Source-Load Coordinated Optimal Scheduling Considering the High Energy Load of Electrofused Magnesium and Wind Power Uncertainty

In fossil energy pollution is serious and the“double carbon”goal is being promoted,as a symbol of fresh energy in the electrical system,solar and wind power have an increasing installed capacity,only conventional units obviously can not solve the new energy as the main body of the scheduling problem.To enhance the systemscheduling ability,based on the participation of thermal power units,incorporate the high energy-carrying load of electro-melting magnesiuminto the regulation object,and consider the effects on the wind unpredictability of the power.Firstly,the operating characteristics of high energy load and wind power are analyzed,and the principle of the participation of electrofusedmagnesiumhigh energy-carrying loads in the elimination of obstructedwind power is studied.Second,a two-layer optimization model is suggested,with the objective function being the largest amount of wind power consumed and the lowest possible cost of system operation.In the upper model,the high energy-carrying load regulates the blocked wind power,and in the lower model,the second-order cone approximation algorithm is used to solve the optimizationmodelwithwind power uncertainty,so that a two-layer optimizationmodel that takes into account the regulation of the high energy-carrying load of the electrofused magnesium and the uncertainty of the wind power is established.Finally,the model is solved using Gurobi,and the results of the simulation demonstrate that the suggested model may successfully lower wind abandonment,lower system operation costs,increase the accuracy of day-ahead scheduling,and lower the final product error of the thermal electricity unit.

Review:Recent Developments in Dynamic Load Identification for Aerospace Vehicles Considering Multi⁃source Uncertainties

The determination of the dynamic load is one of the indispensable technologies for structure design and health monitoring for aerospace vehicles.However,it is a significant challenge to measure the external excitation directly.By contrast,the technique of dynamic load identification based on the dynamic model and the response information is a feasible access to obtain the dynamic load indirectly.Furthermore,there are multi-source uncertainties which cannot be neglected for complex systems in the load identification process,especially for aerospace vehicles.In this paper,recent developments in the dynamic load identification field for aerospace vehicles considering multi-source uncertainties are reviewed,including the deterministic dynamic load identification and uncertain dynamic load identification.The inversion methods with different principles of concentrated and distributed loads,and the quantification and propagation analysis for multi-source uncertainties are discussed.Eventually,several possibilities remaining to be explored are illustrated in brief.

Uncertainty and joint probability of sea ice loads

Ice load is one of the most important factors for design of marine stuctures in cold sea area.The designcriteria of ice loads for marine structures consist of two parts: level ice thickness and crushing strength. Due to thestrong randomness of the affecting factors on ice thickness and crushing strength, such as ice temperature,air temperature, water temperature,salinity,wind field, numerical simulation method method can not produce satisfactory results. Thispaper proposes a method of uncertainty analysis and joint probabilistic prediction of level ice thickness and crushingstrength instead of traditional ice load criteria for marine structures.

Uncertainty Analysis Method of Casing Extrusion Load for Ultra-Deep Wells

With the consideration of the randomness of complex geologic parameters for ultra-deep wells,an uncertainty analysis method is presented for the extrusion load on casing in ultra-deep wells through complex formation at a certain confidence level.Based on the extrusion load model for casing in ultra-deep wells and the prerequisite of integrity of formation-cement ring-casing,the probability and statistics theory are introduced and the sensitivity analysis on the uncertainty of extrusion load on casing is conducted.The distribution types of each formation parameters are determined statistically.The distribution type and distribution function of the extrusion load on casing are derived.Then,the uncertainty analysis of the extrusion load on casing is carried out on several ultra-deep wells in Shanqian block as case study.Several conclusions are made regarding to the field trial result.The randomness of formation elasticity modulus and formation Poisson’s ratio are the main influence factors.The equivalent density profile of extrusion load on casing in ultra-deep wells is a confidence interval with a certain confidence level,rather than a single curve;the higher the confidence level is,the larger the bandwidth of the confidence interval of equivalent density profile becomes,and the larger the range of uncertainty interval becomes.Compared with the result of uncertainty analysis,an error exists in the result of traditional single valued calculation method.The error varies with different casing program and can be either positive or negative.The application of uncertainty analysis of extrusion load on casing provides proof for the accurate determination of casing collapse safety factor.Thus,the over engineering design or under engineering design as a result of tradition casing design will be avoided.

