A novel process integrating vacuum distillation with atmospheric chlorination reaction for flexible production of tetrachloroethane and pentachloroethane

In this paper, we developed a novel process integrating vacuum distillation with atmospheric chlorination reaction(VD-ACR) to realize the flexible production of tetrachloroethane(TeCA) and pentachloroethane(PCA)from 1,2-dichloroethane(DCA). During the simulation, the distillation column and reactors were operated for separation and chlorination respectively under variable pressures and temperatures. It is interesting to note that VD-ACR processes producing pure TeCA or PCA can exhibit the similar configuration parameters after optimization, which enables the flexible production of TeCA and PCA with different molar ratios via changing operating parameters. The molar ratio of TeC A/PCA can be fine-tuned within the range of 0.9:0.1-0.1:0.9 through adjusting the amount of chlorine pumped into side reactors, giving rise to the increase of the heat duty of reboiler by five times. A pilot-scale experiment was then operated based-upon this VD-ACR process and the result matched well with the simulation. Therefore, the VD-ACR model presented in this study will be beneficial for the industrial-scale flexible production of TeCA and PCA from DCA.

Modeling and optimization methods of integrated production planning for steel plate mill with flexible customization

With diversified requirements and varying manufacturing environments, the optimal production planning for a steel mill becomes more flexible and complicated. The flexibility provides operators with auxiliary requirements through an implementable integrated production planning. In this paper, a mixed-integer nonlinear programming(MINLP) model is proposed for the optimal planning that incorporates various manufacturing constraints and flexibility in a steel plate mill. Furthermore, two solution strategies are developed to overcome the weakness in solving the MINLP problem directly. The first one is to transform the original MINLP formulation to an approximate mixed integer linear programming using a classic linearization method. The second one is to decompose the original model using a branch-and-bound based iterative method. Computational experiments on various instances are presented in terms of the effectiveness and applicability. The result shows that the second method performs better in computational efforts and solution accuracy.

Stochastic Economic Dispatch Based Optimal Market Clearing Strategy Considering Flexible Ramping Products Under Wind Power Uncertainties

High penetration level of renewable energy has brought great challenges to operation of power systems,and use of flexible resources(FRs)is becoming increasingly important.Flexibility of power systems can be improved by changing generation arrangements,but the interests of some market participants may be harmed in the process.This study proposes a stochastic economic dispatch model with trading of flexible ramping products(FRPs).To calculate changes in revenue and reasonably compensate units that provide FRs,multisegmented marginal bidding for energy is simulated by linearizing generation cost,and an optimal market clearing strategy for FRPs is developed according to changes in clearing energy and marginal clearing price.Then,the correlation between prediction errors of wind speeds among different wind farms is determined based on a joint distribution function modeled by the copula function,and quasi-Monte Carlo simulation(QMC)is used to generate wind power scenarios.Finally,numerical simulations of modified IEEE-30 and IEEE-118 bus systems is performed with minimum comprehensive cost as the objective function.This verifies the proposed model could effectively deal with wind variability and uncertainty,stabilize the marginal clearing price of the electricity market,and ensure fairness in the market.

Enhanced Flexible Ramping Product Formulation for Alleviating Capacity Shortage in Look-ahead Commitment

The roll-out of a flexible ramping product provides independent system operators(ISOs)with the ability to address the issues of ramping capacity shortage.ISOs procure flexible ramping capability by committing more generating units or reserving a certain amount of headrooms of committed units.In this paper,we raise the concern of the possibility that the procured flexible ramping capability cannot be deployed in realtime operations due to the unit shut-down in a look-ahead commitment(LAC)procedure.As a solution to the issues of ramping capacity shortage,we provide a modified ramping product formulation designed to improve the reliability and reduce the expected operating cost.The trajectories of start-up and shutdown processes are also considered in determining the ramping capability.A new optimization problem is formulated using mixed integer linear programming(MILP)to be readily applied to the practical power system operation.The performance of this proposed method is verified through simulations using a small-scale system and IEEE 118-bus system.The simulation results demonstrate that the proposed method can improve the generation scheduling by alleviating the ramping capacity shortages.