Neural network approach for surface roughness prediction in surface grinding

Several systems are currently tested in order to obtain a feasible and safe method for automation and control of grinding process. This work aims to predict the surface roughness of the parts of SAE 1020 steel ground in a surface grinding machine. Acoustic emission and electrical power signals were acquired by a commercial data acquisition system. The former from a fixed sensor placed near the workpiece and the latter from the electric induction motor that drives the grinding wheel. Both signals were digitally processed through known statistics, which with the depth of cut composed three data sets implemented to the artificial neural networks. The neural network through its mathematical logical system interpreted the signals and successful predicted the workpiece roughness. The results from the neural networks were compared to the roughness values taken from the worpieces, showing high efficiency and applicability on monitoring and controlling the grinding process. Also, a comparison among the three data sets was carried out.

A resolução do problema de despacho ótimo de reativos pelo método da função Lagrangiana-barreira relaxada

This work presents the application of the relaxed barrier-Lagrangian function method to the optimal reactive dispatch problem, which is a nonlinear nonconvex and large problem. In this approach the inequality constraints are treated by the association of modified barrier and primal-dual logarithmic barrier method. Those constraints are transformed in equalities through positive auxiliary variables and are perturbed by the barrier parameter. A Lagrangian function is associated to the modified problem. The first-order necessary conditions are applied generating a non-linear system which is solved by Newton's method. The auxiliary variables perturbation result in an expansion of the feasible set of the original problem, allowing the limits of the inequality constraints to be reach. Numeric tests with the systems CESP 53 buses and the south-southeast Brazilian and the comparative test with the primal-dual logarithmic barrier method indicate that presented method is efficient in the resolution of optimal reactive dispatch problem.

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.

Analysis of electric torque in single machine-infinite bus system using phase shifters

ResumoThe main idea of this work is based on the analysis of the electric torque through the acting of the PS in the power system, provided of a control for the compensation degree (PSC). A linear model of the single machine-infinite bus system is used with a PS installed (SMIB/PS system). The variable that represents the presence of PS in the net is associated to the phase displacement introduced in the terminal voltage of the synchronous machine by PS. For the input signals of the PSC are evaluated variations of the angular speed of the rotor, the current magnitude and the active power through the line where the PS is located. The simulations are accomplished to analyze the influence of the PS in the torque formation (synchronizing and damping), of the SMIB/PS system. The analysis are developed in the time and frequency domain.

Distribution network planning using a constructive heuristic algorithm

An optimization technique to solve distribution network planning (DNP) problem is presented. This is a very complex mixed binary nonlinear programming problem. A constructive heuristic algorithm (CHA) aimed at obtaining an excellent quality solution for this problem is presented. In each step of the CHA, a sensitivity index is used to add a circuit or a substation to the distribution network. This sensitivity index is obtained solving the DNP problem considering the numbers of circuits and substations to be added as continuous variables (relaxed problem). The relaxed problem is a large and complex nonlinear programming and was solved through an efficient nonlinear optimization solver. A local improvement phase and a branching technique were implemented in the CHA. Results of two tests using a distribution network are presented in the paper in order to show the ability of the proposed algorithm. ©2009 IEEE.

On the efficiency of an alternative codification for multiobjective service restoration in electric distribution networks

This paper proposes an alternative codification to solve the service restoration in electric power distribution networks using a SPEA2 multiobjective evolutionary algorithm, assuming the minimization of both the load not supplied and the number of switching operations involved in the restoration plan. Constrains as the line, power source and voltage drop limits in order to avoid the activation of protective devices are all included in the proposed algorithm. Experimental results have shown the convenience on considering these new representations in the sense of feasibility maintenance and also in the sense of better approximation to the Pareto set. ©2009 IEEE.

Modelo AC para el despacho combinado de contratos bilaterales y bolsa de energía considerando restricciones de seguridad

Reliability is a key aspect in power system design and planning. Maintaining a reliable power system is a very important issue for their design and operation. Under the new competitive framework of the electricity sector, power systems find ever more and more strained to operate near their limits. Under this new scenario, it is crucial for the system operator to use tools that facilitate an energy dispatch that minimizes possible power cuts. This paper presents a mathematical model to calculate an energy dispatch that considers security constraints (single contingencies in transmission lines and transformers). The model involves pool markets and fixed bilateral contracts. Traditional methodologies that include security constraints are usually based in multistage dispatch processes. In this case, we propose a single-stage model that avoids the economic inefficiencies which result when conventional multi-stage dispatch approaches are applied. The proposed model includes an AC representation of the transport system and allows calculating the cost overruns incurred in due to reliability restrictions. We found that complying with fixed bilateral contracts, when they go above certain levels, might lead to congestion problems in transmission lines.

Spatial electric load forecasting using a local movement approach

An agent based model for spatial electric load forecasting using a local movement approach for the spatiotemporal allocation of the new loads in the service zone is presented. The density of electrical load for each of the major consumer classes in each sub-zone is used as the current state of the agents. The spatial growth is simulated with a walking agent who starts his path in one of the activity centers of the city and goes to the limits of the city following a radial path depending on the different load levels. A series of update rules are established to simulate the S growth behavior and the complementarity between classes. The results are presented in future load density maps. The tests in a real system from a mid-size city show a high rate of success when compared with other techniques. The most important features of this methodology are the need for few data and the simplicity of the algorithm, allowing for future scalability. © 2009 IEEE.

