Search Results (28)

To enhance stability and reliability, multi-microgrid systems have been developed as replacements for conventional distribution networks. Traditionally, switches have been used to interconnect these microgrids, but this approach often results in uncoordinated power sharing, leading to economic inefficiencies and technical challenges such as voltage fluctuations, delay in response, etc. This research, in turn, introduces a novel multi-microgrid system that utilizes advanced electronic devices known as soft open points (SOPs) to enable effective voltage management and controllable power sharing between microgrids while also providing reactive power support. To account for uncertainties in the system, the two-point estimate method (2PEM) is applied. Simulation results on an IEEE 33-bus network with high renewable energy penetration reveal that the proposed SOP-based system significantly outperforms the traditional switch-based method, with a minimum voltage level of 0.98 p.u., compared to 0.93 p.u. in the conventional approach. These findings demonstrate the advantages of using SOPs for voltage management in forming multi-microgrid systems. Full article

In this paper, a stochastic techno-economic optimization framework is proposed for three different hybrid energy systems that encompass photovoltaic (PV), wind turbine (WT), and hydrokinetic (HKT) energy sources, battery storage, combined heat and power generation, and thermal energy storage (Case I: PV–BA–CHP–TES, Case II: WT–BA–CHP–TES, and Case III: HKT–BA–CHP–TES), with the inclusion of electric and thermal storage using the 2m + 1 point estimate method (2m + 1 PEM) utilizing real data obtained from the city of Espoo, Finland. The objective function is defined as planning cost minimization. A new meta-heuristic optimization algorithm named improved fire hawk optimization (IFHO) based on the golden sine strategy is applied to find the optimal decision variables. The framework aims to determine the best configuration of the hybrid system, focusing on achieving the optimal size for resources and storage units to ensure efficient electricity and heat supply simultaneously with the lowest planning cost in different cases. Also, the impacts of the stochastic model incorporating the generation and load uncertainties using the 2m + 1 PEM are evaluated for different case results compared with the deterministic model without uncertainty. The results demonstrated that Case III obtained the best system configuration with the lowest planning cost in deterministic and stochastic models and. This case is capable of simply meeting the electrical and thermal load with the contribution of the energy resources, as well as the CHP and TESs. Also, the IFHO superiority is proved compared with the conventional FHO, and particle swarm optimization (PSO) achieves the lowest planning cost in all cases. Moreover, incorporating the stochastic optimization model, the planning costs of cases I–III are increased by 4.28%, 3.75%, and 3.57%, respectively, compared with the deterministic model. Therefore, the stochastic model is a reliable model due to its incorporating the existence of uncertainties in comparison with the deterministic model, which is based on uncertain data. Full article

Distributed photovoltaic (PV) output exhibits strong stochasticity and weak adjustability. After being integrated with the network, its interaction with stochastic loads increases the difficulty of assessing the distribution network’s static voltage stability (SVS). In response to this issue, this article presents a probabilistic assessment method for SVS in a distribution network with distributed PV that considers the bilateral uncertainties and correlations on the source and load sides. The probabilistic models for the uncertain variables are established, with the correlation between stochastic variables described using the Copula function. The three-point estimate method (3PEM) based on the Nataf transformation is used to generate correlated samples. Continuous power flow (CPF) calculations are then performed on these samples to obtain the system’s critical voltage stability state. The distribution curves of critical voltage and load margin index (LMI) are fitted using Cornish-Fisher series. Finally, the utility function is introduced to establish the degree of risk of voltage instability under different scenarios, and the SVS assessment of the distribution network is completed. The IEEE 33-node distribution system is utilized to test the method presented, and the results across various scenarios highlight the method’s effectiveness. Full article

Proton-exchange membrane (PEM) fuel cells are increasingly used in the automotive sector. A crucial point for estimating the performance of such systems is open-circuit voltage (OCV) losses, among which the most influential are mixed potential, hydrogen crossover, and internal short circuits. These losses are often overlooked in the modeling of such electrochemical cells, leading to an inaccurate estimation of the real voltage that is calculated starting from the Nernst Equation. An innovative method is presented to estimate the losses based on the division of the membrane into two domains: solid and aqueous. The influence of the macro-parameters (temperature, pressure, and RH) was analyzed for each phenomenon and was linked to the membrane water content. For low levels of PEM hydration, internal short circuits were of the same order of magnitude as hydrogen crossover. The OCV model accuracy was assessed on a commercial stack, used on a vehicle prototype competing in the Shell Eco-Marathon challenge. The data of interest were obtained through laboratory tests and subsequent disassembly of the stack. A PEM thickness of 127 μm was measured corresponding to Nafion 115. For further validation, the model results were compared with data in the literature. Full article

