Title: Financially Adequate Pricing Designs

Abstract: In a commodity market, market-clearing prices refer to prices that allow the commodity producers and consumers (or buyers and sellers) to trade the commodity so no surplus or deficit occurs. In this talk I present the problem of deriving financially adequate prices for trading a perishable commodity under a centralized auction. I study a model based on an electricity market, with a set of producers using conventional technologies; and another set of environmentally clean producers subject to exogenous weather realizations from the use of variable renewable energy sources (VRES).

Using a chance-constrained optimization (CCO) approach, I show how prices that satisfy revenue adequacy in expectation for the market administrator, and cost recovery in expectation for all participants, can be obtained from the optimal dual variables associated with the deterministic equivalent of the CCO market-clearing model. This pricing scheme paves the way for the design of market-clearing pricing schemes with alternative properties, for market-
clearing models in which it is appropriate or desirable to model the market’s uncertainties through the use of chance-constrained optimization.

The proposed pricing scheme produces uncertainty uniform real-time prices that do not depend on the real-time realization of the VRES production outcomes, in contrast to the stochastic approach. I illustrate results considering a case study electricity market, and compare the market prices obtained using a revenue adequate stochastic approach and the proposed revenue adequate CCO approach.

Bio: Alberto J. Lamadrid L. (Ph.D. Applied Economics and Management, Cornell University; M.A. Economics New York University; B.Sc. Electrical Engineering, Universidad de los Andes, Colombia) is associate professor and James T. Kane Faculty Fellow in the Economics Department at the College of Business and Economics, and in the Industrial and Systems Engineering Department at the P.C. Rossin College of Engineering and Applied Science at Lehigh University. He is also a member of the Institute for Cyber Physical Infrastructure and Energy at Lehigh University. His research interests are in electricity markets, power systems, and energy economics. He has worked on topics involving multi-period stochastic optimization in electrical networks, modeling and strategic management of resilient interdependent systems, adoption of renewable energy sources and the valuation of power infrastructure assets.