ANN based day-ahead ancillary services forecast for electricity market simulation

Adequate decision support tools are required by electricity market players operating in a liberalized environment, allowing them to consider all the business opportunities and take strategic decisions. Ancillary services (AS) represent a good negotiation opportunity that must be considered by market players. Based on the ancillary services forecasting, market participants can use strategic bidding for day-ahead ancillary services markets. For this reason, ancillary services market simulation is being included in MASCEM, a multi-agent based electricity market simulator that can be used by market players to test and enhance their bidding strategies. The paper presents the methodology used to undertake ancillary services forecasting, based on an Artificial Neural Network (ANN) approach. ANNs are used to day-ahead prediction of non-spinning reserve (NS), regulation-up (RU), and regulation down (RD). Spinning reserve (SR) is mentioned as past work for comparative analysis. A case study based on California ISO (CAISO) data is included; the forecasted results are presented and compared with CAISO published forecast.

Relationship of milk intake and physical activity to abdominal obesity among adolescents

Background: Diet and physical activity (PA) are recognized as important factors to prevent abdominal obesity (AO), which is strongly associated with chronic diseases. Some studies have reported an inverse association between milk consumption and AO. Objective: This study examined the association between milk intake, PA and AO in adolescents. Methods: A cross-sectional study was conducted with 1209 adolescents, aged 15–18 from the Azorean Archipelago, Portugal in 2008. AO was defined by a waist circumference at or above the 90th percentile. Adolescent food intake was measured using a semi-quantitative food frequency questionnaire, and milk intake was categorized as ‘low milk intake’ (<2 servings per day) or ‘high milk intake’ ( 2 servings per day). PA was assessed via a self-report questionnaire, and participants were divided into active (>10 points) and low-active groups ( 10 points) on the basis of their reported PA. They were then divided into four smaller groups, according to milk intake and PA: (i) low milk intake/low active; (ii) low milk intake/active; (iii) high milk intake/low active and (iv) high milk intake/active. The association between milk intake, PA and AO was evaluated using logistic regression analysis, and the results were adjusted for demographic, body mass index, pubertal stage and dietary confounders. Results: In this study, the majority of adolescents consumed semi-skimmed or skimmed milk (92.3%). The group of adolescents with high level of milk intake and active had a lower proportion of AO than did other groups (low milk intake/low active: 34.2%; low milk intake/active: 26.9%; high milk intake/low active: 25.7%; high milk intake/active: 21.9%, P = 0.008). After adjusting for confounders, low-active and active adolescents with high levels of milk intake were less likely to have AO, compared with low-active adolescents with low milk intake (high milk intake/low active, odds ratio [OR] = 0.412, 95% confidence intervals [CI]: 0.201– 0.845; high milk intake/active adolescents, OR = 0.445, 95% CI: 0.235–0.845).Conclusion: High milk intake seems to have a protective effect on AO, regardless of PA level