Season of birth is associated with anthropometric and neurocognitive outcomes during infancy and childhood in a general population birth cohort

The 'season of birth' effect is one of the most consistently replicated associations in schizophrenia epidemiology. In contrast, the association between season of birth and development in the general Population is relatively poorly understood. The aim of this study was to explore the impact of season of birth on various anthropometric and neurocognitive variables from birth to age seven in a large, community-based birth cohort. A sample of white singleton infants born after 37 weeks gestation (n =22,123) was drawn from the US Collaborative Perinatal Project. Anthropometric variables (weight, head circumference, length/height) and various measures of neurocognitive development, were assessed at birth, 8 months, 4 and 7 years of age. Compared to surnmer/autumn born infants, winter/spring born infants were significantly longer at birth, and at age seven were significantly heavier, taller and had larger head circumference. Winter/spring born infants were achieving significantly higher scores on the Bayley Motor Score at 8 months, the Graham-Ernhart Block Test at age 4, the Wechsler Intelligence Performance and Full Scale scores at age 7, but had significantly lower scores on the Bender-Gestalt Test at age 7 years. Winter/spring birth, while associated with an increased risk of schizophrenia, is generally associated with superior outcomes with respect to physical and cognitive development. (c) 2005 Elsevier B.V. All rights reserved.

Evaluation of economic rent of hydropower: A case of Nepal

Like any other natural resources, hydro resources that are capable of generating electricity at cheaper cost give rise to economic rent. Nepal possesses huge amount of such cheaper hydro resources which is far in excess of the domestic demand. The existing rents levied by the governments are not found to address the potential value of resources. In this study hydro rent is calculated for two types of hydropower projects: (i) domestic demand oriented project and (ii) large and export oriented project. In doing so, the study uses the concept of hydro rent as a measure of cost savings achievable by the use of hydro resources over the least cost alternatives. The WASP-III+ optimisation software developed by IAEA has been used to derive two least cost generation expansion plans i.e. one with and the other without the nominated hydro resource. The difference in the costs of two plans gives the rent of the hydro resource.

Impact of weather dependency on planning decisions in the australian national electricity market

A long-term planning method for the electricity market is to simulate market operation into the future. Outputs from market simulation include indicators for transmission augmentation and new generation investment. A key input to market simulations is demand forecasts. For market simulation purposes, regional demand forecasts for each half-hour interval of the forecasting horizon are required, and they must accurately represent realistic demand profiles and interregional demand relationships. In this paper, a demand model is developed to accurately model these relationships. The effects of uncertainty in weather patterns and inherent correlations between regional demands on market simulation results are presented. This work signifies the advantages of probabilistic modeling of demand levels when making market-based planning decisions.

A new methodology for generation investment in the national electricity market of Australia

Market administrators hold the vital role of maintaining sufficient generation capacity in their respective electricity market. However without the jurisdiction to dictate the generator types, locations and timing of new generation, the reliability of the system may be compromised by delayed entry of new generation. This paper illustrates a new generation investment methodology that can effectively present expected returns from the pool market; while concurrently searching for the type and placement of a new generator to fulfil system reliability requirements.

A genetic algorithm based method for deregulated electricity market dispatch

In a deregulated electricity market, optimizing dispatch capacity and transmission capacity are among the core concerns of market operators. Many market operators have capitalized on linear programming (LP) based methods to perform market dispatch operation in order to explore the computational efficiency of LP. In this paper, the search capability of genetic algorithms (GAs) is utilized to solve the market dispatch problem. The GA model is able to solve pool based capacity dispatch, while optimizing the interconnector transmission capacity. Case studies and corresponding analyses are performed to demonstrate the efficiency of the GA model.

Probabilistic cost benefit analysis of generation investment in a deregulated electricity market

A new methodology is proposed for the analysis of generation capacity investment in a deregulated market environment. This methodology proposes to make the investment appraisal using a probabilistic framework. The probabilistic production simulation (PPC) algorithm is used to compute the expected energy generated, taking into account system load variations and plant forced outage rates, while the Monte Carlo approach has been applied to model the electricity price variability seen in a realistic network. The model is able to capture the price and hence the profitability uncertainties for generator companies. Seasonal variation in the electricity prices and the system demand are independently modeled. The method is validated on IEEE RTS system, augmented with realistic market and plant data, by using it to compare the financial viability of several generator investments applying either conventional or directly connected generator (powerformer) technologies. The significance of the results is assessed using several financial risk measures.