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.

Parallel simulated annealing applied to long term transmission network expansion planning

The simulated annealing optimization technique has been successfully applied to a number of electrical engineering problems, including transmission system expansion planning. The method is general in the sense that it does not assume any particular property of the problem being solved, such as linearity or convexity. Moreover, it has the ability to provide solutions arbitrarily close to an optimum (i.e. it is asymptotically convergent) as the cooling process slows down. The drawback of the approach is the computational burden: finding optimal solutions may be extremely expensive in some cases. This paper presents a Parallel Simulated Annealing, PSA, algorithm for solving the long term transmission network expansion planning problem. A strategy that does not affect the basic convergence properties of the Sequential Simulated Annealing algorithm have been implementeded and tested. The paper investigates the conditions under which the parallel algorithm is most efficient. The parallel implementations have been tested on three example networks: a small 6-bus network, and two complex real-life networks. Excellent results are reported in the test section of the paper: in addition to reductions in computing times, the Parallel Simulated Annealing algorithm proposed in the paper has shown significant improvements in solution quality for the largest of the test networks.

A new three-phase transformer modeling for three-phase harmonic analysis in distribution systems

This work presents a new three-phase transformer modeling suitable for simulations in Pspice environment, which until now represents the electrical characteristics of a real transformer. It is proposed the model comparison to a three-phase transformer modeling present in EMTP - ATP program, which includes the electrical and magnetic characteristics. In addition, a set including non-linear loads and a real three-phase transformer was prepared in order to compare and validate the results of this new proposed model. The three-phase Pspice transformer modeling, different from the conventional one using inductance coupling, is remarkable for its simplicity and ease in simulation process, since it uses available voltage and current sources present in Pspice program, enabling simulations of three-phase network system including the most common configuration, three wires in the primary side and four wires in the secondary side (three-phases and neutral). Finally, the proposed modeling becomes a powerful tool for three-phase network simulations due to its simplicity and accuracy, able to simulate and analyze harmonic flow in three-phase systems under balanced and unbalanced conditions.

Optimal capacitor placement in radial distribution networks

The capacitor placement (replacement) problem for radial distribution networks determines capacitor types, sizes, locations and control schemes. Optimal capacitor placement is a hard combinatorial problem that can be formulated as a mixed integer nonlinear program. Since this is a NP complete problem (Non Polynomial time) the solution approach uses a combinatorial search algorithm. The paper proposes a hybrid method drawn upon the Tabu Search approach, extended with features taken from other combinatorial approaches such as genetic algorithms and simulated annealing, and from practical heuristic approaches. The proposed method has been tested in a range of networks available in the literature with superior results regarding both quality and cost of solutions.

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.

A neural network-based preset generation tool for a steel tandem cold mill

This paper traces the development of a software tool, based oil a combination of artificial neural networks (ANN) and a few process equations. aiming to serve as a backup operation instrument in the reference generation for real-time controllers of a steel tandem cold mill By emulating the mathematical model responsible for generating presets under normal operational conditions, the system works as ail option to maintain plant operation in the event of a failure in the processing unit that executes the mathematical model. The system, built from the production data collected over six years of plant operation, steered to the replacement of the former backup operation mode (based oil a lookup table). which degraded both product quality and plant productivity. The study showed that ANN are appropriated tools for the intended purpose and that by this instrument it is possible to achieve nearly the totality of the presets needed by this land of process. The text characterizes the problem, relates the investigated options to solve it. justifies the choice of the ANN approach, describes the methodology and system implementation and, finally, shows and discusses the attained results. (C) 2009 Elsevier Ltd. All rights reserved

A Top-Down Approach for Distribution Loss Evaluation

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

Bayesian estimation of generalized exponential distribution under noninformative priors

The generalized exponential distribution, proposed by Gupta and Kundu (1999), is a good alternative to standard lifetime distributions as exponential, Weibull or gamma. Several authors have considered the problem of Bayesian estimation of the parameters of generalized exponential distribution, assuming independent gamma priors and other informative priors. In this paper, we consider a Bayesian analysis of the generalized exponential distribution by assuming the conventional non-informative prior distributions, as Jeffreys and reference prior, to estimate the parameters. These priors are compared with independent gamma priors for both parameters. The comparison is carried out by examining the frequentist coverage probabilities of Bayesian credible intervals. We shown that maximal data information prior implies in an improper posterior distribution for the parameters of a generalized exponential distribution. It is also shown that the choice of a parameter of interest is very important for the reference prior. The different choices lead to different reference priors in this case. Numerical inference is illustrated for the parameters by considering data set of different sizes and using MCMC (Markov Chain Monte Carlo) methods.

