时间：2017年12月07日（周四）11：50 - 12：50

地点：经管楼301室

报告人：经济贸易系 陈聪

报告题目：鲁棒性随机优化方法在电力能源系与碳管理中的应用 Abstract 1: In this study, an inexact robust optimization method (IROM) is developed for supporting carbon dioxide (CO 2) emission management in a regional-scale energy system, through incorporating interval-parameter programming (IPP) within a robust optimization (RO) framework. In the modeling formulation, penalties are exercised with the recourse against any infeasibility, and robustness measures are introduced to examine the variability of the second-stage costs that are above the expected levels. The IROM is suitable for risk-aversive planners under high-variability conditions. The IROM is applied to a case of energy systems and CO 2 emission planning under uncertainty. The results obtained can generate desired decision alternatives that are able to not only enhance electricity-supply safety with a low system-failure risk level but also mitigate CO 2 emissions. They can be used for generating decision alternatives and minimizing the system cost of energy system while meeting the CO 2- emission permit requirement.   Abstract 2: This study develops a risk-aversion optimization model for an urban electric power system (RAOM-UEPS), taking into account stochastic uncertainties. The RAOM-UEPS can manage stochastic uncertainties and capture associated risks from the stochastic information. This enables managers to analyze the trade-off between system cost and system risk in detail. Then, as a case study, the RAOM-UEPS is applied to the planning of an urban electric power system in Tianjin. Here, three scenarios are considered, each with different proportions of new energy resources and clean production levels (i.e., energy conversion efficiencies). This study aims to urban electric power system (UEPS) optimization models that support the city's transformation from a coal-fired dominated to a low-carbon electric power mix, as well as to promote the sustainable development of society as a whole. The proposed model can sophisticatedly facilitates a sophisticated system analysis of energy supply, electric power conversion, capacity expansion, and environmental requirements over multiple periods. The results suggest that coal, one of the primary air pollutants and contributors of CO2, is dominant in Tianjin’s electric power system, which was the primary air-pollutants and CO2 contributor in electric power system. Improving clean production levels and the proportion of new energy resources could effectively save energy resources and mitigate air pollutants and CO2 emissions. These findings can provide a scientific basis for the sustainable development of regional electric power systems, as well as for transformations from coal-dominated to low-carbon electric power cities.

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