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Equipment maintenance decision is a very critical technology in power grid asset management. The traditional maintenance decision focuses on the analysis of the operation performance of the equipment itself, but lacks the analysis and description of the fuzziness of power equipment outage parameters. Therefore, this paper establishes the reliability assessment model based on equipment health condition monitoring, which makes the maintenance decision transition from equipment level to system level, and the fuzzy mathematics theory is introduced to establish a model describing the fuzziness of equipment failure rate parameter to make system reliability assessment and equipment maintenance decision scheme. Firstly, this paper proposes a fuzzy failure rate model of power transformer based on condition monitoring. Then the fuzzy parameters are combined with the conventional probabilistic reliability assessment method to establish the fuzzy probability hybrid reliability assessment model of the transmission system, and the fuzzy maintenance reliability benefit index is defined and deduced. Finally, a maintenance strategy of transformer based on fuzzy probability hybrid reliability assessment and fuzzy set theory is proposed, and the case study is carried out on a regional power grid in East China. The results show that the proposed model provides an improved maintenance strategy of power equipment. [ABSTRACT FROM AUTHOR]

This study presents a comprehensive survey on the reliability evaluation of the electrical network system. The impacts of integration of new and renewable energy sources (electric vehicle, energy storage system, solar, and wind) on the reliability of electrical power system (EPS) are discussed. The impacts of these renewable sources have merits/demerits when these sources are integrated with the conventional electric power system. However, the merits are predominant as it includes unlimited, free, and cost‐effective resources. The recent researches depict that the uncertainties of renewable energy resources leads to the probabilistic and reliability analyses of EPS. EPS includes offshore and onshore wind farms, micro‐grid, energy storage system, and other high voltage grids. It also contains the failure‐prone components related to the power systems. For the accomplishment of these aspects, the handling methods of uncertainty parameters in generation, transmission, and distribution systems are discussed. The incorporation of electric vehicles, wind energy system, and energy storage system for reliability assessment is also discussed briefly. This study also presents the scope of a new research area for the researchers on the reliability assessment of renewable energy integrated power system. [ABSTRACT FROM AUTHOR]

Natural gas, as a clean fossil energy, has been widely used in power generation system by converting chemical energy into electrical energy through gas turbines. However, the natural gas pipeline network system (NGPNS) is comprised of many equipments, and the failure of any equipment will probably cause the outage of gas turbines. Therefore, this study proposes an analytical method which can incorporate the uncertainty of NGPNS into the reliability assessment of integrated energy system. Firstly, on the basis of an analytical technique, NGPNS's operating states and the corresponding state probabilities are simulated. Secondly, a state transferring and equivalence technique is proposed for transferring the unreliability of NGPNS to the involved outage of gas turbines. Thirdly, an equivalent reliability model of gas turbine is established for taking into account the uncertainty of NGPNS. Finally, the NGPNS is connected to the Roy Billinton Test System through the coupling of gas turbines between electrical and gas networks. The results of case studies verify the correctness and effectiveness of the proposed algorithm. [ABSTRACT FROM AUTHOR]

This study aims to present an architecture for the planning of microgrids (MGs) in order to support system operator decision. In short, the proposed strategy is an iterative procedure that tries to find the optimal size of distributed energy resource (DER), which attends the necessities of stakeholders. The architecture has five distributed and correlated stages named MG coordination, MG operation optimisation, reliability assessment, contingency assessment, and searching mechanism. Since the DER selection involves multiple criteria and interests of different parts, it requires a multi‐attribute decision system providing a list of possible configurations based on their relative importance as denoted by the stakeholders. Owing to that, the particle swarm optimisation is used to create the multidimensional space of search in which the optimal solution will be selected by means of Pareto front decision criteria. As a result, the architecture provides a candidate solution to optimal size (optimal rated power) of each DER, that must be installed in the MG in order to have an optimal balance between technical, economical, social, and environmental aspects. To have realistic results, such a strategy is performed on a case study of a potential campus MG program. [ABSTRACT FROM AUTHOR]

This study aims to investigate the topology characteristic indices which have a close relationship with reliability of distribution networks via mathematical tools. First, a practical network is extracted into a topology and presented by weighted adjacency matrix associated with a failure degree matrix, which contains more significant information than that of original adjacency matrix. Second, singular value sequence and vertex/edge sharing are proposed as two similarity indices. Finally, similarity functions are applied on two cases to establish the relationship with reliability by curve fitting and clustering. optimisation strategy based on modified contingency‐load‐loss index is elaborated to improve the reliability and guide to distribution network planning. [ABSTRACT FROM AUTHOR]

For the reliability assessment of a distribution system with microgrids (MGs), considerable computation time has to be cost to ensure convergence of an applied Monte‐Carlo method (MCM) to estimating indices of interest, in the context of adopting multi‐state models of constituent components. Towards achieving an efficient and accurate reliability assessment as much as possible, multi‐state models of distributed generation resources, especially the battery energy storage system, are proposed. Based on the proposed models, effect analysis of a given sampled MG state is conducted in a proposed analytical manner. Moreover, an accelerated MCM nesting the proposed effect analysis methodology is also presented, dedicated to reliability evaluation of a resulting multi‐state distribution system from the multi‐state constituent components. Case studies on a modified IEEE‐RBTS Bus6 F4 system demonstrate the effectiveness of the proposed method, against the plain MCM. In addition, impact of an important parameter, termed total state number of state‐of‐charge, on the convergence and speed of the proposed method has been fully analysed. [ABSTRACT FROM AUTHOR]

