Reliability assessment of generating systems containing wind power and air separation unit with cryogenic energy storage

Zamani-Gargari, Milad; Kalavani, Farshad; Abapour, Mehdi; Mohammadi‐Ivatloo, Behnam

doi:10.1016/j.est.2017.12.013

Cited by 22 publications

(10 citation statements)

References 37 publications

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“…This is shown in Figure 6 through the red line in the graph of the superimposed generation and load model. The risk model represents the superimposition of the generation and the load model from which the LOLE reliability index is calculated [20]. The LOLE is the sum of the individual algebraic differences between the load level and the generation capacity at the points where the load level exceeds the generation capacity.…”

Section: The Generation Model Load Model and The Risk Modelmentioning

confidence: 99%

“…In addition, the load system has a record of the consumers' hourly load usage level, hence, also 8736 values. Since both the generation capacity and the load level have the same graphic units (MW versus hours), it becomes easy to superimpose The risk model represents the superimposition of the generation and the load model from which the LOLE reliability index is calculated [20]. The LOLE is the sum of the individual algebraic differences between the load level and the generation capacity at the points where the load level exceeds the generation capacity.…”

Section: The Generation Model Load Model and The Risk Modelmentioning

confidence: 99%

“…The LOLE reliability index was obtained from the reliability assessment via the MCS. The MCS method accommodates the natural stochastic factors in the generation system operating states considering the inherent fluctuations in the generating capacity [20][21][22]. The Monte Carlo model was developed to be dynamic in solving several kinds of problems instead of the problem having to match the model or the method [23,24].…”

Section: The Reliability Assessment and The Monte Carlo Systemmentioning

confidence: 99%

See 2 more Smart Citations

Predictive Reliability Assessment of Generation System

et al. 2020

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Due to increasing load and characteristic stagnation and fluctuations of existing generation systems capacity, the reliability assessment of generation systems is crucial to system adequacy. Furthermore, a rapid load increase could amount to a consequent sudden deficit in the generation supply before the next scheduled assessment. Hence, a reliability assessment is conducted at regular and close intervals to ensure adequacy. This study simulates and establishes the relationship between the load growth and generation capacity using the generation and load data of the IEEE reliability test system (IEEE RTS ‘96 standard). The generation capacity states and the risk model were obtained using the sequential Monte Carlo simulation (MCS) method. The load was gradually increased stepwise and is simulated against the constant generation capacity. In each case, the reliability index was recorded in terms of loss-of-load evaluation (LOLE). The recorded reliability index was thereafter fitted with the load-growth trend by the linear regression approach. A predictive assessment approach is thereafter proffered through the obtained fitting equation. In addition, a reliability threshold is effectively determined at a yield point for a reliability benchmark.

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Section: The Generation Model Load Model and The Risk Modelmentioning

confidence: 99%

Section: The Generation Model Load Model and The Risk Modelmentioning

confidence: 99%

Section: The Reliability Assessment and The Monte Carlo Systemmentioning

confidence: 99%

See 1 more Smart Citation

Predictive Reliability Assessment of Generation System

et al. 2020

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“…These systems, integrating renewable energy generation and storage, are able to follow a guaranteed production program similarly to a conventional generating unit and, therefore, to participate in the electricity market, overcoming the dispatching priority method used for subsidizing the generation of electricity from renewable sources. Some works have been presented which use a cryogenic process for energy storage also for integrating wind generation in the system [6,7]. These works use air liquefaction as an energy storage means but do not exploit the possibility of separately produce liquefied oxygen.…”

Section: Introductionmentioning

confidence: 99%

Long term electricity storage by oxygen liquefaction and LNG oxy-combustion

Barsali

Ciambellotti

Fioriti

et al. 2020

Journal of Energy Storage

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“…Noussan et al [17] proposed an optimization tool to enhance the operation of a CHP system combined with a heat pump. Zamani-Gargari et al [18] proposed a method which combined the Monte Carlo Simulation (MCS) method to assess the reliability of a wind power system with energy storage. Yang et al [19] proposed an approach to analyzing how the wind farm electrical system influenced the system when the electrical system faulted.…”

Section: Introductionmentioning

confidence: 99%

Reliability and Maintenance Prioritization Analysis of Combined Cooling, Heating and Power Systems

et al. 2018

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A combined cooling, heating, and power (CCHP) system is a complex and repairable system containing a large number of components and series of subsystems. When a failure occurs in one component, it might cause a failure of a subsystem or whole system. Traditional maintenance methods might lead to the waste of maintenance resources and a high cost of maintenance. The reliability and maintenance prioritization analyses can help managers optimize maintenance strategies and reduce the total cost. A reliability importance index is one of the factors in maintenance prioritization analysis. This paper aims at selecting the component reliability importance indices to identify the priority of component maintenance of a CCHP system from the perspective of maintenance cost. Failure cost importance index (FCI) and Potential failure cost importance index (PI) are developed for the maintenance prioritization analysis of a CCHP system. A Markov model based on the state-space method (SSM) is used to analyze the reliability and availability of a CCHP system. A set of actual survey reliability data of CCHP systems is used to support the validity of the reliability importance indices. The results indicate that the FCI and PI might lead to different rankings of maintenance prioritization. The FCI and PI will help managers make a reasonable decision for maintenance on a cost basis.

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Reliability assessment of generating systems containing wind power and air separation unit with cryogenic energy storage

Cited by 22 publications

References 37 publications

Predictive Reliability Assessment of Generation System

Predictive Reliability Assessment of Generation System

Long term electricity storage by oxygen liquefaction and LNG oxy-combustion

Reliability and Maintenance Prioritization Analysis of Combined Cooling, Heating and Power Systems

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