Modeling and Control of Co-generation Power Plants: A Hybrid System Approach

Abstract

Abstract. In this paper the optimization of a combined cycle power plant 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 turbine, 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.

Optimization of operation of energy supply systems with co-generation and absorption refrigeration

“…From the presented mathematical model, the following might be concluded: the optimization problem defined is mixed integer (0-1) non-linear, with non-linearities occurring due to startup and shutdown transient behavior of the components, since all the non-linearities are related to 0-1 variables, the model might be transformed to MILP by introducing additional 0-1 decision variables and inequality constraints, as suggested in [16] or [29], and solved by using classical techniques for this type of optimization problems (e. g. BBM), decision variables related to different observed time intervals are connected, because of start-up and shutdown energy, thermal storage and, eventually, some additional constraints, so the problem cannot be decomposed into separate sub problems for each time interval (hour), and if the vector of all the integer decision variables is predefined, the problem becomes a linear continuous economic dispatch problem, suitable to be solved using LP techniques.…”

“…(16) and (17), while total CR electrical input is given in eq. Total AR thermal and auxiliary electrical inputs, are given in eqs.…”

“…MILP are usually solved with the branch and bound method (BBM), but Sakawa et al [13] have shown that for larger problems a combination of genetic algorithms (GA) and LP could be much more effective providing highly accurate approximate solutions. If non-linearities are only related to binary variables, such problems might be transformed to MILP by introducing new decision variables and inequality constraints, as shown in [16]. When included, this usually leads to non-linear models [15].…”

On the complexity and dynamical properties of mixed logical dynamical systems via an automaton‐based realization of discrete‐time hybrid automaton

“…Besides these theoretical aspects, the MLD framework in conjunction with the MPC has been used successfully to address many engineering problems such as traffic control systems, optical grids, networked control systems, co‐generation power plants, microgrid systems, traction control systems, production‐inventory systems, and power electronics control systems . In these applications, the MPC problem in has been implemented online or implicit in which the control problem is solved repeatedly in each step time during the control operation. On the other hand, the MPC in the works of Geyer et al, Mariéthoz et al, Beccuti et al has been executed offline or explicit in which the control problem is transformed into a multiparametric mixed‐integer optimization problem.…”

Constrained Optimal Control of Linear and Hybrid Systems

“…Constrained optimal control for hybrid systems was used for the control of Co-generation Power Plants [61,60], of a benchmark multi-tank system [115], of a gas supply system [23], of a gear shift operation on automotive vehicles [150], of the direct injection stratified charge engine [22], of the integrated management of the power-train [108] and of a traction control problem [36].…”