Optimal Loss of Load Expectation for Generation Expansion Planning Considering Fuel Unavailability

Radhanon Diewvilai and Kulyos Audomvongseree ()
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Radhanon Diewvilai: Department of Electrical Engineering, Chulalongkorn University, Bangkok 10330, Thailand
Kulyos Audomvongseree: Department of Electrical Engineering, Chulalongkorn University, Bangkok 10330, Thailand

Energies, 2022, vol. 15, issue 21, 1-17

Abstract: In generation expansion planning, reliability level is the key criterion to ensure enough generation above peak demand in case there are any generation outages. This reliability criterion must be appropriately optimized to provide a reliable generation system with a minimum generation cost. Currently, a method to determine an optimal reliability criterion is mainly focused on reserve margin, an accustomed criterion used by several generation utilities. However, Loss of Load Expectation (LOLE) is a more suitable reliability criterion for a generation system with a high proportion of renewable energy since it considers both the probabilistic characteristics of the generation system and the entire load’s profile. Moreover, it is also correlated with the reserve margin. Considering the current fuel supply situation, a probabilistic model based on Bayes’ Theorem is also proposed to incorporate fuel supply unavailability into the probabilistic criterion. This paper proposes a method for determining the optimal LOLE along with a model that incorporates fuel supply unavailability into consideration. This method is tested with Thailand’s Power Development Plan 2018 revision 1 to demonstrate numerical examples. It is found that the optimal LOLE of the test system is 0.7 day/year, or shifted to 0.55 day/year in the case of considering the fuel supply unavailability.

Keywords: generation expansion planning; reliability criterion; loss of load expectation; reserve margin; fuel unavailability (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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