O Problema de Minimização do Número Máximo de Pilhas Abertas (MOSP, do inglês minimization of open stacks problem) é um problema de otimização combinatória da família NP-Difícil que vem recebendo grande atenção na literatura especializada. Este trabalho apresenta novas contribuições em termos de modelos e técnicas de resolução para o problema. A primeira parte deste trabalho lidou com modelos matemáticos, sendo analisados os modelos existentes que se baseiam em programação inteira mista. Variações de um modelo da literatura foram propostas, com o objetivo de tentar diminuir o tempo de execução necessário para se obter uma solução exata com a utilização de pacotes comerciais. Os resultados mostraram que as propostas são capazes de acelerar a solução de algumas classes de instâncias mas, que de maneira geral, métodos baseados em relaxação linear encontram dificuldade em provar a otimalidade devido à baixa qualidade dos limitantes inferiores. Uma outra contribuição deste trabalho foi o desenvolvimento de um modelo conjunto para o problema MOSP e para o problema de minimização da duração de pedidos (MORP, do inglês minimization of order spread problem). Este modelo propõe um framework unificado em que os dois problemas podem ser resolvidos ao mesmo tempo...
This paper is on the maximization of total profit in a day-ahead market for a price-taker producer needing a short-term scheduling for wind power plants coordination with concentrated solar power plants, having thermal energy storage systems. The optimization approach proposed for the maximization of profit is a mixed-integer linear programming problem. The approach considers not only transmission grid constraints, but also technical operating constraints on both wind and concentrated solar power plants. Then, an improved short-term scheduling coordination is provided due to the more accurate modelling presented in this paper. Computer simulation results based on data for the Iberian wind and concentrated solar power plants illustrate the coordination benefits and show the effectiveness of the approach.
This paper discusses automatic detection and exploitation
of structural redundancy in large-scale mathematical programming
models. From our perspective, such redundancy represents embedded
special structure which can give significant insight to the model
proponent as well as greatly reduce solution effort. We report
experiments with real-life linear programming (LP) and mixedinteger
(MIP) models in which various methods are developed and
tested as integral modules in an optimization system of advanced
design. We seek to understand the modelling implications of these
embedded redundancies as well as to exploit them during actual
optimization. The latter goal places heavy emphasis on efficient,
as well as effective, identification techniques for economic application
to large models. Several (polynomially bounded) heuristic
detection algorithms are presented from our work. In addition,
bounds are reported for the maximum row dimension of the more
complex structures. These bounds are useful for objectively
estimating the quality of heuristically derived assessments of
structural redundancy. Finally, some additional suggestions are
made for analyzing nonlinear programming (NLP) models.
The use of distributed energy resources, based on natural intermittent power sources, like wind generation, in power systems imposes the development of new adequate operation management and control methodologies. A short-term Energy Resource Management (ERM) methodology performed in two phases is proposed in this paper. The first one addresses the day-ahead ERM scheduling and the second one deals with the five-minute ahead ERM scheduling. The ERM scheduling is a complex optimization problem
due to the high quantity of variables and constraints. In this paper the main goal is to minimize the operation costs from the point of view of a virtual power player that manages the network and the existing resources. The optimization problem is solved by a deterministic mixedinteger non-linear programming approach. A case study considering a distribution network with
33 bus, 66 distributed generation, 32 loads with demand response contracts and 7 storage units and 1000 electric vehicles has been implemented in a simulator developed in the field of the presented work, in order to validate the proposed short-term ERM methodology considering the dynamic power system behavior.