Evaluation of reliability worth in composite systems based on pseudo-sequential Monte Carlo simulation

Mello, J.C.O.; Pereira, M.V.F.; Silva, Armando M. Leite da

doi:10.1109/59.336134

Cited by 141 publications

(37 citation statements)

References 10 publications

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“…The objective of this optimization problem is to minimize the total loss of load subjected to the operating limits of generating units and transmission circuits, and the DC power flow equations [17]. This function can be changed to give preference to the different generating units without modifying the estimates of the composite system loss of load indices [19]. The maximization of the use of wind power and the minimization of the loss of load can be aggregated in the same objective function by using appropriate weights.…”

Section: Influence Of the Transmission Circuits On Wind Power Curtmentioning

confidence: 99%

“…These methods are divided into three approaches according to the representation of the system states: the nonsequential [18], the pseudo-sequential [19], and the sequential approaches [20]. Sequential simulation can accurately reproduce the whole cycle of interruptions and, hence, it is easy to include all chronological aspects in the simulation such as time and spatially correlated load models, loss of load cost, and maintenance schedule.…”

Section: Sequential Monte Carlo Simulationmentioning

confidence: 99%

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Probabilistic Analysis for Maximizing the Grid Integration of Wind Power Generation

Carvalho

Rosa

Silva

et al. 2012

IEEE Trans. Power Syst.

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This paper presents a sequential Monte Carlo simulation algorithm that can simultaneously assess composite system adequacy and detect wind power curtailment events. A simple procedure at the end of the state evaluation stage is proposed to categorize wind power curtailment events according to their cause. Furthermore, the dual variables of the DC optimal power flow procedure are used to identify which transmission circuits are restricting the use of the total wind power available. In the first set of experiments, the composite system adequacy is assessed, incorporating different generation technologies. This is conducted to clarify the usual comparisons made between wind and thermal technologies which, in fact, depend on the performance measure selected. A second set of experiments considering several wind penetration scenarios is also performed to determine the operational rules or system components responsible for the largest amount of wind energy curtailed. The experiments are carried out on configurations of the IEEE-RTS 79 power system. Index Terms-Chronological Monte Carlo simulation, composite system, intermittent energy sources, reliability assessment.

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Section: Influence Of the Transmission Circuits On Wind Power Curtmentioning

confidence: 99%

Section: Sequential Monte Carlo Simulationmentioning

confidence: 99%

Probabilistic Analysis for Maximizing the Grid Integration of Wind Power Generation

Carvalho

Rosa

Silva

et al. 2012

IEEE Trans. Power Syst.

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“…This sequence is obtained by combining the chronological state transition process of each random variable in a given time span. In reliability studies of power systems, a system scenario is composed by the state transitions associated with component outages (generators and circuits), hourly load fluctuations (chronological load curve), and seasonal variations of energy supply (rain/hydropower, wind/windmills, sun/solar cells, and tides/wavepower) [14], [15]. Usually, the state transitions associated with equipment unavailabilities are generated using the state duration sampling technique [21], [22].…”

Section: Outline Of Methodologymentioning

confidence: 99%

Probabilistic Assessment of Available Transfer Capability Based on Monte Carlo Method With Sequential Simulation

Rodrigues

Silva

2007

IEEE Trans. Power Syst.

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The objective of this paper is to assess the chronological variations in the available transfer capability (ATC) caused by uncertainties associated with hourly load fluctuations and equipment unavailabilities. The system states resulting from these uncertainties are generated using the Monte Carlo method with sequential simulation (MCMSS). The ATC for each generated state is evaluated through a linear dc optimal power flow (OPF). The test results, with a modified version of the IEEE Reliability Test System, demonstrate that the time-dependent uncertainties have a significant impact on the ATC. These effects have been assessed through statistical indexes such as expected values, box plot, and percentiles.Index Terms-Available transfer capability (ATC), composite system, linear programming, Monte Carlo method (MCM), power system reliability.

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“…(1) Considering that the transmission part of the IEEE RTS is relatively over-reliable (Mello et al 1994;Leite da Silva et al 2002), the installed capacities of all generators and the values of all loads are increased 1.5 times.…”

Section: Test Systemmentioning

confidence: 99%

Evaluation of hurricane impact on composite power system reliability considering common-cause failures

Liu

Singh

2010

Int J Syst Assur Eng Manag

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Extreme adverse weather such as a hurricane can have a significant impact on composite power system reliability. Since hurricanes can cause the simultaneous failures of multiple system components, common-cause failures (CCF) should be investigated in the reliability evaluation of composite power systems when the effects of hurricanes are considered. A few techniques have been proposed to evaluate the effects of CCF, but they are not suitable for composite power systems. This paper proposes a method based on Bayesian networks (BN) to solve this problem. Basically, the proposed method uses the noisy ORgate model to reduce the dimensional dilemma of the conditional probability method. This model also considers the independent failures of transmission lines and generating units during hurricanes. The functionality of a BN is determined by its configuration and the conditional probability distributions (CPD) associated with the nodes. In this paper, the CPD of BN is obtained by using random sampling. Since hurricanes usually last for only a limited period of time, a pseudo-repetitive temporal model is used to calculate the time-specific system reliability indices. The proposed method is applied to the modified IEEE Reliability Test System (RTS). The implementation demonstrates that the proposed method is effective and flexible in its applications.

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Evaluation of reliability worth in composite systems based on pseudo-sequential Monte Carlo simulation

Cited by 141 publications

References 10 publications

Probabilistic Analysis for Maximizing the Grid Integration of Wind Power Generation

Probabilistic Analysis for Maximizing the Grid Integration of Wind Power Generation

Probabilistic Assessment of Available Transfer Capability Based on Monte Carlo Method With Sequential Simulation

Evaluation of hurricane impact on composite power system reliability considering common-cause failures

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