Abstract
In this study, an inexact two-stage stochastic linear programming (ITSLP) method is proposed for supporting sustainable management of electric power system under uncertainties. Methods of interval-parameter programming and two-stage stochastic programming were incorporated to tackle uncertainties expressed as interval values and probability distributions. The dispatchable loads are integrated into the framework of the virtual power plants, and the support vector regression technique is applied to the prediction of electricity demand. For demonstrating the effectiveness of the developed approach, ITSLP is applied to a case study of a typical planning problem of power system considering virtual power plants. The results indicate that reasonable solutions for virtual power plant management practice have been generated, which can provide strategies in mitigating pollutant emissions, reducing system costs, and improving the reliability of power supply. ITSLP is more reliable for the risk-aversive planners in handling high-variability conditions by considering peak-electricity demand and the associated recourse costs attributed to the stochastic event. The solutions will help decision makers generate alternatives in the event of the insufficient power supply and offer insight into the tradeoffs between economic and environmental objectives.
Highlights
Due to the shortage of fossil fuel and the resulting of environmental pollution problems from energy combustion, renewable energy power generation has caught worldwide attention
An inexact two-stage stochastic linear programming approach is developed for optimal electric power systems management with virtual power plants (VPPs) under uncertainties
Two-stage stochastic programming is incorporated into a two-stage programming optimization framework
Summary
Due to the shortage of fossil fuel and the resulting of environmental pollution problems from energy combustion, renewable energy power generation has caught worldwide attention. Many economic, environmental, and political factors dynamically affect system planning processes, resulting in uncertainties in some key system parameters (e.g., renewable energy availability, load demands, and energy prices) These uncertainties and their latent interactions might further intensify the complexity of the decision-making process. Some techniques were used to handle various uncertainties existing in the electric power systems Among these techniques, stochastic programming (SP) have received extensive attention since they could directly integrate uncertain information expressed as probability distributions into the optimization framework. TSP and IP can be integrated to enhance the capability of addressing multiple uncertainties in power system planning with VPPs. the objective of this study is to develop an inexact two-stage stochastic linear programming model for planning the electric power system including VPPs in a hybrid uncertain environment.
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