Power system transmission network expansion planning using AC model

An optimisation technique to solve transmission network expansion planning problem, using the AC model, is presented. This is a very complex mixed integer nonlinear programming problem. A constructive heuristic algorithm aimed at obtaining an excellent quality solution for this problem is presented. An interior point method is employed to solve nonlinear programming problems during the solution steps of the algorithm. Results of the tests, carried out with three electrical energy systems, show the capabilities of the method and also the viability of using the AC model to solve the problem.

Rural-urban migration in D-dimensional lattices

The rural-urban migration phenomenon is analyzed by using an agent-based computational model. Agents are placed on lattices which dimensions varying from d = 2 up to d = 7. The localization of the agents in the lattice defines that their social neighborhood (rural or urban) is not related to their spatial distribution. The effect of the dimension of lattice is studied by analyzing the variation of the main parameters that characterizes the migratory process. The dynamics displays strong effects even for around one million of sites, in higher dimensions (d = 6, 7).

Analysis of heuristic algorithms for the transportation model in static and multistage planning in network expansion systems

The usefulness of the application of heuristic algorithms in the transportation model, first proposed by Garver, is analysed in relation to planning for the expansion of transmission systems. The formulation of the mathematical model and the solution techniques proposed in the specialised literature are analysed in detail. Starting with the constructive heuristic algorithm proposed by Garver, an extension is made to the problem of multistage planning for transmission systems. The quality of the solutions found by heuristic algorithms for the transportation model is analysed, as are applications in problems of planning transmission systems.

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.

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.

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.

Global and diffuse solar irradiances in urban and rural areas in southeast Brazil

The seasonal evolution of daily and hourly values of global and diffuse solar radiation at the surface are compared for the cities of São Paulo and Botucatu, both located in Southeast Brazil and representative of urban and rural areas, respectively. The comparisons are based on measurements of global and diffuse solar irradiance carried out at the surface during a six year simultaneous period in these two cities. Despite the similar latitude and altitude, the seasonal evolution of daily values indicate that São Paulo receives, during clear sky days, 7.8% less global irradiance in August and 5.1% less in June than Botucatu. on the other hand, São Paulo receives, during clear sky days, 3.6% more diffuse irradiance in August and 15.6% more in June than Botucatu. The seasonal variation of the diurnal cycle confirms these differences and indicates that they are more pronounced during the afternoon. The regional differences are related to the distance from the Atlantic Ocean, systematic penetration of the sea breeze and daytime evolution of the particulate matter in São Paulo. An important mechanism controlling the spatial distribution of solar radiation, on a regional scale, is the sea breeze penetration in São Paulo, bringing moisture and maritime aerosol that in turn further increases the solar radiation scattering due to pollution and further reduces the intensity of the direct component of solar radiation at the surface. Surprisingly, under clear sky conditions the atmospheric attenuation of solar radiation in Botucatu during winter - the biomass burning period due to the sugar cane harvest - is equivalent to that at São Paulo City, indicating that the contamination during sugar cane harvest in Southeast Brazil has a large impact in the solar radiation field at the surface.

Rural property size drives patterns of upland and riparian forest retention in a tropical deforestation frontier

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

VAr planning using genetic algorithm and linear programming

A combined methodology consisting of successive linear programming (SLP) and a simple genetic algorithm (SGA) solves the reactive planning problem. The problem is divided into operating and planning subproblems; the operating subproblem, which is a nonlinear, ill-conditioned and nonconvex problem, consists of determining the voltage control and the adjustment of reactive sources. The planning subproblem consists of obtaining the optimal reactive source expansion considering operational, economical and physical characteristics of the system. SLP solves the optimal reactive dispatch problem related to real variables, while SGA is used to determine the necessary adjustments of both the binary and discrete variables existing in the modelling problem. Once the set of candidate busbars has been defined, the program implemented gives the location and size of the reactive sources needed, if any, to maintain the operating and security constraints.

