An Optimal State of Charge Feedback Control Strategy for Battery Energy Storage in Hourly Dispatch of PV Sources

AbstractThe effects of intermittent cloud and changes in temperature cause a randomly fluctuated output of a photovoltaic (PV) system. To mitigate the PV impacts particularly on a weak electricity network, battery energy storage (BES) system is an effective means to smooth out the power fluctuations. Consequently, the net power injected to the electricity grid by PV/BES systems can be dispatched smoothly such as on an hourly basis. This paper presents an improved control strategy for a grid-connected BES for mitigating PV farm output power fluctuations. A feedback controller for state of charge is proposed where the control parameters are optimized using genetic algorithm. In this way, the optimal size for the BES is also determined to hourly dispatch a 1.2 MW PV farm. The effectiveness of the proposed control scheme is evaluated using PSCAD/EMTDC-based simulation

Predicting the cost of eradication for 41 Class 1 declared weeds in Queensland

The feasibility of state-wide eradication of 41 invasive plant taxa currently listed as ‘Class 1 declared pests’ under the Queensland Land Protection (Pest and Stock Route Management) Act 2002 was assessed using the predictive model ‘WeedSearch’. Results indicated that all but one species (Alternanthera philoxeroides) could be eradicated, provided sufficient funding and labour were available. Slightly less than one quarter (24.4%) (n = 10) of Class 1 weed taxa could be eradicated for less than $100 000 per taxon. An additional 43.9$100 000 and $1M per taxon. Hence, 68.3$1M per taxon. Eradication of 29.3% (n = 12) is predicted to cost more than $1M per taxon. Comparison of these WeedSearch outputs with either empirical analysis or results from a previous application of the model suggests that these costs may, in fact, be underestimates. Considering the likelihood that each weed will cost the state many millions of dollars in long-term losses (e.g. losses to primary production, environmental impacts and control costs), eradication seems a wise investment. Even where predicted costs are over$1M, eradication can still offer highly favourable benefit:cost ratios. The total (cumulative) cost of eradication of all 41 weed taxa is substantial; for all taxa, the estimated cost of eradication in the first year alone is $8 618 000. This study provides important information for policy makers, who must decide where to invest public funding

Single and Multi-Sources Energy Sizing for Electric Vehicle: A Case Study

The automotive industry has introduced various renewable-energy based technologies such as battery electric vehicles (BEV) and fuel-cell electric vehicles (FCEV). However  the main concern is addressing issues to determine which vehicle with different energy sources are more efficiency and cost saving than the others.  In order to overcome this issue detailed analysis need to be performed on the important criterions in vehicle sizing like energy cost, dissipated energy and effective energy source (EES). This paper deals with the modeling, evaluation and analysis of single and multi-source electric vehicle (EV) on three classes of EV, namely the light electric vehicle (LEV), medium electric vehicle (MEV) and electric vehicle (EV). A comparison on dissipated energy with different EES, charging cost and weight were made based on a linear mathematical calculation. The results have shown that multi-sources energy powered-vehicle deliver among the best dissipated energy and EES percentage. Findings of this energy sizing under various combination of EV would be helpful for further research on the EV energy applications

The Measurement of Herzberg’ Employees Satisfaction using Kano Method

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Multi-dimensional optimization of In0.53Ga0.47As thermophotovoltaic cell using real coded genetic algorithm

The optimization of thermophotovoltaic (TPV) cell efficiency is essential since it leads to a significant increase in the output power. Typically, the optimization of In0.53Ga0.47As TPV cell has been limited to single variable such as the emitter thickness, while the effects of the variation in other design variables are assumed to be negligible. The reported efficiencies of In0.53Ga0.47As TPV cell mostly remain < 15%. Therefore, this work develops a multi-variable or multi-dimensional optimization of In0.53Ga0.47As TPV cell using the real coded genetic algorithm (RCGA) at various radiation temperatures. RCGA was developed using Visual Basic and it was hybridized with Silvaco TCAD for the electrical characteristics simulation. Under radiation temperatures from 800 to 2000 K, the optimized In0.53Ga0.47As TPV cell efficiency increases by an average percentage of 11.86% (from 8.5 to 20.35%) as compared to the non-optimized structure. It was found that the incorporation of a thicker base layer with the back-barrier layers enhances the separation of charge carriers and increases the collection of photo-generated carriers near the band-edge, producing an optimum output power of 0.55 W/cm2 (cell efficiency of 22.06%, without antireflection coating) at 1400 K radiation spectrum. The results of this work demonstrate the great potential to generate electricity sustainably from industrial waste heat and the multi-dimensional optimization methodology can be adopted to optimize semiconductor devices, such as solar cell, TPV cell and photodetectors

Creating the conditions for scaling up the integration of reproductive health services for men in health and family welfare centers in Bangladesh

An operations research study, supported by the Population Council’s Frontiers in Reproductive Health (FRONTIERS) program, showed that reproductive health services for men could be feasibly and acceptably integrated within the Health and Family Welfare Centres in Bangladesh, which have been primarily women-centered health facilities. Given these findings, a follow-up study was implemented to create the conditions for scaling up the model through identifying and piloting the operational details to consider when taking the intervention to scale. The findings presented in this report suggest that this model of service delivery and training can be scaled up countrywide, preferably in stages. To ensure compliance with systematic screening by all providers, the report recommends instituting supportive supervision, especially during the early stages of expansion, and holding clinical training in a facility where many RTI/STI cases are treated (such as a district hospital)

Active front-end rectifier modelling using dynamic phasors for more-electric aircraft applications

The More-Electric Aircraft (MEA) has become a dominant trend for next-generation aircraft. The Electrical Power System (EPS) on-board may take many forms: AC, DC, hybrid, frequency-wild, variable voltage, together with the possibility of novel connectivity topologies. To address the stability, availability and capability issues as well as to assess the performance of the power quality and transient behaviour, extensive simulation work is required to develop the EPS architectures. The paper develops a fast-simulation model of active front-end rectifiers based on the dynamic phasor concept. The model is suitable for accelerated simulation studies of EPS under normal, unbalanced and line fault conditions. The performance and effectiveness of the developed model have been demonstrated by comparison against time-domain models in three-phase and synchronous space-vector representations. The experimental verification of the dynamic phasor model is also reported. The prime purpose of the model is for the simulation studies of MEA power architectures at system level; however it can be directly applied for simulation study of any other EPS interfacing with active front-end rectifiers

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Hybridisation of GA and PSO to Optimise N-tuples

Among numerous pattern recognition methods the neural network approach has been the subject of much research due to its ability to learn from a given collection of representative examples. This paper is concerned with the design of a Weightless Neural Network, which demoposes a given pattern into several sets of n points, termed n-tuples. Considerable research has shown that by optimising the input connection mapping of such n-tuple networks classification performance can be improved significantly. This paper investigates the hybridisation of Genetic Algorithm (GA) and Particle Swarm Optimisation (PSO) techniques in search of better connection maps to the N-tuples. Experiments were conducted to evaluate the proposed metho9d of applying the trained classifier to recognise hand-printed digits from a widely used database compiled by US National Institute of Standards and Technology (NIST)