Publications
12 results found
Rivotti P, Karatayev M, Mourao ZS, et al., 2019, Impact of future energy policy on water resources in Kazakhstan, Energy Strategy Reviews, Vol: 24, Pages: 261-267, ISSN: 2211-467X
As part of its strategic economic and social plan, Kazakhstan has a target of increasing the share of renewables and alternative energy sources in power generation to 50% by 2050. This greatly contrasts with the current situation, where around 90% of electricity is produced from fossil fuels. To achieve the target, the introduction of between 600 and 2000 MW of nuclear power is expected by 2030. This would impact water resources, already under stress due to significant losses, heavy reliance on irrigation for agriculture, unevenly distributed surface water, variations in transboundary inflows, amongst others. This study presents an integrated analysis of the water-energy systems in Kazakhstan, to investigate the water resource availability to support such energy system transition.
Karatayev M, Rivotti P, Mourao ZS, et al., 2017, The water-energy-food nexus in Kazakhstan: challenges and opportunities, General Assembly of European-Geosciences-Union-Energy-Resources-and-Environment-Division, Publisher: ELSEVIER SCIENCE BV, Pages: 63-70, ISSN: 1876-6102
Mechleri E, Rivotti P, Staffell I, et al., 2016, Evaluation of Process Control Strategies for Normal, Flexible and Upset Operation Conditions of CO2 Post Combustion Capture Processes
Mechleri E, Staffell I, Lawal A, Ramos A, Shah N, Mac Dowell Nclose, 2016, Evaluation of Process Control Strategies for Normal, Flexible and Upset Operation Conditions of CO2 Post Combustion Capture Processes, 2016/07
Mechleri E, rivotti P, mac Dowell N, et al., 2015, Flexibility issues and controllability analysis of a post-combustion CO2 capture plant integrated with a natural gas power plant, 8th Trondheim Conference on CO2 Capture, Transport and Storage (TCCS-8)
Rivotti P, Pistikopoulos EN, 2015, A dynamic programming based approach for explicit model predictive control of hybrid systems, COMPUTERS & CHEMICAL ENGINEERING, Vol: 72, Pages: 126-144, ISSN: 0098-1354
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- Citations: 16
Rivotti P, Pistikopoulos EN, 2014, Constrained dynamic programming of mixed-integer linear problems by multi-parametric programming, COMPUTERS & CHEMICAL ENGINEERING, Vol: 70, Pages: 172-179, ISSN: 0098-1354
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- Citations: 8
Lambert RSC, Rivotti P, Pistikopoulos EN, 2013, A Monte-Carlo based model approximation technique for linear model predictive control of nonlinear systems, COMPUTERS & CHEMICAL ENGINEERING, Vol: 54, Pages: 60-67, ISSN: 0098-1354
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- Citations: 20
Rivotti P, Lambert RSC, Pistikopoulos EN, 2012, Combined model approximation techniques and multiparametric programming for explicit nonlinear model predictive control, 21st European Symposium on Computer-Aided Process Engineering (ESCAPE), Publisher: PERGAMON-ELSEVIER SCIENCE LTD, Pages: 277-287, ISSN: 0098-1354
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- Citations: 26
Rivotti P, Lambert RSC, Dominguez L, et al., 2011, Combined nonlinear model reduction and multiparametric nonlinear programming for nonlinear model predictive control, Computer Aided Chemical Engineering, Vol: 29, Pages: 617-621, ISSN: 1570-7946
This work presents a methodology which combines nonlinear model reduction techniques with recent advances in multiparametric nonlinear programming (mp-NLP) to derive explicit multiparametric controllers for nonlinear MPC (NMPC). Nonlinear model order reduction (NMOR) techniques based on empirical gramians are used for the model reduction step. The approach is illustrated on a 32 states distillation column model example. © 2011 Elsevier B.V.
Rivotti P, Lambert RSC, Dominguez L, et al., 2011, Combined nonlinear model reduction and multiparametric nonlinear programming for nonlinear model predictive control, 21st European Symposium on Computer Aided Process Engineering (ESCAPE-21), Publisher: ELSEVIER SCIENCE BV, Pages: 617-621, ISSN: 1570-7946
Lambert RSC, Rivotti P, Pistikopoulos EN, 2011, A novel approximation technique for online and multi-parametric model predictive control, 21st European Symposium on Computer Aided Process Engineering (ESCAPE-21), Publisher: ELSEVIER SCIENCE BV, Pages: 738-742, ISSN: 1570-7946
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- Citations: 2
Lambert RSC, Rivotti P, Pistikopoulos EN, 2011, A novel approximation technique for online and multi-parametric model predictive control, Computer Aided Chemical Engineering, Vol: 29, Pages: 738-742, ISSN: 1570-7946
Multi-parametric model predictive control has been widely recognized in the control literature. The objective of explicit MPC is to solve the constrained optimal control problem and derive the control variables as explicit functions of the states. Explicit MPC is particularly relevant for systems in which classical real time MPC implementation is impractical; In effect, the computations to derive the optimal control moves are performed offline. A framework for the development of such multiparametric/explicit controllers has been presented in [1]. The framework emphasizes the need for model approximation as a key challenge for a wider use of multiparametric/explicit MPC. We propose an approach that uses an interpolation method employed in a receding horizon fashion as a transient system identification technique to derive linear explicit algebraic expressions of the dynamics of the system under the form of linear expressions in the state parameter and controls. A major advantage of the approach is the availability of an a priori global error bound for the model mismatch due to the approximation. Linear dependency on the state parameters and controls enables to recast nonlinear and non convex MPC problems, into mp-QP optimization problems. The approach is demonstrated on a nonlinear benchmark model example of a 30 stages distillation column. © 2011 Elsevier B.V.
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