Abstract
Distribution network capacity and services are ideally priced according to the cost-causality principle, where customers are charged according to the extent to which they are responsible for additional network capacity. As such, optimal network pricing should be forward-looking, reflecting the long-run marginal cost of providing network services. Since network investment costs are driven by peak demand, it is imperative that tariffs are demand-based and are able to provide efficient price signals to customers. In this paper, we evaluate customer's contribution to the collective peak demand of a capacity distribution network and then calculate their fair cost share using Shapley value analysis. In light of the computational requirements of these calculations, we use a sample-based approach to approximate the Shapley value with reasonable accuracy. We then employ customer yearly load profiles in the Solar Home Electricity Data to test the efficacy of our methodology.
| Original language | English |
|---|---|
| Title of host publication | 2019 IEEE Milan PowerTech |
| Editors | Federica Foiadelli |
| Place of Publication | Piscataway NJ USA |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 1207-1212 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781538647226 |
| ISBN (Print) | 9781538647233 |
| DOIs | |
| Publication status | Published - 2019 |
| Externally published | Yes |
| Event | IEEE Milan PowerTech 2019 - Politecnico di Milano (Bovisa Campus), Milan, Italy Duration: 23 Jun 2019 → 27 Jun 2019 https://attend.ieee.org/powertech-2019/ https://ieeexplore.ieee.org/xpl/conhome/8792346/proceeding (Proceedings) |
Conference
| Conference | IEEE Milan PowerTech 2019 |
|---|---|
| Abbreviated title | PowerTech 2019 |
| Country/Territory | Italy |
| City | Milan |
| Period | 23/06/19 → 27/06/19 |
| Internet address |
Keywords
- Cooperative game theory
- Cost-causality
- Demand-based tariffs
- Network tariffs
- Optimal network pricing
- Randomised sampling
- Shapley value