Performance Analyze of Ultra-Low Emission of Thermal Power Generation Based on Multi-Objective Optimization

2016 ◽  
Author(s):  
Xiaoen Li ◽  
Ningling Wang ◽  
Yumeng Zhang ◽  
Yongping Yang
Keyword(s):  
Power Plant ◽  
Environmental Impact ◽  
Thermal Power ◽  
Weighting Factor ◽  
Pollutant Emission ◽  
Support Vector ◽  
Total System ◽  
Multi Objective Optimization ◽  
Coal Consumption ◽  
Multi Objective

The present study deals with a multi-objective optimization problem on design condition. A multi-objective algorithm model is established to weigh up the relationship between coal consumption rate and environmental impact of pollutant. A simulated thermodynamic system model of traditional supercritical coal-fired units coupled with environment protect equipment is designed on the platform of Ebsilon. The environmental impact, which consist of the pollutant emission of NOx, SOx and dust, is acquired with the help of support vector machine (SVM) from the historical record of that power plant. The restriction of pollutant emission in Chinese newly policy is taken into account to determine the weighting factor. By considering energy and environment as the multi-objective, the simulation, which evaluates the solutions by interfacing with the programmed optimization algorithm, is developed. And corresponding total system performance and characteristic of pollutant emission in flue gas is derived. The result show that the performance of system and environment protect equipment will be influenced as boundary conditions changed. Coal consumption around 290g/kWh and 292g/kWh can reach minimum environmental impact in the case of our testing power plant.

scholarly journals Multi-objective optimization identifies trade-offs between self-sufficiency and environmental impacts of regional agriculture in Baden-Württemberg, Germany

2020 ◽  
pp. 1-20
Author(s):  
Christian Buschbeck ◽  
Larissa Bitterich ◽  
Christian Hauenstein ◽  
Stefan Pauliuk
Keyword(s):  
Environmental Impact ◽  
Environmental Impacts ◽  
Food Supply ◽  
Optimal Solution ◽  
Multi Objective Optimization ◽  
Regional Food ◽  
Multi Objective ◽  
Impact Reduction ◽  
Self Sufficiency ◽  
Political Targets

Regional food supply, organic farming, and changing food consumption are three major strategies to reduce the environmental impacts of the agricultural sector. In the German Federal State of Baden-Württemberg (population: 11 million), multiple policy and economic incentives drive the uptake of these three strategies, but quantitative assessments of their overall impact abatement potential are lacking. Here, the question of how much food can be produced regionally while keeping environmental impacts within political targets is tackled by comparing a scenario of maximum productivity to an optimal solution obtained with a multi-objective optimization (MO) approach. The investigation covers almost the entirety of productive land in the state, two production practices (organic or conventional), four environmental impact categories, and three demand scenarios (base, vegetarian, and vegan). We present an area-based indicator to quantify the self-sufficiency of regional food supply, as well as the database required for its calculation. Environmental impacts are determined using life cycle assessment. Governmental goals for reducing environmental impacts from agriculture are used by the MO to determine and later rate the different Pareto-efficient solutions, resulting in an optimal solution for regional food supply under environmental constraints. In the scenario of maximal output, self-sufficiency of food supply ranged between 61% and 66% (depending on the diet), and most political targets could not be met. On the other hand, the optimal solution showed a higher share of organic production (ca. 40%–80% com¬pared to 0%) and lower self-sufficiency values (between 40% and 50%) but performs substantially better in meeting political targets for environmental impact reduction. At the county level, self-sufficiency varies between 2% for densely populated urban districts and 80% for rural counties. These results help policy-makers benchmark and refine their goalsetting regarding regional self-sufficiency and environmental impact reduction, thus ensuring effective policymaking for sustainable community development.

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