Comparing methods for customer baseline load estimation for residential demand response in south korea and france: predictive power and policy implications

Auteurs

Seungman LEE

Astract

Worldwide concern on climate change and paradigm shifts in the electricity sector towards more flexibility contribute to making Demand-side management (DSM) an increasingly important element for establishing the demand and supply balance. In particular, Demand Response (DR) is expected to improve the security of electricity supply by reducing peak demand, reduce CO2 emissions, contribute to the integration of variable renewable energy (VRE) and minimize overall costs. DR activities are complex and depend on a number of technical, meteorological and behavioral parameters. It is thus instructive to compare the DR pilot programs launched in different countries, such as the Notification d’Échange de Blocs d’Effacement (NEBEF) mechanism in France in 2013 or the market-based DR programs in South Korea in 2014. Among the different economic issues at stake, the estimation of the Customer Baseline Load (CBL) emerges as a key component for defining the nature, performance, and costs of different DR programs. Based on the re-scaled load profile for an average household, this research thoroughly examines the performance of several CBL estimation methods in the context of the South Korean and French DR mechanisms. In particular, it is shown how optimizing the methodologies for CBL estimation allows improving the incentives for DR participation. For instance, the more accurate CBL estimation methods currently in use in South Korea could significantly enhance the potential for DR also in the context of the French electricity market. To assess this potential quantitatively, different CBL methodologies are integrated into a Cost-Benefit Analysis (CBA), which allows determining both overall changes in consumer surplus and the profits of private operators. The results of this research on CBL estimation methods are indeed relevant for public policy-making as well as for the design of industrial and commercial DR programs.