language: en

AUCTION-DRIVEN COORDINATION FOR PLANTWIDE OPTIMIZATION

Rinaldo A. Jose and Lyle H. Ungar
University of Pennsylvania
Philadelphia, PA 19104

Abstract Model predictive control strategies generally focus on controlling plant outputs to setpoints; in industry, however, a more desirable goal is maximizing a plants profitability. In principle, this can be done by creating a plant model and maximizing profit with respect to the market prices of the plants inputs and outputs, but in practice, such centralized approaches often cannot effectively be applied at the operations time scale due to the size and complexity of the problem. One solution is to use decentralized optimization at the unit operations level by tearing process streams and coordinating the resulting pieces. Such optimization, however, requires that unit inputs and outputs be priced. We show that a traditional Lagrangean-based approach to this pricing fails for simple systems. Instead, we define slack resources over the torn process streams and price them using auctions. Unlike Lagrange multipliers, slack resource prices contain useful information and can be used to make decisions regarding capital improvements, thus providing a strong tie between the operations and management layers in chemical plants.

Keywords auctions, distributed optimization, resource prices, process decomposition, optimal coordination, penalty-based methods, Lagrangean decomposition

Introduction