[1]王歆智１,黄文涛１,贺忠尉２,等.阶梯碳交易下新型电力系统协同优化出力策略[J].湖北工业大学学报,2024,39(1):57-62.
　WANG Xinzhi,HUANG Wentao,HE Zhongwei,et al.A New Power System Collaborative Optimization Output Strategy under Tiered Carbon Trading[J].,2024,39(1):57-62.
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阶梯碳交易下新型电力系统协同优化出力策略()
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《湖北工业大学学报》[ISSN:1003-4684/CN:42-1752/Z]

卷:
39
期数:
2024年第1期
页码:
57-62
栏目:
出版日期:
2024-02-20

文章信息/Info

Title:
A New Power System Collaborative Optimization Output Strategy under Tiered Carbon Trading
文章编号:
1003-4684(2024)01-0057-06
作者:
王歆智１; 黄文涛１; 贺忠尉２; 何　俊１; 罗　杰１; 邓明辉１
(１ 湖北工业大学电气与电子工程学院,湖北 武汉 ４３００６８;２ 国网湖北省电力有限公司恩施供电公司,湖北 恩施 ４４５０００)
Author(s):
WANG Xinzhi1; HUANG Wentao1; HE Zhongwei2; HE Jun1; LUO Jie1; DENG Minghui1
(1 School of Electrical and Electronic Engineering, Hubei Univ. of Tech., Wuhan 430068,China;2 Enshi Power Supply Company, State Grid Hubei Electric Power Company, Enshi 445000, China)
关键词:
新型电力系统; 协同优化; 改进 NSGAＧⅡ算法; 阶梯式碳交易; 电力系统灵活性
Keywords:
new power system;  collaborative optimization;  improved NSGAⅡ algorithm;  tiered carbon trading;  power system flexibility
分类号:
TM732
文献标志码:
A
摘要:
为协调新能源与火电协调配合过程中的经济性和灵活性问题.提出一种电源经济 灵活协同优化出力策略.为约束碳排放和碳交易成本,引入碳交易机制对系统中的碳排放配额及实际碳排放进行建模,将碳排放转化为有经济价值的调度资源.针对新能源高占比系统灵活性不足问题,进行系统灵活性供需能力分析并建立电源经济 灵活协同优化出力模型,然后用轮盘赌选择和跳跃基因改进 NSGAＧⅡ算法提高模型求解效率.最后以改进的IEEE３０节点为算例进行仿真分析并设置对比,结果表明模型的有效性.
Abstract:
With the increase in the proportion of new energy in the power system, the contradiction between the comprehensive economic benefits of the system and the lack of flexibility in output regulation caused by fluctuations in new energy has intensified. To this end, this paper proposes a power economy flexible synergistic optimization output strategy. In order to constrain carbon emissions and carbon trading costs, a carbon trading mechanism is introduced to model carbon emissions quotas and actual carbon emissions in the system, and convert carbon emissions into dispatch resources with economic value. Aiming at the lack of flexibility of the high proportion of new energy system, the system flexibility supply and demand capability is analyzed and a power economy flexible collaborative optimal scheduling model is established. Then, the NSGA Ⅱ algorithm is improved by roulette selection and jumping genes to improve the model solving efficiency. Finally, the improved IEEE30 node is taken as an example for simulation analysis and comparison. The results show that the model proposed in this paper is effective.

参考文献/References:

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备注/Memo

备注/Memo:
[收稿日期]２０２２ -０５ -２６[基金项目]湖北工业大学博士基金(BSQD２０１９０１３)[第一作者]王歆智(１９９６－),男,湖北十堰人,湖北工业大学硕士研究生,研究方向为电网安全稳定与控制.[通信作者]黄文涛(１９８４－),男,湖北武汉人,湖北工业大学高级工程师,研究方向为电网安全稳定与控制.
更新日期/Last Update: 2024-03-14