Abstract In the power system stochastic economic dispatch with wind power integration, the uncertainty cost caused by wind power forecast error needs to be considered. The uncertainty cost is usually formulated as an integral form of wind power random variable and solved based on an iterative algorithm, which is difficult to guarantee the convergence performance due to the step size selection. In this paper, a convex optimization for economic dispatch based on multiple wind farms sum power conditional distribution was proposed. Firstly, the wind power marginal distribution was modeled based on the mixture form of truncated versatile distribution. Copula theory was used to obtain the conditional distribution of multiple wind farms sum power, and the power correlation of multi wind farms was considered to avoid the use of high-dimensional distribution. Taking the sum power conditional distribution as input, an economic dispatch model was established to optimize the unit output and system reserve confidence. The economic dispatch model with wind power integration was transformed into a quadratic programming, which can be solved by off-the-shelf solver reliably and efficiently. Finally, the proposed methods were verified in IEEE 30-Bus system.
Tang Chenghui,Zhang Fan,Zhang Ning等. Quadratic Programming for Power System Economic Dispatch Based on the Conditional Probability Distribution of Wind Farms Sum Power[J]. Transactions of China Electrotechnical Society, 2019, 34(10): 2069-2078.
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2019, Vol. 34 