Geometric Interpretation of the Uncertainty Principle

The problems of unattainable infinity and infinitesimal are discussed. Limitations connected with the absolute zero of temperature and the maximal velocity are considered, as well as the consequences of these limitations. A geometric approach is proposed as an alternative to the wave-particle duality to explain the anomalous motion of micro objects. The basis of the geometric approach is a comparison between two geometries differing from each other in the metric of infinitesimal. The interconnection of these geometries is possible through the direct and inverse Weierstrass transformation. The application of this transformation allows one to explain diffraction effects.

Uncertainty Analysis of the Residual Strength of Non-Uniformly Loaded Casingsin Deep Wells

An uncertainty analysis method is proposed for the assessment of the residual strength of a casing subjected to wear and non-uniform load in a deep well.The influence of casing residual stress,out-of-roundness and non-uniform load is considered.The distribution of multi-source parameters related to the residual anti extrusion strength and residual anti internal pressure strength of the casing after wear are determined using the probability theory.Considering the technical casing of X101 well in Xinjiang Oilfield as an example,it is shown that the randomness of casing wear depth,formation elastic modulus and formation Poisson’s ratio are the main factors that affect the uncertainty of residual strength.The wider the confidence interval is,the greater the uncertainty range is.Compared with the calculations resulting from the proposed uncertainty analysis method,the residual strength obtained by means of traditional single value calculation method is either larger or smaller,which leads to the conclusion that the residual strength should be considered in terms of a range of probabilities rather than a single value.

Dynamic Economic Scheduling with Self-Adaptive Uncertainty in Distribution Network Based on Deep Reinforcement Learning

Traditional optimal scheduling methods are limited to accurate physical models and parameter settings, which aredifficult to adapt to the uncertainty of source and load, and there are problems such as the inability to make dynamicdecisions continuously. This paper proposed a dynamic economic scheduling method for distribution networksbased on deep reinforcement learning. Firstly, the economic scheduling model of the new energy distributionnetwork is established considering the action characteristics of micro-gas turbines, and the dynamic schedulingmodel based on deep reinforcement learning is constructed for the new energy distribution network system with ahigh proportion of new energy, and the Markov decision process of the model is defined. Secondly, Second, for thechanging characteristics of source-load uncertainty, agents are trained interactively with the distributed networkin a data-driven manner. Then, through the proximal policy optimization algorithm, agents adaptively learn thescheduling strategy and realize the dynamic scheduling decision of the new energy distribution network system.Finally, the feasibility and superiority of the proposed method are verified by an improved IEEE 33-node simulationsystem.

Nonlinear uncertainty impact of geometric variations on aerodynamic performance of low-pressure turbine blades with ultra-high loading under extreme operational conditions

Uncertainty impact of random geometric variations on the aerodynamic performance of low-pressure turbine blades is considerable,which is further amplified by the current ultra-high-lift design trend for weight reduction.Therefore,this uncertainty impact on ultra-highly loaded blades under extreme operational conditions near the margins with potential large-scale open separation is focused on in this study.It is demonstrated that this impact is significant,unfavourable,and nonlinear,which is clearly severer under extreme conditions.In addition to the overall attenuation and notable scattering of specific performance,the operational margins with open separation are also notably scattered with great risk of significant reduction.This scattering and nonlinearity are dominated by the variations in leading-edge thickness.The thinning of leading edge triggers local transition,enhancing downstream friction and reducing resistance to open separation,which is further exacerbated by operational deterioration.However,the opposite thickening yields less benefit,implying nonlinearity.This unfavourable impact highlights the need for robust aerodynamic design,where both a safer operational condition and a more robust blade are indispensable,i.e.,a compromise among performance,weight,and robustness.Besides the necessary limitation of loading levels,a mid-loaded design is recommended to reduce adverse pressure gradients in both the leading edge and rear region of the suction side,which helps to decrease the susceptibility of the transition and open separation to random perturbations.Similar improvements can also be achieved by appropriately thickening the leading edge.

