Routine demographic data was collected plus data on performance status, primary cancer site, details of surgery, adjuvant treatment and survival. The only independent positive prognostic factors identified on multivariate analysis were good performance status (if Karnofsky performance score >70, hazard ratio (HR) for death 0.36, 95 % confidence interval (CI) 0.18–0.69), adjuvant whole brain radiotherapy (HR 0.37, 95 % CI 0.21–0.65) and adjuvant chemotherapy where there was extracranial disease and non-synchronous presentation (HR 0.51, 95 % CI 0.31–0.82). Patients presenting with posterior fossa metastases may not be investigated as thoroughly as those with supratentorial tumours. Staging and assessment is essential however, and in the meantime emergencies related to tumour mass effect should be managed with steroids and cerebrospinal fluid diversion as required

Enhanced Network Voltage Management (NVM) Techniques Under the Proliferation of Rooftop Solar PV Installation in Low Voltage Distribution Network (LVDN)

Proliferation of rooftop solar PV distributed generator (PVDG) installation in low voltage distribution network (LVDN) imposes voltage fluctuation challenges that are a threat to distribution system operators. Reactive power control (RPC) methods are insufficient in isolation to combat the overvoltage fluctuations manifested in LVDN with significant grid-tied PVDG installations. Whereas active power curtailment (APC) control can alleviate the voltage fluctuation in such situations and it is achieved at the cost of reduced active power injection. This paper explores how deficiencies in both RPC and APC as separate approaches can be mitigated by suitably combining RPC and APC algorithms. Strategies combining two RPCs and one RPC in conjunction with APC are proposed as two coordinating algorithms by means of instantaneous measurement of node voltage and active power. These coordinating algorithms are embedded in all the rooftop PVDG grid-tied-inverters (GTI), where the GTI coordinates among them for voltage support without exceeding individual inverter VA rating. The result of the combined approach show significant improvement in managing and stabilising the voltage and allows the penetration of PVDG to be increased from 35.65% to 66.7% of distribution transformer (DT) kVA rating

Levilised Cost of Energy Analysis: a Comparison of Urban (Micro) Wind Turbines and Solar PV Systems

The relatively high capital cost associated with micro wind energy systems and the resulting long payback periods, makes for a challenging argument for these technologies. However, as the global population becomes increasingly concentrated in urban areas, the potential for accessing any available renewable energy resource, including wind and solar PV, could become a necessity. This infers that the economics associated with small/micro energy systems need to be better appreciated. This paper presents a levelised cost of energy (LCOE) analysis for rural/urban small/micro wind energy systems that is contextualised by a solar PV system comparison. Further insight is offered through a design of experiments (DOE) consideration that affords an understanding of how system parameters, such as primary energy (rural/urban wind resource and solar insolation), capital cost and loan/finance interest rate individually and collectively affect the respective technologies. The results suggest that from an economic justification perspective, urban installations are difficult to justify and solar PV systems, with the associated lowering system costs, are challenging the viability of small/micro rural wind energy systems

Advances in the Quantification of Turbulence: a Wind Resource Characteristic

Wind resource assessment is a critical parameter in a diverse range of considerations within the built environment. Engineers and scientists, engaging in building design, energy conservation/application and air-quality/air-pollution control measures, need to be cognisant of how the associated wind resource imposes increased complexities in their design and modelling processes. In this regard, the topographical heterogeneities within these environments, present significant challenges to quantifying the resource and its turbulent characteristics. Indeed, from the perspective of assessing the wind resource within the built environment, topographical heterogeneity is the primary proponent of turbulence and the main inhibitor to acquiring meaningful measurements. This paper presents two aspects of turbulence assessment within the built environment. Firstly, an analysis of how turbulence is quantified is considered. The industry standard, turbulent intensity (TI) [1] is compared with a proposed alternative metric described as Fourier Dimension modelling (Df). Secondly, the application of the turbulence assessment is considered with respect to how it affects the productivity of small/micro wind turbines in complex environments. The TI metric is the only metric utilised in the consideration of wind turbine productivity though Gaussian distribution analysis [2]. The TDf model has yet to be developed sufficiently to apply it in this regard. [1] IEC, International Standard 61400-2. Wind Turbines - Part 2: Design requirements for small turbines, ed, 2006. [2] A. Albers Turbulence Normalisation of Wind Turbine Power Curve Measurements, Deutsche WindGuard Consulting GmbH,2009

Small Wind Turbines in Turbulent (urban) Environments: A Consideration of Normal and Weibull Distributions for Power Prediction

The urban terrain and the associated morphological complexities therein, present significant challenges for the deployment of small wind turbines. In particular, a considerable amount of uncertainty is attributable to the lack of understanding concerning how turbulence within urban environments affects turbine productivity. Current wind turbine power output measurements (particularly for small/micro wind turbines) are based on an average wind speed over an observation period; with limited accountability of the variability of wind speed within the observation time frame. This paper however, presents two models that can instead accurately consider such wind speed variation and how it affects the turbine, based solely on the observed mean wind speed and standard deviation within successive (10 minutes) time intervals. These models are predicated on an appreciation of the industry standard metric, turbulence intensity (TI), in conjunction with the power curve of a 2.5kW wind turbine. Simple ‘look-up’ tables collating how the turbine’s power curve is affected by varying TI are used so that a novel methodology for estimating the turbine’s electrical performance is achievable. Ultimately, the two models presented afford an opportunity to provide an indicative real-world wind speed distribution based on the two standard measurements. The first approach is an adaptation of a model originally derived to quantify the degradation of power performance of wind farm turbines, using a Gaussian probability distribution to simulate turbulence (and more specifically, turbulence intensity (TI)). Such Gaussian modelling has potential however, for disproportionately high and asymptotic TI, associated, for example, with gusting within low mean wind speed observation windows. Furthermore, the approach requires an accurate turbine power curve. The second approach overcomes these limitations through the novel application of the Weibull Distribution, a widely accepted means to probabilistically describe wind speed. Both models are tested at an urban and suburban location in Dublin City, Ireland, where sonic anemometry is positioned at approximately 1.5 times the average height of buildings at the respective locations. Both observation sites represent two distinct urban landscapes. The instrumentation is positioned specific to their surrounding locations and, record the three dimensional wind vectors at a temporal resolution of 10Hz. The hypotheses presented here consider an idealised electrical performance of the turbine, with results suggesting that both approaches can replicate very accurately this idealised basis