scholarly journals Analysis of the influence of input data uncertainties on determining the reliability of reservoir storage capacity

2015 ◽  
Vol 63 (4) ◽  
pp. 287-294 ◽  
Author(s):  
Daniel Marton ◽  
Miloš Starý ◽  
Pavel Menšík
Keyword(s):  
Water Management ◽  
Sensitivity Analysis ◽  
Simulation Model ◽  
Reservoir Operation ◽  
Input Data ◽  
Storage Capacity ◽  
Reservoir Storage ◽  
Operating Data

Abstract The paper contains a sensitivity analysis of the influence of uncertainties in input hydrological, morphological and operating data required for a proposal for active reservoir conservation storage capacity and its achieved values. By introducing uncertainties into the considered inputs of the water management analysis of a reservoir, the subsequent analysed reservoir storage capacity is also affected with uncertainties. The values of water outflows from the reservoir and the hydrological reliabilities are affected with uncertainties as well. A simulation model of reservoir behaviour has been compiled with this kind of calculation as stated below. The model allows evaluation of the solution results, taking uncertainties into consideration, in contributing to a reduction in the occurrence of failure or lack of water during reservoir operation in low-water and dry periods.

Exploring incomplete information in maintenance materials inventory optimization

2014 ◽  
Vol 114 (1) ◽  
pp. 144-158 ◽  
Author(s):  
Antti Puurunen ◽  
Jukka Majava ◽  
Pekka Kess
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Model ◽  
Input Data ◽  
Real Life ◽  
Significant Risk ◽  
Service Level ◽  
Content Type ◽  
Imperfect Data ◽  
Inventory Optimization ◽  
Critical Materials

Purpose – Ensuring the sufficient service level is essential for critical materials in industrial maintenance. This study aims to evaluate the use of statistically imperfect data in a stochastic simulation-based inventory optimization where items' failure characteristics are derived from historical consumption data, which represents a real-life situation in the implementation of such an optimization model. Design/methodology/approach – The risks of undesired shortages were evaluated through a service-level sensitivity analysis. The service levels were simulated within the error of margin of the key input variables by using StockOptim optimization software and real data from a Finnish steel mill. A random sample of 100 inventory items was selected. Findings – Service-level sensitivity is item specific, but, for many items, statistical imprecision in the input data causes significant uncertainty in the service level. On the other hand, some items seem to be more resistant to variations in the input data than others. Research limitations/implications – The case approach, with one simulation model, limits the generalization of the results. The possibility that the simulation model is not totally realistic exists, due to the model's normality assumptions. Practical implications – Margin of error in input data estimation causes a significant risk of not achieving the required service level. It is proposed that managers work to improve the preciseness of the data, while the sensitivity analysis against statistical uncertainty, and a correction mechanism if necessary, should be integrated into optimization models. Originality/value – The output limitations in the optimization, i.e. service level, are typically stated precisely, but the capabilities of the input data have not been addressed adequately. This study provides valuable insights into ensuring the availability of critical materials.

A Multi-decadal Analysis of Reservoir Storage Change in Developing Regions

2021 ◽  
Keyword(s):  
Reservoir Operation ◽  
Storage Capacity ◽  
Assessment Tool ◽  
Severity Index ◽  
Drought Severity ◽  
Developing Regions ◽  
Reservoir Storage ◽  
Historical Observation ◽  
Reservoir Assessment ◽  
Storage Change

Abstract The limited amount of shared reservoir monitoring data around the world is insufficient to quantify the dynamic nature of reservoir operation with conventional ground-based methods. With the emergence of the Reservoir Assessment Tool (RAT) driven by a multitude of earth observing satellites and models, historical observation of reservoir operation spanning 35 years was made using open-source techniques. Trends in reservoir storage change were compared with trends of four critical hydrologic variables (precipitation, runoff, evaporation, and Palmer Drought Severity Index) to understand the potential role of natural drivers in altering reservoir operating pattern. It was found that the reservoirs in Africa were losing active storage at a rate of more than 1% per year of total storage capacity. Smaller reservoirs (with a capacity of less than 0.5 km3) in South-East Asia were found to experience a sharp gain in storage of 0.5% to 1% per year of total storage capacity. Storage change trends of large reservoirs with multiple years of residence time that are designed for strategic water supply needs and drought control were found to be less affected by precipitation trends and influenced more by drought and evaporation trends. Over Africa, most reservoir storage change trends were dictated by evaporation trends, while South Asian reservoirs appear to have their storage change influenced by drought and evaporation trends. Finally, findings suggest that operation of newer reservoirs are more sensitive to long-term hydrological trends and the regulated surface water variability that is controlled by older dams in the upstream.

