Impact Of Uncertain Parameters Research Articles

Three-tier integrated demand-supply energy management for optimized energy usage in institutional building

Sustainable Energy Plan is an indispensable field of study in the context of Building Energy Management (BEM) which yearns for a cutting-edge technique to raise consumers’ level of contentment with energy usage. This paper introduces a three-tier strategic approach for demand cum supply side management at the prosumer end named TID-SEM (Three-tier Integrated Demand cum Supply Energy Management) framework. The framework commences with data collection, machine learning, and Random Forest classifier-based Demand side management to reduce peak demand. Followingly, a feasibility study on available sources (Solar PV + Battery + Diesel Generator + Grid) was done using the HOMER simulator. The quality techno-enviro-economic shows distinguished optimal one under each criterion. Ultimately to overcome, an ideal computative multicriteria decision-making approaches Fuzzy Analytic Hierarchy Process, the Fuzzy Preference Ranking Organization Method for Enrichment Evaluations, and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution employed to highlight the most optimal configuration. The study focuses on a department building within a higher education institution in the Madurai district, Tamil Nadu, India. On implementing the TID-SEM, ‘PV + Grid’ after DSM configuration was ranked as the most optimum. Lastly, a sensitivity analysis was conducted to evaluate the techno-enviro-economic impact of uncertain parameters on the optimal configuration, ensuring the robustness of the proposed framework.

A Hierarchical Optimal Control of Uncertain and Time-Varying Knowledge Dissemination Model in Complex Network

In this paper, considering the multifactor influence of the knowledge dissemination process, a new ignorant-knower-spreader-forgetter (IKSF) knowledge dissemination model is proposed, which considers internalization mechanism, degradation mechanism, communication, and willingness, as well as time-varying and uncertain parameters. First, we prove that the knowledge loss equilibrium of the model is globally asymptotically stable when the basic reproduction number R 0 < 1 , and knowledge is permanent when R 0 > 1 . Next, improving the willingness of knower individuals and reducing the knowledge degradation function of spreader individuals can make the best effect of propagation; a hierarchical control strategy is designed. At the upper layer, an effective optimal control mechanism of the IKSF knowledge dissemination model is studied to provide optimal control action and minimization costs. At the lower layer, to guarantee robustness control performance and track the control targets, an intervention optimal guaranteed cost control strategy for the IKSF knowledge dissemination system with uncertain parameters is studied. Converting the controller’s design problem into a minimization problem with linear matrix inequalities, not only the impact of uncertain parameters is reduced but also the propagation effect of the knowledge dissemination model is guaranteed. Simulation results confirm our method.

Two-stage stochastic minimum cost consensus models with asymmetric adjustment costs

When dealing with consensus cost problems with asymmetric adjustment costs, the uncertain scenarios with certain probabilities which are becoming a serious problem decision-makers have to face. However, existing optimization-based consensus models have failed to consider uncertain factors that could influence the final consensus and total consensus cost. In order to better deal with these issues, it is necessary to develop practical consensus optimal models. Thus, we establish three two-stage stochastic minimum cost consensus models with asymmetric adjustment costs that may eventually lead the way to better consensus outcomes. The impact of uncertain parameters (such as individual opinions, unit asymmetric adjustment costs, compromise limits, cost-free thresholds) are investigated by modeling three kinds of uncertain consensus models. We solve the proposed two-stage stochastic consensus problem iteratively using the L-shaped algorithm and show the convergence of the algorithm. Furthermore, a case of pollution control negotiations verifies the practicability of the proposed models. Moreover, the comparison of results with the L-shaped algorithm and CPLEX shows that the L-shaped algorithm is more effective in solving time. Some discussions and comparisons on local and global sensitivity analysis of the uncertain parameters are presented to reveal the features of the proposed models. Finally, the relationships between the minimum cost consensus model and minimum cost consensus models with asymmetric adjustment costs and the proposed models are also provided.

