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Power system unreliability tracing model allocates the system's reliability index to individual components, identifying potential weaknesses. This study expands its scope by considering the impact of storage resources. Unreliable factors leading to load shedding are categorized into two groups: objective factors inherent to the component and insufficient storage resources. The latter requires a retrospective analysis of other components that caused unreliability previously. When allocating responsibility for load shedding at a certain time, it begins by allocating it among components based on differences between fixed expected output and actual supply. Expected output insufficiency is considered as the unreliable factor. This insufficiency due to insufficient storage resources is then decomposed into segments, each caused by excessive output in earlier instances of the same component. The expected output excess is attributed to the expected output insufficiency of other components in previous times, for which responsibility has been allocated to each component. Consequently, the expected output insufficiency at a particular time can be traced back based on a temporal recursive model, with the load shedding further allocated to components before that time. Case studies based on several systems demonstrate that the proposed model's allocation results are reasonable and more accurate than the traditional model. [ABSTRACT FROM AUTHOR]

Conventionally, the 2-parameter Weibull model, Arrhenius-Weibull model, has been used vastly for transformer aging-dependent unavailability modeling. However, this model only uses the lifetime feature to describe the transformer's degradation process and to calibrate the Weibull parameters, which harms the accuracy of aging-dependent unavailability forecasting. In response, this paper develops a 3-calibratable-parameter Weibull model for evaluating the transformer aging-dependent unavailability. In the proposed model, both the individualized aging threshold and lifetime are taken into the calibration of the Weibull parameters to accurately characterize the heterogeneity in transformer populations. First, a degree of polymerization (DP) analysis and Monte Carlo Simulation (MCS) based approach is proposed for estimating the transformers’ uncertain aging thresholds and lifetimes. Then, the Maximum Likelihood Estimate and Particle Swarm Optimization are jointly adopted to model the relationship among the calibratable Weibull parameters, aging threshold, and lifetime. Finally, the analytical formula of aging-dependent unavailability is derived from the established 3-calibratable-parameter Weibull model using an integral-discretization method. A real utility application example in China's Chongqing power system has been presented to validate and demonstrate the practicality and usefulness of this method. [ABSTRACT FROM AUTHOR]

The integration of the variable renewable energies makes the operation conditions of the power system ever-changeable. Consequently, the power system operational reliability evaluation is increasingly important. This paper introduces the concept of decision-dependent uncertainty (DDU) in the operational reliability evaluation. Unlike the exogenous uncertainties, DDU reveals that the decisions of the system operation could significantly affect the resolution of the uncertainties which influence the reliability metrics. In this paper, the proposed DDU modeling method links the device reliability indices, i.e., the forced outage rate, and the operational-decision variables. The impacts of DDU on operational reliability are analyzed based on a reliability-constrained stochastic unit commitment (UC) model. An adaptive reliability improvement UC (ARIUC) algorithm is proposed to efficiently solve the problem. Case studies underline the necessity of considering DDU in power system operational reliability evaluations. [ABSTRACT FROM AUTHOR]

The cross-entropy (CE) method can accelerate power system reliability evaluation effectively. An importance sampling (IS) based iterative parameter updating algorithm is usually used in CE optimization. However, the efficiency in capturing the concerned samples for parameter updating may be unsatisfactory, especially for a system with intrinsic nature of rare failure events. Besides, the stopping criterion of this iterative algorithm is usually determined subjectively, incurring insufficient or excessive parameter updating and a resultant higher computational burden of the entire simulation. To address the above two problems, a CE method based on subset simulation and minimum computational burden criterion is proposed. In CE optimization, the subset simulation combined with M-H sampling is adopted as an alternative to IS to effectively improve the efficiency of capturing desired samples for parameter updating at each iteration. Moreover, a novel quantitative stopping criterion is presented in such a way that the computational burden for the entire simulation is estimated and compared after each parameter updating iteration, and the optimal parameters corresponding to the minimum computational burden can be determined. The computational performance of the proposed method is validated by comparing the proposed approach with existing methods under several numerical tests including a realistic power system. [ABSTRACT FROM AUTHOR]

