One of the issues of reliable performance in the power grid is the existence of electromechanical oscillations between interconnected generators. The number of generators participating in each electromechanical oscillation mode and the frequency oscillation depends on the structure and function of the power grid. In this paper, to improve the transient nature of the network and damping electromechanical fluctuations, a decentralized robust adaptive control method Based on dynamic programming has been used to Design a stabilizing power system and a complementary static var compensator (SVC) controller. By applying a single line to ground fault in the network, the robustness of the Designed control systems is demonstrated. Also, the simulation results of the method used in this paper are compared with controllers whose parameters are adjusted using the PSO algorithm. The simulation results show the superiority of the decentralized robust adaptive control method Based on dynamic programming for the stabilizing Design of the power system and the complementary SVC controller. The performance of the control method is tested using the IEEE 16-machine, 68-bus, 5-area is verified with time domain simulation.

Non-cooperative intelligent control agents (ICAs) with dedicated cost functions, can lead the system to poor performance and in some cases, closed-loop instability. A robust solution to this challenge is to place the ICAs at the feedback Nash equilibrium point (FNEP) of the differential game between them. This paper introduces the Designation of a robust decentralized infinite horizon LQR control system Based on the FNEP for a linear time-invariant system. For this purpose, two control strategies are defined. The first one is a centralized infinite horizon LQR (CIHLQR) problem (i.e. a supervisory problem), and the second one is a decentralized control problem (i.e. an infinite horizon linear-quadratic differential game). Then, while examining the optimal solution of each of the above strategies on the performance of the other, the necessary and sufficient conditions for the equivalence of the two problems are presented. In the absence of the conditions, by using the least-squares error criterion, an approximated CIHLQR controller is presented. It is shown that the theorems could be extended from a two-agent control system to a multi-agent system. Finally, the results are evaluated using the simulation results of a Two-Area non-reheat power system.

The need to improve the Reliability and safety requirements, has led to increasingly utilization of Reliability Based Design approaches. In this study, Reliability Based multidisciplinary Design optimization for a bipropellant propulsion system has been investigated. The objective function is minimizing the total system mass and Design constraints are the total impulse and the temperature of the wall of the combustion chamber. Monte Carlo simulation methodology is used to apply uncertainties in the problem and to show the Reliability of the system under these uncertainties. The mass, functional and geometric results of the bipropellant propulsion system are differentiated for optimal Design, Reliability Based Design and optimal Reliability Based Design. Then, considering the results, the concepts and definitions of Design methods are compared and discussed and it is shown that the Reliability Based multidisciplinary optimization while having the desired mass, has high Reliability.

The seismic Design of the structures is subjected to the uncertainties originating from various sources. To ensure that a safe Design is achieved, the uncertainties must be considered in the seismic Design process. The Reliability-Based seismic Design is the proper approach that directly takes into account the uncertainties. In this approach, the performance objectives are the Reliability-Based seismic criteria expressed either in terms of an annual probability of exceeding a given performance level or in terms of a probability of exceeding a given performance level conditioned on the seismic intensity corresponding to a specific hazard level. It is obvious that the ultimate aim of the Reliability-Based seismic Design of a building is not only to satisfy the Reliability-Based seismic criteria, but also to minimize the initial or life-cycle cost. The Reliability-Based seismic Design optimization (RBDO) is the method that achieves the most economic Design satisfying the Reliability-Based seismic criteria (probabilistic constraints). However, the RBDO is less preferred. This is because to ensure that Reliability-Based seismic criteria are achieved, the statistics parameters of the seismic demand and capacity must be determined through the results of the nonlinear dynamic analyses. On the other hand, the use of the nonlinear dynamic analyses in the RBDO method can lead to the increase of the computational cost so that the personal computers require several years to run it. In this study, a method to produce the Reliability-Based economic seismic Design is proposed. Reliability-Based seismic criteria are expressed in terms of a mean annual probability of exceeding a given performance level. The main goals are to ensure satisfying the Reliability-Based seismic criteria through the use of the results of the incremental dynamic analyses and to produce the economic seismic Design within reasonable computing time. The proposed method achieves the two goals through determining the optimum Design of the force-Based Design method that satisfies the Reliability-Based seismic criteria. The optimum Design of the force-Based Design method depends on the value of the response modification factor. The value of the response modification factor of a building, which leads to satisfying the Reliability-Based seismic criteria, is in the range of one to a maximum value. From an economic point of view, the desirable value of the response modification factor is the maximum one, which results in a minimum Design base shear and accordingly in an economic Design. In order to respond to the two main goals, the method aims to determine the maximum value of the response modification factor of a building so that leads to satisfying the Reliability-Based seismic criteria. The proposed method is used to produce the seismic Design of a 4-story building for two Reliability-Based seismic criteria. The steel special moment resisting frame is considered as the lateral load resisting system in the studied building. The results reveal that the proposed method can efficiently produce the economic seismic Designs satisfying the Reliability-Based seismic criteria within reasonable computing time. While the Designed frame by Zacharenaki et al using existing RBDO method can not satisfy spesifications of Reliability.

