Smart tariffs, as incentives to trigger DSR, play a critical role in the energy sector to exploit the huge resources from the customer side. Load shifting in response to appropriate pricing signals could produce energy cost savings and network investment deferral in addition to other benefits. This chapter investigates smart tariff design enabled by smart metering platform and its application to end customers. The variable ToU tariffs are designed based on energy price variations, which are then scaled to include network transportation costs. In detail, RTP tariffs are developed based on annual energy price variations, where two novel approaches are proposed to convert the tariffs into ToU tariffs. The two new approaches are equal interval grouping and hierarchical clustering. The developed tariffs by both approaches are for eight scenarios/days, i.e. weekdays and weekends in four seasons, to reflect the tariff diversity throughout a calendar year. The DSR to these tariffs are therefore able to reduce energy cost by moving part of energy consumption from periods with expensive energy, where demand is met by expensive generation units.

Chapter Contents:

• 4.1 Introduction
• 4.2 Electricity tariff review
• 4.2.1 Current energy tariff products
• 4.2.2 Variable electricity tariffs
• 4.2.2.1 ToU tariff
• 4.2.2.2 Critical peak pricing tariff
• 4.2.2.3 Real-time pricing tariff
• 4.2.2.4 Direct load control tariff
• 4.3 Variable ToU tariff design
• 4.3.1 Introduction
• 4.3.2 Rationale of proposed tariff design
• 4.3.2.1 Characteristics of energy price variation
• 4.3.2.2 Proposed ToU tariff pattern formation
• 4.3.2.3 Typical energy price variations
• 4.3.2.4 Determination of RTP tariffs
• 4.3.3 ToU tariff design by equal interval grouping
• 4.3.3.1 Determination of ToU time windows
• 4.3.3.2 Determination of ToU rates
• 4.3.4 ToU tariff development by hierarchical clustering
• 4.3.4.1 Number of price categories and time window
• 4.3.4.2 Determination of ToU rates
• 4.4 Results and discussion
• 4.4.1 Results of RTP tariffs
• 4.4.2 ToU tariffs by equal interval grouping
• 4.4.2.1 Time windows
• 4.4.2.2 Tariff rates
• 4.4.2.3 ToU tariff profiles
• 4.4.3 ToU tariffs by hierarchical clustering
• 4.4.3.1 Number of clusters
• 4.4.3.2 Time windows
• 4.4.3.3 Tariff rates
• 4.4.3.4 ToU tariff profiles
• 4.5 Impact analysis of ToU tariffs
• 4.5.1 Flexible load modelling
• 4.5.2 Impact analysis of designed ToU tariffs
• 4.5.3 Benefit quantification
• 4.5.4 Cooperation with energy storage
• 4.5.4.1 Benefit comparison with energy storage
• 4.5.4.2 Cooperation with energy storage
• 4.5.5 Case study
• 4.6 Impact of networks on tariff design
• 4.6.1 Quantification of DSR on network investment
• 4.6.2 Tariff design in response to network conditions
• 4.7 Discussion and conclusion
• 4.7.1 Discussion
• 4.7.2 Conclusion
• Bibliography

Inspec keywords: investment; tariffs; demand side management; incentive schemes; smart meters

Other keywords: pricing signals; smart metering platform; interval grouping; DSR; generation units; network transportation costs; energy sector; time of use; energy cost savings; smart tariff design; annual energy price variations; demand side response; real-time pricing; hierarchical clustering; load shifting; tariff diversity; energy consumption; network investment deferral; ToU tariffs; RTP tariffs

Subjects: Power system management, operation and economics; Power system measurement and metering