Efficient linear programming algorithm for the transmission network expansion planning problem

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.

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.

Influence of temperature upon effects of crotoxin and gamma-irradiated crotoxin at rat neuromuscular transmission

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.

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.

Applying a new methodology to verify transmission line model performance - the equivalent impedance test

The objective of this paper is to present a methodology to analyze a transmission line model used in electromagnetic transitory simulators, called equivalent impedance test. Initially the definition of equivalent impedance reference test is shown. Soon after this methodology is applied to a transmission line model, the Quasi-Modes model. The studies were accomplished in a hypothetical non-transposed three-phase transmission fine of 440 kV. The line length is 500 km, and it was modeled through cascades of pi-circuits (with 50 pi's circuits, each with 10 km length).

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.

Allocation of the costs of transmission losses

An analysis of the performance of six major methods of loss allocation for generators and demands was conducted, based on pro-rata (two), on incremental factors (two), on proportional sharing (PS) (one), and on electric circuit theory (one). Using relatively simple examples which can easily be checked, the advantages and disadvantages of each were ascertained and the results confirmed using a larger sample system (IEEE-118). The discussion considers the location and size of generators and demands, as well as the merits of the location of these agents for each configuration based on an analysis of the effect of various network modifications. Furthermore, an application in the South-Southeastern Brazilian Systems is performed. Conclusions and recommendations are presented. (C) 2004 Elsevier B.V. All rights reserved.