AZTUSIA: A new application software for Uncertainty and Sensitivity analysis for nuclear reactors

The AZTLAN Platform project is a Mexican national initiative which aims to have a platform for analysis and design of nuclear reactors. In order to enhance the AZTLAN Platform with Uncertainty and Sensitivity (U&S) capabilities, the AZTUSIA (AZtlan Tool for Uncertainty and SensItivity Analysis) code has been developed to perform U&S analysis.The main characteristics and capabilities of AZTUSIA are briefly described together with some verification exercises. The versatility of the AZTUSIA code has been used to analyze a transient of a BWR-5 with the SIMULATE 3-K code. An artificial perturbation has been caused for creating a more challenging case and to demonstrate the capabilities of an extended interface in which AZTUSIA can be easily adapted to other codes outside AZTLAN Platform. The U&S analysis conducted using the AZTUSIA code reflect, as expected, the impact of uncertain parameters and all capabilities of the tool are demonstrated. It is possible to assess the influence of uncertainty in the calculations and to distinguish trends and readily group and/or separate results by means of scatter and cobweb color plots. As a main conclusion, a new tool has been developed allowing U&S analysis. It is foreseen to continue increasing the tool capabilities.

Understanding and Evaluating Systemwide Impacts of Uncertain Parameters in the Dynamic Load Model on Short-Term Voltage Stability

This paper investigates systemwide short-term voltage stability concerns of power systems due to the multiple parametric uncertainties in the dynamic load model. The impact of regional load model uncertainty can be widespread and may mislead the whole system analysis and subsequent measures, if not properly addressed. This research discloses that the systemwide impact is related to the voltage weak areas through voltage stability modal analysis, and suggests that the impact of uncertain parameters needs to be assessed from a systems perspective, which has rarely been done in the existing practices. We thus present a three-step methodology for evaluating the systemwide uncertainty impacts: Firstly, it screens possible trajectories of all buses. The second step verifies whether the screened trajectories comply with the defined criteria, and determines the necessity of the final step. The final detailed analysis is conducted for those selected scenarios. Comprehensive studies for both the IEEE test and real Korea power systems consistently confirm the observations and demonstrate the efficacy and validity of the proposed method.

Impact of Uncertain Parameters on TCL Power Capacity Calculation via HDMR for Generating Power Pulses

Thermostatically controlled loads (TCLs) have attracted additional in power system operations, is mostly because of their flexibility in supplying demand response (DR). So, it is vital to identify accurate parameters for aggregated TCL populations, which is often a cumbersome task in practical applications due to inaccurate power metering, end-users’ random behavior for consuming energy in real-time, and privacy issues pertaining to the availability and the collection of individuals’ data. This paper investigates the TCL power capacity calculation strategy and the impact of uncertain parameters on TCL power capacity for generating power pulses. First, a TCL power capacity calculation strategy which links on–off switching states with temperature set-point adjustments is proposed to remove TCLs that are deemed unsuitable for DR dispatch as they satisfy end-users’ comfort needs. Second, high dimensional model representative (HDMR) is applied to identify important parameters for quantifying the impact of uncertain heterogeneous parameters on TCL power capacities. In addition, a fast framework is provided for reducing the computation burdens in capacity calculation. Simulation results demonstrate that: 1) proposed TCL power capacity calculation strategy can maintain end-users in respective comfort ranges; 2) important parameters can be effectively identified by HDMR; and 3) TCL power capacity can be calculated quickly via HDMR in various dispatch periods.

Affordable Uncertainty Quantification for Industrial Problems: Application to Aero-Engine Fans

Uncertainty quantification (UQ) is an increasingly important area of research. As components and systems become more efficient and optimized, the impact of uncertain parameters is likely to become critical. It is fundamental to consider the impact of these uncertainties as early as possible during the design process, with the aim of producing more robust designs (less sensitive to the presence of uncertainties). The cost of UQ with high-fidelity simulations becomes therefore of fundamental importance. This work makes use of least-squares approximations in the context of appropriately selected polynomial chaos (PC) bases. An efficient technique based on QR column pivoting has been employed to reduce the number of evaluations required to construct the approximation, demonstrating the superiority of the method with respect to full-tensor quadrature (FTQ) and sparse-grid quadrature (SGQ). Orthonormal polynomials used for the PC expansion are calculated numerically based on the given uncertainty distribution, making the approach optimal for any type of input uncertainty. The approach is used to quantify the variability in the performance of two large bypass-ratio jet engine fans in the presence of shape uncertainty due to possible manufacturing processes. The impacts of shape uncertainty on the two geometries are compared, and sensitivities to the location of the blade shape variability are extracted. The mechanisms at the origin of the change in performance are analyzed in detail, as well as the differences between the two configurations.

