Mathematical optimisation techniques applied to power system operation and planning

Nowadays, power system operation becomes more complex because of the critical operating conditions resulting from the requirements of a market-driven operation. In this context, efficient methods for optimisation of power system operation and planning become critical to satisfy the operational (technical), financial and economic demands. Therefore, the detailed analysis of modern optimisation techniques as well as their application to the power system problems represent a relevant issue from the scientific and technological points of view. This paper presents a brief overview of the developments on modern mathematical optimisation methods applied to power system operation and planning. Copyright © 2007 Inderscience Enterprises Ltd.

A combinatorial approach for transmission expansion & reactive power planning

A metaheuristic technique for solving the short-term transmission network expansion and reactive power planning problems, at the same time, in regulated power systems using the AC model is presented. The problem is solved using a real genetic algorithm (RGA). For each topology proposed by RGA an indicator is employed to identify the weak buses for new reactive power sources allocation. The fitness function is calculated using the cost of each configuration as well as constraints deviation of an AC optimal power flow (OPF) in which the minimum reactive generation of new reactive sources and the active power losses are objectives. With allocation of reactive power sources at load buses, the circuit capacity increases and the cost of installation could be decreased. The method is tested in a well known test system, presenting good results when compared with other approaches. © 2011 IEEE.

Strategies to reduce the number of variables and the combinatorial search space of the multistage transmission expansion planning problem

This paper proposes strategies to reduce the number of variables and the combinatorial search space of the multistage transmission expansion planning problem (TEP). The concept of the binary numeral system (BNS) is used to reduce the number of binary and continuous variables related to the candidate transmission lines and network constraints that are connected with them. The construction phase of greedy randomized adaptive search procedure (GRASP-CP) and additional constraints, obtained from power flow equilibrium in an electric power system are employed for more reduction in search space. The multistage TEP problem is modeled like a mixed binary linear programming problem and solved using a commercial solver with a low computational time. The results of one test system and two real systems are presented in order to show the efficiency of the proposed solution technique. © 1969-2012 IEEE.

Optimisation of High Hydrostatic Pressure Processing of Pêra Rio Orange Juice

The influence of high hydrostatic pressure (HHP) on Pêra Rio orange juice was investigated using response surface methodology. A central composite design was used to evaluate the effects of three processing conditions (independent variables), namely pressure (100-600 MPa), temperature (30-60 °C) and time (30-360 s), on the native microflora and pectin methylesterase (PME) activity of orange juice. Analysis of variance showed that second-order polynomial models fitted well with the experimental data for PME residual activity (R2 = 0.9586, p < 0.001) and aerobic microorganism count (R2 = 0.9879, p < 0.001). The optimum HHP processing conditions to produce orange juice with PME residual activity of less than 20 % and low microorganism count (<2 log cycles CFU/mL) were 550 to 600 MPa, 55 to 60 °C and 330 to 360 s. © 2013 Springer Science+Business Media New York.

Ethanolysis optimisation of Jupati (Raphia taedigera Mart.) oil to biodiesel using response surface methodology

In this work, the transesterification of jupati (Raphia taedigera Mart.) oil using ethanol and acid catalyst was examined. The production of biodiesel was performed using a central composite design (CCD). A range of values for catalyst concentration (1 to 4.21%), temperature (70-80 °C), and the molar ratio of alcohol to oil (6:1-13.83:1) were tested, and ester content, viscosity, and yield were the response variables. The synthesis process was optimised using response surface methodology (RSM), resulting in the following optimal conditions for the production of jupati ethyl esters: a catalyst concentration of 3.85% at 80 °C and an alcohol-to-oil molar ratio of 10:1.

