Adaptive Model Predictive Control; Organic Rankine Cycle; Energy Efficiency
Abstract :
[en] Increasing the energy efficiency of industrial processes is a challenge that involves, not only improving the methodologies for design and manufacturing, but optimizing performance during part-load operation and transient conditions. A well-adopted solution consists of developing waste heat recovery (WHR) systems based on Organic Rankine Cycle (ORC) power units. The highest efficiency for such cycle is obtained at low superheating values, corresponding to the situation where the system exhibits time-varying nonlinear dynamics, triggered by the fluctuating nature of the waste heat source. In this paper, an adaptive control law using the Model Predictive Control (MPC) framework is proposed. This work goes a step beyond most of the existing scientific works in the field of ORC power systems, since the MPC controller is implemented in a lab-scale prototype, and its performance compared against a gain-scheduled PID strategy. The experimental results show that the adaptive MPC outperforms the gain-scheduled PID based strategy, as it allows to accurately regulate the evaporating temperature, while keeping vapor condition at the inlet of the expander i.e., the superheating, in a safe operating range, thus increasing the net power generation.
(2014), Industrial excess heat recovery technologies & applications, Tech. rep., Technical report. Industrial Energy-related Technologies and Systems (IETS)
Carcasci, C., Ferraro, R., Miliotti, E., Thermodynamic analysis of an organic rankine cycle for waste heat recovery from gas turbines (2014) Energy, 65, pp. 91-100
Verneau, A., Waste heat recovery by organic fluid rankine cycle. (1979) In: Proceedings from the first industrial energy technology conference. Houston (TX), pp. 940-52
Obernberger, I., Thonhofer, P., Reisenhofer, E., Description and evaluation of the new 1000kwel organic rankine cycle process integrated biomass chp plant in Lienz, Austria (2002) Euroheat and Power, 10, pp. 1-17
Quoilin, S., Van Den Broek, M., Declaye, S., Dewallef, P., Lemort, V., Techno-economic survey of organic rankine cycle (ORC) systems (2013) Renew Sustain Energy Rev, 22, pp. 168-186
Toffolo, A., Lazzaretto, A., Manente, G., Paci, M., A multi-criteria approach for the optimal selection of working fluid and design parameters in organic rankine cycle systems (2014) Appl Energy, 121, pp. 219-232
Quoilin, S., Orosz, M., Hemond, H., Lemort, V., Performance and design optimization of a low-cost solar organic rankine cycle for remote power generation (2011) Solar Energy, 85 (5), pp. 955-966
Song, J., wei Gu, C., Performance analysis of a dual-loop organic rankine cycle (orc) system with wet steam expansion for engine waste heat recovery (2015) Appl Energy, 156, pp. 280-289
Guillaume, L., Legros, A., Desideri, A., Lemort, V., Performance of a radial-inflow turbine integrated in an orc system and designed for a whr on truck application: an experimental comparison between r245fa and r1233zd (2017) Appl Energy, 186, pp. 408-422. , [sustainable Thermal Energy Management (SusTEM2015)]
Xie, H., Yang, C., Dynamic behavior of rankine cycle system for waste heat recovery of heavy duty diesel engines under driving cycle (2013) Appl Energy, 112, pp. 130-141
Sun, J., Li, W., Operation optimization of an organic rankine cycle (orc) heat recovery power plant (2011) J Appl Therm Eng, 31, pp. 2032-2041
Lecompte, S., Huisseune, H., vanden Broek, M., Paepe, M.D., Methodical thermodynamic analysis and regression models of organic rankine cycle architectures for waste heat recovery (2015) Energy, 87, pp. 60-76
Casella, F., Mathijssen, T., Colonna, P., Van Buijtenen, J., Dynamic modeling of organic rankine cycle power systems (2013) J Eng Gas Turb Power, 135. , 042310–042310-12
Colonna, P., van Putten, H., Dynamic modeling of steam power cycles.: Part i modeling paradigm and validation (2007) Appl Therm Eng, 27 (2-3), pp. 467-480
Desideri, A., Hernandez, A., Gusev, S., vanden Broek, M., Lemort, V., Quoilin, S., Steady-state and dynamic validation of a small-scale waste heat recovery system using the thermocycle modelica library (2016) Energy, 115, pp. 684-696
Grelet, V., Reiche, T., Lemort, V., Nadri, M., Dufour, P., Transient performance evaluation of waste heat recovery rankine cycle based system for heavy duty trucks (2016) Appl Energy, 165, pp. 878-892
Horst, T.A., Rottengruber, H.-S., Seifert, M., Ringler, J., Dynamic heat exchanger model for performance prediction and control system design of automotive waste heat recovery systems (2013) Appl Energy, 105, pp. 293-303
Feru, E., Willems, F., de Jager, B., Steinbuch, M., Modeling and control of a parallelwaste heat recovery system for euro-vi heavy-duty diesel engines (2014) Energies, 7, pp. 6571-6592
Tona, P., Peralez, J., Control of organic rankine cycle systems on board heavy-duty vehicles: a survey (2015) IFAC-PapersOnLine, 48 (15), pp. 419-426
