In power systems

in order to optimize the spinning reserve (SR)

a trade-off between reliability and economy objectives is always needed. The methods and indices of traditional reliability assessment based on overall averages regard high-damage/low-probability events as commensurate with low-damage/high probability events

making it impossible to reflect the risk preference and the range of damages the decision-makers might particularly concern about; nor is it possible to reflect the sensitivity of SR configuration to the catastrophic generation deficits. This paper introduces conditional reliability assessment methods and indices

then develops a conditional cost/benefit analytic model

and optimizes the SR within the risk range of the decision-makers’ concern. Firstly

a time-decoupled unit commitment (UC) is made hour by hour to determine the operating cost and dispatch schedule. Secondly

state sampling of the online units is made to calculate the conditional reliability costs. Then the conditional optimal SR capacity making the conditional total cost minimum in the said hour is found. Finally

the reserve is allocated to each unit by a UC with complete constraints. The case study shows that decision-makers’ risk preferences have significant influence on the optimal SR: with the damage range concerned transferred from overall average to extreme adverse situations

the SR demand continually increases─so much so that it may even go beyond the supply ability of the current installed capacity.