An application of CHA to concurrent short-term transmission expansion & reactive power planning

In this paper a heuristic technique for solving simultaneous short-term transmission network expansion and reactive power planning problem (TEPRPP) via an AC model is presented. A constructive heuristic algorithm (CHA) aimed to obtaining a significant quality solution for such problem is employed. An interior point method (IPM) is applied to solve TEPRPP as a nonlinear programming (NLP) during the solution steps of the algorithm. For each proposed network topology, an indicator is deployed to identify the weak buses for reactive power sources placement. The objective function of NLP includes the costs of new transmission lines, real power losses as well as reactive power sources. By allocating reactive power sources at load buses, the circuit capacity may increase while the cost of new lines can be decreased. The proposed methodology is tested on Garver's system and the obtained results shows its capability and the viability of using AC model for solving such non-convex optimization problem. © 2011 IEEE.

An unequivocal normalization-based paradigm to solve dynamic economic and emission active-reactive OPF (optimal power flow)

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

Despacho ótimo de potências ativa e reativa de sistema elétricos multi-áreas considerando restrições físicas, econômicas e ambientais =: Envronmentally constrained active-reactive optimal power flow-a compromising strategy for economic-emission dispatch and a multi-area paradigm

Pós-graduação em Engenharia Elétrica - FEIS

Interior-exterior point method with global convergence strategy for solving the reactive optimal power flow problem

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Optimal Conditions for Biomass and Recombinant Glycerol Kinase Production Using the Yeast Pichia pastoris

The extracellular glycerol kinase gene from Saccharomyces cerevisiae (GUT]) was cloned into the expression vector pPICZ alpha. A and integrated into the genome of the methylotrophic yeast Pichia pastoris X-33. The presence of the GUT1 insert was confirmed by PCR analysis. Four clones were selected and the functionality of the recombinant enzyme was assayed. Among the tested clones, one exhibited glycerol kinase activity of 0.32 U/mL, with specific activity of 0.025 U/mg of protein. A medium optimized for maximum biomass production by recombinant Pichia pastoris in shaker cultures was initially explored, using 2.31 % (by volume) glycerol as the carbon source. Optimization was carried out by response surface methodology (RSM). In preliminary experiments, following a Plackett-Burman design, glycerol volume fraction (phi(Gly)) and growth time (t) were selected as the most important factors in biomass production. Therefore, subsequent experiments, carried out to optimize biomass production, followed a central composite rotatable design as a function of phi(Gly) and time. Glycerol volume fraction proved to have a significant positive linear effect on biomass production. Also, time was a significant factor (at linear positive and quadratic levels) in biomass production. Experimental data were well fitted by a convex surface representing a second order polynomial model, in which biomass is a function of both factors (R(2)=0.946). Yield and specific activity of glycerol kinase were mainly affected by the additions of glycerol and methanol to the medium. The optimized medium composition for enzyme production was: 1 % yeast extract, 1 % peptone, 100 mM potassium phosphate buffer, pH=6.0, 1.34 % yeast nitrogen base (YNB), 4.10(-5) % biotin, 1 %, methanol and 1 %, glycerol, reaching 0.89 U/mL of glycerol kinase activity and 14.55 g/L of total protein in the medium after 48 h of growth.

A geometric interpretation for transmission real losses minimization through the optimal power flow and its influence on voltage collapse

This work presents an approach for geometric solution of an optimal power flow (OPF) problem for a two bus system (a slack and a PV busses). Additionally, the geometric relationship between the losses minimization and the increase of the reactive margin and, therefore, the maximum loading point, is shown. The algebraic equations for the calculation of the Lagrange multipliers and for the minimum losses value are obtained. These equations are used to validate the results obtained using an OPF program. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Optimised placement of control and protective devices in electric distribution systems through reactive tabu search algorithm

Optimised placement of control and protective devices in distribution networks allows for a better operation and improvement of the reliability indices of the system. Control devices (used to reconfigure the feeders) are placed in distribution networks to obtain an optimal operation strategy to facilitate power supply restoration in the case of a contingency. Protective devices (used to isolate faults) are placed in distribution systems to improve the reliability and continuity of the power supply, significantly reducing the impacts that a fault can have in terms of customer outages, and the time needed for fault location and system restoration. This paper presents a novel technique to optimally place both control and protective devices in the same optimisation process on radial distribution feeders. The problem is modelled through mixed integer non-linear programming (MINLP) with real and binary variables. The reactive tabu search algorithm (RTS) is proposed to solve this problem. Results and optimised strategies for placing control and protective devices considering a practical feeder are presented. (c) 2007 Elsevier B.V. All rights reserved.

Efficient method for AC transmission network expansion planning

A combinatorial mathematical model in tandem with a metaheuristic technique for solving transmission network expansion planning (TNEP) using an AC model associated with reactive power planning (RPP) is presented in this paper. AC-TNEP is handled through a prior DC model while additional lines as well as VAr-plants are used as reinforcements to cope with real network requirements. The solution of the reinforcement stage can be obtained by assuming all reactive demands are supplied locally to achieve a solution for AC-TNEP and by neglecting the local reactive sources, a reactive power planning (RPP) will be managed to find the minimum required reactive power sources. Binary GA as well as a real genetic algorithm (RCA) are employed as metaheuristic optimization techniques for solving this combinatorial TNEP as well as the RPP problem. High quality results related with lower investment costs through case studies on test systems show the usefulness of the proposal when working directly with the AC model in transmission network expansion planning, instead of relaxed models. (C) 2010 Elsevier B.V. All rights reserved.

