This model can not only deal with uncertainties embedded in the complex energy system described as interval values and random variables but also reflect dynamic linkage between multiple stages over a time series. In this study, a risk explicit interval multistage stochastic programming model considering inter-regional carbon subsidy is developed to support an optimal energy system planning in Inner Mongolia, China.
It is vital to compensate for the economic and environmental loss of power output region by taking the carbon subsidy strategy into account. Inter-regional electricity transmission inevitably brings about unbalanced carbon emission and air pollution among different regions. The model results and trade-offs would be valuable for supporting the EU vehicle recycling factories in creating optimal long-term production strategies and reducing the risk for uncertain situations. Quantity of land-filled wastes will be radically reduced after January 1, 2015. The success of the final phase of implementation of the EU ELV Directive is not jeopardized, because even the future eco-efficiency quotas were reached in all created test problems.
The future eco-efficiency quotas will not endanger their business. Vehicle recycling factories aim at reaching the highest possible level of quantity and quality of sorted metal flows. A numerical study demonstrated the potentials and applicability of the proposed model. It can create optimal plans for procuring vehicle hulks, sorting of generated material fractions, allocation of sorted waste flows and allocation of sorted metals for desired value of the system aspiration level. In order to meet the imposed eco-efficiency quotas, maximize system profit and minimize decision risk, and at the same time fill the identified research gaps, a risk explicit interval linear programming model for optimal long-term planning in the EU vehicle recycling factories was developed. However, there is a lack of research of uncertainties in the vehicle recycling system, none of the previous studies analyzed the linkage and trade-offs between decision risk and system performances, and no previous research was reported on interval-based programming for vehicle recycling planning problem. Long-term optimization planning of vehicle recycling is increasingly important. The EU Directive on end-of-life vehicles (EU ELV Directive) aims to increase recovery and recycling rates of ELVs in order to reduce waste and improve environmental performances. With the number of vehicles expected to increase to 1.85 billion by 2030 and the scrap generated from end-of-life vehicles (ELVs) expected to be 3.71 billion tonnes, there is a strong motivation to properly process the flow of these materials.
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