International Business Machines Corporation

Dmitriy A Katz-Rogozhnikov

Jayant R Kalagnanam

Soumyadip Ghosh

Mark Steven Squillante

Xiaoxuan Zhang

James R Luedtke

System and method of solving, in a single-period, an optimal dispatching problem for a network of energy generators connected via multiple transmission lines, where it is sought to find the lowest operational cost of dispatching of various energy sources to satisfy demand. The model includes traditional thermal resources and renewable energy resources available generation capabilities within the grid. The method considers demand reduction as a virtual generation source that can be dispatched quickly to hedge against the risk of unforeseen shortfall in supply. Demand reduction is dispatched in response to incentive signals sent to consumers. The control options of the optimization model consist of the dispatching order and dispatching amount energy units at generators together with the rebate signals sent to end-users at each node of the network under a demand response policy. Numerical experiments based on an analysis of representative data illustrate the effectiveness of demand response as a hedging option.

Integration of demand response and renewable resources for power generation management

Cycle time and throughput of a manufacturing facility is effectively manages by a control system that employs a combination of a long-term horizon model and at least one short-term horizon model to generate control signals for a set of machines in a manufacturing facility. The long-term horizon model determines long-term average time allocation percentage for each machine for a given set of throughput targets and cycle time targets for products to be manufactured. Each of the at least one short-term horizon model determines queues for immediate use at processing tools, while the queues are subjected to a secondary adjustment based on the time allocation constraints generated by the long-term horizon model. The combination of the long-term and the at least one short-term horizon models provides a stable long-term proactive WIP bubble-management as well as short-term WIP bubble management.

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Ossining, NY, United States of America

Dmitriy A Katz-Rogozhnikov