Transmission network expansion planning considering uncertainty in demand

This paper presents two mathematical models and one methodology to solve a transmission network expansion planning problem considering uncertainty in demand. The first model analyzed the uncertainty in the system as a whole; then, this model considers the uncertainty in the total demand of the power system. The second one analyzed the uncertainty in each load bus individually. 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 models presented are solved using a specialized genetic algorithm. The results obtained for several known systems from literature show that cheaper plans can be found satisfying the uncertainty in demand.

Harmonic identification using parallel neural networks in single-phase systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

An implementation of modified scatter search algorithm to transmission expansion planning

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

Utilização de índices de estabilidade transitória para a avaliação de segurança dinâmica

Indices that report how much a contingency is stable or unstable in an electrical power system have been the object of several studies in the last decades. In some approaches, indices are obtained from time-domain simulation; others explore the calculation of the stability margin from the so-called direct methods, or even by neural networks.The goal is always to obtain a fast and reliable way of analysing large disturbance that might occur on the power systems. A fast classification in stable and unstable, as a function of transient stability is crucial for a dynamic security analysis. All good propositions as how to analyse contingencies must present some important features: classification of contingencies; precision and reliability; and efficiency computation. Indices obtained from time-domain simulations have been used to classify the contingencies as stable or unstable. These indices are based on the concepts of coherence, transient energy conversion between kinetic energy and potential energy, and three dot products of state variable. The classification of the contingencies using the indices individually is not reliable, since the performance of these indices varies with each simulated condition. However, collapsing these indices into a single one can improve the analysis significantly. In this paper, it is presented the results of an approach to filter the contingencies, by a simple classification of them into stable, unstable or marginal. This classification is performed from the composite indices obtained from step by step simulation with a time period of the clearing time plus 0.5 second. The contingencies originally classified as stable or unstable do not require this extra simulation. The methodology requires an initial effort to obtain the values of the intervals for classification, and the weights. This is performed once for each power system and can be used in different operating conditions and for different contingencies. No misplaced classification o- - ccurred in any of the tests, i.e., we detected no stable case classified as unstable or otherwise. The methodology is thus well fitted for it allows for a rapid conclusion about the stability of th system, for the majority of the contingencies (Stable or Unstable Cases). The tests, results and discussions are presented using two power systems: (1) the IEEE17 system, composed of 17 generators, 162 buses and 284 transmission lines; and (2) a South Brazilian system configuration, with 10 generators, 45 buses and 71 lines.

A FEM approach to the equations of magneto-aerodynamics

In this work, a Finite Element Method treatment is outlined for the equations of Magnetoaerodynamics. In order to provide a good basis for numerical treatment of Magneto-aerodynamics, a full version of the complete equations is presented and FEM contribution matrices are deduced, as well as further terms of stabilization for the compressible flow case.

Optimized allocation of sectionalizing switches and control and protection devices for reliability indices improvement in distribution systems

Reliability of power supply is related, among other factors, to the control and protection devices allocation in feeders of distribution systems. In this way, optimized allocation of sectionalizing switches and protection devices in strategic points of distribution circuits, improves the quality of power supply and the system reliability indices. In this work, it is presented a mixed integer non-linear programming (MINLP) model, with real and binary variables, for the sectionalizing switches and protection devices allocation problem, in strategic sectors, aimed at improving reliability indices, increasing the utilities billing and fulfilling exigencies of regulatory agencies for the power supply. Optimized allocation of protection devices and switches for restoration, allows that those faulted sectors of the system can be isolated and repaired, re-managing loads of the analyzed feeder into the set of neighbor feeders. Proposed solution technique is a Genetic Algorithm (GA) developed exploiting the physical characteristics of the problem. Results obtained through simulations for a real-life circuit, are presented. © 2004 IEEE.

Reliability evaluation of distribution systems considering automatic reclosers

This paper presents a new methodology to evaluate in a predictive way the reliability of distribution systems, considering the impact of automatic recloser switches. The developed algorithm is based on state enumeration techniques with Markovian models and on the minimal cut set theory. Some computational aspects related with the implementation of the proposed algorithm in typical distribution networks are also discussed. The description of the proposed approach is carried out using a sample test system. The results obtained with a typical configuration of a Brazilian system (EDP Bandeirante Energia S.A.) are presented and discussed.