Sensitivity Analysis of Hydroelectric Power Generation from Cascading Reservoirs

2012 ◽  
Vol 622-623 ◽  
pp. 1152-1156
Author(s):  
Tilahun Derib Asfaw ◽  
Khamaruzaman Wan Yusof ◽  
Ahmad Mustafa Hashim
Keyword(s):  
Power Generation ◽  
Sensitivity Analysis ◽  
Water Balance ◽  
Storage Capacity ◽  
Reverse Order ◽  
Hydroelectric Power ◽  
Reservoir Storage ◽  
Cascading Reservoirs ◽  
Relationship Of ◽  
Hydroelectric Power Generation

The cascading reservoirs in Perak, Malaysia, were used to test the sensitivity analysis of hydroelectric power generation during refill and deplete period of the reservoirs. The cascading scheme comprises four reservoirs namely Temenggor, Bersia, Kenering and Chenderoh. The test was conducted after the analysis of water balance and stage-storage relationship of each reservoir in the cascading scheme. The result showed that power generation from the smaller reservoir, Bersia, is more sensitive to the change of headrace level, while the larger storage capacity and rated head reservoir is the most sensitive to the change of release. Therefore, to maximize the power generation from the cascading reservoir, the refill operations should be ranked according to the increasing order of the reservoir storage capacity and a reverse order should be followed during deplete period.

scholarly journals Assessing the impacts of reservoirs on downstream flood frequency by coupling the effect of scheduling-related multivariate rainfall with an indicator of reservoir effects

2019 ◽  
Vol 23 (11) ◽  
pp. 4453-4470 ◽  
Author(s):  
Bin Xiong ◽  
Lihua Xiong ◽  
Jun Xia ◽  
Chong-Yu Xu ◽  
Cong Jiang ◽  
...  
Keyword(s):  
Bayesian Inference ◽  
Frequency Analysis ◽  
Reservoir Operation ◽  
Storage Capacity ◽  
Flood Frequency ◽  
Return Level ◽  
Flood Frequency Analysis ◽  
Exceedance Probability ◽  
Antecedent Rainfall ◽  
Reservoir Storage

Abstract. Many studies have shown that downstream flood regimes have been significantly altered by upstream reservoir operation. Reservoir effects on the downstream flow regime are normally performed by comparing the pre-dam and post-dam frequencies of certain streamflow indicators, such as floods and droughts. In this study, a rainfall–reservoir composite index (RRCI) is developed to precisely quantify reservoir impacts on downstream flood frequency under a framework of a covariate-based nonstationary flood frequency analysis using the Bayesian inference method. The RRCI is derived from a combination of both a reservoir index (RI) for measuring the effects of reservoir storage capacity and a rainfall index. More precisely, the OR joint (the type of possible joint events based on the OR operator) exceedance probability (OR-JEP) of certain scheduling-related variables selected out of five variables that describe the multiday antecedent rainfall input (MARI) is used to measure the effects of antecedent rainfall on reservoir operation. Then, the RI-dependent or RRCI-dependent distribution parameters and five distributions, the gamma, Weibull, lognormal, Gumbel, and generalized extreme value, are used to analyze the annual maximum daily flow (AMDF) of the Ankang, Huangjiagang, and Huangzhuang gauging stations of the Han River, China. A phenomenon is observed in which although most of the floods that peak downstream of reservoirs have been reduced in magnitude by upstream reservoirs, some relatively large flood events have still occurred, such as at the Huangzhuang station in 1983. The results of nonstationary flood frequency analysis show that, in comparison to the RI, the RRCI that combines both the RI and the OR-JEP resulted in a much better explanation for such phenomena of flood occurrences downstream of reservoirs. A Bayesian inference of the 100-year return level of the AMDF shows that the optimal RRCI-dependent distribution, compared to the RI-dependent one, results in relatively smaller estimated values. However, exceptions exist due to some low OR-JEP values. In addition, it provides a smaller uncertainty range. This study highlights the necessity of including antecedent rainfall effects, in addition to the effects of reservoir storage capacity, on reservoir operation to assess the reservoir effects on downstream flood frequency. This analysis can provide a more comprehensive approach for downstream flood risk management under the impacts of reservoirs.