Optimisation of a sample preparation method for the determination of fumonisin B-1 in rice

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Reactive power planning under conditional-value-at-risk assessment using chance-constrained optimisation

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Combinatorial-topological framework for the analysis of global dynamics

We discuss an algorithmic framework based on efficient graph algorithms and algebraic-topological computational tools. The framework is aimed at automatic computation of a database of global dynamics of a given m-parameter semidynamical system with discrete time on a bounded subset of the n-dimensional phase space. We introduce the mathematical background, which is based upon Conley's topological approach to dynamics, describe the algorithms for the analysis of the dynamics using rectangular grids both in phase space and parameter space, and show two sample applications. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4767672]

Huckebein is part of a combinatorial repression code in the anterior blastoderm

The hierarchy of the segmentation cascade responsible for establishing the Drosophila body plan is composed by gap, pair-rule and segment polarity genes. However, no pair-rule stripes are formed in the anterior regions of the embryo. This lack of stripe formation, as well as other evidence from the literature that is further investigated here, led us to the hypothesis that anterior gap genes might be involved in a combinatorial mechanism responsible for repressing the cis-regulatory modules (CRMs) of hairy (h), even-skipped (eve), runt (run), and fushi-tarazu (ftz) anterior-most stripes. In this study, we investigated huckebein (hkb), which has a gap expression domain at the anterior tip of the embryo. Using genetic methods we were able to detect deviations from the wild-type patterns of the anterior-most pair-rule stripes in different genetic backgrounds, which were consistent with Hkb-mediated repression. Moreover, we developed an image processing tool that, for the most part, confirmed our assumptions. Using an hkb misexpression system, we further detected specific repression on anterior stripes. Furthermore, bioinformatics analysis predicted an increased significance of binding site clusters in the CRMs of h 1, eve 1, run 1 and ftz 1 when Hkb was incorporated in the analysis, indicating that Hkb plays a direct role in these CRMs. We further discuss that Hkb and Slp1, which is the other previously identified common repressor of anterior stripes, might participate in a combinatorial repression mechanism controlling stripe CRMs in the anterior parts of the embryo and define the borders of these anterior stripes. (C) 2011 Elsevier Inc. All rights reserved.

Structural analysis of combinatorial optimization problem characteristics and their resolution using hybrid approaches

Many combinatorial problems coming from the real world may not have a clear and well defined structure, typically being dirtied by side constraints, or being composed of two or more sub-problems, usually not disjoint. Such problems are not suitable to be solved with pure approaches based on a single programming paradigm, because a paradigm that can effectively face a problem characteristic may behave inefficiently when facing other characteristics. In these cases, modelling the problem using different programming techniques, trying to ”take the best” from each technique, can produce solvers that largely dominate pure approaches. We demonstrate the effectiveness of hybridization and we discuss about different hybridization techniques by analyzing two classes of problems with particular structures, exploiting Constraint Programming and Integer Linear Programming solving tools and Algorithm Portfolios and Logic Based Benders Decomposition as integration and hybridization frameworks.

Intrinsic ordering, combinatorial numbers and reliability engineering

[EN]A new algorithm for evaluating the top event probability of large fault trees (FTs) is presented. This algorithm does not require any previous qualitative analysis of the FT. Indeed, its efficiency is independent of the FT logic, and it only depends on the number n of basic system components and on their failure probabilities. Our method provides exact lower and upper bounds on the top event probability by using new properties of the intrinsic order relation between binary strings. The intrinsic order enables one to select binary n-tuples with large occurrence probabilities without necessity to evaluate them. This drastically reduces the complexity of the problem from exponential (2n binary n-tuples) to linear (n Boolean variables)...

Algorithms and Models For Combinatorial Optimization Problems

In this thesis we present some combinatorial optimization problems, suggest models and algorithms for their effective solution. For each problem,we give its description, followed by a short literature review, provide methods to solve it and, finally, present computational results and comparisons with previous works to show the effectiveness of the proposed approaches. The considered problems are: the Generalized Traveling Salesman Problem (GTSP), the Bin Packing Problem with Conflicts(BPPC) and the Fair Layout Problem (FLOP).