Design And Operation Optimization Research Of Steam Power System Considering Complex Uncertainty

Huge energy consumption and pollutant discharge exacerbate the world energy shortage and environmental pressure.Improving energy efficiency,optimizing energy utilization and reducing pollutant emission have become the focus of future sustainable energy development strategy.Steam power system supplies the required steam and electricity for the process industry,and at the same time,it also consumes a large amount of primary energy and produces a large amount of pollutants to discharge into the surrounding environment.Therefore,the design and operation optimization of steam power system has important theoretical and practical significance for enterprise economic benefit,environmental protection and energy saving.Uncertain factors must be taken into account in the design and operation optimization research of steam power system.It may make the existing design and operation strategy of the system conservative or unreasonable,and even bring security risks.The traditional method can not reflect the influence of uncertainty on the objective function and constraint conditions reasonably,which will lead to the design and operation deviate from the optimal state;besides,in practical engineering systems,there are usually multi-source and multi-type uncertainties,and these uncertainties are usually not isolated.The single traditional uncertainty optimization method has its applicable conditions and advantages and disadvantages in solving practical problems,and cannot deal with complex mixed uncertainty systems;furthermore,complex uncertainties may cause system risks,so that the absolute feasibility of optimization results cannot be guaranteed,or even lead to system instability and high risk.Therefore,for the design and operation optimization of steam power system,it is urgent to develop new methods and models to deal with the complex uncertainties and system risks in the system.In this paper,based on mathematical model and uncertainty programming theory,the uncertainty optimization methods are coupled to solve complex uncertainty problems.The coupling of the uncertain optimization methods not only integrates the advantages of the traditional methods,but also achieves a certain degree of complementarity among their limitations.Aiming at the mixed uncertainties in the steam power system,such as steam and electricity demand,fuel and electricity price,the properties of these uncertainties and their effects on the objective function and constraints of the system are analy zed firstly,and then based on different demand characteristics,components and policy requirements,a series of design and optimization models of system are established by coupling the uncertainty optimization methods with the goal of minimizing the total cost of the system.It is expected that the optimal design and optimization strategy can not only realize the economic objective optimization,but also ensure that the system can deal with the complex uncertainties and operate safely and stably.The main research contents are as follows:(1)Chance-constrained robust optimization method is obtained by coupling min-max robust optimization and chance-constrained programming.This method improves the traditional uncertainty optimization methods and can deal with the complex uncertainties represented by probability density functions,bounded sets and their combinations.Under the acceptable risk scale of complex uncertainty,it allows the system constraints to be satisfied under the specified confidence level,and a robust solution can be obtained based on system cost minimization.A chance-constrained robust optimization model of steam power system is established and applied in a refinery engineering case.Numerical results show that the decision maker of utility system can determine the system reliability coefficient based on the decision requirements and relevant regulations,and then obtain the corresponding robust optimal decision scheme,and realize the trade-off between economy and reliability.(2)In fact,the parameter distribution information required by the chance-constrained robust optimization strategy is difficult to obtain,or there is a large error in the obtained parameter distribution information.Thus,the uncertainty can be expressed as interval number and the interval-parameter programming strategy is introduced.The interval-parameter programming does not need to consider the multi-source and complexity of the uncertain factors of the system,nor does it need the distribution information of the parameter data.It only needs to know the fluctuation interval of the parameters to carry out the uncertainty optimization.The intervalparameter programming model of steam power system is established.Applying the model to an engineering case,the numerical results show that the interval-parameter programming model can obtain the optimization results in the form of intervals,which can provide more intuitive decision support for the decision maker of utility system to evaluate the trade-off between economy and reliability.(3)The design and optimization of steam power system is necessary not only to obtain the optimal design and operation scheme,but also to ensure that when the uncertain variable conditions occur,the operation scheme can be adjusted quickly to ensure the safety and stability of the production,and at the same time to ensure higher efficiency and better economy.The interval-parameter programming is coupled to the two-stage stochastic programming framework and an interval two-stage stochastic programming model considering complex uncertainties is proposed.Based on a refinery engineering case,it is proved that the model gives the optimization results in the form of intervals,and it can not only realize the tradeoff between system economy and reliability,but also put forward the corresponding scheduling adjustment scheme for various variable working conditions caused by uncertainties.(4)Considering the interval two-stage stochastic programming method is based on the assumption that the decision-maker is risk neutral.Under high variable conditions,when the decision-maker is risk averse,the interval two-stage stochastic programming method may become unfeasible.Thus aiming at the limitations of the interval two-stage stochastic programming method,the robust optimization of risk aversion is introduced into the interval two-stage stochastic programming frame to obtain the interval two-stage robust optimization method.Based on a refinery project case,the numerical results show that the proposed model can evaluate the tradeoff between the economy and stability of the system,so that the decision maker of utility system can realize the ideal solution with low system cost and acceptable system risk.