含大用户直购电的风火储联合环境经济调度
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北京信息科技大学 自动化学院

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TM614

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北京市自然科学基金资助项目(3172015)。


Environmental Economic Dispatch of Wind- thermal-storage System with Direct Power Purchasing of Large Consumers
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School of Automation,Beijing Information Science and Technology University

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    摘要:

    节能减排政策的实施、风电并网容量的攀升、储能新技术的出现、以及大用户交易模式的改革等,都给电力系统调度带来了新的挑战。为此,提出一种大用户直购电参与的风火储联合系统环境经济调度模型,该模型综合考虑了风电出力、碳排放权交易、储能系统及大用户直购电等多因素参与的优化求解问题,分析了储能系统、大用户的参与对风火联合系统调度在环境和经济效益方面的影响。针对传统萤火虫算法寻优过程中易出现振荡的问题,提出一种混沌自适应萤火虫算法对调度模型进行求解。利用IEEE39节点算例进行仿真分析,结果表明了所提调度模型的正确性及混沌自适应萤火虫算法求解此类问题的有效性。

    Abstract:

    The implementation of carbon emission reduction policy, the increase of wind power integration capacity, the emergence of new energy storage technology, and the reform of large user trading mode, all bring new challenges to the power system dispatching. Therefore, an environmental economic dispatch (EED) model of the wind-thermal-storage combined system with direct power purchase of large consumers is proposed in this paper. A multi-objective optimization problem including the wind power output, carbon emissions trading, energy storage system and direct power purchase of large consumers is considered comprehensively in the model. Meanwhile, the influences of energy storage systems and large consumers on the environmental and economic benefits of wind-thermal combined system scheduling are analyzed. A chaotic adaptive glowworm swarm optimization (GSO) algorithm is presented to solve the problem of oscillation in the optimization of traditional GSO algorithm. The IEEE-39 system is used for the simulation analysis. The results show that the proposed EED model is accurate and the chaos adaptive glowworm swarm optimization algorithm is effective in solving this problem.

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  • 收稿日期:2021-03-19
  • 最后修改日期:2021-05-17
  • 录用日期:2021-09-11
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