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Reliability based computational model for stochastic unit commitment of a bulk power system integrated with volatile wind power

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  • Jain, Tanmay
  • Verma, Kusum

Abstract

Reliable and economic operation of transmission systems is one of the most onerous problems faced by the grid operators as a penetration rate of wind energy is on rise. It is a crucial carbon-free source and alleviates dependency upon the conventional resources, though its stochastic and unpredictable nature can cause the risk of random component failures. Therefore, reliability evaluation of the system under wind power is of paramount importance and is suggested as the proposed study. A Reliability based Stochastic Unit Commitment (RSUC) model is proposed for a bulk power system integrated with volatile wind power. It is formulated using Mixed Integer Linear problem considering networks and spinning reserve constraints. The volatility of wind speed is modeled by generating different scenarios using K-means clustering approach with computation of correlation among them using autocorrelation factor and their transition probabilities is proposed using Markov Chain (MC). Further, the system's reliability is evaluated using Loss of Load Probability (LOLP) and Expected Energy Not Supplied (EENS). The proposed approach is investigated on the IEEE 24 Reliability Test System (RTS) under the various overloading and random component outage conditions. Further, its results effectiveness is compared and validated with the other existing approaches.

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  • Jain, Tanmay & Verma, Kusum, 2024. "Reliability based computational model for stochastic unit commitment of a bulk power system integrated with volatile wind power," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
  • Handle: RePEc:eee:reensy:v:244:y:2024:i:c:s0951832024000243
    DOI: 10.1016/j.ress.2024.109949
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    1. Zou, Yanhua & ÄŒepin, Marko, 2024. "Loss of load probability for power systems based on renewable sources," Reliability Engineering and System Safety, Elsevier, vol. 247(C).

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