Yeli Zhou

Constrained predictive control based on state space model of Organic Rankine Cycle system for waste heat recovery

Due to the advantages of recovering energy from low-grade heat sources, Organic Rankine Cycle (ORC) system is adopted as the primary technology for waste heat recovery. As the ORC system is a multivariable system with high complexity and nonlinear coupling, the conventional control strategy may not achieve satisfactory results. In this paper, the application of constrained model predictive control (MPC) for an ORC system is demonstrated. The simulation results are given to illustrate the efficiency and feasibility of the proposed control strategy.

Inexact Probabilistic Optimization Model and Its Application to Flood Diversion Planning in a Dynamic and Uncertain Environment

AbstractFlood management systems involve a variety of complexities, such as multiple uncertainties and their interdependences, as well as multiregion and dynamic features. This paper thus presents an inexact two-stage mixed-integer programming with random coefficients (ITMP-RC) model for flood management in a dynamic and uncertain environment. ITMP-RC is capable of addressing dual uncertainties expressed as random boundary intervals that exist in the coefficients of the objective function. A case study of flood diversion planning is used to demonstrate the applicability of the proposed methodology. Results indicate that total system costs would be rising gradually with increased probabilities of occurrence, implying a trade-off between economic objective and system safety. A variety of decision alternatives can be obtained under different policy scenarios, which are useful for decision makers to formulate appropriate flood management policies according to practical situations. The performance of ITMP-RC i...

Development of Optimal Water-Resources Management Strategies for Kaidu-Kongque Watershed under Multiple Uncertainties

In this study, an interval-stochastic fractile optimization (ISFO) model is advanced for developing optimal water-resources management strategies under multiple uncertainties. The ISFO model can not only handle uncertainties presented in terms of probability distributions and intervals with possibility distribution boundary, but also quantify subjective information (i.e., expected system benefit preference and risk-averse attitude) from different decision makers. The ISFO model is then applied to a real case of water-resources systems planning in Kaidu-kongque watershed, China, and a number of scenarios with different ecological water-allocation policies under varied p-necessity fractiles are analyzed. Results indicate that different policies for ecological water allocation can lead to varied water supplies, economic penalties, and system benefits. The solutions obtained can help decision makers identify optimized water-allocation alternatives, alleviate the water supply-demand conflict, and achieve socioeconomic and ecological sustainability, particularly when limited water resources are available for multiple competing users.

Dynamic characteristics for evaporator in Organic Rankine Cycle

Organic Rankine Cycle (ORC) is suitable for recovering energy from low-grade heat sources. A moving boundary model is introduced to describe the transient phenomena of evaporator, which is an important component of ORC. Based on the partial-differential equations expressing the conservation principles of mass and energy, coupled with flue gas and tube wall energy equations, a set of ordinary-differential equations can be obtained by integrating separately over the three regions: unsaturated liquid, liquid-vapor mixture, and the superheat vapor. The state space equation of evaporator can be derived by linearizing the obtained equations at the operating point. Finally, the simulation results are presented to show the feasibility of the proposed method of modeling.

Multivariable Control of an ORC Power Plant for Utilizing Waste Heat

In this paper, a multivariable control system is designed for organic Rankine cycle (ORC) power plants. The established dynamic model can be employed to design controller for ORC power plants. A multivariable control algorithm is proposed for the ORC power plant by combining linear quadratic regulator with PI controller. Simulation results demonstrate that the presented control strategy can obtain satisfactory performance.