| 引用本文: | 崔杨,周慧娟,仲悟之,李鸿博,赵钰婷.考虑源荷两侧不确定性的含风电电力系统低碳调度[J].电力自动化设备,2020,40(11): |
| CUI Yang,ZHOU Huijuan,ZHONG Wuzhi,LI Hongbo,ZHAO Yuting.Low-carbon scheduling of power system with wind power considering uncertainty of both source and load sides[J].Electric Power Automation Equipment,2020,40(11): |
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| 摘要: |
| 大规模风电并网是实现电力低碳环保发展的必然趋势，而风电与负荷的随机波动性对系统的影响不容忽视。提出一种考虑模糊机会约束的低碳型经济调度模型，同时计及源荷两侧不确定性对含风电电力系统低碳调度的影响。将阶梯型的碳交易成本引入目标函数中，旨在降低系统碳排放量，提高系统风电消纳量。针对风电并网后系统的不确定因素，引入模糊机会约束，将确定性约束松弛为含有模糊变量的系统约束，利用梯形模糊参数将其清晰化处理，并通过CPLEX对模型进行求解。算例分析表明所提模型可有效提高风电消纳水平以及降低碳排放。 |
| 关键词: 风电 碳交易 不确定性 模糊机会约束 低碳调度 |
| DOI：10.16081/j.epae.202009019 |
| 分类号:TM614 |
| 基金项目:国家自然科学基金资助项目(51777027) |
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| Low-carbon scheduling of power system with wind power considering uncertainty of both source and load sides |
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CUI Yang1, ZHOU Huijuan1, ZHONG Wuzhi2, LI Hongbo3, ZHAO Yuting1
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1.Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology, Ministry of Education, Northeast Electric Power University, Jilin 132012, China;2.China Electric Power Research Institute, Beijing 100192, China;3.Training Centre of State Grid Jilin Province Electric Power Supply Company, Changchun 130022, China
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| Abstract: |
| Large-scale wind power integration is an inevitable trend for realizing low-carbon environmental protection development of electricity, while the impact of random fluctuation of wind power and load on system cannot be ignored. A low-carbon economic scheduling model considering fuzzy opportunity constraints is proposed, and the impact of the uncertainty of both the source and load sides on low carbon scheduling of power system with wind power is considered. The ladder-type carbon trading cost is introduced into the objective function, which aims at reducing carbon emission and increasing wind power consumption. Aiming at the uncertainty after wind power integration, the fuzzy chance constraints are introduced to relax the deterministic constraints into system constraints with fuzzy variables, which are cleared by the trapezoidal fuzzy parameters. CPLEX is used to solve the model. Case analysis shows that the proposed model can effectively improve the wind power consumption level and reduce carbon emission. |
| Key words: wind power carbon trading uncertainty fuzzy opportunity constraint low-carbon scheduling |
