AGENT-BASED SIMULATION OF CONSUMER DEMAND FOR SMART METERING TARIFFS

An agent-based model simulates consumer demand for smart metering tariffs. It utilizes the Bass Diffusion Model and Rogers's adopter categories to locate demand-side barriers and drivers. Integration of empirical census microdata enables a validated socio-economic background for each consumer. The key performance indicators diffusion-speed and diffusion-level measure the effectiveness of regulatory interventions to induce diffusion. Pricing, promotion and quantity-regulation policies are tested. Scenario results emphasize the impact of both epidemic and probit effects. Speed of adoption is mainly triggered via interactions and consumer awareness. Level of diffusion primarily depends on pricing, willingness-to-pay and cost-benefit-thresholds. Data mining on agent's attributes highlight weaknesses in current regulatory requirements due to disadvantages in consumer acceptance and policy effectiveness. A "cash-for-clunkers" program could tackle major barriers for adoption and boost diffusion through synergies of pricing and promotion interventions.