This study proposes a novel dynamic reliability network‐equivalent approach (RNEA) for distribution generations (DGs) enhanced distribution system. This method includes a bottom‐up process and a top‐down process, which are developed based on equivalent principle, and the synthesis of both processes yields the reliability performance of any node in the system. In addition, a novel switch zone concept is defined and introduced into the bottom‐up equivalent process as to save the computation cost. Besides, a hybrid restoration model is proposed to account for the practical restoration process in power grids, and solved using particle swarm optimisation. The most significant of the proposed approach over other equivalent methods such as section technique, RNEA, and zone‐branch method is that it provides a more generalised element‐by‐element equivalent approach that can greatly simplify the network for reliability assessment irrespective of the network topology. The proposed methodology has been successfully tested on a real 362‐node urban distribution system in China, with and without DGs considered. [ABSTRACT FROM AUTHOR]

Owing to the increasing electricity load demand on one hand and in order to have a reliable electric network on the other hand, constructions of new transmission lines and generation sources are extremely essential. Such expansions, however, raise the fault current level which can even exceed the maximum short‐circuit level rating of the circuit breakers (CBs). High fault current, in addition to the adverse effect on the CB function, can damage other substation equipment suddenly or over the time. To this end, severity of the fault current is a key factor in the substation reliability assessment. In this context, fault current limiters (FCLs) which are employed to decline the fault current level need to be precisely modelled and their impact should be extensively studied. In this study, the effect of FCL on the failure rate of substation equipment is first investigated. A computational technique for assessing the substation reliability is accordingly devised. As the location of FCL installation in a given substation or in substations with different arrangements would not be the same, various credible configurations are incorporated here. The results show that from the perspective of reliability indices, double‐bus double‐breaker and one breaker and a half configurations are more suitable for FCL installation. [ABSTRACT FROM AUTHOR]

This study presents a mixed‐integer second‐order conic programming (MISOCP) model for the robust reconfiguration of electrical distribution systems, considering the minimisation of active power losses and reliability constraints. The uncertainty at the reliability data is considered by using a linear and adjustable robust approach. The indices used to evaluate the reliability of the system are the system average interruption frequency index (SAIFI) and the system average interruption duration index (SAIDI), both of which are calculated as functions of the switch status (open or closed). Under radiality constraints, the solution generated by the proposed model is robust in terms of the reliability, i.e. the SADI and SAIFI limits imposed by regulators are not violated even if the uncertain data changes stochastically. The use of an MISOCP model guarantees convergence to optimality by using existing convex optimisation solvers. To evaluate the robustness of each solution generated by the proposed model, a set of Monte Carlo simulations were deployed. Finally, all tests were executed in a 136‐node real distribution system. [ABSTRACT FROM AUTHOR]

Future grids will be operated much closer to their security limits due to the ever increasing power demands and the restrictions on land and space to build more transmission corridors. As one of the many smart grid technologies, the dynamic thermal rating (DTR) system of transmission lines offers the solution to increase line current capacity without infringing the conductor's maximum operating temperature. Hence, it has emerged as a popular solution for the aforementioned challenges. Owing to that, there is a strong need to assess the integrity of this technology. For this reason, this study presents a systematic framework for assessing the reliability and the risk of a DTR system. The research was carried out in two parts and is able to optimise the risk and the reliability (cost) of the DTR system. In addition, a weather estimation model is proposed to estimate the weather data when the DTR sensors are not functional. This is contrary to the existing literature which suggests that conservative assumptions be made. The results show that the proposed weather estimation model avoids overestimation of the DTR system risk. [ABSTRACT FROM AUTHOR]

In the future, energy framework of European Union and other countries, renewable energy plays an important role tackling the problems of the climate change and security of energy supply. The high penetration of renewable energy sources will increase the burden of system operator for maintaining system reliabilities. However, the current strategy of reliability management developed for conventional power systems and existing electricity market design may not cope with the future challenges the power system faces. The development of smart grid will enable power system scheduling and the electricity market to operate in a shorter time horizon for better integrating renewable energy sources into power systems. This study presents an electricity market scheme including a multi‐period energy and reserve pre‐dispatch model and an energy re‐dispatch model for real time operation, respectively. The multi‐period energy and reserve pre‐dispatch model is formulated using the multi‐period optimal power flow technique. During the real time operation, the energy re‐dispatch model is used for contingency management and providing balancing services. The proposed market scheme coupled with a contingency analysis methodology has been used to evaluate both real‐time electricity price risk and short term reliabilities during the operational hour in the new environment. [ABSTRACT FROM AUTHOR]

This study introduces a new theoretical interruption model for assessing more accurately the moment in time when interruptions of electricity customers are likely to occur. Recordings of short and long interruptions from two power supply systems are analysed and the similarity between their patterns is identified and then used to introduce a general interruption probability distribution model, defined in stages as multi‐zone theoretical curves. The effectiveness of the proposed theoretical interruption model is firstly verified for a basic test system supplying an aggregate load point whose power profiles (residential, commercial, industrial and mixed load) are engaged in assessing the energy not supplied, and afterwards for a typical UK power supply system consisting of about 15 000 electricity customers. The results show that a correct representation of the moment of interruption performed with the proposed model leads to completely different results than those obtained based on the conventional assumption that the time when interruption occurs is given by a known probability distribution. Moreover, comparisons against reported figures of reliability indices determine the most suitable probability distribution that shall be used to model the initial conditions of the Monte Carlo simulation and accompany the proposed theoretical model throughout the simulation process. [ABSTRACT FROM AUTHOR]