A one-dimensional model for fluid and solute transport in poroelastic materials (PEMs) is studied. Although the model was recently derived and some exact solutions, in particular steady-state solutions and their applications, were studied, special cases occurring when some parameters vanish were not analysed earlier. Since the governing equations are nonintegrable in nonstationary cases, the Lie symmetry method and modern tools for solving ODE systems are applied in order to construct time-dependent exact solutions. Depending on parameters arising in the governing equations, several special cases with new Lie symmetries are identified. Some of them have a highly nontrivial structure that cannot be predicted from a physical point of view or using Lie symmetries of other real-world models. Applying the symmetries obtained, multiparameter families of exact solutions are constructed, including those in terms of elementary and special functions (hypergeometric, Whittaker, Bessel and modified Bessel functions). A possible application of the solutions obtained is demonstrated, and it is shown that some exact solutions can describe (at least qualitatively) the solute transport in PEM. The obtained exact solutions can also be used as test problems for estimating the accuracy of approximate analytical and numerical methods for solving relevant boundary value problems. Full article

Heavy-haul railways have a high passing frequency of trains with a large axle weight, causing rapid accumulation of fatigue damage in reinforced concrete (RC) bridge structures, which significantly affects the safety of the bridges. To study the fatigue reliability of RC beams in heavy-haul railways, the fatigue performance function for RC beams in heavy-haul railways was established, and the fatigue reliability assessment method for bridge structures in heavy-haul railways based on the point estimate method (PEM) was developed. An 8 meter-span plate beam in an existing heavy-haul railway illustrates the method. The train axle weight and dynamic coefficient were considered random variables, and the first four moments of equivalent stress ranges were obtained. The traffic quantity of the heavy-haul railways was investigated, and the fatigue reliability was evaluated using the proposed method. In addition, the effects of annual freight volume and train axle weight on fatigue reliability were discussed. Results indicate that PEM can effectively and accurately evaluate the fatigue reliability of RC beams in heavy-haul railways. In the first 20 years of operation, the fatigue failure probability was less than the limit value specified in the standard. The increase in annual traffic volume and train axle weight will cause a significant increase in fatigue failure probability. The research results of this paper are expected to provide an important basis for the design and maintenance of reinforced concrete bridges for heavy-haul railways in the future. Full article

In this paper, stochastic sizing of a stand-alone Photovoltaic/Hydrokinetic/Hydrogen storage energy system is performed with aim of minimizing the cost of project life span (COPL) and satisfying the reliability index as probability of load shortage (POLS). The stochastic sizing is implemented using a novel framework considering two-point estimate method (2m+1 PEM) and improved gradient-based optimizer (IGBO). The 2m+1 PEM is used to evaluate the impact of uncertainties of energy resource generation and system demand on sizing problem. The 2m+1 PEM utilizes the approximate method to account for these uncertainties. In order to avoid premature convergence, the gradient-based optimizer (GBO), a meta-heuristic algorithm influenced by Newtonian concepts, is enhanced using a dynamic lens-imaging learning approach. The size of the system devices, which is determined utilizing the IGBO with the COPL minimization and optimally satisfying the POLS, is one of the optimization variables. The results of three hPV/HKT/FC, hPV/FC, and hHKT/FC configurations of the system are presented in two situations of deterministic and stochastic sizing without and with taking uncertainty into consideration. The findings showed that the hPV/HKT/FC configuration and the IGBO performed better than other configurations and techniques like conventional GBO, particle swarm optimization (PSO), and artificial electric field algorithm (AEFA) to achieve the lowest COPL and POLS (higher reliability) in various cases. Additionally, the COPL for the hPV/HKT/FC, hPV/FC, and hHKT/FC configurations increased by 7.63%, 7.57%, and 7.65%, respectively, while the POLS fell by 5.01%, 4.48%, and 4.59%, respectively, contrasted to the deterministic sizing, according to the results of stochastic sizing based on 2m+1 PEM. As a result, the findings indicate that in the deterministic sizing model, the quantity of output and energy storage is insufficient to meet demand under unknown circumstances. Applying stochastic sizing while taking into account the volatility of both supply and demand can, therefore, be an economically sound way to meet demand. Full article

This paper introduces a probabilistic assessment of steel column damage caused by blast loads, utilizing simulation reliability methods and gene expression programming. The research focuses on an H-section steel column and incorporates uncertainties associated with input loads (axial and blast loads) and geometric factors (i.e., maximum slenderness) under various boundary conditions (pinned and fixed supports). The reliability analysis employs three different methods: the point estimate method (PEM), the Monte Carlo simulation (MCS) method, and the Monte Carlo simulation with Latin hypercube sampling method (MCS-LHS). To perform the reliability analysis, formulas derived from a previous study conducted by the authors using gene expression programming (GEP) were employed. Damage assessment was carried out based on a damage index criterion, considering the post-blast residual axial load-bearing capacity of the steel column. The research results are presented in terms of damage probability, considering the different reliability analysis methods and boundary conditions. The findings demonstrate that the PEM effectively estimates the probabilistic response of the steel column with acceptable accuracy and less effort compared with the MCS and MCS-LHS. Furthermore, the MCS-LHS demonstrates higher accuracy in estimating the probability distribution function by utilizing the Latin hypercube sampling (LHS) method, as compared to the MCS. These findings emphasize the importance of considering uncertainties in calculating the column response under extreme dynamic blast loading. Full article

