Browsing by Author "Abeygunawardane, S"

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item: Conference-Full-text
Application of novel evolutionary algorithms for analyzing the impact of integrating renewables on the adequacy of composite power systems
(IEEE, 2022-07) Amarasinghe, G; Abeygunawardane, S; Singh, C; Rathnayake, M; Adhikariwatte, V; Hemachandra, K
The adequacy evaluation of modern renewable-rich power systems tends to be a computationally challenging task due to variations of renewable power generation. Recently, more computationally efficient evolutionary algorithms and swarm intelligence-based methods are utilized for evaluating the adequacy of power systems. In this paper, the authors have proposed a wind and solar integrated composite system adequacy evaluation framework using an Evolutionary Swarm Algorithm (ESA). The system failure states which have a higher probability of occurrence are explored using the ESA to estimate the adequacy indices of the system. The wind and solar power generation are modeled using a clustering-based method considering their annual effective power output. Moreover, the correlation between the system load and renewable power generation is modeled in the adequacy evaluation framework. Using the proposed framework, several case studies are conducted on the IEEE Reliability Test System to analyze the impact of integrating renewables on the adequacy of composite systems. The results show that wind generation tends to improve system reliability than solar due to its higher availability. In addition, the equivalent capacities of wind and solar generators are found to be 125MW and 215MW against a 50MW hydro generator.
item: Conference-Full-text
A markov model based algorithm for calculating mean downtimes of distribution feeders
(IEEE, 2023-12-09) Ranawaka, S; Hewa, NW; Ranathunga, M; Abeygunawardane, S; De Silva, N; Abeysooriya, R; Adikariwattage, V; Hemachandra, K
Distribution utilities compute several reliability indices to assess the reliability performance of power systems. In reliability-based planning, these indices are computed using reliability planning models. Such models require failure rates and mean downtimes of distribution feeders as inputs. At present, there is a lack of models for calculating operational mean downtimes of distribution feeders. This paper proposes a Markov model which represents failures in a feeder and operations circumstances in fault recovery. This proposed model can efficiently calculate the operational mean downtime of a feeder, using analytical equations. An algorithm and a graphical user interface are also developed based on the proposed model, in order to integrate the proposed model with software tools. Two case studies are conducted on two selected feeders, using actual data obtained from failure and repair histories and experts’ opinion. Results of case studies show the applicability of our proposed Markov model-based algorithm to calculate mean downtimes of distribution feeders. The Markov model is validated by comparing results provided by the proposed algorithm with the results obtained using Monte Carlo simulation. The proposed Markov model-based algorithm would be very useful for utilities to calculate operational mean downtimes required for reliability-based planning models.