Integrating scheduling and control for economic MPC of buildings with energy storage

Touretzky, Cara R.; Bâldea, Michael

doi:10.1016/j.jprocont.2014.04.015

Cited by 131 publications

(63 citation statements)

References 22 publications

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“…Bauer et al has recently suggested that key performance indicators (KPI) are already implemented in industry as the integrating factor between scheduling and control. Scheduling and control for economic model predictive control (EMPC) of buildings with energy storage has been investigated [50].…”

Section: Literature Reviewmentioning

confidence: 99%

Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes

et al. 2017

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Abstract:A novel formulation for combined scheduling and control of multi-product, continuous chemical processes is introduced in which nonlinear model predictive control (NMPC) and noncyclic continuous-time scheduling are efficiently combined. A decomposition into nonlinear programming (NLP) dynamic optimization problems and mixed-integer linear programming (MILP) problems, without iterative alternation, allows for computationally light solution. An iterative method is introduced to determine the number of production slots for a noncyclic schedule during a prediction horizon. A filter method is introduced to reduce the number of MILP problems required. The formulation's closed-loop performance with both process disturbances and updated market conditions is demonstrated through multiple scenarios on a benchmark continuously stirred tank reactor (CSTR) application with fluctuations in market demand and price for multiple products. Economic performance surpasses cyclic scheduling in all scenarios presented. Computational performance is sufficiently light to enable online operation in a dual-loop feedback structure.

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Section: Literature Reviewmentioning

confidence: 99%

Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes

et al. 2017

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“…Precooling decisions are often made using just the RC model in an optimization calculation with a time of use pricing profile [36]. The incentive for load shifting comes from having a higher price during the peak afternoon period.…”

Section: Arx Model Developmentmentioning

confidence: 99%

Building-level power demand forecasting framework using building specific inputs: Development and applications

Touretzky

Patil²

2015

Applied Energy

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“…This means that, in EMPC, an economic cost function or objective is directly optimized instead of tracking a predetermined set-point [13,14]. To date, EMPC has had some successful applications in different processes [15][16][17][18][19]. In the studies of Zeng et al [15] and Liu et al [16], for example, EMPC was applied to improve the effluent quality of a waste water treatment process and the operation of an oil sands primary separation vessel, respectively.…”

Section: Introductionmentioning

confidence: 99%

“…In the studies of Zeng et al [15] and Liu et al [16], for example, EMPC was applied to improve the effluent quality of a waste water treatment process and the operation of an oil sands primary separation vessel, respectively. Idris et al [17] applied EMPC to a continuous catalytic distillation process whileMendoza-Serrano et al [18] and Touretzky et al [19] applied EMPC to temperature control in buildings. In these applications, EMPC showed a potential to significantly improve the performance of the classical MPC.…”

Section: Introductionmentioning

confidence: 99%

Improving Flexibility and Energy Efficiency of Post-Combustion CO2 Capture Plants Using Economic Model Predictive Control

Decardi‐Nelson

Liu

2018

Processes

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Abstract:To reduce CO 2 emissions from power plants, electricity companies have diversified their generation sources. Fossil fuels, however, still remain an integral energy generation source as they are more reliable compared to the renewable energy sources. This diversification as well as changing electricity demand could hinder effective economical operation of an amine-based post-combustion CO 2 capture (PCC) plant attached to the power plant to reduce CO 2 emissions. This is as a result of large fluctuations in the flue gas flow rate and unavailability of steam from the power plant. To tackle this problem, efficient control algorithms are necessary. In this work, tracking and economic model predictive controllers are applied to a PCC plant and their economic performance is compared under different scenarios. The results show that economic model predictive control has a potential to improve the economic performance and energy efficiency of the amine-based PCC process up to 6% and 7%, respectively, over conventional model predictive control.

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Integrating scheduling and control for economic MPC of buildings with energy storage

Cited by 131 publications

References 22 publications

Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes

Combined Noncyclic Scheduling and Advanced Control for Continuous Chemical Processes

Building-level power demand forecasting framework using building specific inputs: Development and applications

Improving Flexibility and Energy Efficiency of Post-Combustion CO2 Capture Plants Using Economic Model Predictive Control

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