A new hybrid technique for power systems multi-facts optimization design

Abstract

Summary The purpose of this paper is to develop a new tool to the dispatching and optimization of reactive power resources using two kinds of the flexible alternating current transmission system devices, namely the static volt ampere reactive compensator and the Thyristor controlled series compensator. The fast voltage stability index and line stability index (Lmn) are used to identify the critical buses and lines, which will receive the flexible alternating current transmission system devices. The methodology carried out in this work is deployed in two phases. In the first one, we consider that the power system network is secure and operates within its stability limits and the balance between consumption and generation is satisfied. Thus, the solution of optimization program of the fuel cost minimization problem using the interior point method gives a feasible solution where the reactive power compensation is not considered. In the second phase, the power system network is unsecure and operates close to its secure limits. Although the optimization program of the fuel cost minimization problem gives a non‐feasible solution, the reactive power compensation is, in this case, introduced to solve the problem. The power transmission line factor minimization problem is applied after each phase to improve the solution of the problem by minimizing the power flow in the transmissions lines. The reactive power planning and the power transmission line factor minimization problems are solved with a new hybrid technique combining particle swarm optimization with a nonlinear interior point method. Furthermore, the fuel cost minimization problem is solved with the interior point method. The methodology has been tested with the IEEE 57‐bus system, and the simulation results show the effectiveness of the proposed approach for improving the reactive power planning problem. Copyright © 2014 John Wiley & Sons, Ltd.

A comprehensive assessment to propose an improved line stability index

“…However, in real systems, P and Q may flow in opposite directions. In such conditions, the above‐mentioned indicators may not properly evaluate the stability status, which has not considered in research works . To clarify this problem, in the network shown in Figure , the L index is calculated in the following operating points: Case P Load = 600 MW, Q Load = 200 MVAr. In this case, since P and Q are flowing from bus 1 to the other one, bus 1 is considered as the SB.…”

“…In this regard, these indicators may seem to be a proper tool for voltage stability assessment. Nevertheless, in the sequel, it will be shown that these indices have a major drawback, which is not considered in the literature . To explain this drawback, consider the simple network shown in Figure A, which includes three transmission lines connected in series.…”

“…In such conditions, the abovementioned indicators may not properly evaluate the stability status, which has not considered in research works. 35,[48][49][50][51][52][53][54][55][56][57][58][59][60][61][62][63][64][65] To clarify this problem, in the network shown in Figure 2, the L index is calculated in the following operating points: In this case, since P and Q are flowing from bus 1 to the other one, bus 1 is considered as the SB. Also, the value of L index is 0.51, which is shown in Table 4.…”

Voltage stability analysis based on multi - objective optimal reactive power dispatch under various contingency

“…), the reactive power planning can reduce voltage deviations and active power losses. And in the same time maximizing voltage stability margin [1][2]. Since the generator reactive power, generator voltages, the transformer ratios and reactive power sources are continuous, the optimization problem is a nonconvex nonlinear programming problem (NLP).…”

“…Since the generator reactive power, generator voltages, the transformer ratios and reactive power sources are continuous, the optimization problem is a nonconvex nonlinear programming problem (NLP). To solve such problem many conventional methods [3][4][5], like stochastic search methods [5][6][7][8][9][10][11] and hybrid conventional-stochastic methods [1], have been proposed.…”