Process parameters-weld bead geometry interactions and their influence on mechanical properties:A case of dissimilar aluminium alloy electron beam welds

Prediction of weld bead geometry is always an interesting and challenging research topic as it involves understanding of complex multi input and multi output system. The weld bead geometry has a profound impact on the load bearing capability of a weld joint, which in-turn decides the performance in real time service conditions. The present study introduces a novel approach of detecting a relationship between weld bead geometry and mechanical properties(e.g. tensile load) for the purpose of catering the best the process could offer. The significance of the proposed approach is demonstrated by a case of dissimilar aluminium alloy(AA2219 and AA5083) electron beam welds. A mathematical model of tensile braking load as a function of geometrical attributes of weld bead geometry is presented. The results of investigation suggests the effective thickness of weld-a geometric parameter of weld bead has the most significant influence on tensile breaking load of dissimilar weld joint. The observations on bead geometry and the mechanical properties(microhardness, ultimate tensile load and face bend angle) are correlated with detailed metallurgical analysis. The fusion zone of dissimilar electron beam weld has finer grain size with a moderate evaporation and segregation of alloying elements magnesium and copper respectively.The mechanical properties of weld joint are controlled by optimum bead geometry and HAZ softening in weaker AA5083 Al alloy.

Closure behavior of rock joint under dynamic loading

The normal compression tests on intact samples and artificial joints with different saw-tooth shape under cyclic loading and half-sine waves of different frequencies were performed by using Instron1342 servo-controlled material testing machine. The specimens were made artificially with mortar. The loading frequency ranged from 0.005 Hz to 0.1 Hz. The experimental results show that joint closure curves are non-linear and concave up. The stress-deformation curves under cyclic loading exhibit hysteresis and permanent set that diminish rapidly and keep constant finally on successive cycles. Normal displacement successively decreases from the joint J1 to J2, to J3 under the same normal loads regardless of frequency. Considering the loading frequency effect, normal displacement of joint J1 decreases with increasing the loading frequency except that the loading frequency is 0.05 Hz. Normal displacement of joint J2 increases with increasing the loading frequency. Normal displacement of joint J3 increases with increasing the loading frequency when the frequency ranges from 0.005 Hz to 0.05 Hz. Its normal displacement, however, becomes least when the loading frequency is 0.1 Hz.

The impact of geological uncertainty on primary production from a fluvial reservoir

Deposition of fluvial sandbodies is controlled mainly by characteristics of the system, such as the rate of avulsion and aggradation of the fluvial channels and their geometry. The impact and the interaction of these parameters have not received adequate attention. In this paper, the impact of geological uncertainty resulting from the interpretation of the fluvial geometry, maximum depth of channels, and their avulsion rates on primary production is studied for fluvial reservoirs. Several meandering reservoirs were generated using a process-mimicking package by varying several con- trolling factors. Simulation results indicate that geometrical parameters of the fluvial channels impact cumulative pro- duction during primary production more significantly than their avulsion rate. The most significant factor appears to be the maximum depth of fluvial channels. The overall net-to-gross ratio is closely correlated with the cumulative oil production of the field, but cumulative production values for individual wells do not appear to be correlated with the local net-to-gross ratio calculated in the vicinity of each well. Connectedness of the sandbodies to each well, defined based on the minimum time-of-flight from each block to the well, appears to be a more reliable indicator of well-scale production.

Numerical Uncertainty and Its Implications

A scrutiny of the contributions of key mathematicians and scientists shows that there has been much controversy (throughout the development of mathematics and science) concerning the use of mathematics and the nature of mathematics too. In this work, we try to show that arithmetical operations of approximation lead to the existence of a numerical uncertainty, which is quantic, path dependent and also dependent on the number system used, with mathematical and physical implications. When we explore the algebraic equations for the fine structure constant, the conditions exposed in this work generate paradoxical physical conditions, where the solution to the paradox may be in the fact that the fine-structure constant is calculated through different ways in order to obtain the same value, but there is no relationship between the fundamental physical processes which underlie the calculations, since we are merely dealing with algebraic relations, despite the expressions having the same physical dimensions.

