This paper presents the analysis of power supply restoration time after failures occurring in power lines. It found that the power supply restoration time depends on several constituents, such as the time for obtaining information on failures, the time for information recognition, the time to repair failures, and the time for connection harmonization. All these constituents have been considered more specifically. The main constituents’ results values of the power supply restoration time were analyzed for the electrical networks of regional power supply company “Oreolenergo”, a branch of Interregional Distribution Grid Company (IDGC) of Center. The Delphi method was used for determining the time for obtaining information on failures as well as the time for information recognition. The method of mathematical statistics was used to determine the repair time. The determined power supply restoration time (5.28 h) is similar to statistical values of the examined power supply company (the deviation was equal to 9.9%). The technical means of electrical network automation capable of the reduction of the power supply restoration time have also been found. These means were classified according to the time intervals they shorten.

https://www.mdpi.com/1996-1073/13/11/2736/pdf

Analysis of the Power Supply Restoration Time after Failures in Power Transmission Lines

The Role of Virtual Synchronous Machines in Future Power Systems: A Review and Future Trends

Despite the fact that tremendous efforts have been placed to avoid outages on power system networks, forced outages can occur as a result of catastrophic event, device error, operator fault and cyber threats. These outages, when occur, can lead to partial or complete blackout. The effects of the blackout are national safety, financial losses, system reliability reduction, and threaten personnel. To minimise such impacts of the blackouts, it is essential to utilise the available black-start units to restore power system to normal condition with minimum restoration time. In this paper a black start modelling and simulation study is accomplished, using real data from Benghazi North Power Plant (BNPP), to validate the feasibility of a black start plan in terms of both steady state and transient operating conditions. It is found that selection of the optimum size of the black start depends on the capacity of the largest motor during starting, the capacitive charging reactance of the connected cable or transmission line as well as the size and vector group of the transformers.

A Case Study on Black Start Capability Assessment

Black Start Operation using a MMC based HVDC system

AC/DC hybrid micro-grid combines the advantages of DC and AC micro-grids, and it is one of the future development directions for micro-grid. Five kinds of typical structures of AC/DC hybrid grid are introduced, and the functions and characteristics of those structures are analyzed. Considering the influence of micro-grid structure on the power supply reliability, three kinds of AC/DC hybrid power grid reliability evaluation methods are established, which are the Minimal Path Method, the Convolution Method and the Monte-Carlo Simulation Method. The reliability of five typical structures is analyzed and compared by using three kinds of reliability evaluation methods.

https://google.iopscience.iop.org/article/10.1088/1757-899X/394/4/042086/pdf

Research on Reliability Evaluation Method of AC/DC Hybrid Micro-Grid

The reliability of an electric supply system has been defined as the probability of providing the users with continuous service of satisfactory quality. Generation system reliability indices have been used as a standard for measuring system reliability. Therefore, it becomes essential to predict how these indices vary as system annual peak increases. In this paper, a convolution algorithm has been used to build a risk model by convoluting the load model and the capacity model. The constructed model has been used to calculate the reliability indices of Benghazi North Power Plant (BNPP) using data of one year period (stage I). The same model has been used to determine these indices values after some capacity has been installed (stage II). Testing this model using data from two year period show that the suggested method is effective in calculating the reliability indices and predicting the required installed capacity.

Salem Shuaib

Papers

A Case Study on Black Start Capability Assessment

Generation system reliability evaluation based on convolution algorithm and data modeling