An energy integrated, multi-microgrid, MILP (mixed-integer linear programming) approach for residential distributed energy system planning - A South Australian case-study

The integration of distributed generation units and microgrids in the current grid infrastructure requires an efficient and cost effective local energy system design. A mixed-integer linear programming model is presented to identify such optimal design. The electricity as well as the space heating and cooling demands of a small residential neighbourhood are satisfied through the consideration and combined use of distributed generation technologies, thermal units and energy storage with an optional interconnection with the central grid. Moreover, energy integration is allowed in the form of both optimised pipeline networks and microgrid operation. The objective is to minimise the total annualised cost of the system to meet its yearly energy demand. The model integrates the operational characteristics and constraints of the different technologies for several scenarios in a South Australian setting and is implemented in GAMS. The impact of energy integration is analysed, leading to the identification of key components for residential energy systems. Additionally, a multi-microgrid concept is introduced to allow for local clustering of households within neighbourhoods. The robustness of the model is shown through sensitivity analysis, up-scaling and an effort to address the variability of solar irradiation

A multi-objective framework for cost-unavailability optimisation of residential distributed energy system design

Future energy systems are expected to include distributed energy systems (DES) and microgrids (MG) at the distribution level. These energy efficient environments enable participating consumers to locally generate and share both electrical and thermal energy. Apart from the potential for a more cost-efficient energy system design, improved system availability is also increasingly put forward as a major advantage of MGs. This paper proposes a mixed-integer linear programming (MILP) approach for the design of a neighbourhood-based energy system, considering the trade-off between total annualised cost and electrical system unavailability. System design is optimised to meet the yearly neighbourhood energy demands by selecting technologies and interactions from a pool of dispatchable and renewable poly-generation and storage alternatives. The availability implementation employs a Markov chain approach combined with logic-gate integer programming. The Pareto trade-off sets of on- and off-grid MG modes are obtained using a weighted-sum approach. The developed model is subsequently applied to an Australian case-study. The sought after trade-off “knee” points for each Pareto curve are hereby identified. Additionally, through comparing on- and off-grid design trade-offs, the need for component redundancy for systems with islanding capabilities is analysed

Parental cigarette smoking and childhood risks of hepatoblastoma: OSCC data

Historically health care data and especially health care cost data were not collected by disease. This is due on one side to a lack of readily available information on the diagnosis that led to the health care given and on the other side to the diversity of actors and organizations taking charge of patients. This results in a major difficulty of linking together incompatible and separate data. A few countries have tried to desagregate their global health cost data in a top-down approach. The limits of such undertakings appeared however quickly, not the least because of the difficulties in allocating the expenditures by sector and disease. Other approaches, probably more fecund in the long run, such as the one used by the SEER-Medicare database in the U.S. favour the linkage of individual patient clinical and cost data in a bottom-up approach. However one should not ignore the potential bias problems raised by the use of even large databases such as this one. A major advantage of clinical trials for costing purposes is that they include homogeneous groups of patients randomly allocated to several treatments for comparative purposes. They are therefore potentially better adapted for comparing new treatments with standard reference care

Bilateral Spontaneous Chylothorax After Severe Vomiting In Children

Objective To report the case of a child with bilateral chylothorax due to infrequent etiology: thoracic duct injury after severe vomiting. Case description Girl, 7 years old, with chronic facial swelling started after hyperemesis. During examination, she also presented with bilateral pleural effusion, with chylous fluid obtained during thoracentesis. After extensive clinical, laboratory, and radiological investigation of the chylothorax etiology, it was found to be secondary to thoracic duct injury by the increased intrathoracic pressure caused by the initial manifestation of vomiting, supported by lymphoscintigraphy findings. Comments Except for the neonatal period, chylothorax is an infrequent finding of pleural effusion in children. There are various causes, including trauma, malignancy, infection, and inflammatory diseases; however, the etiology described in this study is poorly reported in the literature. © 201634451852

The frailty index outperforms DNA methylation age and its derivatives as an indicator of biological age

The measurement of biological age as opposed to chronological age is important to allow the study of factors that are responsible for the heterogeneity in the decline in health and function ability among individuals during aging. Various measures of biological aging have been proposed. Frailty indices based on health deficits in diverse body systems have been well studied, and we have documented the use of a frailty index (FI(34)) composed of 34 health items, for measuring biological age. A different approach is based on leukocyte DNA methylation. It has been termed DNA methylation age, and derivatives of this metric called age acceleration difference and age acceleration residual have also been employed. Any useful measure of biological age must predict survival better than chronological age does. Meta-analyses indicate that age acceleration difference and age acceleration residual are significant predictors of mortality, qualifying them as indicators of biological age. In this article, we compared the measures based on DNA methylation with FI(34). Using a well-studied cohort, we assessed the efficiency of these measures side by side in predicting mortality. In the presence of chronological age as a covariate, FI(34) was a significant predictor of mortality, whereas none of the DNA methylation age-based metrics were. The outperformance of FI(34) over DNA methylation age measures was apparent when FI(34) and each of the DNA methylation age measures were used together as explanatory variables, along with chronological age: FI(34) remained significant but the DNA methylation measures did not. These results indicate that FI(34) is a robust predictor of biological age, while these DNA methylation measures are largely a statistical reflection of the passage of chronological time