An Algorithm for Mixed-Integer Optimal Control of Solar Thermal Climate Systems with MPC-Capable Runtime

Bürger, Adrian; Zeile, Clemens; Altmann-Dieses, Angelika; Säger, Sebastian; Diehl, Moritz

doi:10.23919/ecc.2018.8550424

Cited by 14 publications

(10 citation statements)

References 17 publications

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“…Therefore, the decomposition approach by Sager (2009) is applied, where the solution of the original MINLP is approximated by solving first a relaxed version of the MINLP, which is a Non-Linear Program (NLP), then obtaining an integer trajectory for the discrete controls by application of either Sum-Up-Rounding (SUR) (Sager, 2009) or Combinatorial Integral Approximation (CIA) (Sager et al, 2011), and afterwards solving the NLP again with binary controls fixed according to the solution of the integer approximation step. In the literature, several successful applications of this approach can be found (Kirches, 2011;Ebrahim et al, 2018;Bürger et al, 2018a).…”

Section: Ocp Setup and Implementationmentioning

confidence: 99%

A whole-year simulation study on nonlinear mixed-integer model predictive control for a thermal energy supply system with multi-use components

et al. 2020

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This work presents a whole-year simulation study on nonlinear mixed-integer Model Predictive Control (MPC) for a complex thermal energy supply system which consists of a heat pump, stratified water storages, free cooling facilities, and a large underground thermal storage. For solution of the arising Mixed-Integer Non-Linear Programs (MINLPs) we apply an existing general and optimalcontrol-suitable decomposition approach. To compensate deviation of forecast inputs from measured disturbances, we introduce a moving horizon estimation step within the MPC strategy. The MPC performance for this study, which consists of more than 50,000 real time suitable MINLP solutions, is compared to an elaborate conventional control strategy for the system. It is shown that MPC can significantly reduce the yearly energy consumption while providing a similar degree of constraint satisfaction, and autonomously identify previously unknown, beneficial operation modes.

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Section: Ocp Setup and Implementationmentioning

confidence: 99%

A whole-year simulation study on nonlinear mixed-integer model predictive control for a thermal energy supply system with multi-use components

et al. 2020

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“…We define and an activation block B ∈ P i holds this would imply that the (max{k ∈ B}) th activation of i has been processed before its release interval because B can not be interrupted by activations from other controls. Therefore, the above inequality does not hold and block deadline feasibility [6,7], [7,8], [8, ∞], [4,6], [6, ∞].…”

Section: Lemma 1 For An Equidistant Grid Let W ∈ ω N Be Feasible Formentioning

confidence: 99%

“…In [6,7], a complex renewable energy system in the form of a solar thermal climate system with nonlinear system behavior is introduced as an MIOCP. The system's core is an adsorption cooling machine, which can be switched on to intensify the cooling down of ambient temperature.…”

Section: Dualmode Adsorption Cooling Machine Problemmentioning

confidence: 99%

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On mixed-integer optimal control with constrained total variation of the integer control

Säger

Zeile

2020

Comput Optim Appl

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The combinatorial integral approximation (CIA) decomposition suggests solving mixed-integer optimal control problems by solving one continuous nonlinear control problem and one mixed-integer linear program (MILP). Unrealistic frequent switching can be avoided by adding a constraint on the total variation to the MILP. Within this work, we present a fast heuristic way to solve this CIA problem and investigate in which situations optimality of the constructed feasible solution is guaranteed. In the second part of this article, we show tight bounds on the integrality gap between a relaxed continuous control trajectory and an integer feasible one in the case of two controls. Finally, we present numerical experiments to highlight the proposed algorithm’s advantages in terms of run time and solution quality.

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“…With a given initial temperature distribution, the differential equation is applied to each layer and integrated over the entire forecast horizon to calculate the analytical temperature distribution over that time period. The limitations of this approach for application in our scenarios are as follows:  Differentiability: For application within gradient-based optimization methods, models must be continuous and differentiable (Bürger et al, 2018). The presence of "If-Else"-statements within models, however, introduces discontinuities and must therefore be avoided.…”

Section: Thermal Energy Storage (Htes and Ctes) Modelmentioning

confidence: 99%

Development and experimental evaluation of grey-box models of a microscale polygeneration system for application in optimal control

Sawant

Bürger

Doan

et al. 2020

Energy and Buildings

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With the need for optimisation based supervisory controllers for complex energy systems, comes the need for reduced order system models representing not only the non-linear characteristics of the components, but also certain unknown process dynamics like their internal control logic. We present in this paper an extensive literature study of existing methods and a rational modelling procedure based on the grey-box methodology that satisfies the necessary characteristics for models to be applied in an economic-MPC of a real-world polygeneration system at the Offenburg University of Applied Sciences. The engineering application of the models and their fitting coefficients are shared in this paper. Finally, the models are evaluated against experimental data and the efficacy of the methodology is discussed based on quantitative and qualitative arguments.

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An Algorithm for Mixed-Integer Optimal Control of Solar Thermal Climate Systems with MPC-Capable Runtime

Cited by 14 publications

References 17 publications

A whole-year simulation study on nonlinear mixed-integer model predictive control for a thermal energy supply system with multi-use components

A whole-year simulation study on nonlinear mixed-integer model predictive control for a thermal energy supply system with multi-use components

On mixed-integer optimal control with constrained total variation of the integer control

Development and experimental evaluation of grey-box models of a microscale polygeneration system for application in optimal control

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