考虑市场力风险约束的最优AGC控制模型

针对传统自动发电控制(AGC)优化模型中难以考虑市场力风险的问题,引入度量市场风险的价值模型,提出了以风险价值为限值的辅助服务成本约束混合整数非线性规划的AGC优化模型。为处理模型的非线性,引入两态辅助变量,将三态的机组状态变量进行等效转化,实现了模型的线性化,有效地降低了模型求解难度。以广西电网运行数据为例,对比不同风险置信水平下AGC控制性能,结果表明:置信水平越高,调节成本越大,控制效果越好,但无论置信水平高低,所提模型均能确保控制性能标准(CPS)合格,验证了模型的有效性,为电力市场环境下的AGC控制提供了有益参考。

Optimal AGC model with risk constraints of market power

Aiming at the problem that the market power risk is difficult to be considered in the traditional AGC(Automatic Generation Control) optimization model, the VaR(Value at Risk) for measuring market risk is introduced, and the AGC optimization model of mixed integer nonlinear programming under the constraint of ancillary service cost with VaR as the limit value is constructed. For dealing with the nonlinearity of the model, the two-state auxiliary variables are introduced to equivalently transform the three-state variables of the unit, which realizes the linearization of the model and thus effectively reduces the difficulty of solving the model. Taking the operation data of Guangxi Power Grid as an example, the performances of AGC under different risk confidence levels are compared. The results show that the higher the confidence level is, the greater the regulation cost will be, but with better control effect. However, whether the confidence level is high or not, the proposed model can ensure the CPS(Control Performance Standard) qualification, verifying the validity of the model. It can provide a useful reference for the AGC in the power market environment.