Frans Davelaar

An Optimization Procedure of the Start-Up of Combined Cycle Power Plants

Abstract This paper presents an optimization procedure for the definition of the gas turbine load profile during the hot start-up of Combined Cycle Power Plants (CCPP). First a dynamic model of CCPP is briefly described, together with its implementation in the Modelica language. Then, an identification procedure is developed to determine a simplified model to be implemented in Matlab/Simulink and to be used for the solution of the optimization problem. This simplified model is built by interpolating a number of linear estimated models with local validity. The load profile is assumed to be described by a suitable function, whose parameters are optimized by solving a minimum time problem subject to the plant (simulator) dynamics and to a number of constraints to be imposed on the main plant variables, such as temperatures, pressures, thermal and mechanical stresses. A number of simulation experiments is reported to witness the performance of the proposed approach.

Model Based Start-up Optimization of a Combined Cycle Power Plant

Abstract This paper deals with the modeling and the optimization of the start-up of a combined cycle. It decomposes the transient in several phases that are optimized separately. For each phase a simple model is used to minimize its duration under constraints. Several state and control input constraints are given in the paper to impose a trajectory that respects the stress limitation and ensures the damping of the responses. Each constrained minimum time optimization problem is solved by a SQP algorithm available in Matlab™. The optimal trajectories are tested on a complete dynamic model which consists of a process modeled by first principle equations and a sequence described by a finite state machine. This validation model is developed in Simulink™ and Stateflow™.

Hierarchical Model Predictive Control Approach for Start-up Optimization of a Combined Cycle Power Plant

Due to their numerous advantages, Combined Cycle Power Plants (CCPPs) have become an important technology for power generation. The participation of the CCPPs on the power production market involves frequent start-up/shutdown operations. In this context, optimizing their start-up procedure is of high interest. The optimization objective corresponds to problems that must be solved in real time while fulfilling operating constraints and in the mean time minimizing costs. In this paper a hierarchical model predictive control (H-MPC) structure is proposed to improve the start-up performances and to reduce the computation time. The structure includes two layers, each having a different time scale. The control problem at each level is formulated and based on a model developed in the modeling language Modelica and it aims at determination of an optimal profile of the gas turbine (GT) load. The CCPP model is adapted for optimization purposes and the load profile is assumed to be describable by parameterized functions, whose parameters are computed by solving a constrained optimal control problem. Numerical results prove the potential advantages of the proposed approach.

Solar parabolic trough reflector modeling and application to control for a Combined Cycle Power Plant

This paper presents a dynamical model for a Parabolic Trough (PT) reflector. In particular, this model describes the behavior of the output steam enthalpy and can be used to develop a control strategy for the coupling with a conventional power plant such as a Combined Cycle Power Plant (CCPP). The modeling uses the principle of a moving-boundary configuration with a two-phase flow region, and a nonlinear dynamical state space description is obtained. A linearization-based approach with an observer is proposed for a LQR control law that is validated on the nonlinear model.

Hierarchical nonlinear model predictive control for combined cycle start-up optimization

A hierarchical model predictive control (H-MPC) structure is proposed to improve the start-up performances of Combined Cycle Power Plants (CCPPs) start-up. The structure includes two layers. At each layer, the control problem aims at deriving the profile of the gas turbine (GT) load at different time scales. To achieve this, the profile is assumed to be described by parameterized functions, whose parameters are computed by solving an optimal time control problem, based on a model developed in the modeling language Modelica and subject to a number of constraints on the plant variables. Numerical results prove the potential advantages of the proposed approach.

Coordinated control for an Integrated Solar Combined Cycle

This paper deals with control strategies for an Integrated Solar Combined Cycle (ISCC). It first presents a hybrid dynamical model of an ISCC plant, obtained by coupling a Combined Cycle Power Plant with a solar Parabolic Trough reflector. In particular, this model describes the behavior of the ISCC power. This model is used to develop and compare two control strategies on the global power: decentralized control and coordinated control. The coordinated control shows that the solar part can help to reduce the global fuel consumption.

Modeling and control of a two-tank molten salt thermal storage for a concentrated solar plant

This paper is focused on a two-tank molten salt sensible Thermal Energy Storage (TES) that exchanges heat with a Concentrated Solar Plant (CSP) in a indirect active way. A detailed dynamical model that reproduces the physical behavior of a two-tank molten salt sensible TES is presented first. Then a control strategy is designed to regulate the enthalpy of the CSP fluid after charging or discharging it and to also regulate the tank levels in order to ensure a certain amount of available storage material at any time. Finally some illustrative simulation results are given.

Modeling and control of a Linear Fresnel Reflector for an Integrated Solar Combined Cycle

This paper presents a dynamic model of a Linear Fresnel Reflector (LFR) used to describe the evolution of the output steam enthalpy and the control strategy that was developed to allow coupling with Combined Cycle Power Plants (CCPP) while respecting operational constraints. The modeling approach uses the principle of a moving boundary formulation of a two-phase flow region and results in a nonlinear finite dimensional state space description. In order to circumvent the problem of nonlinearities, a simple linearization-based approach is proposed, providing accurate simulation results. Simulations illustrating tracking performances compatible with the CCPP coupling, as well as good (solar) disturbance rejection are shown.

Explicit price method for coordinated control and hydro-power production example

In the context of a general renewed interest in decomposition-coordination control approaches, and in the more particular continuity of former studies of the authors in that respect, the present paper focuses on some so-called price coordination method based on distributed receding horizon controllers, here emphasizing possible explicit schemes both at the controllers level and at the coordinator level. This can clearly be of interest for the control of large scale systems as they arise in power management issues, and is illustrated with an example of hydropower application. In short, the coordinator computes a price vector and distributes it to the various subsystems composing the overall system to be controlled, on the basis of the predicted control strategies that each of them communicate to it. The main point is that the coordinator here takes advantage of the explicit solutions for local linear Receding Horizon Controls, to globally update those price values in an explicit way as well. This method is illustrated with simulations of an industrial Hydro-Power Valley case-study, using real-data from French main electricity provider EDF (Electricite de France), and a comparison with the more classical coordination scheme based on a gradient algorithm is presented.

Hierarchical Model Predictive Control applied to Hydro Power Valley

Abstract Hydro Power Valleys are large scale systems made of several power plants equipped with pumps and turbines located along the river or at the lower part of the penstocks. These plants are linked together by the electrical grid, and also by the water network. The latter is characterized by a significant time delay. The plant operations have also to comply with technical and environmental requirements concerning the level and flow rate variations. A HD-MPC solution is proposed to manage the large scale constrained and time delayed Hydro Power Valleys. The control consists of two layers. The upper layer optimizes the power profiles on a one-day horizon with a coarse step size. The lower level refines the control for shorter horizon and finer step size. Platform tests in simulation show that the coordination is able to improve the maneuverability of the Hydro Power Valley.