Understanding the Effect of Rock Compressibility on CO2 Storage Capacity Estimation in a Depleted Carbonate Gas Reservoir

2021 ◽  
Author(s):  
Prasanna Chidambaram ◽  
Raj Deo Tewari ◽  
Siti Syareena Mohd Ali ◽  
Chee Phuat Tan
Keyword(s):  
Sensitivity Analysis ◽  
Greenhouse Gases ◽  
Simulation Model ◽  
Reservoir Simulation ◽  
Storage Capacity ◽  
Co2 Storage ◽  
History Match ◽  
Hydrocarbon Reservoir ◽  
Rock Compressibility

Abstract Avoiding or reducing greenhouse gases emission in the atmosphere requires extensive application of technologies and one of them is underground CO2 sequestration. Capture and storage of CO2 in depleted hydrocarbon reservoirs can reduce greenhouse gases released into the atmosphere effectively. Hydrocarbon reservoirs are considered one of the ideal geologic storage sites as they have held hydrocarbons over millions of years. Their architecture and properties are well understood due to exploration and production activities from these reservoirs. Storage projects require a large depleted hydrocarbon reservoir with good reservoir properties and are affected by several factors including voidage created by hydrocarbon production, pressure, architecture, formation permeability, aquifer influx, subsidence and compaction, and rock compressibility to name a few. Thus, realistic estimation of the storage capacity of the reservoir is a key step in the evaluation of CO2 storage plan. A good history matched simulation model incorporating the geomechanical parameters is essential to estimate storage capacity of the reservoir. Three major depleted gas reservoirs in Central Luconia field, located in offshore Sarawak, are being evaluated for future CO2 storage. Reservoir simulation is used as a tool to estimate future CO2 storage capacity of these reservoirs. Reliability of forecast from a reservoir simulation model is dependent on the quality of history match achieved. Hence it is believed that CO2 storage capacity estimates obtained from a good history matched simulation model must be reliable. However, during history matching exercise in these reservoirs, it was observed that an acceptable history match could be achieved with a range of rock compressibility values and aquifer influxes. Generally, a constant value of rock compressibility is used in conventional simulation. For example, in order to obtain an acceptable history match, with a lower compressibility, a larger aquifer influx is needed and vice versa. Interestingly, a forecast using these history match cases yield different CO2 storage capacities. A closer evaluation shows that aquifer influx has a strong impact on future CO2 storage capacity. An acceptable quality of history match can be obtained for a range of rock compressibility values when aquifer influx is adjusted along with it. Sensitivity analysis shows that future CO2 storage capacity in depleted hydrocarbon reservoir is sensitive to rock compressibility used in the simulation model. A detailed sensitivity analysis along with multiple history match scenarios is necessary to understand the range in future storage capacity when evaluating CO2 storage plan.

Sensitivity Analysis and Selection of Check Index of Signal Intersection Simulation Model Based on VISSIM

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Mengda Zhang ◽  
Chenjing Zhou ◽  
Tian-tian Zhang ◽  
Yan Han
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Model ◽  
Optimal Process ◽  
Parameter Calibration ◽  
Index Set ◽  
The Core ◽  
Core Module ◽  
Simulation Parameter ◽  
Simulation Parameters ◽  
Selection Of

Selecting check index quantitatively is the core of the calibration of micro traffic simulation parameters at signal intersection. Five indexes in the node (intersection) module of VISSIM were selected as the check index set. Twelve simulation parameters in the core module were selected as the simulation parameters set. Optimal process of parameter calibration was proposed and model of the intersection of Huangcun west street and Xinghua street in Beijing was built in VISSIM to verify it. The sensitivity analysis between each check index and simulation parameter in their own set was conducted respectively. Sensitive parameter sets of different check indices were obtained and compared. The results show that different indexes have different size of set, and average vehicle delay's is maximum, so it's necessary to select index quantitatively. The results can provide references for scientific selection of the check indexes and improve the study efficiency of parameter calibration.

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