Model predictive control and the optimization of power plant load while considering lifetime consumption

Gallestey, Eduardo; Stothert, A.; Antoine, Marc; Morton, SK

doi:10.1109/59.982212

Cited by 55 publications

(23 citation statements)

References 9 publications

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“…In particular, we have introduced a novel approach to take into account the effect of a given operational mode on the asset depreciation, see also (Gallestey et al, 2001). Clearly, whether profits can be obtained via this method or not will depend largely on the plant characteristics, electricity and fuel prices, contractual constrains, etc.…”

Section: Discussionmentioning

confidence: 99%

“…The functions f on , f startup and f shutdown are strongly nonlinear and are the result of elaborated tuning procedures considering the overall process conditions, temperature/stress distributions and material properties, see (Gallestey et al, 2001) for details and references.…”

Section: Hybrid Model Of a Combined Cycle Power Plantmentioning

confidence: 99%

“…The usual recipe is to recast the economic optimization into the minimization of a cost functional and to account for the physical model of the plant through suitably defined constraints. See (Ferrari-Trecate et al, 2002b) and (Gallestey et al, 2001) for a list of related work.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Modelling and Control of Co-Generation Power Plants Under Consideration of Lifetime Consumption: A Hybrid System Approach

Ferrari-Trecate

Gallestey

Stothert

et al. 2002

IFAC Proceedings Volumes

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In this paper the load optimization of a combined cycle power plant under consideration of the real cost of lifetime usage is accomplished by exploiting hybrid systems, i.e., systems evolving according to continuous dynamics, discrete dynamics, and logic rules. The possibility of turning on/off the gas and steam turbines, the operating constraints (minimum up and down times) and the different types of start up of the turbines characterize the hybrid behavior of a combined cycle power plant. In order to model both the continuous/discrete dynamics and the switching between different operating conditions we use the framework of Mixed Logic Dynamical systems. Next, we recast the economic optimization problem as a Model Predictive Control (MPC) problem, that allows us to optimize the plant operations by taking into account the time variability of both prices and electricity/steam demands. Because of the presence of integer variables, the MPC scheme is formulated as a mixed integer linear program that can be solved in an efficient way by using commercial solvers.

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Section: Discussionmentioning

confidence: 99%

Section: Hybrid Model Of a Combined Cycle Power Plantmentioning

confidence: 99%

See 1 more Smart Citation

Modelling and Control of Co-Generation Power Plants Under Consideration of Lifetime Consumption: A Hybrid System Approach

Ferrari-Trecate

Gallestey

Stothert

et al. 2002

IFAC Proceedings Volumes

View full text Add to dashboard Cite

show abstract

“…A heating system optimization model is used to predict the future building behavior following the selected operational strategy and the weather and occupancy forecasts. Implementation of the receding horizon in controlling a single conventional power plant output to balance the demand has been explored by Gallestey et al (2002). A few researchers have applied this approach to the analysis of electric energy systems that incorporate intermittent resources (Xie and Ilic , 2008).…”

Section: Introductionmentioning

confidence: 99%

Energy dispatch strategy for a photovoltaic–wind–diesel–battery hybrid power system

2014

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In this paper, an energy dispatch model that satisfies the load demand, taking into account the intermittent nature of the solar and wind energy sources and variations in demand, is presented for a solar photovoltaic-wind-diesel hybrid power supply system. Model predictive control techniques are applied in the management and control of such a power supply system. The emphasis in this work is on the co-ordinated management of energy flow from the battery, wind, photovoltaic and diesel generators when the system is subject to disturbances. The results show that the advantages of the approach become apparent in its capability to attenuate and its robustness against uncertainties and external disturbances. When compared with the open loop model, the closed-loop model is shown to be more superior owing to its ability to predict future system behavior and compute appropriate corrective control actions required to meet variations in demand and radiation. Diesel consumption is generally shown to be more in winter than in summer. This work thus presents a more practical solution to the energy dispatch problem. Keywords: energy management, disturbance, intermittent nature, hybrid energy system, optimization scheme

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“…Most of other approaches that study component-health management and system reliability lie within the framework of fault-tolerant control or in the field of maintenance scheduling (see, e.g., the works of Guida and Giorgio (1995), Martorell et al (1999), Gallestey et al (2002), Khelassi et al (2011), Pereira et al (2010), Chamseddine et al (2014) and the references therein), but they do not consider demand uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Reliability–based economic model predictive control for generalised flow–based networks including actuators’ health–aware capabilities

Grosso

Ocampo‐Martínez

Puig

2016

International Journal of Applied Mathematics and Computer Science

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This paper proposes a reliability-based economic model predictive control (MPC) strategy for the management of generalised flow-based networks, integrating some ideas on network service reliability, dynamic safety stock planning, and degradation of equipment health. The proposed strategy is based on a single-layer economic optimisation problem with dynamic constraints, which includes two enhancements with respect to existing approaches. The first enhancement considers chance-constraint programming to compute an optimal inventory replenishment policy based on a desired risk acceptability level, leading to dynamical allocation of safety stocks in flow-based networks to satisfy non-stationary flow demands. The second enhancement computes a smart distribution of the control effort and maximises actuators' availability by estimating their degradation and reliability. The proposed approach is illustrated with an application of water transport networks using the Barcelona network as the case study considered.

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Model predictive control and the optimization of power plant load while considering lifetime consumption

Cited by 55 publications

References 9 publications

Modelling and Control of Co-Generation Power Plants Under Consideration of Lifetime Consumption: A Hybrid System Approach

Modelling and Control of Co-Generation Power Plants Under Consideration of Lifetime Consumption: A Hybrid System Approach

Energy dispatch strategy for a photovoltaic–wind–diesel–battery hybrid power system

Reliability–based economic model predictive control for generalised flow–based networks including actuators’ health–aware capabilities

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