Reliability evaluation of bulk power systems (BPSs) has inherent computational complexity due to the numerous system states and the time‐consuming system state analysis, including power flow calculation, load curtailment, recognition of split power systems and network reconfiguration. In this study, a novel uniform‐design based method is proposed to improve the computational efficiency of power system reliability evaluation. The main idea is that the uniform‐design technique is used to generate the system states in reliability evaluation, which makes the sampled states more uniform and representative in the overall state space compared to the enumerated system states in an analytical method or the random‐generated system states in Monte Carlo simulation. As a result, the sample size and the computational time can be significantly reduced. In addition, the confidence intervals of the reliability indices, such as LOLP, FLOL and EENS, are given. And the estimation errors of reliability indices are discussed. The proposed method is tested on several BPSs, including the IEEE‐RTS79, IEEE‐RTS96 and a real BPS in China. All the case studies indicate that the proposed technique can significantly improve the computational efficiency of BPS reliability evaluation. [ABSTRACT FROM AUTHOR]

Power system reliability evaluation (PSRE) typically involves with finding the system (or bus) reliability index from known component reliability parameters. In this paper, we consider the case of using the system (or bus) reliability index to obtain the unknown component reliability parameter (UCRP). This problem is called the inverse PSRE problem. Analytical model of the inverse PSRE problem is constructed and formulated as the nonlinear algebraic equations. In particular, analytical models for the composite generation and transmission system and the generating system are developed based on the state enumeration method. Solution method using the interval analysis is developed by transforming the nonlinear algebraic equations into the interval nonlinear equations with UCRPs represented by the interval numbers. A modified Krawczyk-operator algorithm based on interval bisection elimination scheme is developed to overcome the difficulty of selecting the appropriate initial interval in the problem-solving process. The RBTS, IEEE-RTS, and a 91-bus system are used for the case study to verify the effectiveness of the proposed model and the solution method. In addition, an application to power system planning is investigated to examine how the component reliability parameters can be modified quantitatively to achieve the desired system reliability improvement. [ABSTRACT FROM AUTHOR]

The electrical power grid is a critical infrastructure that plays a key role in supporting modern society. The reliability of power systems needs to be continuously maintained to deliver high-quality electric services. Due to the tremendous amounts of potential investment demanded for constructing new electricity transmission facilities, electric utilities need economical solutions that can enable them to supply electricity to their customers in a cost-effective and reliable way. Dynamic thermal rating (DTR) and network topology optimization (NTO) technologies aim to maximize the use of existing transmission assets and to provide flexible ways to enhance reliability of the power system. In this study, the DTR and NTO are incorporated into the power grid reliability assessment procedure using the sequential Monte Carlo simulation. Multiple case studies are carried out based on the modified IEEE RTS-79 and IEEE RTS-96 systems, accounting for long-term multiarea weather conditions. The numerical results indicate that with the incorporation of DTR and NTO, the reliability of power systems can be improved. The effect of these methods is especially significant for power grids with lower electricity delivery capabilities. [ABSTRACT FROM AUTHOR]

In this paper, a reliability evaluation model and a bilevel unreliability allocation model for the ±500-kV HVdc transmission system with the double-circuit lines on the same tower (DCLST) are proposed. The reliability evaluation indices associated with this DCLST HVdc system are also defined. The reliability model is based on the characteristics of common starting point and terminal point structure and double-circuit HVdc coordination operation. And it is developed by integrating HVdc subsystem reliability models together. A multistate Markov model for the dc line (DCL) subsystem is built by considering the common-cause outage of four DCLs on the same tower. The reliability evaluation model of the ac filter (ACF) subsystem is constructed by considering the derated capacity operation state caused by ACF failures. On the other hand, a bilevel unreliability allocation model is constructed based on the proportion-allocation criterion. The allocation model is embedded into the reliability evaluation model so that all reliability indices can be allocated to each component after only one reliability evaluation calculation. As a result, the impact of each component on the system reliability and weak components of the system can be explicitly and unambiguously identified. An actual ±500-kV HVdc transmission project with the DCLST is used for case study to validate the effectiveness of the proposed models and indices. [ABSTRACT FROM PUBLISHER]

In this paper, an optimal reliability allocation (ORA) model of ±800 kV ultra-high voltage direct current (HVDC) transmission system is proposed. The model intends to provide the means to determine the availability requirements of components in the bidding process of ±800 kV ultra HVDC transmission projects. In this model, the component availability is optimized based on the prespecified system reliability. The objective function is composed of the component investment cost and the operation and maintenance cost. The ORA is formulated as a constrained nonlinear programming problem, and the genetic algorithm (GA) is used to find its solution. An improved dagger sampling (IDS) method is proposed to evaluate the reliability of ultra HVDC systems, and a bisection method is used to generate the initial population of the GA. An actual ultra HVDC project is used to conduct the case study. Results show that the proposed ORA model can minimize the component investment, operation, and maintenance costs, while achieving optimal allocation of the system reliability index to obtain the availability of components. In addition, the impact of the component spare on the ORA result is investigated. Performance comparison on the sampling efficiency of the IDS method and the direct Monte Carlo sampling method is also presented. [ABSTRACT FROM AUTHOR]