Robust asymptotic stability of parametric switched linear systems with dwell time

Switched linear systems with dwell time constraints constitute a very popular class of switched systems. In this study, impact of uncertain parameters on the stability of Parametrised switched linear (SL) systems with dwell time is investigated. Sufficient conditions are first proposed to analyse the global asymptotic stability of SL systems with dwell time. The conditions are then generalised to the case with parametric uncertainties to determine upper bounds on parametric uncertainties such that robust asymptotic stability is assured under dwell time constraints. Finally, an off-line computational algorithm is proposed to enlarge the estimated stability intervals. Effectiveness and simplicity of the computations are shown by a numerical example.

Interval-valued facility location model: An appraisal of municipal solid waste management system

This study presents an interval-valued facility location model to find economically best locations for transfer stations under uncertainty. Transfer stations are the vital part of contemporary municipal solid waste management systems and economical siting of transfer stations using developed model lead to a financially sustainable system. Often, the associated uncertainty of these systems cannot be modeled by conventional probabilistic or fuzzy approaches under a data scarce scenario; however, models based on interval analysis are found to be very effective in such cases. A set of univariate and multivariate sensitivity analyses adduces the need of uncertainty analysis for quantification and propagation of uncertainty. The demonstration of model on city of Nashik (India) provides (i) economical feasibility, optimum capacity and economically best locations of transfer stations; and (ii) impact of uncertain parameters on the best locations. The developed model felicitates a convenient decision-making to identify economically best locations of transfer stations under uncertain environment.

Improving risk assessment in financial feasibility of international engineering projects: A risk driver perspective

Major engineering projects characterized by intensive technologies and high investment are becoming more complex with increasing risks in a global market. Because incorrect investment decision-making can cause great losses to investors, quantitative risk assessment is widely used in establishing the financial feasibility of projects. However, existing methods focus on the impact of uncertain parameters, such as income, on decision variables of investment, neglecting assessing the impact of risk events, such as the sales of products falling short of expectations. In the context of international engineering projects from a risk driver perspective, this paper presents an improved quantitative risk assessment model to help risk managers identify the direct relationships between specific risk events and decision variables of investment. Stress testing is also introduced to assess the negative impact of extreme risks. The new model is applied to an on-going international petrochemical project to demonstrate its use and validate its applicability and effectiveness.

Parameters Setting Impact Analysis of Composite Cockpit Finite Element Analysis Based on Properties of Composite Materials

At present, mechanics properties of composite at home and abroad only include data of the single-layer board. On the basis of researching literature of composite finite element analysis, approaches of setting composite three-dimensional parameters based on the parameters of single-layer material are summarized. By three-dimensional finite element analysis on composite whole cockpit, the impact of uncertain parameters on cockpit analysis results is studied. Adopting maximum stress criteria, maximum strain criteria and Tsai-Wu criteria to evaluate the initial failure of composite whole cockpit, the impact of material uncertain parameters on initial breaking strength prediction of cockpit is studied. The study can provide reference for three-dimensional finite element analysis of composite whole cockpit.

Adaptive Backstepping Stopping Control of Urban Rail Vehicle

Stopping accuracy is an important index to measure the performance of Automatic Train Operation (ATO), as well as a significant guarantee of the safety of the train’s operation. However, during the process of braking, the stopping accuracy of the urban rail vehicle is affected by the line conditions, brake shoe friction coefficients and random noise. A braking model of the train reflecting these uncertain conditions and principle of braking system is derived in this paper. Based on this model, an adaptive backstepping control scheme is proposed to track ideal braking curve. Using Lyapunov stability theorem, the stability and the convergence of the adaptive algorithms are proved. Simulation results verify that this method not only overcomes the impact of uncertain parameters but also greatly improves the stopping accuracy of the train without loss of the comfort level of passengers.

Quantification of Uncertainties for Drilling-Induced Formation Damage

Summary It has been widely recognized that formation damage caused by drilling fluid has a huge impact on well productivities. The degree of formation damage can be studied using a numerical model. However, uncertainties in the prediction of productivity loss need to be investigated. To quantify these uncertainties, experimental designs combined with the Response Surface Methodology (RSM) are used to assess the impact of uncertain parameters on formation damage. This approach allows to identify the most influential parameters on well productivity loss and to estimate the risks of formation damage. A good control of the most sensitive parameters can limit productivity loss. This approach provides key recommendations for the selection of drilling fluid to maximize well performance.