Cost dependent strategy for electricity markets bidding based on adaptive reinforcement learning

Electricity markets are complex environments, involving a large number of different entities, playing in a dynamic scene to obtain the best advantages and profits. MASCEM is a multi-agent electricity market simulator to model market players and simulate their operation in the market. Market players are entities with specific characteristics and objectives, making their decisions and interacting with other players. MASCEM provides several dynamic strategies for agents’ behavior. This paper presents a method that aims to provide market players with strategic bidding capabilities, allowing them to obtain the higher possible gains out of the market. This method uses a reinforcement learning algorithm to learn from experience how to choose the best from a set of possible bids. These bids are defined accordingly to the cost function that each producer presents.

Multi-agent based electricity market simulator with VPP: Conceptual and implementation issues

This paper presents a new architecture for the MASCEM, a multi-agent electricity market simulator. This is implemented in a Prolog which is integrated in the JAVA program by using the LPA Win-Prolog Intelligence Server (IS) provides a DLL interface between Win-Prolog and other applications. This paper mainly focus on the MASCEM ability to provide the means to model and simulate Virtual Power Producers (VPP). VPPs are represented as a coalition of agents, with specific characteristics and goals. VPPs can reinforce the importance of these generation technologies making them valuable in electricity markets.

Influence of cardiorespiratory fitness and parental lifestyle on adolescents' abdominal obesity

The aims of this study were (1) to analyse the influence of cardiorespiratory fitness (CRF) and parental overweight status (POS) and socioeconomic status (SES) on abdominal obesity. This study was comprised of 779 adolescents (12-18 years). Waist-height ratio (WHtR), 20 m shuttle-run test to ascertain CRF, POS according to World Health Organization recommendations and SES of parents using level of education were analysed. Using WHtR, the prevalence of abdominal obesity was 21.3% (23.5% girls and 17.9% boys; p = 0.062). Regardless of gender, participants who belonged to the WHtR risk group had significantly (p ≤ 0.05) lower CRF scores than the WHtR non-risk group; 84.4% of girls who belonged to the WHtR risk group had one or two overweight parents (p ≤ 0.05). Boys with low CRF (OR: 6.43; CI: 3.33-12.39) were more likely to belong to the WHtR risk group compared with their lean peers. Girls with low CRF (OR: 1.78; CI: 1.14-2.78) and with at least one overweight parent (OR: 2.50; CI: 1.07-5.85) or two overweight parents (OR: 4.90; CI: 2.08-11.54) were associated with the risk of abdominal obesity. This study highlights the influence of adolescents' family on abdominal obesity, especially in girls. Further, the data suggested that low CRF was a strong predictor of risk values of abdominal obesity in adolescence.