952 resultados para TRANSMISSION
Resumo:
In this letter, a genetic algorithm (GA) is applied to solve - the static and multistage transmission expansion planning (TEP) problem. The characteristics of the proposed GA to solve the TEP problem are presented. Results using some known systems show that the proposed GA solves a smaller number of linear programming problems in order to find the optimal solutions and obtains a better solution for the multistage TEP problem.
Resumo:
A novel constructive heuristic algorithm to the network expansion planning problem is presented the basic idea comes from Garver's work applied to the transportation model, nevertheless the proposed algorithm is for the DC model. Tests results with most known systems in the literature are carried out to show the efficiency of the method.
Resumo:
A mathematical model and a methodology to solve the transmission network expansion planning problem with security constraints are presented. The methodology allows one to find an optimal and reliable transmission network expansion plan using a DC model to represent the electrical network. The security (n-1) criterion is used. The model presented is solved using a genetic algorithm designed to solve the reliable expansion planning in an efficient way. The results obtained for several known systems from literature show the excellent performance of the proposed methodology. A comparative analysis of the results obtained with the proposed methodology is also presented.
Resumo:
A constructive heuristic algorithm to solve the transmission system expansion planning problem is proposed with the aim of circumventing some critical problems of classical heuristic algorithms that employ relaxed mathematical models to calculate a sensitivity index that guides the circuit additions. The proposed heuristic algorithm is in a branch-and-bound algorithm structure, which can be used with any planning model, such as Transportation model, DC model, AC model or Hybrid models. Tests of the proposed algorithm are presented on real Brazilian systems.
Resumo:
This paper addresses the problem of allocating the cost of the transmission network to generators and demands. A physically-based network usage procedure is proposed. This procedure exhibits desirable apportioning properties and is easy to implement and understand. A case study based on the IEEE 24-bus system is used to illustrate the working of the proposed technique. Some relevant conclusions are finally drawn.
Resumo:
A quantum treatment for nonlocal factorizable potentials is presented in which the Weyl-Wiper quantum phase space description plays an essential role. The nonlocality is treated in an approximated form and allows for a Feynman propagator that can be handled in standard way. The semi-classical limit of the propagator is obtained which permits the calculation of the transmission factor in quantum tunnelling processes. An application in nuclear physics is also discussed.
Resumo:
A method for optimal transmission network expansion planning is presented. The transmission network is modelled as a transportation network. The problem is solved using hierarchical Benders decomposition in which the problem is decomposed into master and slave subproblems. The master subproblem models the investment decisions and is solved using a branch-and-bound algorithm. The slave subproblem models the network operation and is solved using a specialised linear program. Several alternative implementations of the branch-and-bound algorithm have been rested. Special characteristics of the transmission expansion problem have been taken into consideration in these implementations. The methods have been tested on various test systems available in the literature.
Resumo:
An algorithm is presented that finds the optimal plan long-term transmission for till cases studied, including relatively large and complex networks. The knowledge of optimal plans is becoming more important in the emerging competitive environment, to which the correct economic signals have to be sent to all participants. The paper presents a new specialised branch-and-bound algorithm for transmission network expansion planning. Optimality is obtained at a cost, however: that is the use of a transportation model for representing the transmission network, in this model only the Kirchhoff current law is taken into account (the second law being relaxed). The expansion problem then becomes an integer linear program (ILP) which is solved by the proposed branch-and-bound method without any further approximations. To control combinatorial explosion the branch- and bound algorithm is specialised using specific knowledge about the problem for both the selection of candidate problems and the selection of the next variable to be used for branching. Special constraints are also used to reduce the gap between the optimal integer solution (ILP program) and the solution obtained by relaxing the integrality constraints (LP program). Tests have been performed with small, medium and large networks available in the literature.
Resumo:
The transmission network planning problem is a non-linear integer mixed programming problem (NLIMP). Most of the algorithms used to solve this problem use a linear programming subroutine (LP) to solve LP problems resulting from planning algorithms. Sometimes the resolution of these LPs represents a major computational effort. The particularity of these LPs in the optimal solution is that only some inequality constraints are binding. This task transforms the LP into an equivalent problem with only one equality constraint (the power flow equation) and many inequality constraints, and uses a dual simplex algorithm and a relaxation strategy to solve the LPs. The optimisation process is started with only one equality constraint and, in each step, the most unfeasible constraint is added. The logic used is similar to a proposal for electric systems operation planning. The results show a higher performance of the algorithm when compared to primal simplex methods.
Resumo:
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.
Resumo:
The influence of temperature upon the effects of crotoxin (CTX)? from Crotalus durissus terrificus venom, and gamma-irradiated (Co-60, 2000 Gy) crotoxin (iCTX) was studied in rat neuromuscular transmission 'in vitro'. Indirect twitches were evoked in the phrenic-diaphragm preparation by supramaximal strength pulses with a duration of 0.5 ms and frequency of 0.5 Hz. The phospholipase A(2) (PLA(2)) enzymatic activity of CTX and iCTX was assayed against phosphadityl choline in Triton X-100. At 27 degrees C, CTX (14 mu g/ml) did not affect the amplitude of indirectly evoked twitches. However, at 37 degrees C, CTX induced a time-dependent blockade of the neuromuscular transmission that started at 90 min and was completed within 240 min, iCTX (14 mu g/ml) was inneffective on the neuromuscular transmission either at 27 or 37 degrees C. The PLA(2) enzymatic activity of CTX at 37 degrees C was 84 and that at 27 degrees C was 27 mu mol fatty acid released/min/mg protein, and that of the iCTX at 37 degrees C was 39 mu mol fatty acid released/min/mg protein. Thus, it was concluded that the mechanism of detoxification of CTX by gamma radiation at the neuromuscular level relies on the loss of its PLA(2) enzymatic activity. 2000 Elsevier B.V. Ireland Ltd. All rights reserved.