Power system structure optimization subject to reliability constraints

Lisnianski, Anatoly; Levitin, Gregory; Ben-Haim, Hanoch; Elmakis, David

doi:10.1016/s0378-7796(96)01106-6

Cited by 129 publications

(51 citation statements)

References 5 publications

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“…The ROP for the multi-state reliability was introduced in [9]. In [10] and [1], genetic algorithms were used to find the optimal or nearly optimal power system structure. In [11] the multi-stage expansion-planning problem for multi-state series-parallel system is solved by using a genetic algorithm as an optimization tool.…”

Section: Literature Reviewmentioning

confidence: 99%

Efficient harmony search algorithm for multi-stages scheduling problem for power systems degradation

et al. 2010

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Usually power energy demand increases randomly with time. To enhance system performance, expansion-planning to adapt the power system capacity to the demand is predicted. This paper uses a harmony search metaheuristic optimization method to solve the multi-stage expansion problem for multi-state series-parallel power systems. The study horizon is divided into several periods. At each period the demand distribution is forecasted in the form of a cumulative demand curve. A multiple-choice of additional components from a list of available products can be chosen and included into any subsystem component at any stage to improve the system performance. The components are characterized by their cost, performance (capacity), and availability. The objective is to minimize each investment over its study period while satisfying availability or performance constraints. A universal generating function technique is applied to evaluate power system availability. The harmony search approach is required to identify the optimal combination of adding components with different parameters to be allocated in parallel at each stage.

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Section: Literature Reviewmentioning

confidence: 99%

Efficient harmony search algorithm for multi-stages scheduling problem for power systems degradation

et al. 2010

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“…For capacitated multi-state systems, the Loss Of Load Probability (LOLP) index is commonly used as a system reliability metric (Lisnianski et al, 1996). This index is understood as the probability that the system cannot supply a given demand load for an operating period that is divided into k operating intervals.…”

Section: Multi-state Reliability Modeling Computation and Simulationmentioning

confidence: 99%

“…, T k ) defines the duration T w and demand level d w during the wth interval. Lisnianski et al (1996) define the LOLP as…”

Section: Multi-state Reliability Modeling Computation and Simulationmentioning

confidence: 99%

Holistic reliability analysis of weighted voting systems from a multi-state perspective

Ramírez-Márquez

2007

IIE Transactions

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The computation of the reliability of weighted voting systems is an important problem in reliability theory due to its potential application in security, target identification, safety and monitoring areas. Voting systems are used in a wide variety of applications where an acceptance or rejection decision has to be made about a binary proposition presented to the system. For these systems, it is of interest to obtain the probability so that based on the vote of decision-making units, the system aggregates these votes into the right decision when presented with such a proposition. This paper presents a holistic work on weighted voting system reliability by presenting modeling, computation, estimation and optimization techniques. The modeling part takes advantage of the structure of weighted voting systems to present a model of its reliability as a multi-state system. Next, based on the multi-state view of the system, an exact computational approach based on multi-state minimal cut and path vectors is introduced. The paper then acknowledges the computational complexity of the problem and provides a Monte Carlo simulation approach that estimates system reliability accurately and in an efficient computational time. Finally, an optimization heuristic that generates quasi-optimal solutions is presented that is able to solve the problem of maximizing the reliability of a weighted voting system based on a specified number of decision-making units with known reliability characteristics.

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“…A brief overview of the method with respect to its applications for MSS reliability assessment is presented in [3]. The method was first applied to the real power system reliability assessment and optimization in [45,46]. For MSS which has a finite number of states, there can be K different levels of output performance at each time t: G(t) ∈ G = {G k , 1 ≤ k ≤ K} and the system output performance distribution (OPD) can be defined by two finite vectors G and…”

Section: Mss Reliability Indices Evaluation Based On the Ugfmentioning

confidence: 99%

A new approach to solving problems of multi‐state system reliability optimization

Levitin

Lisnianski

2001

Quality & Reliability Eng

Self Cite

187

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SUMMARYUsually engineers try to achieve the required reliability level with minimal cost. The problem of total investment cost minimization, subject to reliability constraints, is well known as the reliability optimization problem. When applied to multi-state systems (MSS), the system has many performance levels, and reliability is considered as a measure of the ability of the system to meet the demand (required performance). In this case, the outage effect will be essentially different for units with different performance rate. Therefore, the performance of system components, as well as the demand, should be taken into account. In this paper, we present a technique for solving a family of MSS reliability optimization problems, such as structure optimization, optimal expansion, maintenance optimization and optimal multistage modernization. This technique combines a universal generating function (UGF) method used for fast reliability estimation of MSS and a genetic algorithm (GA) used as an optimization engine. The UGF method provides the ability to estimate relatively quickly different MSS reliability indices for series-parallel and bridge structures. It can be applied to MSS with different physical nature of system performance measure. The GA is a robust, universal optimization tool that uses only estimates of solution quality to determine the direction of search.

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Power system structure optimization subject to reliability constraints

Cited by 129 publications

References 5 publications

Efficient harmony search algorithm for multi-stages scheduling problem for power systems degradation

Efficient harmony search algorithm for multi-stages scheduling problem for power systems degradation

Holistic reliability analysis of weighted voting systems from a multi-state perspective

A new approach to solving problems of multi‐state system reliability optimization

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