Integrating Test Data and ATBM Simulations into Dose Propagation Uncertainty Formulation for Bone Fracture Risk Assessment

We consider the problem of assessing bone fracture risk for a subject hit by a blunt impact projectile. We aim at constructing a framework for integrating test data and Advanced Total Body Model (ATBM) simulations into the risk assessment. The ATBM is a finite element model managed by the Joint Non-Lethal Weapons Directorate for the purpose of assessing the risk of injury caused by blunt impacts from non-lethal weapons. In ATBM simulations, the quantity that determines arm bone fracture is the calculated maximum strain in the bone. The main obstacle to accurate prediction is that the calculated strain is incompatible with the measured strain. The fracture strain measured in bending tests of real bones is affected by random inhomogeneity in bones and uncertainty in measurement gauge attachment location/orientation. In contrast, the strain calculated in ATBM simulations is based on the assumption that all bones are perfectly elastic with homogeneous material properties and no measurement uncertainty. To connect test data and ATBM simulations in a proper and meaningful setting, we introduce the concept of elasticity-homogenized strain. We interpret test data in terms of the homogenized strain, and build an empirical dose-injury model with the homogenized strain as the input dose for predicting injury. The maximum strain calculated by ATBM has randomness due to uncertainty in specifications of ATBM setup parameters. The dose propagation uncertainty formulation accommodates this uncertainty efficiently by simply updating the shape parameters in the dose-injury model, avoiding the high computational cost of sampling this uncertainty via multiple ATBM runs.

Load Distribution of Base Stations in User-Centric Heterogeneous UDN

In ultra-dense networks(UDN),multiple association can be regarded as a user-centric pattern in which a user can be served by multiple base stations(BSs).The data rate and quality of service can be improved.However,BSs in user-centric paradigm are required to serve more users due to this multiple association scheme.The improvement of system performance may be limited by the improving load of BSs.In this letter,we develope an analytical framework for the load distribution of BSs in heterogeneous user-centric UDN.Based on open loop power control(OLPC),a user-centric scheme is considered in which the clustered serving BSs can provide given signal to interference plus noise ratio(SINR)for any typical user.As for any BS in different tiers,by leveraging stochastic geometry,we derive the Probability Mass Function(PMF)of the number of the served users,the Cumulative Distribution Function(CDF)of total power consumption,and the CDF bounds of downlink sum data rate.The accuracy of the theoretical analysis is validated by numerical simulations,and the effect the system parameters on the load of BSs is also presented.

Sensitivity analysis and probability modelling of the structural response of a single-layer reticulated dome subjected to an external blast loading

The structural response of a single-layer reticulated dome to external explosions is shaped by many variables,and the associated uncertainties imply non-deterministic results.Existing deterministic methods for predicting the consequences of specific explosions do not account for these uncertainties.Therefore,the impact of the uncertainties associated with these input variables on the structures’response needs to be studied and quantified.In this study,a parametric uncertainty analysis was conducted first.Then,local and global sensitivity analyses were carried out to identify the drivers of the structural dynamic response.A probabilistic structural response model was established based on sensitive variables and a reasonable sample size.Furthermore,some deterministic empirical methods for explosion-resistance design,including the plane blast load model of CONWEP,the curved blast load model under the 50%assurance level,and the 20%mass-increased method,were used for evaluating their reliability.The results of the analyses revealed that the structural response of a single-layer reticulated dome to an external blast loading is lognormally distributed.Evidently,the MB0.5 method based on the curved reflector load model yielded results with a relatively stable assurance rate and reliability,but CONWEP did not;thus,the 1.2MB0.5 method can be used for making high-confidence simple predictions.In addition,the results indicated that the structural response is very sensitive to the explosion parameters.Based on these results,it is suggested that for explosion proofing,setting up a defensive barrier is more effective than structural strengthening.

Long-Term Electricity Demand Forecasting for Malaysia Using Artificial Neural Networks in the Presence of Input and Model Uncertainties

Electricity demand is also known as load in electric power system.This article presents a Long-Term Load Forecasting(LTLF)approach for Malaysia.An Artificial Neural Network(ANN)of 5-layer Multi-Layered Perceptron(MLP)structure has been designed and tested for this purpose.Uncertainties of input variables and ANN model were introduced to obtain the prediction for years 2022 to 2030.Pearson correlation was used to examine the input variables for model construction.The analysis indicates that Primary Energy Supply(PES),population,Gross Domestic Product(GDP)and temperature are strongly correlated.The forecast results by the proposed method(henceforth referred to as UQ-SNN)were compared with the results obtained by a conventional Seasonal Auto-Regressive Integrated Moving Average(SARIMA)model.The R^(2)scores for UQ-SNN and SARIMA are 0.9994 and 0.9787,respectively,indicating that UQ-SNN is more accurate in capturing the non-linearity and the underlying relationships between the input and output variables.The proposed method can be easily extended to include other input variables to increase the model complexity and is suitable for LTLF.With the available input data,UQ-SNN predicts Malaysia will consume 207.22 TWh of electricity,with standard deviation(SD)of 6.10 TWh by 2030.

