刘丽军, 罗宁, 吴桐, 郑文迪. 基于混合整数二阶锥规划的考虑需求侧响应虚拟电厂优化调度[J]. 太阳能学报, 2021, 42(8): 96-104. DOI: 10.19912/j.0254-0096.tynxb.2020-0439
引用本文: 刘丽军, 罗宁, 吴桐, 郑文迪. 基于混合整数二阶锥规划的考虑需求侧响应虚拟电厂优化调度[J]. 太阳能学报, 2021, 42(8): 96-104. DOI: 10.19912/j.0254-0096.tynxb.2020-0439
Liu Lijun, Luo Ning, Wu Tong, Zheng Wendi. OPTIMAL SCHEDULING OF VIRTUAL POWER PLANT CONSIDERING DEMAND SIDE RESPONSE BASED ON MIXED INTEGER SECOND-ORDER CONE PROGRAMMING[J]. Acta Energiae Solaris Sinica, 2021, 42(8): 96-104. DOI: 10.19912/j.0254-0096.tynxb.2020-0439
Citation: Liu Lijun, Luo Ning, Wu Tong, Zheng Wendi. OPTIMAL SCHEDULING OF VIRTUAL POWER PLANT CONSIDERING DEMAND SIDE RESPONSE BASED ON MIXED INTEGER SECOND-ORDER CONE PROGRAMMING[J]. Acta Energiae Solaris Sinica, 2021, 42(8): 96-104. DOI: 10.19912/j.0254-0096.tynxb.2020-0439

基于混合整数二阶锥规划的考虑需求侧响应虚拟电厂优化调度

OPTIMAL SCHEDULING OF VIRTUAL POWER PLANT CONSIDERING DEMAND SIDE RESPONSE BASED ON MIXED INTEGER SECOND-ORDER CONE PROGRAMMING

  • 摘要: 从技术型虚拟电厂角度考虑内部网络运行约束和安全约束,建立计及配电网灵活性和经济性的技术型虚拟电厂优化调度模型。在电力市场环境下,建立灵活性指标以保证系统各个时段运行有充足的灵活性裕度。同时基于阶梯式弹性方法构建价格型需求响应,引导用户响应风、光出力和电力市场电价的变化。采用场景法构建风、光出力的随机不确定性,并优化极限场景以确保其灵活性。基于二阶锥凸优化理论和Big-M方法,将该文模型中非凸非线性条件松弛为混合整数二阶锥规划问题以更加有效求解。最后,基于仿真结果验证了该文模型的有效性和合理性。

     

    Abstract: High penetration rate of renewable energy is inevitable in the future grid, in which the volatility and randomness characteristics may cause flexibility insufficient to system operation of the distribution network. An optimal scheduling model of technical virtual power plant that takes into account the flexibility and economy of the distribution network is proposed in this paper, in which the internal network operation constraints and security constraints are considered. Firstly, an index of flexibility is established to ensure that the system has sufficient flexibility margins for each period of operation in the electricity market environment. The pricebased demand response is established through a stepwise elasticity method, by which the users are guided to responded to the changes of wind and photovoltaic power output, and electricity market prices. Scenario analysis method is used to describe the uncertainty of wind power and photovoltaics, and the extreme scenario is optimized to ensure flexibility of the system. Then, the non-convex nonlinear conditions in the model are relaxed into a mixed-integer second-order cone programming problem based on the second-order cone convex optimization theory and Big-M approach so as to get the solutions more effectively. Finally, the validity and rationality of the model are verified based on the simulation results.

     

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