IFRO Seminar: Designing Nonlinear Price Schedules for Urban Water Utilities to Balance Revenue and Conservation Goals
The IFRO seminar series in economics takes place (ususally) every last Friday of the month.
The seminar series offers an opportunity to get to know the work of colleagues within the field, to get feedback on your own papers and to enhance your professional network.
Frank Wolak, Professor at Standford University, will give two presentations:
Designing Nonlinear Price Schedules for Urban Water Utilities to Balance Revenue and Conservation Goals
- Optimal Network Tariffs for Renewable Electricity Generation
Abstract: Designing Nonlinear Price Schedules for Urban Water Utilities to Balance Revenue and Conservation Goals
This paper formulates and estimates a household-level, billing-cycle water demand model
under increasing block prices that accounts for the impact of monthly weather variation, the amount of vegetation on the household’s property, and customer-level heterogeneity in demand due to household demographics. The model utilizes US Census data on the distribution of household demographics in the utility’s service territory to recover the impact of these factors on water demand. An index of the amount of vegetation on the household’s property is obtained from NASA satellite data. The household-level demand models are used to compute the distribution of utility-level water demand and revenues for any possible price schedule. Knowledge of the structure of customer-level demand can be used by the utility to design nonlinear pricing plans that achieve competing revenue or water conservation goals, which is crucial for water utilities to manage increasingly uncertain water availability yet still remain financially viable. Knowledge of how these demands differ across customers based on observable household characteristics can allow the utility to reduce the utility-wide revenue or sales risk it faces for any pricing plan. Knowledge of how the structure of demand varies across customers can be used to design personalized (based on observable household demographic characteristics) increasing block price schedules to further reduce the risk the utility faces on a system-wide basis. For the utilities considered, knowledge of the customer-level demographics that predict demand differences across households reduces the uncertainty in the utility’s systemwide revenues from 70 to 96 percent. Further reductions in the uncertainty in the utility’s systemwide revenues in the, range of 5 to 15 percent, are possible by re-designing the utility’s nonlinear price schedules to minimize the revenue risk it faces given the distribution of household level demand in its service territory.
Abstract: Optimal Network Tariffs for Renewable Electricity Generation
The intermittency (variability) of solar and wind power imposes network costs associated with maintaining system stability. We examine how the socially optimal deployment of intermittent renewable generation capacity depends on such ancillary services costs and demonstrate how network interconnection tari_s can be designed to implement the e_cient outcome. We then apply our theory to obtain quantitative results for the California electricity market.
Key words: Ancillary services costs, e_ciency, network tari_s, renewable electricity production, system stability.
JEL: L94, Q20, Q42
Contact: Carsten Lynge Jensen
If you would like to present something at the Economics Seminars, feel free to contact Jens Leth Hougaard.