Large-scale renewable energy generation connected to the grid requires support from system reserve capacity with immediate response of all grades. Wise allocation of instant spinning-grade reserve on the generation and demand side becomes a vital mission to balance the reliability and economy of power system. The core task of a market which encourages non-free use of reserve capacity is to purchase proper reserve capacity and reduce the total cost of the system by satisfying dispatch needs of all potential risk scenarios. To achieve this

the reserve values of every available reserve measure(RM)under all risk scenarios are estimated

and RMs or their combinations with high performance cost ratio are selected. Three series articles present a novel way to model and solve the multi-grade reserve optimization problem considering variant scenarios. As the first article in the series

on the basis of analyzing existing reserve optimization methods

a cost-performance ratio based spinning-grade reserve optimization method is proposed. Using the exhaustively searching method as the benchmark

the effectiveness of the proposed method is verified by comparing with the mixed-integer linear programming method. Simulation cases on systems with different scales also give the general picture about the efficiency and accuracy of the proposed method relative to its main competitors.