| Summary: | 碩士 === 國立中興大學 === 應用經濟學系所 === 102 === This article aims at looking from the residential users’ perspective. It simulates seven electricity rate programs pertaining to time-of-use rate or non-time-of-use rate, utilizing Participant Cost Test (PCT) to assess those residential customers’ programs and the cost-benefit analysis. The costs and the discount rate of the smart meter are also artificially varied in this study for sensitive analysis. For each of the tariff programs, the electricity expenditure for the users are compared and shows the following results: those users selecting the present two-tier time-of-use rate program has the highest expenditures, followed by the two-tier time-of-use rate scheme A-1. Those with the lowest expenditures were those who chose the Real-Time Pricing program. When those who have taken the Participant Cost Test for the cost-benefit analysis, taking the existing non-time-of-use program as a benchmark, most of the ratio are less than 1, only the userU1 in a summer month and userU5 selecting the Real-Time Pricing have passed the PCT test. Using the present two-tier time-of-use rate scheme as a benchmark: the cost benefit ratio is highest for Real-Time Pricing, followed by Two-tier Time-of-Use, Three-tier Time-of-Use and the Two-tire Time-of-Use A-1.
The cost of the smart meter and the discount rate for sensitive analysis. With existing non-time-of-use rate program as a benchmark and the discount rate with different scenarios, most users’ cost benefit ratio cannot pass the PCT test. Only user U1 in a summer month and user U5 choosing Real-Time Pricing with smart meters costing betweenNT$3000 to NT$6000, then the cost benefit ratio will be greater than1. Taking the present two-tier time-of-use rate program as a benchmark, when the smart meter costs between NT$3000 to NT$9000, the ratio for the majority of users will be greater than 1, thus passing the Participant Cost Test. However, when the smart meter reaches NT$15000, then most users benefit cost ratio will plummet to less than 1. This implies that the cost of the smart meter does matter to the adoption willingness of the demand-side management programs for residential users.
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