Influences of uncertainties to the generation feasible region for medium- and long-term electricity transaction

For the implementation of power market in China,medium-and Iong-term security checks are essential for bilateral transactions,of which the electricity quantity that constitutes the generation feasible region(GFR)is the target.However,uncertainties from load forecasting errors and transmission contingencies are threats to medium-and Iong-term electricity tradi ng in terms of their in flue nces on the GFR.In this paper,we prese nt a graphic distortio n pattern in a typical threegenerator system using the Monte Carlo method and projection theory based on security constrained economic dispatch.The underlying potential risk to GFR from uncertainties is clearly visualized,and their impact characteristics are discussed.A case study on detailed GFR distortion was included to dem on strate the effectiveness of this visualization model.The result implies that a small uncertainty could distort the GFR to a remarkable extent and that different line-contingency precipitates disparate the GFR distortion patterns,thereby eliciting great emphasis on load forecasting and line reliability in electricity transacti ons.

Generalized Uncertainty Relations, Curved Phase-Spaces and Quantum Gravity

Modifications of the Weyl-Heisenberg algebra are proposed where the classical limit corresponds to a metric in (curved) momentum spaces. In the simplest scenario, the 2D de Sitter metric of constant curvature in momentum space furnishes a hierarchy of modified uncertainty relations leading to a minimum value for the position uncertainty . The first uncertainty relation of this hierarchy has the same functional form as the stringy modified uncertainty relation with a Planck scale minimum value for at . We proceed with a discussion of the most general curved phase space scenario (cotangent bundle of spacetime) and provide the noncommuting phase space coordinates algebra in terms of the symmetric and nonsymmetric metric components of a Hermitian complex metric , such . Yang’s noncommuting phase-space coordinates algebra, combined with the Schrodinger-Robertson inequalities involving angular momentum eigenstates, reveals how a quantized area operator in units of emerges like it occurs in Loop Quantum Gravity (LQG). Some final comments are made about Fedosov deformation quantization, Noncommutative and Nonassociative gravity.

Optimal Operation of Electric Vehicles and Distributed Generation Resources in Smart Grid Considering Load Management

Technology advancement and the global tendency to use renewable energy in distributed generation units in the distribution network have been proposed as sources of energy supply.Despite the complexity of their protection,as well as the operation of distributed generation resources in the distribution network,factors such as improving reliability,increasing production capacity of the distribution network,stabilizing the voltage of the distribution network,reducing peak clipping losses,as well as economic and environmental considerations,have expanded the influence of distributed generation(DG)resources in the distribution network.The location of DG sources and their capacity are the key factors in the effectiveness of distributed generation in the voltage stability of distribution systems.Nowadays,along with the scattered production sources of electric vehicles with the ability to connect to the network,due to having an energy storage system,they are known as valuable resources that can provide various services to the power system.These vehicles can empower the grid or be used as a storage supply source when parked and connected to the grid.This paper introduces and studies a two-stage planning framework for the concurrent management of many electric vehicles and distributed generation resources with private ownership.In the first stage,the aim is to increase the profit of electric vehicles and distributed generation sources;finally,the purpose is to reduce operating costs.The proposed scheduling framework is tested on a distribution network connected to bus 5 of the RBTS sample network.Besides distributed generation sources and electric vehicles,we integrate time-consistent load management into the system.Due to distributed generation sources such as photovoltaic systems and wind turbines and the studied design in the modeling,we use the Taguchi TOAT algorithm to generate and reduce the scenario to ensure the uncertainty in renewable energy.MATLAB software is used to solve the problem and select the optimal answer.

Using the Analytic Hierarchy Process in Long-Term Load Growth Forecast

The load growth is the most important uncertainties in power system planning process. The applications of the classical long-term load forecasting methods particularly applied to utilities in transition economy are insufficient and may produce incorrect decisions in power system planning process. This paper discusses using the method of analytic hierarchy process to calculate the probability distribution of load growth obtained previously by standard load forecasting methods.