Specialized genetic algorithm for transmission network expansion planning considering reliability

This paper presents a methodology to solve the transmission network expansion planning problem (TNEP) considering reliability and uncertainty in the demand. The proposed methodology provides an optimal expansion plan that allows the power system to operate adequately with an acceptable level of reliability and in an enviroment with uncertainness. The reliability criterion limits the expected value of the reliability index (LOLE - Loss Of Load Expectation) of the expanded system. The reliability is evaluated for the transmission system using an analytical technique based in enumeration. The mathematical model is solved, in a efficient way, using a specialized genetic algorithm of Chu-Beasley modified. Detailed results from an illustrative example are presented and discussed. © 2009 IEEE.

Fast non-technical losses identification through Optimum-Path Forest

Fraud detection in energy systems by illegal consumers is the most actively pursued study in non-technical losses by electric power companies. Commonly used supervised pattern recognition techniques, such as Artificial Neural Networks and Support Vector Machines have been applied for automatic commercial frauds identification, however they suffer from slow convergence and high computational burden. We introduced here the Optimum-Path Forest classifier for a fast non-technical losses recognition, which has been demonstrated to be superior than neural networks and similar to Support Vector Machines, but much faster. Comparisons among these classifiers are also presented. © 2009 IEEE.

Distributed generation impact evaluation using a multi-objective tabu search

Distribution networks paradigm is changing currently requiring improved methodologies and tools for network analysis and planning. A relevant issue is analyzing the impact of the Distributed Generation penetration in passive networks considering different operation scenarios. Studying DG optimal siting and sizing the planner can identify the network behavior in presence of DG. Many approaches for the optimal DG allocation problem successfully used multi-objective optimization techniques. So this paper contributes to the fundamental stage of multi-objective optimization of finding the Pareto optimal solutions set. It is proposed the application of a Multi-objective Tabu Search and it was verified a better performance comparing to the NSGA-II method. © 2009 IEEE.

Flujo de potencia AC descentralizado para sistemas de potencia multi-área usando un método de descomposición basado en relajación Lagrangiana

A decentralized solution method to the AC power flow problem in power systems with interconnected areas is presented. The proposed methodology allows finding the operation point of a particular area without explicit knowledge of network data of adjacent areas, being only necessary to exchange border information related to the interconnection lines between areas. The methodology is based on the decomposition of the first-order optimality conditions of the AC power flow, which is formulated as a nonlinear programming problem. A 9-bus didactic system, the IEEE Three Area RTS-96 and the IEEE 118 bus test systems are used in order to show the operation and effectiveness of the distributed AC power flow.

Accountability and revenue metering in smart micro-grids

Smart micro-grids offer a new challenging domain for power theories and metering techniques, because they include a variety of intermittent power sources which positively impact on power flow and distribution losses, but may cause voltage asymmetry and frequency variation. Due to the limited power capability of smart micro-grids, the voltage distortion can also get worse (in case of supplying non-linear loads), affecting measurement accuracy and possibly causing tripping of protections. In such a context, a reconsideration of power theories is required, since they form the basis for supply and load characterization. A revision of revenue metering techniques is also needed, to ensure a correct penalization of the loads for their responsibility in generating reactive power, voltage unbalance and distortion. This paper shows that the Conservative Power Theory (CPT) provides a suitable background to cope with smart grids characterization and metering needs. Experimental results validate the proposed approach. © 2010 IEEE.

Multi-area decentralized optimal VAr planning using the Dantzig-Wolfe decomposition principle

This paper presents a new methodology for solving the optimal VAr planning problem in multi-area electric power systems, using the Dantzig-Wolfe decomposition. The original multi-area problem is decomposed into subproblems (one for each area) and a master problem (coordinator). The solution of the VAr planning problem in each area is based on the application of successive linear programming, and the coordination scheme is based on the reactive power marginal costs in the border bus. The aim of the model is to provide coordinated mechanisms to carry out the VAr planning studies maximizing autonomy and confidentiality for each area, assuring global economy to the whole system. Using the mathematical model and computational implementation of the proposed methodology, numerical results are presented for two interconnected systems, each of them composed of three equal subsystems formed by IEEE30 and IEEE118 test systems. © 2011 IEEE.

An unproblematic method to solve economic and emission dispatch

This paper proposes a method to determine the output of all online units with minimum total cost when the amount of emission is reasonable. A joint economic and emission dispatch is proposed in order to get a significant compromise between costs and emission such that real power supply-demand equilibrium is satisfied. In order to have a meaningful compromise between costs and emission in the problem formulation, two variables are used, weighting factor and price penalty factor. A case study comprising of a 3-unit power system is employed, where various demand is used. Results for the test system indicate the fastness and effectiveness of proposed method. © 2011 IEEE.