A fuzzy-based power system reliability evaluation

Power system is one of the most complex systems ever designed. Determining its reliability is therefore a demanding process, which is mostly dealt with in a way that partial problems are stated and solved. A reliability method of loss of load expectation is selected and improved and the model of conventional power system is considered as a standpoint. Reliability of the initial conventional power system is evaluated. Then, the conventional power system is changed, where one conventional power plant is abandoned and new wind power plants stand to its place. The reliability of the initial and the changed power system is calculated and compared. Discussion shows the problems of decreased reliability of the power system with increasing the percentage of wind power plants within the power system replacing conventional plants, if not enough reserve is added to the power system at the same time. The other related problems are discussed in addition, to show that the problem is very complex and one cannot only consider a limited number of influencing parameters when deciding on power system configurations.

With the integration of large scale wind power, the characteristics of power system operation has been changing, and, some problems come forth. On-line security assessment and control decision support system provides the stability and security state message for dispatcher in time, and, some suggestions to improve the level of power system stability and security. To suit the requirements of large amount wind power integrated power system, the technology of on-line security assessment and control decision support must be modified. This paper focuses on the technology of on-line security assessment and control decision for operation of power system with large scale wind power and designing the support system. In the paper, the study and application of on-line security assessment and control decision support technology in China are introduced. Considering the wind power in China having some distinct characteristics such as large scale, centralized development, long-distance and high voltage transportation, the new requirements to on-line security assessment and control decision support are analyzed. They includes need for new information, on-line modelling with large scale wind farm, transfer limitation calculation under the constraint condition of wind power integration requirement, auxiliary preventive control decision based on the forecasting and adjustment properties of wind power output, coordinated emergency control wind power with hydraulic and thermal power. On the basis of technical rule for connecting wind farm into power grid and the interaction between wind power and power grid, the advices on engineering application of on-line security assessment and control decision support technology for large amount wind power integrated power system, are proposed, for example, with respect to the standard of security assessment and selection of pre-contingency sets. (7 pages)

On-line steady-state security assessment of power systems

Introduction. The assessment of the reliability and cost of complex systems, such as Complex Bridge Systems (CBS) and Life Support Systems in Space Capsules (LSSSC), is fascinating. To achieve the ideal system design through diverse constraints and increase overall system reliability, researchers have extensively explored system reliability and cost optimization problems. Hence, the significant advancement in metaheuristic methods is the primary source of further system reliability and cost optimization process refinement.
 Aim and tasks. This research attempts to enhance the reliability and cost of complex systems named CBC and LSSSC has been presented. 
 Results. The structure is based on few recent metaheuristic techniques, such as Moth Flame Optimization (MFO), Whale Optimization Algorithm (WOA), Gazelle Optimization Algorithm (GOA), Dragonfly Algorithm (DA), and Coati Optimization Algorithm (COA). Comparing the acquired findings to those found in other proposed techniques demonstrates the usefulness of a methodology based on COA. The proposed COA algorithm exhibits enhanced efficiency by offering superior solutions to reliability and cost-optimization problems. In addition, a non-parametric Friedman ranking was performed for validation. The results of this research are based on improving the reliability of the parameters and decreasing complex systems’ costs used by the five metaheuristic methods. Observing the convergence graph, Friedman ranking, statistical results test, and tables determined that COA is the most effective algorithm for a complex system’s cost and reliability parameters compared to other existing approaches, and also provided a faster solution.
 Conclusions. This study proposes unique ways to reduce costs while increasing parameter reliability in complex systems. After analysing the comparative solution, the authors found that when comparing these approaches (GOA, DA, MFO, WOA, and COA), the COA provided the best minimum solution for the cost and reliability of complex systems. Hence, the suggested COA procedure was more successful than that described in this study.

Reliability and economic evaluation of power system with renewables: A review

In the power system of the future, reliability will play an important role. This reliability is influenced by different developments like the increase in electricity consumption and the use of renewable and distributed generation. It is important to have a good insight into the reliability performance of the system. With probabilistic methods, the reliability of the power system can be analyzed and decisions can be made to maintain the high reliability level that we demand. This paper gives an overview of the different developments in power systems and describes how these developments influence the reliability of the future power system. The possibilities to implement these developments into the probabilistic reliability analysis in network planning and operational planning are discussed. By use of an example, the possibilities and challenges of probabilistic methods in operational planning are illustrated.

The reliability of power system will obviously be influenced by wind farms connected because of the volatility of wind power. With the increase of wind power penetration, it's necessary to research the influence of wind power integration on the reliability level of system and how much reserve capacity should we increase in order to stabilize the influence of wind power on power system reliability. In this paper a reliability evaluation model is built by Monte Carlo method and also a reserve optimization model, which can be used to analyze changes of system reliability in conditions of different grid-connected wind farms, and to find out the optimum of system reserve to achieve unifying the maximum utilization of new energy and meanwhile high reliability of power system.

Reliability measures how well a system can be expected to perform its intended purpose; it is expressed as a probability function with time and environment as variables. This paper discusses the mechanics of component failure and repair and shows that power system behavior follows a Markov process. The reliability of simple system configurations is evaluated analytically by solving the Markov equations. The reliability of complex systems is more easily evaluated by the use of digital computer simulation. The simulation method is described.

Three-parameter interval number theory and its application in power system reliability evaluation

In order to ensure the reliability and security of electric power system, the faults must be removed exactly and quickly. The fault location method is one of key issues for the researches of electric power system. Extracting fault feature information from large amount of synchronized data will be a new challenge for locating of faulted components or faulted area. Multivariate analysis theory is superior in reducing dimensions and simplifying data structure featured without key information loss. In this paper, according to multivariate analysis theory, the reliability and security of complex power system has been accomplished.

