Publication: Optimal pricing for electricity retailers based on data-driven consumers' price-response
Loading...
Identifiers
Publication date
2022-02-22
Defense date
Advisors
Tutors
Journal Title
Journal ISSN
Volume Title
Publisher
Springer
Impact
Export
Abstract
In the present work, we tackle the problem of fnding the optimal price tarif to be
set by a risk-averse electric retailer participating in the pool and whose customers
are price sensitive. We assume that the retailer has access to a sufciently large
smart-meter dataset from which it can statistically characterize the relationship
between the tarif price and the demand load of its clients. Three diferent models
are analyzed to predict the aggregated load as a function of the electricity prices
and other parameters, as humidity or temperature. More specifcally, we train linear
regression (predictive) models to forecast the resulting demand load as a function of
the retail price. Then, we will insert this model in a quadratic optimization problem
which evaluates the optimal price to be ofered. This optimization problem accounts
for diferent sources of uncertainty including consumer"s response, pool prices and
renewable source availability, and relies on a stochastic and risk-averse formulation.
In particular, one important contribution of this work is to base the scenario generation and reduction procedure on the statistical properties of the resulting predictive
model. This allows us to properly quantify (data-driven) not only the expected value
but the level of uncertainty associated with the main problem parameters. Moreover, we consider both standard forward-based contracts and the recently introduced
power purchase agreement contracts as risk-hedging tools for the retailer. The results
are promising as profts are found for the retailer with highly competitive prices and
some possible improvements are shown if richer datasets could be available in the
future. A realistic case study and multiple sensitivity analyses have been performed
to characterize the risk-aversion behavior of the retailer considering price-sensitive
consumers. It has been assumed that the energy procurement of the retailer can be
satisfed from the pool and diferent types of contracts. The obtained results reveal
that the risk-aversion degree of the retailer strongly infuences contracting decisions,
whereas the price sensitiveness of consumers has a higher impact on the selling
price ofered.
Description
Keywords
Electricity retailer, Price-sensitive consumers, Risk aversion, Smart meter data, Stochastic programming, Time-of-use rate
Bibliographic citation
Pérez-Santalla, R., Carrión, M., & Ruiz, C. (2022). Optimal pricing for electricity retailers based on data-driven consumers’ price-response. TOP.