【摘要】：多個風電場之間的風速相關(guān)性會影響潮流分布,進而影響輸電網(wǎng)規(guī)劃方案。采用逆Nataf變換建立風速相關(guān)性模型。結(jié)合基于半不變量法的概率潮流和機會約束規(guī)劃,綜合考慮經(jīng)濟性、電網(wǎng)負載均衡度、環(huán)保效應(yīng)3個指標,構(gòu)建考慮風速相關(guān)性的含風電場多目標電網(wǎng)優(yōu)化規(guī)劃模型。針對多目標優(yōu)化問題的求解,提出一種改進NSGA-Ⅱ,該算法采用控制參數(shù)動態(tài)調(diào)整策略,提高了算法的全局搜索性能。采用基于熵的序數(shù)偏好方法對最優(yōu)解集進行排序,給出決策方案。IEEE 24節(jié)點系統(tǒng)和某區(qū)域?qū)嶋H算例證明了所提模型的合理性和方法的有效性。研究結(jié)果表明,風速相關(guān)性對目標分量有重要的影響,考慮風速相關(guān)性能夠給出更準確的電網(wǎng)規(guī)劃方案。
[Abstract]:The correlation of wind speed among wind farms will affect the distribution of power flow and then the transmission network planning scheme. The inverse Nataf transform is used to establish the wind speed correlation model. Combined with the probabilistic power flow and chance constrained programming based on semi-invariant method, a multi-objective power network optimization planning model with wind speed correlation was constructed, considering three indexes: economy, power grid load balance and environmental protection effect. In order to solve the multi-objective optimization problem, an improved NSGA- 鈪，

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