This work considers the influence of concrete creep on track irregularities and establishes the dynamic motion equation of the train-track-bridge coupling system. The track irregularity is obtained by superposition of the initial geometric irregularity and additional geometric irregularity of the steel rail caused by creep. When high-speed railway trains pass through bridges; the vertical acceleration and vertical displacement of continuous beam bridges are related to the train’s operating speed, and the influence of creep camber is relatively small. At the same time, considering the randomness of track irregularities, the dynamic responses of the train track bridge coupling system under the action of random track irregularities are analyzed, and the dynamic responses of trains at different operating speeds are obtained. The deterministic and uncertain dynamic responses of the train track bridge system were compared and analyzed to verify the accuracy of the Karhunen Loéve expansion (KLE)-Point estimate method (PEM) calculation results. The results indicate that the random characteristics of track irregularities have a significant impact on train dynamic response. Based on the random system vibration analysis and considering the safety and comfort indicators of high-speed railway trains, the creep deformation limit of a continuous beam bridge with a length of 48 m + 80 m + 48 m is obtained to be 19 mm. This is the first time that the dynamic responses of train-symmetry-bridge system are calculated by considering concrete creep and the creep-induced track irregularity, which has certain significance for understanding the dynamics of train -bridge system. In addition, the proposed creep threshold is also of great significance to ensure the safety of traveling. Full article

Many studies have pointed out that the Performance Evaluation Matrix (PEM) is a convenient and useful tool for the evaluation, analysis, and improvement of service operating systems. All service items of the operating system can collect customer satisfaction and importance through questionnaires and then convert them into satisfaction indices and importance indices to establish PEM and its evaluation rules. Since the indices have unknown parameters, if the evaluation is performed directly by the point estimates of the indices, there will be a risk of misjudgment due to sampling error. In addition, most of the studies only determine the critical-to-quality (CTQ) that needs to be improved, and do not discuss the treatment rules in the case of limited resources nor perform the confirmation after improvement. Therefore, to address similar research gaps, this paper proposed the unbiased estimators of these two indices and determined the critical-to-quality (CTQ) service items which need to be improved through the one-tailed statistical hypothesis test by building a PEM method of the satisfaction index. In addition, through the one-tailed statistical hypothesis test method of the importance index, the improvement priority of service items was determined under the condition of limited resources. Confirmation of the effect on improvement is an important step in management. Thus, this paper adopted a statistical two-tailed hypothesis test to verify whether the satisfaction of all the CTQ service items that need to be improved was enhanced. Since the method proposed in this paper was established through statistical hypothesis tests, the risk of misjudgment due to sampling error could be reduced. Obviously, reducing the misjudgment risk is the advantage of the method in this paper. Based on the precondition, utilizing the model in this study may assist the industries to determine CTQ rapidly, implement the most efficient improvement under the condition of limited resources and also confirm the improvement effect at the same time. Finally, a case study of computer-assisted language learning system (CALL System) was used to illustrate a way to apply the model proposed in this paper. Full article

As a type of urban life project in China, bridges need a certain capacity of trains running safely after an earthquake to ensure and guarantee transportation on railway lines, post-disaster reconstruction and relief work. Since aftershocks may occur after the main shock, the earthquake-induced irregularity and aftershock intensity are fully considered, based on the running safety index in the seismic design of bridges. However, there is a lack of research on the running safety of trains after an earthquake; it is mainly judged on experience, and lacks theoretical basis. In this paper, the established finite element model of a train bridge interaction system with symmetry was considered. The point estimation method (PEM) combined with moment expansion approximation (MEA) is used for random calculation of the Housner Intensity (HI). Furthermore, running safety indexes were analyzed and the running safety performance of a simply supported bridge with symmetry was assessed under a post-earthquake condition. Then the limit value, to ensure the traffic safety performance after an earthquake, is calculated based on stochastic analysis. The HI can be calculated with full consideration of the randomness of aftershock intensity and structural parameters. On this basis, a calculation method of the HI that considers the randomness of aftershock intensity is proposed. This study can be helpful for the performance-based design of symmetric railway structures under post-earthquake conditions. Full article

