雙重不確定環(huán)境下的微網(wǎng)優(yōu)化運(yùn)行調(diào)度風(fēng)險(xiǎn)分析研究
[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(diǎn)實(shí)驗(yàn)室(華北電力大學(xué));
【基金】:國家自然科學(xué)基金項(xiàng)目(51577068) 國家863高技術(shù)基金項(xiàng)目(2015AA050104)~~
【分類號(hào)】:TM73
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