考虑参数不确定性的区域电-气联合系统的概率-模糊能流评估

Probabilistic-possibilistic energy flow evaluation of regional electricity-gas integrated system considering parameter uncertainties

电-气联合系统(EGS)中存在大量的不确定因素,而现有研究仅考虑了电、气负荷以及风电功率的概率不确定性对EGS能流分布的影响。为此,提出在EGS的能流分析中进一步考虑天然气管道及电-气耦合设备参数的不确定性,并根据这些参数呈现的不精确、受主观经验影响等特点,提出用模糊模型来描述其不确定性。在此基础上,以中压配电网和配气网耦合形成的区域EGS为对象,综合考虑上述概率、模糊不确定因素以及中压配电网的不对称、不接地特点,提出区域EGS的概率-模糊能流评估方法。所提方法以蒙特卡罗模拟、α-截集法和证据理论为基础,适用于区域EGS能流的概率评估、模糊评估以及概率-模糊综合评估。以33节点中压配电网以及11节点配气网构成的区域EGS为算例,验证所提方法的有效性。仿真结果表明,不计及天然气管道和耦合设备参数的不确定性,很可能导致对区域EGS能流分布的评估结果过于乐观,从而低估区域EGS的运行风险。

There are many uncertainties in the EGS( Electricity-Gas integrated System). However,the existing researches have only considered the influences of the probabilistic uncertainties of electricity/gas loads and wind power on the energy flow distribution of EGS. Therefore,the uncertainties of natural gas pipeline and electricity-gas coupling equipment parameters are further considered and the possibilistic model is proposed to describe these parameter uncertainties according to their features of imprecision and being influenced by subjective experiences.Based on this,a regional EGS formed by the coupling of medium-voltage distribution network and gas distribution network is taken as the object,and the probabilistic-possibilistic energy flow evaluation method for this regional EGS is proposed considering the above probabilities,possibilistic uncertainties and the asymmetric and ungrounded characteristics of medium-voltage distribution network. The proposed method is based on Monte Carlo simulation,α-cut set method and evidence theory and can be applied to pure probabilistic,pure possibilistic and probabilistic-possibilistic comprehensive evaluation of regional EGS energy flow. The effectiveness of the proposed method is verified by a regional EGS example composed of 33-bus medium voltage distribution network and 11-node gas distribution network. Simulative results demonstrate that the ignorance of the uncertainties of the natural gas pipeline and the coupling equipment parameters may lead to over-optimistic evaluation results of energy flow distribution,and thus the operational risk of regional EGS is underestimated.