Uncertainty parameters of battery energy storage integrated grid and their modeling approaches: A review and future research directions

Large-scale adoption of gas-fired power plants (GPPs) significantly accelerates the integration of power systems and natural gas systems (NGSs). Because the operation of NGS has a significant impact on the reliability of power system, it is important to simultaneously evaluate the reliabilities of power system and NGS. Moreover, due to the stochastic failures and various operating characteristics of components, the integrated gas and power systems (IGPS) considering multiple states can be viewed as a multi-state system. Therefore, a multi-state model is proposed for reliability evaluation of IGPS based on universal generating function (UGF) techniques. First, a framework is proposed to evaluate the reliability of NGS: multi-state models for different components in the NGS are developed as the corresponding UGFs. These UGFs are aggregated utilizing the gas flow calculation operator to obtain the multi-state model of NGS. Moreover, a gas-to-power calculation operator is developed to convert the multi-state model of gas injection at each node to the power output models of GPPs in power system. In this manner, the impacts of NGS could be incorporated into the reliability evaluation of power system. Furthermore, nodal reliability indices for both the NGS and the power system are proposed to evaluate the reliability performances of IGPS. The proposed methods are validated using the integrated gas and power test system.

Small power systems such as those found on offshore platforms are fragile; yet, they must operate reliably for economy and safety for personnel and the environment. These systems often include combustion turbine generators for main process power requirements and black-start diesel generators that can supply essential and emergency buses and be used to restart the main generation in the event of a power system collapse. The power distribution systems on these offshore platforms have built-in redundancy with multiple circuits to supply critical loads for fault tolerance and operating flexibility. A system to easily and safely synchronize islanded buses via many possible synchronization points can revolutionize the operational flexibility and therefore the safety and reliability of the power system. This paper reports on advanced synchronizing systems installed on two offshore platforms.

Ensuring the provision of high-quality and dependable power supply to customers stands as a paramount responsibility within the realm of power systems. The concept of restructuring the power system emerges as an efficient approach to deliver economically viable and uninterrupted power supply. The assessment of power system reliability hinges on various factors, with the reliability index serving as a pivotal metric, dependent on both system security and adequacy. To enhance the reliability index, strategically locating FACTS devices becomes essential, a task facilitated through power flow analysis with specified constraints, pinpointing the weakest points through Genetic Algorithm-driven fast-acting device placement. The correlation between DG establishment and the reliability index was meticulously calculated, further bolstered by the introduction of a Derated Forced Outage Rate for enhanced performance assessment. In the pursuit of heightened power system reliability, sequential simulations prove invaluable, particularly in minimizing Expected Energy Not Supplied (EENS) and improving overall system reliability. The results obtained through sequential simulations underscore the effectiveness of this approach within bulk electrical systems. The installation of multiple FACTS devices in the system's weakest areas facilitated EENS computation, coupled with the assessment of related reliability indices such as system frequency and system duration. This approach not only enhances system reliability but also promotes the economic operation of both transmission and distribution.The simulation results substantiate the alignment of power system reliability objectives in deregulated power systems with the required standards, advocating for the restructuring of power networks. The reliability assessments, driven by the optimal placement of DGs and FACTS devices, reveal substantial improvements in system reliability, underscoring the pivotal role of these technologies in enhancing overall power system dependability.

This work deals with assessing the reliability of wind energy sources incorporated into a microgrid system to increase grid stability. As the share of power generated from wind energy continues to increase due to environmental concerns and to reduce carbon footprints, the case study proposed is designing an effective wind energy system for a smart building environment to reduce the burden on the grid. Incorporating wind energy systems into grid-connected buildings increases the reliability of the microgrid system for smart building environments. Applying smart techniques with integrated automation in the built environment can play a key role in decreasing peak demand for load development in smart cities. This can also enhance the overall efficiency of power grids, reduce waste, and enable the effective use of energy resources. Furthermore, researchers are finding new ways to collect energy from renewable sources and power-built environments due to dwindling fossil fuel resources and increased environmental awareness. The analysis of wind-connected power systems has been initiated to satisfy the increasing demand for reliable supply systems by consumers. This has prompted the use of wind energy systems with controlled techniques to enhance the reliability of power systems and reduce carbon footprints generated by fossil fuel-based power systems. Therefore, the main purpose of this work is to understand the economic prospects of wind energy sources for smart building environments, reliability analysis of wind energy sources-based power systems, reduce carbon footprints, and balance power demand through wind energy systems. The Progressive Wind Model Taylor-Sequence Proliferation (PWMTSP) and Innovative Six Parameters Based Progressive Beta Creative Model (ISPBPBCM) approaches are proposed to understand the reliability of wind energy-based power systems in smart building environments. The work also provides an economic analysis of the proposed low-cost wind power system with different capacities for residential consumers in selected geographic location. Eight cases are considered for the proposed effective wind energy system for smart building environments ranging from 2 MW to 32 MW. Hence, the economic analysis of the proposed systems is discussed for residential users. All eight cases are eco-friendly and reduce carbon emissions as these generated units from wind energy sources need not be purchased from fossil fuel-based plants, which increases the reliability of the proposed system. The expected energy not supplied (EENS) in the planned work increases as wind power capacity increases. Loss of load expectation (LOLE), loss of load probability (LOLP), and failure rate all decrease with the installation of more wind power systems. Moreover, it can be seen that mean time to repair (MTTR) improves when wind energy capacity rises incrementally from 2 MW to 32 MW. The proposed method is anticipated to be adaptable to various types of wind energy systems where dependability is a crucial component of system design and scalable to large wind integrated power systems.