ELECTRICITY TARIFFS UNDER IMPERFECT KNOWLEDGE OF PARTICIPANT BENEFITS

We consider the problem of establishing tariffs for electrical energy under uncertainty about the value of the energy to the participants. A tariff update is proposed that achieves welfare maximization asymptotically through successive approximations to the ideal tariff. The successive update of the tariff avoids the need for accurate a priori knowledge of electricity system demand and generation as a function of price. Our key results are a tariff update algorithm and a proof of local convergence two necessary steps for implementation of practical responsive pricing.