On a moment problem associated with Chebyshev polynomials

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

An overview on network cost allocation methods

This work is devoted to Study and discuss the main methods to solve the network cost allocation problem both for generators and demands. From the presented, compared and discussed methods, the first one is based on power injections, the second deals with proportional sharing factors, the third is based upon Equivalent Bilateral Exchanges, the fourth analyzes the power How sensitivity in relation to the power injected, and the last one is based on Z(bus) network matrix. All the methods are initially illustrated using a 4-bus system. In addition, the IEEE 24-bus RTS system is presented for further comparisons and analysis. Appropriate conclusions are finally drawn. (C) 2008 Elsevier B.V. All rights reserved.

Comparison of Reactive Power Support in Distribution Networks Provided by Capacitor Banks and Distributed Generators

This paper presents a comparison of reactive power support in distribution networks provided by switched Capacitor Banks (CBs) and Distributed Generators (DGs). Regarding switched CBs, a Tabu Search metaheuristic algorithm is developed to determine their optimal operation with the objective of reducing the power losses in the lines on the system, while meeting network constraints. on the other hand, the optimal operation of DGs is analyzed through an evolutionary Multi-Objective (MO) programming approach. The objectives of such approach are the minimization of power losses and operation cost of the DGs. The comparison of the reactive power support provided by switched CBs and DGs is carried out using a modified IEEE 34 bus distribution test system.

NDACC/SAOZ UV-visible total ozone measurements: improved retrieval and comparison with correlative ground-based and satellite observations

Accurate long-term monitoring of total ozone is one of the most important requirements for identifying possible natural or anthropogenic changes in the composition of the stratosphere. For this purpose, the NDACC (Network for the Detection of Atmospheric Composition Change) UV-visible Working Group has made recommendations for improving and homogenizing the retrieval of total ozone columns from twilight zenith-sky visible spectrometers. These instruments, deployed all over the world in about 35 stations, allow measuring total ozone twice daily with limited sensitivity to stratospheric temperature and cloud cover. The NDACC recommendations address both the DOAS spectral parameters and the calculation of air mass factors (AMF) needed for the conversion of O-3 slant column densities into vertical column amounts. The most important improvement is the use of O-3 AMF look-up tables calculated using the TOMS V8 (TV8) O-3 profile climatology, that allows accounting for the dependence of the O-3 AMF on the seasonal and latitudinal variations of the O-3 vertical distribution. To investigate their impact on the retrieved ozone columns, the recommendations have been applied to measurements from the NDACC/SAOZ (Systeme d'Analyse par Observation Zenithale) network. The revised SAOZ ozone data from eight stations deployed at all latitudes have been compared to TOMS, GOMEGDP4, SCIAMACHY-TOSOMI, SCIAMACHY-OL3, OMI-TOMS, and OMI-DOAS satellite overpass observations, as well as to those of collocated Dobson and Brewer instruments at Observatoire de Haute Provence (44 degrees N, 5.5 degrees E) and Sodankyla (67 degrees N, 27 degrees E), respectively. A significantly better agreement is obtained between SAOZ and correlative reference ground-based measurements after applying the new O-3 AMFs. However, systematic seasonal differences between SAOZ and satellite instruments remain. These are shown to mainly originate from (i) a possible problem in the satellite retrieval algorithms in dealing with the temperature dependence of the ozone cross-sections in the UV and the solar zenith angle (SZA) dependence, (ii) zonal modulations and seasonal variations of tropospheric ozone columns not accounted for in the TV8 profile climatology, and (iii) uncertainty on the stratospheric ozone profiles at high latitude in the winter in the TV8 climatology. For those measurements mostly sensitive to stratospheric temperature like TOMS, OMI-TOMS, Dobson and Brewer, or to SZA like SCIAMACHY-TOSOMI, the application of temperature and SZA corrections results in the almost complete removal of the seasonal difference with SAOZ, improving significantly the consistency between all ground-based and satellite total ozone observations.

Algorithms for network piecewise-linear programs: A comparative study

Piecewise-Linear Programming (PLP) is an important area of Mathematical Programming and concerns the minimisation of a convex separable piecewise-linear objective function, subject to linear constraints. In this paper a subarea of PLP called Network Piecewise-Linear Programming (NPLP) is explored. The paper presents four specialised algorithms for NPLP: (Strongly Feasible) Primal Simplex, Dual Method, Out-of-Kilter and (Strongly Polynomial) Cost-Scaling and their relative efficiency is studied. A statistically designed experiment is used to perform a computational comparison of the algorithms. The response variable observed in the experiment is the CPU time to solve randomly generated network piecewise-linear problems classified according to problem class (Transportation, Transshipment and Circulation), problem size, extent of capacitation, and number of breakpoints per arc. Results and conclusions on performance of the algorithms are reported.

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.