【摘要】：提出一種高維多目標(biāo)電力系統(tǒng)無功優(yōu)化模型。相比于傳統(tǒng)的電力系統(tǒng)無功優(yōu)化模型,該模型能夠在無功優(yōu)化中同時(shí)兼顧系統(tǒng)的有功損耗、電壓水平、靜態(tài)電壓穩(wěn)定性以及供電能力。針對(duì)已有的求解多目標(biāo)無功優(yōu)化模型的算法應(yīng)用于求解所提模型時(shí)存在的局限性,進(jìn)一步引入一種基于帕雷托熵的高維多目標(biāo)粒子群優(yōu)化算法并加以改進(jìn),使得該算法能夠有效求解高維多目標(biāo)優(yōu)化問題。最后,利用IEEE-39節(jié)點(diǎn)系統(tǒng)驗(yàn)證了所提模型和求解算法的正確性和有效性。仿真結(jié)果表明,在傳統(tǒng)的多目標(biāo)無功優(yōu)化模型中引入系統(tǒng)供電能力,能夠在不惡化其他目標(biāo)函數(shù)優(yōu)化效果的情況下,使系統(tǒng)的供電能力得到提高。
[Abstract]:A reactive power optimization model for high dimensional multi-objective power system is proposed. Compared with the traditional reactive power optimization model, this model can take into account the active power loss, voltage level, static voltage stability and power supply capacity at the same time in reactive power optimization. In view of the limitations of the existing algorithms for solving the multi-objective reactive power optimization model, a high-dimensional multi-objective particle swarm optimization algorithm based on Pareto entropy is further introduced and improved. So that the algorithm can effectively solve the high-dimensional multi-objective optimization problem. Finally, the correctness and effectiveness of the proposed model and algorithm are verified by IEEE-39 node system. The simulation results show that the power supply capacity of the system can be improved without deteriorating the optimization effect of other objective functions by introducing the power supply capacity into the traditional multi-objective reactive power optimization model.
【作者單位】： 華北電力大學(xué)新能源電力系統(tǒng)國(guó)家重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(51677069)~~
【分類號(hào)】：TM714.3;TP18

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相關(guān)期刊論文 前9條

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本文編號(hào)：2497043