Transmission network expansion planning in full open market considering security constraints

This paper presents a mathematical model and a methodology to solve the transmission network expansion planning problem with security constraints in full competitive market, assuming that all generation programming plans present in the system operation are known. The methodology let us find an optimal transmission network expansion plan that allows the power system to operate adequately in each one of the generation programming plans specified in the full competitive market case, including a single contingency situation with generation rescheduling using the security (n-1) criterion. In this context, the centralized expansion planning with security constraints and the expansion planning in full competitive market are subsets of the proposal presented in this paper. The model provides a solution using a genetic algorithm designed to efficiently solve the reliable expansion planning in full competitive market. The results obtained for several known systems from the literature show the excellent performance of the proposed methodology.

Reliability assessment of energy limited systems using sequential montecarlo simulation

This paper explains why the reliability assessment of energy limited systems requires more detailed models for primary generating resources availability, internal and external generating dispatch and customer demand than the ones commonly used for large power systems and presents a methodology based on the full sequential Montecarlo simulation technique with AC power flow for their long term reliability assessment which can properly include these detailed models. By means of a real example, it is shown how the simplified modeling traditionally used for large power systems leads to pessimistic predictions if it is applied to an energy limited system and also that it cannot predict all the load point adequacy problems. © 2006 IEEE.

Intelligent alarm processing

This paper presents the analysis that have been carried out in the alarm system of the DCRanger EMS. The intention of this study is to present the problem of alarm processing in electric energy control centers, its various aspects and operational difficulties due to operator needs. Some tests are produced in order to identify the desirable features an alarm system should possess in order to be of effective help in the operative duty. © 2006 IEEE.

Fatigue resistance of bovine teeth restored with resin-bonded fiber posts: Effect of post surface conditioning

This study evaluated the effect of post surface conditioning on the fatigue resistance of bovine teeth restored with resin-bonded fiber-reinforced composite (FRC). Root canals of 20 single-rooted bovine teeth (16 mm long) were prepared to 12 mm using a preparation drill of a double-tapered fiber post system. Using acrylic resin, each specimen was embedded (up to 3.0 mm from the cervical part of the specimen) in a PVC cylinder and allocated into one of two groups (n = 10) based on the post surface conditioning method: acid etching plus silanization or tribochemical silica coating (30 μm SiOx + silanization). The root canal dentin was etched (H2PO3 for 30 seconds), rinsed, and dried. A multi-step adhesive system was applied to the root dentin and the fiber posts were cemented with resin cement. The specimens were submitted to one million fatigue cycles. After fatigue testing, a score was given based on the number of fatigue cycles until fracture. All of the specimens were resistant to fatigue. No fracture of the root or the post and no loss of retention of the post were observed. The methodology and the results of this study indicate that tribochemical silica coating and acid etching performed equally well when dynamic mechanical loading was used.

A comparative study of the damping oscillation function of TCSC and UPFC

The main objective of this work is to analyze the ability of FACTS devices like TCSC and UPFC to damp low frequency oscillations and a POD controller is also included. A comparative study of damping effect of those devices IS carried out. The Power Sensitivity Model (PSM) is used to the representation of the electric power system. Sensibility analysis using the residue method shows the best place for the installation of FACTS and the procedure to determine POD parameters. ©2008 IEEE.

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.

Transmission network expansion planning considering multiple generation scenarios

This paper presents a mathematical model and a methodology to solve a transmission network expansion planning problem considering open access. The methodology finds the optimal transmission network expansion plan that allows the power system to operate adequately in an environment with multiples generation scenarios. The model presented is solved using a specialized genetic algorithm. The methodology is tested in a system from the literature. ©2008 IEEE.

Planeamiento de la expansión de sistemas de transmisión considerando contingencias y demanda incierta

This paper presents a methodology and a mathematical model to solve the expansion planning problem that takes into account the effect of contingencies in the planning stage, and considers the demand as a stochastic variable within a specified range. In this way, it is possible to find a solution that minimizes the investment costs guarantying reliability and minimizing future load shedding. The mathematical model of the expansion planning can be represented by a mixed integer nonlinear programming problem. To solve this problem a specialized Genetic Algorithm combined with Linear Programming was implemented.