Based on new policies and social changes, renewable energies have highly penetrated electrical systems, making the system more vulnerable than before. On the other hand, it leads to congestion and competition within the network. To this end, this paper developed a probabilistic multi-objective-based congestion management approach and applied it to the optimal transmission switching (OTS) strategies, to maximize system suitability and minimize total production costs. A point estimation economic method (PEM) has been applied, as one of the best management and economic tools to handle the uncertainties associated with a wind turbine’s power production and load demand (LD). Results demonstrate the effectiveness and merit of the proposed technique, compared to the existing one, which can lead to higher reliability and sustainability for the grids. Full article

Mathematical models are used for simulating the electrochemical phenomena of proton-exchange-membrane (PEM) fuel cells. They differ in the scale, modeling variables, precision in specific features, and the required parameters. Often, the input parameters are not measurable and need to be estimated by minimizing the error between the model output and experimental data; however, the estimated parameters could differ from one model to another, hence provoking uncertainty about the correct values and the model’s suitability for simulating the real phenomenon. To address these issues, we introduced a self-validating methodology using three different mathematical models: The first set of parameters was estimated with a semi-empirical (SE) model; then, it was used for computing several points of the polarization curve (PC). The SE parameters and points were used to estimate a second set of parameters and to compute a single point of the PC with a macro-homogeneous (MH) model. The parameters and concentration profiles from the MH solution were used to estimate the last set of parameters with the reaction–convection–diffusion (SP-RCD) model, increasing the detail of the simulation. The SP-RCD parameters were returned to the MH model to recover the complete PC. The proposed methodology requires a few data points to consistently recover the same PC from the three models through estimating parameters in one model and validating them in the others. As output, the method provides complete information about several variables and the physical properties of the catalysts. In addition to the consistent simulation, the numerical results are consistent with those reported in the literature, thus validating the proposed method. Full article

The objective of the present paper is to study the optimum installation of Non-dispatchable Distributed Generations (NDG) in the distribution network of given sizes under the given scheme. The uncertainty of various random (uncertain) parameters like load, wind and solar operated DG besides uncertainty of fuel prices has been investigated by the three-point estimate method (3-PEM) and Monte Carlo Simulation (MCS) based methods. Nearly twenty percent of the total number of buses are selected as candidate buses for NDG placement on the basis of system voltage profile to limit the search space. Weibull probability density function (PDF) is considered to address uncertain characteristics of solar radiation and wind speed under different scenarios. Load uncertainty is described by Standard Normal Distribution Function (SNDF). To investigate the solution of optimal probabilistic load flow (OPLF) three-point PEM-based technique was applied. For optimization, Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and GA-PSO hybrid-based Artificial Intelligent (AI) based optimization techniques are employed to achieve the optimum value of the multi-objectives function. The proposed multi-objective function comprises loss and different costs. The proposed methods have been applied to IEEE 33- bus radial distribution network. Simulation results obtained by these techniques are compared based on loss minimization capability, enhancement of system bus voltage profile and reduction of cost and fitness functions. The major findings of the present study are the PEM-based method which provides almost similar results as MCS based method with less computation time and as far as loss minimization capacity, voltage profile improvement etc. is concerned, the hybrid-based optimization methods are compared with GA and PSO based optimization techniques. Full article

The rock slope stability analysis can be performed using deterministic and probabilistic approaches. The deterministic analysis based on the safety concept factor uses fixed representative values for each input parameter involved without considering the variability and uncertainty of the rock mass properties. Probabilistic analysis with the calculation of probability of failure instead of the factor of safety against failure is emerging in practice. Such analyses offer a more rational approach to quantify risk by incorporating uncertainty in the input variables and evaluating the probability of the failure of a system. In rock slope engineering, uncertainty and variability involve a large scatter of geo-structural data and varied geomechanical test results. There has been extensive reliability analysis of rock slope stability in the literature, and different methods of reliability are being employed for assessment of the probability of failure and the reliability of a slope. Probabilistic approaches include Monte Carlo simulation (MCS), the point estimate method (PEM), the response surface method (RSM), first- and second-order reliability methods (FORMs and SORMs), and the first-order second-moment method (FOSM). Although these methods may be complicated, they provide a more complete definition of risk. Probabilistic slope stability analysis is an option in most commercial software; however, the use of this method is not common in practice. This paper provides an overview of the literature on some of the main probabilistic reliability-based methods available for the design of the rock slope in open pit mining. To demonstrate its applicability, the paper investigates the stability of a rock slope in an open pit mine in the Goldfields region, Western Australia. Two different approaches were adopted: deterministic stability analysis using two-dimensional limit equilibrium and finite element shear strength reduction methods using SLIDE and RS2 software, respectively, and probabilistic analysis by applying the MCS and RSM methods in the limit equilibrium method. In this example, the slope stability analysis was performed using the Spencer method with Cuckoo search optimization to locate the critical slip surface. The results obtained were compared and commented on. Full article