Energy production of a wind farm is greatly affected by the wake-effect. In wind farm planning, it is essential to optimize the layout of wind turbine generators (WTGs) to alleviate the impact of wake-effect. This paper presents a new wind farm layout optimization model with an objective function to maximizing equivalent power of the wind farm. The proposed model incorporates the discrete joint probability distribution and characteristics of the wind, wind energy model, and the wake-effect. A particle swarm optimization algorithm is used to solve the optimization problem. In the optimization process, geometric analysis is conducted to determine the upstream WTGs and to calculate the horizontal and deviating distances among WTGs along the wind direction. An effective look-up table is constructed to directly determine the upstream/downstream WTGs. Then the optimal layout of a wind farm can be obtained. The proposed technique is applied to the wind farm layout optimization and the modified Roy Billinton Test System and IEEE Reliability Test System for reliability analysis of a generating system containing a wind farm. Simulation results demonstrate the validity and flexibility of the proposed technique in the layout optimization of WTGs in a wind farm. [ABSTRACT FROM AUTHOR]

Double 12-pulse ultra HVDC transmission systems of \pm 800 kV and \pm 660 kV have larger transmission capacities, more complicated configurations, more complex operation modes, and more components, in comparison to \pm 500 kV or less HVDC transmission systems. Hence, the reliability evaluation of the ultra HVDC transmission system is more complicated than that of the HVDC system. To thoroughly describe different operating modes, this paper presents two new reliability measures for ultra HVDC transmission systems, that is, partial monopole forced outage times and partial bipole-forced outage times. Reliability evaluation models for individual subsystems, including converter transformers (CT), ac filters, converter valve groups, and smoothing reactors have been built considering operation modes and configuration characteristics. In particular, the reliability model of the CT subsystem was built by considering the type and the number of standby CTs, and that of the ac filter subsystem was built by considering the capacity state table of filters. A reliability evaluation model for ultra HVDC transmission systems was proposed by combining reliability logic relationships among subsystems and using the state enumeration method. Case studies of practical ultra HVDC transmission systems illustrate the correctness of indices and the proposed models. In addition, sensitivity analysis and standby analysis of major components were also conducted. [ABSTRACT FROM PUBLISHER]

Due to the lack of feeder corridors, the Chinese utility companies frequently choose the technique of putting multiple overhead feeders on a same tower (MFST) to meet the load demand in a heavy load area. In many situations, the distance among the feeders of MFST in an electrical distribution network (EDN) is usually too small to meet the requirements of safety regulation for repairing and maintenance. Therefore, when a fault occurs on a feeder of MFST, the other feeders have to be in a triggered passive outage (TPO) state to assist the repairing of the failed feeder. This paper presents a reliability evaluation algorithm for EDNs containing MFST using the section technique. The definition of TPO and the equivalent TPO rate and TPO duration are also proposed. Based on the TPO parameters and the section technique, the reliability evaluation algorithm containing the MFST can be obtained. Case studies on the modified RBTS-BUS6 and the EDNs of three districts in Dongguan city, China, show that the MFST has a significant impact on the EDN reliability and should be considered in the reliability evaluation. The results also show the effectiveness and applicability of the proposed approach. [ABSTRACT FROM PUBLISHER]

The economic and reliability benefits of adding a wind energy conversion system (WECS) to a power system are highly dependent on the wind turbine generator (WTG) installation design, i.e., the type and number of WTG. This paper presents an approach to determine the optimum installation design at each wind site considering the WTG parameters, the total cost of WECS and the power system reliability performance. The model is formulated as a combinatorial constrained optimization problem with a nonlinear, nondifferentiable objective function, which consists of the capital, maintenance and operating costs, and the costumer interruption costs. A number of constraints, including the total installed capacity at a specific wind site and the capital cost, are considered in the model. The model is solved using a genetic algorithm with adaptive crossover and mutation probabilities based on the standard deviation of chromosome fitness in a generation population. The proposed model and algorithm are tested on two power systems. The results show that the proposed approach can be used to obtain the maximum economic and reliability benefits associated with a WECS installation and is a powerful search technique for determining the optimum number and type of WTG considering reliability performance and costs. [ABSTRACT FROM PUBLISHER]