A data-mining-based methodology for transmission expansion planning

In recent decades, all over the world, competition in the electric power sector has deeply changed the way this sector’s agents play their roles. In most countries, electric process deregulation was conducted in stages, beginning with the clients of higher voltage levels and with larger electricity consumption, and later extended to all electrical consumers. The sector liberalization and the operation of competitive electricity markets were expected to lower prices and improve quality of service, leading to greater consumer satisfaction. Transmission and distribution remain noncompetitive business areas, due to the large infrastructure investments required. However, the industry has yet to clearly establish the best business model for transmission in a competitive environment. After generation, the electricity needs to be delivered to the electrical system nodes where demand requires it, taking into consideration transmission constraints and electrical losses. If the amount of power flowing through a certain line is close to or surpasses the safety limits, then cheap but distant generation might have to be replaced by more expensive closer generation to reduce the exceeded power flows. In a congested area, the optimal price of electricity rises to the marginal cost of the local generation or to the level needed to ration demand to the amount of available electricity. Even without congestion, some power will be lost in the transmission system through heat dissipation, so prices reflect that it is more expensive to supply electricity at the far end of a heavily loaded line than close to an electric power generation. Locational marginal pricing (LMP), resulting from bidding competition, represents electrical and economical values at nodes or in areas that may provide economical indicator signals to the market agents. This article proposes a data-mining-based methodology that helps characterize zonal prices in real power transmission networks. To test our methodology, we used an LMP database from the California Independent System Operator for 2009 to identify economical zones. (CAISO is a nonprofit public benefit corporation charged with operating the majority of California’s high-voltage wholesale power grid.) To group the buses into typical classes that represent a set of buses with the approximate LMP value, we used two-step and k-means clustering algorithms. By analyzing the various LMP components, our goal was to extract knowledge to support the ISO in investment and network-expansion planning.

Predictors of consistent condom use among Portuguese women attending family planning clinics

Women account for 30% of all AIDS cases reported to the Health Ministry in Portugal and most infections are acquired through unprotected heterosexual sex with infected partners. This study analyzed socio-demographic and psychosocial predictors of consistent condom use and the role of education as a moderator variable among Portuguese women attending family planning clinics. A cross-sectional study using interviewer-administered fully structured questionnaires was conducted among 767 sexually active women (ages 18–65). Logistic regression analyses were used to explore the association between consistent condom use and the predictor variables. Overall, 78.7% of the women were inconsistent condom users. The results showed that consistent condom use was predicted by marital status (being not married), having greater perceptions of condom negotiation self-efficacy, having preparatory safer sexual behaviors, and not using condoms only when practicing abstinence. Living with a partner and having lack of risk perception significantly predicted inconsistent condom use. Less educated women were less likely to use condoms even when they perceive being at risk. The full model explained 53% of the variance in consistent condom use. This study emphasizes the need for implementing effective prevention interventions in this population showing the importance of taking education into consideration.