Achieving new technologies with high Reliability while reducing the cost and time of the Design cycle is one of the most significant challenges in developing complex systems. This paper discusses the Reliability-Based Design of a space system during the conceptual Design phase. Generally, there are eight steps in Designing for Reliability. As applied to a liquid propellant engine with electro-pump technology, these steps include planning, determination of failure modes, Reliability modeling, Reliability allocation, propagation of uncertainty, implementation of the chosen method in Reliability analysis, Reliability prediction, and Reliability evaluation. Each step contains sub-steps that follow in a specific order.In the second step, the prediction of failure modes is carried out using two FMEA methods alongside Design constraints. The third step involves developing the Reliability block diagram for the electro-pump. In the fourth step, various Reliability feature methods are introduced and reviewed. The fifth step presents four approaches to investigate uncertainty: sampling methods, analytical methods such as FORM and SORM, polynomial estimation using Taylor series, and advanced methods like random expansion.Subsequently, the uncertainty in the electro-pump engine is addressed alongside the limited functions in the electro-pump engine. Finally, in the seventh step, the Reliability evaluation of the electro-pump engine is discussed. This evaluation is conducted to validate the proposed method, where Reliability is determined using two indicators: specific impulse and mass ratio (initial mass to final mass).

In this study, the stability of the foundation near a slope is investigated through a typical example of Designing a shallow foundation. Foundation stability is typically evaluated through the bearing capacity’s factor of safety and the Reliability of the Design, which depicts a more realistic perspective of Design safety. Although an increase in the bearing capacity of the foundation leads to a subsequent increase in the safety factor and Reliability index, a monotonically increasing functional relationship between the safety factor and Reliability does not exist. This study investigates the effects of the foundation and slope properties on the Reliability-Based Design (RBD) and Safety-Factor Based Design (SBD). Also, some valuable hints for practical engineers” who are not familiar with Reliability concepts” are presented to achieve a more reliable SBD. The results show that it is vital to consider how to increase the bearing capacity in the SBD methods. For example, in cohesive-frictional soils, by changing the embedment depth of the foundation (df), and the distance between the foundation and slope crest (x) to reach the target safety factor, we can obtain a more reliable SBD.

In this paper, the Reliability Based Design optimization of columns under buckling load is investigated using evolutionary structural optimization. To determine the Reliability index, the Hasofer-Lind method is employed and results are compared with the Monte Carlo method. The standard response surface method with central composite Design is used to estimate the limit state function. An optimization algorithm for optimal Design of columns against buckling with different cross-sections and boundary conditions is presented while keeping the column weight constant.The Taguchi method is used to provide the most suitable levels of the Design variables. Then by introducing Reliability constraints into the algorithm, the optimized shape of the column under buckling load Based on Reliability is obtained. Optimized Design obtained from Deterministic Optimization (DO) and Reliability Based Design Optimization (RBDO) are compared. Numerical examples show that maximum buckling load capacity is increased compared to the initial uniform Design and also RBDO model is more reliable than DO.

Probability density functions of the involved random variables are essential for the Reliability-Based Design of offshore structures. The objective of present research was the derivation of probability density function (PDF) for the local joint flexibility (LJF) factor, fLJF, in two-planar tubular DK-joints commonly found in jacket-type offshore structures. A total of 162 finite element (FE) analyses were carried out on 81 FE models of DK-joints subjected to two types of axial loading. Generated FE models were validated using available experimental data, FE results, and Design formulas. Based on the results of parametric FE study, a sample database was prepared for the fLJF values and density histograms were generated for respective samples Based on the Freedman-Diaconis rule. Nine theoretical PDFs were fitted to the developed histograms and the maximum likelihood (ML) method was applied to evaluate the parameters of fitted PDFs. In each case, the Kolmogorov-Smirnov and chi-squared tests were used to evaluate the goodness of fit. Finally, the Inverse Gaussian model was proposed as the governing probability distribution function for the fLJF. After substituting the values of estimated parameters, two fully defined PDFs were presented for the fLJF in tubular DK-joints subjected to two types of axial loading.

The regulatory schemes currently used for Reliability improvement have weaknesses in the provision of quality services Based on the customers’ perspective. These schemes consider the average of the service as a criterion to incentivize or penalize the distribution system operators (DSOs). On the other hand, most DSOs do not differentiate electricity services at the customer level, due to the status of the electricity grid and lack of adequate information about customers’ preferences. This paper proposes a novel Reliability insurance scheme (RIS), which enables the electricity consumers to determine their desired Reliability levels according to their preferences and pay corresponding premiums to the DSO. The DSO can use the premiums to improve Reliability or reimburse consumers. To Design efficient insurance contracts, this paper uses utility function to estimate customers’ viewpoints of electricity energy consumption. This function measures the customers’ satisfaction of electricity energy consumption. The proposed utility Based Reliability insurance scheme (URIS) may create a free-riding opportunity for the DSO, in which low quality service is provided and the collected premiums are used to pay the reimbursements. To prevent free-riding opportunity, this paper incorporates the proposed URIS and reward/penalty schemes (RPSs). The results show that the success of the proposed Reliability scheme increases as the grid flexibility increases.

1. Introduction: Optimization by explicit and deterministic variables is called deterministic optimization. It is known that there are wide varieties of uncertainties which are originated from the errors in modeling and simulation and condition of services such as changes in loading. Moreover, we must consider these uncertainties in different stages of Design process of structures. Some of the most important factors which should be considered in structural Designing are variation of material properties, geometrical dimensions of the structures, and the loading patterns. On the other hand, deterministic optimization on structures uses the strong safety factors instead of uncertainties. Thus, the resultant Designed-structures are leading to the excessive conservative structures that would not be economical and optimal. According to, existing some uncertainties in each level of engineering Design process; it is required to consider safety factors in computation of the deterministic optimization. In order to resolve this problem, an efficient approach is recently developed which is called Reliability Based optimal Design. In this method the safety of structures are evaluated Based on the failure probability and the aforementioned uncertainties are modeled by the probability distribution of random variables. Finally, the investigated components embedded in the assessed acceptable ranges of safety which is introduces with the failure definition. This practical method can be applied to different structures...