Optimal Demand Side Management for Cryogenic Air Separation Plants
The management of electricity demand, also referred to as demand side management (DSM), has been recognized as an effective approach to improving power grid performance. For electricity consumers, DSM constitutes the opportunity to benefit from financial
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Optimal Demand Side Management for Cryogenic Air Separation Plants Qi Zhang, Ignacio E. Grossmann and Jose M. Pinto
Abstract The management of electricity demand, also referred to as demand side management (DSM), has been recognized as an effective approach to improving power grid performance. For electricity consumers, DSM constitutes the opportunity to benefit from financial incentives by adjusting their electricity consumption. The cost of electricity is the single largest variable operating cost incurred in cryogenic air separation plants; hence, there is a strong interest in reducing the electricity cost in such plants through DSM. However, to perform effective DSM, we need to develop systematic and innovative decision-making tools that can help us answer questions such as the following: How much potential for load adjustment exists in the plant? How can production and energy management decisions be optimized in an integrated fashion? How can we make long-term strategic decisions while considering hourly changing electricity prices? How do we deal with uncertainty in process data and future information? In this chapter, we draw insights from multiple projects in which we have used mathematical optimization approaches to perform industrial DSM and demonstrated the potential for air separation plants using real-world case studies. In particular, we emphasize the importance of accurate integrated scheduling models, the impact of considering uncertainty and risk in the decision-making, the implementation of robust models, and the modeling of multiple time scales.
Q. Zhang ⋅ I.E. Grossmann (✉) Department of Chemical Engineering, Carnegie Mellon University, Pittsburgh, PA 15213, USA e-mail: [email protected] Q. Zhang e-mail: [email protected] J.M. Pinto Business and Supply Chain Optimization R&D, Praxair, Inc., Danbury, CT 06810, USA e-mail: [email protected] © Springer International Publishing Switzerland 2017 G.M. Kopanos et al. (eds.), Advances in Energy Systems Engineering, DOI 10.1007/978-3-319-42803-1_18
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18.1 Introduction The power grid is designed to reliably match electricity supply and demand. This task has become increasingly challenging due to high fluctuations in electricity demand, deregulation of electricity markets, and increasing penetration of intermittent renewable energy into the electricity supply mix. The steadily rising energy demand and the pressure to reduce greenhouse gas emissions have further amplified the need to improve the efficiency, reliability, and sustainability of the power grid. In recent years, the notion of a smart grid (Farhangi 2010) has been evolving, which represents the idea of effectively coordinating the major grid operations—electricity generation, transmission, distribution, and consumption—through improved communication, holistic optimization, and market design. One major innovation in the smart grid concept is the utilization of the load adjustment capabilities on the electricity consumers’ side, referred to as demand side management (DSM)
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