Short-Term Trading for a Wind-PV Power Producer in an Electricity Market

This paper deals with the problem of coordinated trading of wind and photovoltaic systems in order to find the optimal bid to submit in a pool-based electricity market. The coordination of wind and photovoltaic systems presents uncertainties not only due to electricity market prices, but also with wind and photovoltaic power forecast. Electricity markets are characterized by financial penalties in case of deficit or excess of generation. So, the aim o this work is to reduce these financial penalties and maximize the expected profit of the power producer. The problem is formulated as a stochastic linear programming problem. The proposed approach is validated with real data of pool-based electricity market of Iberian Peninsula.

Bidding and Optimization Strategies for Wind-PV Systems in Electricity Markets

The variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modeled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market.

Bidding and Optimization Strategies for Wind-PV Systems in Electricity Markets Assisted by CPS

The variability in non-dispatchable power generation raises important challenges to the integration of renewable energy sources into the electricity power grid. This paper provides the coordinated trading of wind and photovoltaic energy assisted by a cyber-physical system for supporting management decisions to mitigate risks due to the wind and solar power variability, electricity prices, and financial penalties arising out the generation shortfall and surplus. The problem of wind-photovoltaic coordinated trading is formulated as a stochastic linear programming problem. The goal is to obtain the optimal bidding strategy that maximizes the total profit. The wind-photovoltaic coordinated operation is modelled and compared with the uncoordinated operation. A comparison of the models and relevant conclusions are drawn from an illustrative case study of the Iberian day-ahead electricity market.

Bidding Decision of Wind-Thermal GenCo in Day-Ahead Market

This paper deals with the self-scheduling problem of a price-taker having wind and thermal power production and assisted by a cyber-physical system for supporting management decisions in a day-ahead electric energy market. The self-scheduling is regarded as a stochastic mixed-integer linear programming problem. Uncertainties on electricity price and wind power are considered through a set of scenarios. Thermal units are modelled by start-up and variable costs, furthermore constraints are considered, such as: ramp up/down and minimum up/down time limits. The stochastic mixed-integer linear programming problem allows a decision support for strategies advantaging from an effective wind and thermal mixed bidding. A case study is presented using data from the Iberian electricity market.

Optimal Wind Bidding Strategies in Day-Ahead Markets

This paper presents a computer application for wind energy bidding in a day-ahead electricity market to better accommodate the variability of the energy source. The computer application is based in a stochastic linear mathematical programming problem. The goal is to obtain the optimal bidding strategy in order to maximize the revenue. Electricity prices and financial penalties for shortfall or surplus energy deliver are modeled. Finally, conclusions are drawn from an illustrative case study, using data from the day-ahead electricity market of the Iberian Peninsula.

Visual programming in a heterogeneous multi-core environment

É do conhecimento geral de que, hoje em dia, a tecnologia evolui rapidamente. São criadas novas arquitecturas para resolver determinadas limitações ou problemas. Por vezes, essa evolução é pacífica e não requer necessidade de adaptação e, por outras, essa evolução pode Implicar mudanças. As linguagens de programação são, desde sempre, o principal elo de comunicação entre o programador e o computador. Novas linguagens continuam a aparecer e outras estão sempre em desenvolvimento para se adaptarem a novos conceitos e paradigmas. Isto requer um esforço extra para o programador, que tem de estar sempre atento a estas mudanças. A Programação Visual pode ser uma solução para este problema. Exprimir funções como módulos que recebem determinado Input e retomam determinado output poderá ajudar os programadores espalhados pelo mundo, através da possibilidade de lhes dar uma margem para se abstraírem de pormenores de baixo nível relacionados com uma arquitectura específica. Esta tese não só mostra como combinar as capacidades do CeII/B.E. (que tem uma arquitectura multi­processador heterogénea) com o OpenDX (que tem um ambiente de programação visual), como também demonstra que tal pode ser feito sem grande perda de performance. ABSTRACT; lt is known that nowadays technology develops really fast. New architectures are created ln order to provide new solutions for different technology limitations and problems. Sometimes, this evolution is pacific and there is no need to adapt to new technologies, but things also may require a change every once ln a while. Programming languages have always been the communication bridge between the programmer and the computer. New ones keep coming and other ones keep improving ln order to adapt to new concepts and paradigms. This requires an extra-effort for the programmer, who always needs to be aware of these changes. Visual Programming may be a solution to this problem. Expressing functions as module boxes which receive determined Input and return determined output may help programmers across the world by giving them the possibility to abstract from specific low-level hardware issues. This thesis not only shows how the CeII/B.E. (which has a heterogeneous multi-core architecture) capabilities can be combined with OpenDX (which has a visual programming environment), but also demonstrates that lt can be done without losing much performance.

A Case Based Methodology for Problem Solving aiming at Knee Osteoarthritis Detection

Knee osteoarthritis is the most common type of arthritis and a major cause of impaired mobility and disability for the ageing populations. Therefore, due to the increasing prevalence of the malady, it is expected that clinical and scientific practices had to be set in order to detect the problem in its early stages. Thus, this work will be focused on the improvement of methodologies for problem solving aiming at the development of Artificial Intelligence based decision support system to detect knee osteoarthritis. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing that caters for the handling of incomplete, unknown, or even self-contradictory information.

Age Prediction through Pelvis X-Ray Images - A Case Based approach to Problem Solving

It is well known that the dimensions of the pelvic bones depend on the gender and vary with the age of the individual. Indeed, and as a matter of fact, this work will focus on the development of an intelligent decision support system to predict individual’s age based on pelvis’ dimensions criteria. On the one hand, some basic image processing technics were applied in order to extract the relevant features from pelvic X-rays. On the other hand, the computational framework presented here was built on top of a Logic Programming approach to knowledge representation and reasoning, that caters for the handling of incomplete, unknown, or even self-contradictory information, complemented with a Case Base approach to computing.