Network reconfiguration and loss allocation for distribution systems with distributed generation

Distribution systems with distributed generation require new analysis methods since networks are not longer passive. Two of the main problems in this new scenario are the network reconfiguration and the loss allocation. This work presents a distribution systems graphic simulator, developed with reconfiguration functions and a special focus on loss allocation, both considering the presence of distributed generation. This simulator uses a fast and robust power flow algorithm based on the current summation backward-forward technique. Reconfiguration problem is solved through a heuristic methodology and the losses allocation function, based on the Zbus method, is presented as an attached result for each obtained configuration. Results are presented and discussed, remarking the easiness of analysis through the graphic simulator as an excellent tool for planning and operation engineers, and very useful for training. © 2004 IEEE.

Cytogenetic and random amplified polymorphic DNA analysis of Leptodactylus species from rural and urban environments (Anura, Amphibia)

Cytogenetic and random amplified polymorphic DNA analyses carried out in the species Leptodactylus podicipinus, L. ocellatus, L. labyrinthicus, and L. fuscus from rural and urban habitats of the northwest region of São Paulo State, Brazil, showed that the karyotypes (2n = 22), constitutive heterochromatin distribution and nucleolus organizer region (NOR) location did not differ between the populations from the two environments. The in situ hybridization with an rDNA probe confirmed the location of the NORs on chromosome 8 revealing an in tandem duplication of that region in one of the chromosomes of L. fuscus. DAPI showed that part of the C-band-positive heterochromatin is rich in AT, including that in the proximity the NORs in L. podicipinus and L. ocellatus. The molecular analyses showed that the two populations (urban and rural) of L. podicipinus and L. fuscus are similar from a genetic point of view. The urban and rural populations of species L. ocellatus and L. labyrinthicus showed differences in genetic structures, probably due to urbanization which interferes with the dispersion of those frogs. The marked differences observed between the two populations of L. ocellatus can be representing the cryptic condition of the species. Unweighted pair-group method of analysis and genetic distance analysis detected the genetic proximity between L. ocellatus and L. fuscus. The results indicate that there was no reduction in the genetic diversity in the populations from the urban environment; however, the survival of these frogs would not be guaranteed in the case of an increase in human impact especially for populations of L. labyrinthicus and L. ocellatus. ©FUNPEC-RP.

Avaliação de interpoladores estatísticos e determinísticos na estimativa de atributos do solo em agricultura de precisão

The obtaining of the correct space distribution for attributes of the soil is relevant in the agricultural planning, in what concerns to the installation and maintenance of the cultures. The objective of that work was to compare statistical interpolation methods (ordinary krigagem) and deterministic methods (inverse square distance) in the estimate of CTC and V% in a distrophic yellow-red Latossolo. The study was accomplished in the State of Experimental Hands on of the Instituto Capixaba de Pesquisa, Assistência Técnica e Extensão Rural (INCAPER), in an irregular grading with 109 points. The data were collected in the layer of 0 - 0,20 m in the projection of the cup of the plants, in the superior part of the slope. The performance of the interpolators was obtained and compared using the criterion of the medium mistake. The observations are dependent in space until a maximum reach of 14,1 m, considering the isotropy. IDW presented larger mistake in the estimate of the data; however its difference in relation to KRIG was small for both variables.

Planning accelerated life tests under Exponentiated-Weibull-Arrhenius model

Purpose - The purpose of this paper is to present designs for an accelerated life test (ALT). Design/methodology/approach - Bayesian methods and simulation Monte Carlo Markov Chain (MCMC) methods were used. Findings - In the paper a Bayesian method based on MCMC for ALT under EW distribution (for life time) and Arrhenius models (relating the stress variable and parameters) was proposed. The paper can conclude that it is a reasonable alternative to the classical statistical methods since the implementation of the proposed method is simple, not requiring advanced computational understanding and inferences on the parameters can be made easily. By the predictive density of a future observation, a procedure was developed to plan ALT and also to verify if the conformance fraction of the manufactured process reaches some desired level of quality. This procedure is useful for statistical process control in many industrial applications. Research limitations/implications - The results may be applied in a semiconductor manufacturer. Originality/value - The Exponentiated-Weibull-Arrhenius model has never before been used to plan an ALT. © Emerald Group Publishing Limited.

Transmission network expansion planning considering uncertainty in generation and demand

This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering uncertainty in demand and generation. The methodology used to solve the problem, finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with uncertainty. The model presented results in an optimization problem that is solved using a specialized genetic algorithm. The results obtained for known systems from the literature show that cheaper plans can be found satisfying the uncertainty in demand and generation. ©2008 IEEE.