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Reliability Assessment of a Power System Incorporating Wind and Solar Farms
https://orcid.org/http://orcid.org/0000-0003-3643-4524
Reliability of electrical supply is one of the most important factors to be maintained in the supply demand chain of electrical energy. In this paper, reliability indices are evaluated using probabilistic approach that is based on probability theory that considers the likeliness of occurrence of an event. This approach considers stochastic nature of the scheme, demand or failure of the components, and the solution is based on the similarity of the available data. The reliability assessment is based on the evaluation of the reliability indices, namely Loss of Load Expectation, Loss of Energy Expectation and Energy Index Reliability, are evaluated for a power system with and without integration of renewable sources (wind and solar) and generation indicated by Capacity Outage Probability Table. In this paper, the effect of peak demand on the system’s reliability in the presence of renewable energy sources is determined. The reliability indices are found using MATLAB R2017a, and it is observed that incorporating non-conventional sources into the existing power system improves system's reliability.
Reliability Assessment of a Power System Incorporating Wind and Solar Farms
https://orcid.org/http://orcid.org/0000-0003-3643-4524
Reliability of electrical supply is one of the most important factors to be maintained in the supply demand chain of electrical energy. In this paper, reliability indices are evaluated using probabilistic approach that is based on probability theory that considers the likeliness of occurrence of an event. This approach considers stochastic nature of the scheme, demand or failure of the components, and the solution is based on the similarity of the available data. The reliability assessment is based on the evaluation of the reliability indices, namely Loss of Load Expectation, Loss of Energy Expectation and Energy Index Reliability, are evaluated for a power system with and without integration of renewable sources (wind and solar) and generation indicated by Capacity Outage Probability Table. In this paper, the effect of peak demand on the system’s reliability in the presence of renewable energy sources is determined. The reliability indices are found using MATLAB R2017a, and it is observed that incorporating non-conventional sources into the existing power system improves system's reliability.
Reliability Assessment of a Power System Incorporating Wind and Solar Farms
https://orcid.org/http://orcid.org/0000-0003-3643-4524
Reliability of electrical supply is one of the most important factors to be maintained in the supply demand chain of electrical energy. In this paper, reliability indices are evaluated using probabilistic approach that is based on probability theory that considers the likeliness of occurrence of an event. This approach considers stochastic nature of the scheme, demand or failure of the components, and the solution is based on the similarity of the available data. The reliability assessment is based on the evaluation of the reliability indices, namely Loss of Load Expectation, Loss of Energy Expectation and Energy Index Reliability, are evaluated for a power system with and without integration of renewable sources (wind and solar) and generation indicated by Capacity Outage Probability Table. In this paper, the effect of peak demand on the system’s reliability in the presence of renewable energy sources is determined. The reliability indices are found using MATLAB R2017a, and it is observed that incorporating non-conventional sources into the existing power system improves system's reliability.
Reliability Assessment of a Power System Incorporating Wind and Solar Farms
J. Inst. Eng. India Ser. B
Ballireddy, Tulasi Ramakrishna Rao (author) / Ray, Papia (author)
Journal of The Institution of Engineers (India): Series B ; 105 ; 165-174
2024-02-01
10 pages
Article (Journal)
Electronic Resource
English
Reliability Assessment of a Power System Incorporating Wind and Solar Farms
| Springer Verlag | 2024
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| DOAJ | 2013