On non-linear dynamics and an optimal control synthesis of the action potential of membranes (ideal and non-ideal cases) of the Hodgkin-Huxley (HH) mathematical model

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

Evaluation of economic impact of external eauivalent models used in reactive OPF studies for interconnected systems

Reactive-optimisation procedures are responsible for the minimisation of online power losses in interconnected systems. These procedures are performed separately at each control centre and involve external network representations. If total losses can be minimised by the implementation of calculated local control actions, the entire system benefits economically, but such control actions generally result in a certain degree of inaccuracy, owing to errors in the modelling of the external system. Since these errors are inevitable, they must at least be maintained within tolerable limits by external-modelling approaches. Care must be taken to avoid unrealistic loss minimisation, as the local-control actions adopted can lead the system to points of operation which will be less economical for the interconnected system as a whole. The evaluation of the economic impact of the external modelling during reactive-optimisation procedures in interconnected systems, in terms of both the amount of losses and constraint violations, becomes important in this context. In the paper, an analytical approach is proposed for such an evaluation. Case studies using data from the Brazilian South-Southeast system (810 buses) have been carried out to compare two different external-modelling approaches, both derived from the equivalent-optimal-power-flow (EOPF) model. Results obtained show that, depending on the external-model representation adopted, the loss representation can be flawed. Results also suggest some modelling features that should be adopted in the EOPF model to enhance the economy of the overall system.

A metaheuristic to solve the transmission expansion planning

In this letter, a genetic algorithm (GA) is applied to solve - the static and multistage transmission expansion planning (TEP) problem. The characteristics of the proposed GA to solve the TEP problem are presented. Results using some known systems show that the proposed GA solves a smaller number of linear programming problems in order to find the optimal solutions and obtains a better solution for the multistage TEP problem.

Transmission network expansion planning with security constraints

A mathematical model and a methodology to solve the transmission network expansion planning problem with security constraints are presented. The methodology allows one to find an optimal and reliable transmission network expansion plan using a DC model to represent the electrical network. The security (n-1) criterion is used. The model presented is solved using a genetic algorithm designed to solve the reliable expansion planning in an efficient way. The results obtained for several known systems from literature show the excellent performance of the proposed methodology. A comparative analysis of the results obtained with the proposed methodology is also presented.

Altered patterns of maltose and glucose fermentation by brewing and wine yeasts influenced by the complexity of nitrogen source

Maltose and glucose fermentations by industrial brewing and wine yeasts strains were strongly affected by the structural complexity of the nitrogen source. In this study, four Saccharomyces cerevisiae strains, two brewing and two wine yeasts, were grown in a medium containing maltose or glucose supplemented with a nitrogen source varying from a single ammonium salt (ammonium sulfate) to free amino acids (casamino acids) and peptides (peptone). Diauxie was observed at low sugar concentration for brewing and wine strains, independent of nitrogen supplementation, and the type of sugar. At high sugar concentrations altered patterns of sugar fermentation were observed, and biomass accumulation and ethanol production depended on the nature of the nitrogen source and were different for brewing and wine strains. In maltose, high biomass production was observed under peptone and casamino acids for the brewing and wine strains, however efficient maltose utilization and high ethanol production was only observed in the presence of casamino acids for one brewing and one wine strain studied. Conversely, peptone and casamino acids induced higher biomass and ethanol production for the two other brewing and wine strains studied. With glucose, in general, peptone induced higher fermentation performance for all strains, and one brewing and wine strain produced the same amount of ethanol with peptone and casamino acids supplementation. Ammonium salts always induced poor yeast performance. The results described in this paper suggest that the complex nitrogen composition of the cultivation medium may create conditions resembling those responsible for inducing sluggish/stuck fermentation, and indicate that the kind and concentration of sugar, the complexity of nitrogen source and the yeast genetic background influence optimal industrial yeast fermentation performance.

Specialised branch-and-bound algorithm for transmission network expansion planning

An algorithm is presented that finds the optimal plan long-term transmission for till cases studied, including relatively large and complex networks. The knowledge of optimal plans is becoming more important in the emerging competitive environment, to which the correct economic signals have to be sent to all participants. The paper presents a new specialised branch-and-bound algorithm for transmission network expansion planning. Optimality is obtained at a cost, however: that is the use of a transportation model for representing the transmission network, in this model only the Kirchhoff current law is taken into account (the second law being relaxed). The expansion problem then becomes an integer linear program (ILP) which is solved by the proposed branch-and-bound method without any further approximations. To control combinatorial explosion the branch- and bound algorithm is specialised using specific knowledge about the problem for both the selection of candidate problems and the selection of the next variable to be used for branching. Special constraints are also used to reduce the gap between the optimal integer solution (ILP program) and the solution obtained by relaxing the integrality constraints (LP program). Tests have been performed with small, medium and large networks available in the literature.

Efficient linear programming algorithm for the transmission network expansion planning problem

The transmission network planning problem is a non-linear integer mixed programming problem (NLIMP). Most of the algorithms used to solve this problem use a linear programming subroutine (LP) to solve LP problems resulting from planning algorithms. Sometimes the resolution of these LPs represents a major computational effort. The particularity of these LPs in the optimal solution is that only some inequality constraints are binding. This task transforms the LP into an equivalent problem with only one equality constraint (the power flow equation) and many inequality constraints, and uses a dual simplex algorithm and a relaxation strategy to solve the LPs. The optimisation process is started with only one equality constraint and, in each step, the most unfeasible constraint is added. The logic used is similar to a proposal for electric systems operation planning. The results show a higher performance of the algorithm when compared to primal simplex methods.