Transmission-expansion planning using the DC model and nonlinear-programming technique

The paper presents a constructive heuristic algorithm (CHA) for solving directly the long-term transmission-network-expansion-planning (LTTNEP) problem using the DC model. The LTTNEP is a very complex mixed-integer nonlinear-programming problem and presents a combinatorial growth in the search space. The CHA is used to find a solution for the LTTNEP problem of good quality. A sensitivity index is used in each step of the CHA to add circuits to the system. This sensitivity index is obtained by solving the relaxed problem of LTTNEP, i.e. considering the number of circuits to be added as a continuous variable. The relaxed problem is a large and complex nonlinear-programming problem and was solved through the interior-point method (IPM). Tests were performed using Garver's system, the modified IEEE 24-Bus system and the Southern Brazilian reduced system. The results presented show the good performance of IPM inside the CHA.

Test systems and mathematical models for transmission network expansion planning

The data of four networks that can be used in carrying out comparative studies with methods for transmission network expansion planning are given. These networks are of various types and different levels of complexity. The main mathematical formulations used in transmission expansion studies-transportation models, hybrid models, DC power flow models, and disjunctive models are also summarised and compared. The main algorithm families are reviewed-both analytical, combinatorial and heuristic approaches. Optimal solutions are not yet known for some of the four networks when more accurate models (e.g. The DC model) are used to represent the power flow equations-the state of the art with regard to this is also summarised. This should serve as a challenge to authors searching for new, more efficient methods.

Fruit maturation as a parameter for selection of sweet orange cultivars in Brazil

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Transmission system expansion planning by a branch-and-bound algorithm

A branch and bound (B& B) algorithm using the DC model, to solve the power system transmission expansion planning by incorporating the electrical losses in network modelling problem is presented. This is a mixed integer nonlinear programming (MINLP) problem, and in this approach, the so-called fathoming tests in the B&B algorithm were redefined and a nonlinear programming (NLP) problem is solved in each node of the B& B tree, using an interior-point method. Pseudocosts were used to manage the development of the B&B tree and to decrease its size and the processing time. There is no guarantee of convergence towards global optimisation for the MINLP problem. However, preliminary tests show that the algorithm easily converges towards the best-known solutions or to the optimal solutions for all the tested systems neglecting the electrical losses. When the electrical losses are taken into account, the solution obtained using the Garver system is better than the best one known in the literature.

Real-time monitoring and kinetic parameter estimation of the affinity interaction of jArtinM and rArtinM with peroxidase glycoprotein by the electrogravimetric technique

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

Morse basis expansion applied to diatomic molecules

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

Using traditional heuristic algorithms on an initial genetic algorithm population applied to the transmission expansion planning problem

This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network expansion planning. Constructive heuristic algorithms were used to generate good initial populations, particularly those used in resolving transmission network expansion planning. The results were compared to those found by a genetic algorithm with random initial populations. The results showed that an efficiently generated initial population led to better solutions being found in less time when applied to low complexity electricity distribution networks and better quality solutions for highly complex networks when compared to a genetic algorithm using random initial populations.

ENERGY GENERATION EXPANSION PLANNING MODEL CONSIDERING EMISSIONS CONSTRAINTS

The generation expansion planning (GEP) problem consists in determining the type of technology, size, location and time at which new generation units must be integrated to the system, over a given planning horizon, to satisfy the forecasted energy demand. Over the past few years, due to an increasing awareness of environmental issues, different approaches to solve the GEP problem have included some sort of environmental policy, typically based on emission constraints. This paper presents a linear model in a dynamic version to solve the GEP problem. The main difference between the proposed model and most of the works presented in the specialized literature is the way the environmental policy is envisaged. Such policy includes: i) the taxation of CO(2) emissions, ii) an annual Emissions Reduction Rate (ERR) in the overall system, and iii) the gradual retirement of old inefficient generation plants. The proposed model is applied in an 11-region to design the most cost-effective and sustainable 10-technology US energy portfolio for the next 20 years.

An implementation of modified scatter search algorithm to transmission expansion planning

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

The tension as perturbative parameter in string theory

The author proposes an approach to string theory where the zero-order theory is the null string. An explicit form of the propagator for the null string in the momentum space is found. Considering the tension as a perturbative parameter, the perturbative series is completely summable and the propagator of the bosonic open string with tension T is found.

Comparative studies on non-convex optimization methods for transmission network expansion planning

We have investigated and extensively tested three families of non-convex optimization approaches for solving the transmission network expansion planning problem: simulated annealing (SA), genetic algorithms (GA), and tabu search algorithms (TS). The paper compares the main features of the three approaches and presents an integrated view of these methodologies. A hybrid approach is then proposed which presents performances which are far better than the ones obtained with any of these approaches individually. Results obtained in tests performed with large scale real-life networks are summarized.

The δ expansion and the principle of minimal sensitivity

The δ-expansion is a nonperturbative approach for field theoretic models which combines the techniques of perturbation theory and the variational principle. Different ways of implementing the principle of minimal sensitivity to the δ-expansion produce in general different results for observables. For illustration we use the Nambu-Jona-Lasinio model for chiral symmetry restoration at finite density and compare results with those obtained with the Hartree-Fock approximation.

Physico-chemical parameter correlations in the [RuCl2(CO)(L)(PPh3)2] complexes (L = N-heterocycles)

Fourteen complexes in the series [RuCl2(CO)(L)(PPh3)2] (where L = N-heterocycles) have been prepared and characterized by IR and NMR spectroscopies, and cyclic voltammetry. A good correlation is found between observed and calculated electrochemical potentials; E1/2 vs pKa or (Gp, σm for a series of similar ligands. It is now reported that the carbonyl stretching frequency, νCO, and the 13C and 31P NMR signals do not correlate well with any of the physico-chemical parameters used (E1/2, Taft's and Hammett's parameters). This behaviour is probably due to the characteristics of the Ru(II) species, which does not transmit the steric and electron donor/acceptor properties of the ligands to the carbonyl group, or because the measurements are not able to detect the effect induced by the changes in the ligand L. Indeed, good correlations are obtained when the measurements directly involve the metal centre, as is the case in the E1/2 measurements. Crystals of o[RuCl2(CO)(4-pic)(PPh3)2] are monoclinic, space group P21/n, a = 12.019(2), b = 13.825(3) and c = 22.253(3) . The structure was solved by the Patterson method and was refined by full-matrix least-squares procedure to R = 0.054 and Rw = 0.055, for 2114 reflections with I > 3σ(I). For L = 2-acetylpyridine and 2-methylimidazole, complexes with formulae [RuCl2(CO)(L)(PPh3)] · L and [RuCl2(CO)(L)2 (PPh3)], respectively, were obtained. © 1998 Elsevier Science Ltd. All rights reserved.