In this paper, robust unit commitment with defensive viewpoint and probability model of plants inaccessibility have been surveyed. From strategic and military viewpoint, due to the possibility of a military attack, the electrical energy operation depends on arrangements codification and utilization of effective planning in the production part. In a sample power network, because of the variable possibility of attack, some plants have different probability of inaccessibility. Thus, technique of identification and weight assignment has been employed to find sensitive power plants. In the proposed scheme, random contingencies, including sudden unit outage due to military attacks have been considered with scenarios taking into account the probability of their occurrence. In this paper, probability values of plants inaccessibility have been extracted by presenting a comprehensive model. The proposed method has been implemented on IEEE standard 30 bus system. Comparative analysis results indicate that to reach a secure plan, preserving an optimal production level from power plants to maintain feeding continuity is inevitable.
Ghaffarpour, R., Hashemi, Y., & Ehsan, M. (2019). Involving Defensive Approach in Unit Commitment Scheduling and Presenting Probability Model of Plants Inaccessibility. Journal of Advanced Defense Science & Technology, 5(4), 231-246.
MLA
Reza Ghaffarpour; Yashar Hashemi; Mahdi Ehsan. "Involving Defensive Approach in Unit Commitment Scheduling and Presenting Probability Model of Plants Inaccessibility". Journal of Advanced Defense Science & Technology, 5, 4, 2019, 231-246.
HARVARD
Ghaffarpour, R., Hashemi, Y., Ehsan, M. (2019). 'Involving Defensive Approach in Unit Commitment Scheduling and Presenting Probability Model of Plants Inaccessibility', Journal of Advanced Defense Science & Technology, 5(4), pp. 231-246.
VANCOUVER
Ghaffarpour, R., Hashemi, Y., Ehsan, M. Involving Defensive Approach in Unit Commitment Scheduling and Presenting Probability Model of Plants Inaccessibility. Journal of Advanced Defense Science & Technology, 2019; 5(4): 231-246.
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