Impacts of incorporating distributed generation (DG) to the reliability of electric distribution network using Monte Carlo simulation (MCS)
Ahmad Zairi Mohd Zain, Mohd Ikhwan Muhammad Ridzuan, N. Z. M. Ali
Abstract
Ahmad Zairi Mohd Zain, Mohd Ikhwan Muhammad Ridzuan, N. Z. M. Ali
Abstract
Reliability evaluation is one of the primary techniques for assessing the stability of the distribution network. Placement of distributed generation (DG) into the network provide a significant impact on reliability performance. Commonly, more research focuses on voltage and power loss-based placement rather than reliability-based. Therefore, this paper presents the impact of the placement of two different DG size scenarios based on reliability effectiveness. IEEE-30 bus system will be used to simulate the reliability of the network. Monte Carlo Simulation (MCS) will be implemented to determine customer-related as well as system reliability performance. Based on the output of the simulation, the values of the reliability indices (SAIFI, SAIDI and CAIDI) give a different result between scenarios as impact of the placement of DG to the network.
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Reliability evaluation is one of the primary techniques for assessing the stability of the distribution network. Placement of distributed generation (DG) into the network provide a significant impact on reliability performance. Commonly, more research focuses on voltage and power loss-based placement rather than reliability-based. Therefore, this paper presents the impact of the placement of two different DG size scenarios based on reliability effectiveness. IEEE-30 bus system will be used to simulate the reliability of the network. Monte Carlo Simulation (MCS) will be implemented to determine customer-related as well as system reliability performance. Based on the output of the simulation, the values of the reliability indices (SAIFI, SAIDI and CAIDI) give a different result between scenarios as impact of the placement of DG to the network.
Key concepts: Reliability (semiconductor), Monte Carlo method, Reliability engineering, Computer science, Electric power system, Power (physics), Engineering, Mathematics