2005
Authors
Miranda, V; Monteiro, C;
Publication
Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, ISAP'05
Abstract
Decision problems cannot be fully represented without underlying assumptions about the Decision Maker motivations and behavior. This paper describes one technique to build a rule model representing the interaction of preferences of a Decision Maker, by training a Fuzzy Inference System based on examples. © 2005 ISAP.
2005
Authors
Oo, NW; Miranda, V;
Publication
Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, ISAP'05
Abstract
This paper presents a comparison in performance of 3 variants of Genetic Algorithms (GA) vs. 2 variants of Evolutionary Particle Swarm Optimization (EPSO), made in the extremely complex context of a multi-energy market simulation where the behavior of energy retailers is observed. The simulations are on JADE, a FIPA compliant platform based on intelligent autonomous agents running in a cluster of PCs. Each agent formulates its strategy by an inner complex simulation process using a meta-heuristic that tries to define optimum decisions. The results suggest that an EPSO approach is more efficient than GA. © 2005 ISAP.
2005
Authors
Miranda, V;
Publication
Proceedings of the 13th International Conference on Intelligent Systems Application to Power Systems, ISAP'05
Abstract
This text introduces a family of Evolutionary Algorithms named EPSO - Evolutionary Particle Swarm Optimization. EPSO algorithms are evolutionary methods that borrow the movement rule from Particle Swarm Optimization methods (PSO) and use it as a recombination operator that evolves under the pressure of selection. This hybrid approach builds up an algorithm that, in several cases, in application to complex problems in Power Systems, has already proven to be more efficient, accurate and robust than classical evolutionary methods or classical PSO. The text presents the description of the method, didactic examples and examples of applications in real world problems. © 2005 ISAP.
2005
Authors
Ramirez Rosado, IJ; Fernandez Jimenez, LA; Garcia Garrido, E; Zorzano Santamaria, P; Zorzano Alba, E; Miranda, V; Monteiro, C;
Publication
Series on Energy and Power Systems
Abstract
Expansion planning of electric power or natural gas networks has become a consuming time engineering task due to the multiple factors that must be taken into account: technical, economic, environmental or social factors. This paper presents an advanced model of natural gas distribution networks based on Geographic Information Systems (GIS) methodologies, to evaluate the cost associated to the expansion of these networks in order to meet a demand imposed by the user in any location of a region. The experimental results show that this approach produces visual and useful information for planning the expansion of natural gas distribution networks.
2005
Authors
Viana, A; Sousa, JP; Matos, MA;
Publication
Operations Research/ Computer Science Interfaces Series
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.
2005
Authors
Matos, MA; Gouveia, E;
Publication
2005 IEEE Russia Power Tech, PowerTech
Abstract
The idea behind the first proposal of the Fuzzy Power Flow (FPF) was to analyze the impact of the uncertainties in load and generation at the power flow level, when no statistical information is available. Further development of the field addressed the optimal power flow problem and the use of fuzzy methodologies to help planners of the composite generation-transmission system. In a market environment, transmission system adequacy may be defined as the ability of the system to meet reasonable demands for the transmission of electricity. The starting point of this paper is that FPF can be used as a tool to quantify this adequacy, without the need of making too many assumptions about load and generation uncertainties. However, some changes in the basic concept of the FPF are needed in order to accomplish this task - part of the paper is devoted to the description of the adequate formulation. We'll also show that this formulation can be used both in the normal operation situation and in the reliability evaluation of the transmission system. An illustrative example completes the paper.
The access to the final selection minute is only available to applicants.
Please check the confirmation e-mail of your application to obtain the access code.