Abstract

Abstract

Abstract
This paper presents an approach for including nonstatistical uncertainties in engineering economic analysis, particularly utility economic analysis, by modeling uncertain variables with fuzzy numbers. In this case, the mathematical operations are defined by the extension principle and the results obtained are also in a form of fuzzy numbers. This approach can be seen as an extension of a previously proposed one that uses interval numbers and interval analysis for including such uncertainties. However, this paper considers also the dependence which may exist between the fuzzy variables and shows the impact this dependence may have on the results. In this context, a way of modeling partial correlation between the variables of the same kind is proposed.

Abstract
One major practical problem when applying traditional metaheuristics seems to be their strong dependency on parameter tuning. This issue is frequently pointed out as a major shortcoming of metaheuristics and is often a reason for Decision-Makers to reject using this type of approach in practical situations. In this paper we present a new search strategy - Constraint Oriented Neighbourhoods - that tries to overcome the referred drawback. The aim is to control the grade of randomness of metaheuristics, by defining "special" neighbourhood movements, that lead to a more robust heuristic, less dependent on parameter tuning. This is achieved by selecting and applying particular movements that take into account the potential violation of problem constraints. The strategy is illustrated in a real problem arising in the area of Power Systems Management - the Unit Commitment Problem, the computational experiments on a set of problem instances systematically outperforming those presented in the literature, both in terms of efficiency, quality of the solution and robustness of the algorithm.

Abstract
Reserve definition is a compromise between economic issues (additional capacity costs) and reliability (risk of loss of load due to outages of the generators), generally approached by deterministic criteria (e.g. the percentage rule defined by UCTE in Europe) and probabilistic methods like PJM (Pennsylvania-New Jersey, Maryland) and its enhancements, based on the concept of risk. With wind power generation increasing in power systems worldwide, these operational issues gain a renewed interest due to the volatile nature of this kind of energy. The aim of this paper is therefore to address this issue from a risk evaluation point of view, showing that it is possible to extend classical probabilistic methods to this new situation, by introducing a detailed Markov model of wind parks that accounts both for machine failures and different wind power levels. This evaluation, where wind generation fluctuation and uncertainty is included, can be helpful for transmission system operators (TSO). when defining the reserve requirements for the next hours. In fact, the results obtained for the risk can be used by TSO to check if the reserve levels that results from traditional deterministic rules are acceptable or need to be increased.

Abstract
This paper presents an application of probabilistic methodologies to evaluate the reserve requirements of generating systems with a large penetration of renewable energy sources. The idea is to investigate the behavior of reliability indices, including those from the well-being analysis, when the major portion of the renewable sources comes from wind power and other intermittent sources. A new simulation process to address operating reserve adequacy is introduced, and the correspondent reliability indices are observed. Case Studies on the Portuguese and Spanish generating systems are presented and discussed.