【摘要】：相對于傳統(tǒng)大電網(wǎng),新能源高滲透率下微網(wǎng)中的不確定因素是限制微網(wǎng)發(fā)展的關鍵。為克服傳統(tǒng)優(yōu)化運行中僅考慮單一不確定性導致的調(diào)度結(jié)果保守性問題,該文深入研究微網(wǎng)中的不確定因素,從不確定理論出發(fā),將風電出力和光伏出力分別處理為模糊隨機變量和模糊變量,構(gòu)造雙重不確定環(huán)境下的機會約束模糊隨機規(guī)劃模型。為更為靈活直觀地描述該環(huán)境下的復雜雙重不確定性,利用機會測度衡量模糊隨機事件的機會,并提出一種模糊隨機模擬技術與遺傳算法相結(jié)合的混合智能算法對機會約束模糊隨機規(guī)劃模型進行求解。針對不同置信水平下的最優(yōu)解,進一步將傳統(tǒng)優(yōu)化問題中單一的經(jīng)濟分析擴展為風險分析,分析結(jié)果表明,隨著置信水平的減小,微網(wǎng)運行成本降低,而對新能源發(fā)電的管控也隨之降低,導致風險增大。以一個包含風、光、儲以及燃料電池和微型燃氣輪機的微網(wǎng)系統(tǒng)為實例進行計算分析,驗證該模型及求解算法的可行性及有效性。
[Abstract]:Compared with the traditional large power grid, the uncertainty factor in the micro-grid under the new energy and high permeability is the key to limit the development of the micro-grid. In order to overcome the conservative problem of scheduling results caused by single uncertainty in the traditional optimal operation, the uncertainty factors in micro-grid are studied in this paper, and the uncertainty theory is set out. The wind power and photovoltaic output are treated as fuzzy random variables and fuzzy variables respectively, and the chance constrained fuzzy stochastic programming model is constructed under double uncertain environment. In order to describe the complex double uncertainty in this environment more flexibly and intuitively, the opportunity of fuzzy random events is measured by chance measure. A hybrid intelligent algorithm based on the combination of fuzzy stochastic simulation and genetic algorithm is proposed to solve the chance constrained fuzzy stochastic programming model. In view of the optimal solution at different confidence levels, the single economic analysis in traditional optimization problem is further extended to risk analysis. The results show that with the decrease of confidence level, the running cost of micro-grid decreases, and the cost of micro-grid operation decreases with the decrease of confidence level. And the control of new energy generation will also be reduced, resulting in increased risk. Taking a micro-grid system including wind, light, storage, fuel cell and micro gas turbine as examples, the feasibility and effectiveness of the model and the algorithm are verified.
【作者單位】： 新能源電力系統(tǒng)國家重點實驗室(華北電力大學);
【基金】：國家自然科學基金項目(51577068) 國家863高技術基金項目(2015AA050104)~~
【分類號】：TM73

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