Wei, D., Lu, X., Lu, Z., Gu, J., Performance analysis and optimization of organic rankine cycle (orc) for waste heat recovery (2007) J Energy Convers Manage, 48, pp. 1113-1119
Ziviani, D., Gusev, S., Lecompte, S., Groll, E., Braun, J., Horton, W., vanden Broek, M., Paepe, M.D., Optimizing the performance of small-scale organic rankine cycle that utilizes a single-screw expander (2017) Appl Energy, 189, pp. 416-432
Hou, G., Sun, R., Hu, G., Zhang, J., Supervisory predictive control for evaporator in organic rankine cycle (orc) system for waste heat recovery. (2011) In: Proceedings of the 2011 international conference on advanced mechatronics systems, pp. 306-11
Lemort, V., Zoughaib, A., Quoilin, S., Comparison of control strategies for waste heat recovery organic rankine cycle systems. (2011), In: Sustainable thermal energy management in the process industries international conference (SusTEM2011)
Zhang, J., Zhou, Y., Li, Y., Hou, G., Fang, F., Generalized predictive control applied in waste heat recovery power plants (2013) Appl Energy, 102, pp. 320-326
Hernandez, A., Desideri, A., Ionescu, C., Quoilin, S., Lemort, V., De Keyser, R., Increasing the efficiency of organic rankine cycle technology by means of multivariable predictive control. (2014), http://dx.doi.org/10.3182/20140824-6-ZA-1003.01796, In: 19th IFACWorld congress of the IFAC proceedings, vol. 47(3)
. p. 2195–200, doi
Hernandez, A., Desideri, A., Ionescu, C., Quoilin, S., Lemort, V., De Keyser, R., Experimental study of predictive control strategies for optimal operation of organic rankine cycle systems. (2015) In: Proceedings of the European control conference (ECC15)., , Linz (Austria)
Grelet, V., Dufour, P., Nadri, M., Lemort, V., Reichel, T., Explicit multi-model predictive control of a waste heat rankine based system for heavy duty trucks. (2015), In: In IEEE conference on decision and control. Osaka (Japan)
Zhang, J., Lin, M., Fang, F., Xu, J., Li, K., Gain scheduling control of waste heat energy conversion systems based on an {LPV} (linear parameter varying) model (2016) Energy, 107, pp. 773-783
Peralez, J., Tona, P., Nadri, M., Dufour, P., Sciarretta, A., Optimal control for an organic rankine cycle on board a diesel-electric railcar (2015) J Process Control, 33, pp. 1-13
Hernandez, A., Desideri, A., Ionescu, C., De Keyser, R., Lemort, V., Quoilin, S., Real-time optimization of organic rankine cycle systems by extremum-seeking control (2016) Energies, 9 (5), p. 334
Feru, E., Murgovski, N., deJager, B., Willems, F., Supervisory control of a heavy-duty diesel engine with an electrified waste heat recovery system (2016) Control Eng Pract, 54, pp. 190-201
Peralez, J., Nadri, M., Dufour, P., Tona, P., Sciarretta, A., Organic rankine cycle for vehicles: control design and experimental results (2017) IEEE Trans Control Syst Technol, 25 (3), pp. 952-965
Quoilin, S., Aumann, R., Grill, A., Schuster, A., Lemort, V., Dynamic modeling and optimal control strategy for waste heat recovery organic rankine cycles (2011) Appl Energy, 88, pp. 2183-2190
Pierobon, L., Chan, R., Li, X., Lyengar, K., Haglind, F., Ydstie, E., Model predictive control of offshore power stations with waste heat recovery (2016) J Eng Gas Turb Power, 138 (7), p. 071801
Maraver, D., Royo, J., Lemort, V., Quoilin, S., Systematic optimization of subcritical and transcritical organic rankine cycles (orcs) constrained by technical parameters in multiple applications (2014) Appl Energy, 117, pp. 11-29
Camacho, E.F., Bordons, C., (2004) Model predictive control, 405. , 2nd ed. Springer-Verlag London
De Keyser, R., (2003), Model based predictive control for linear systems, Invited chapter in UNESCO EoLSS. Oxford (6.43.16.1)
Normey-Rico, J., Camacho, E., Robust design of gpc for processes with time delay (2000) Int J Robust Nonlin Control, 10, pp. 1105-1127
De Keyser, R., Ionescu, C., The disturbance model in model based predictive control. (2003) In: Proceedings of IEEE conference on control applications, 1, pp. 446-51. , http://dx.doi.org/10.1109/CCA.2003.1223451
Torrico, B., Roca, L., Normey-Rico, J., Guzman, J., Yebra, L., Robust nonlinear predictive control applied to a solar collector field in a solar desalination plant (2010) IEEE Trans Control Syst Technol, 18 (6), pp. 1430-1439
Wang, L., (2010) Model predictive control system design and implementation using Matlab, Advances in industrial control, , Springer
Hernandez, A., Ruiz, F., Desideri, A., Ionescu, C., Quoilin, S., Lemort, V., Nonlinear identification and control of organic rankine cycle systems using sparse polynomial models. (2016), pp. 1012-7. , In: IEEE conference on control applications (CCA), part of IEEE multi-conference on systems and control
Zhang, J., Zhang, T., Lin, M., Hou, G., Li, K., Multiple model predictive control for organic rankine cycle (orc) based waste heat energy conversion systems. (2016), pp. 1-7. , http://dx.doi.org/10.1109/CONTROL.2016.7737577, In: 2016 UKACC 11th international conference on control (CONTROL)
Ljung, L., System identification: theory for the user (2007), Prentice-Hall