Treffer: 天然气集输系统能效动态综合评价模型.
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The energy consumption systems of gas fields in the middle and late stages of development shall be evaluated and optimized. However, most of the existing static energy efficiency evaluation methods ignore ambiguity and randomness, and do not take into account the impact of time effect on evaluation results. It is necessary to upgrade and optimize the static algorithms. Taking the dynamic data of energy efficiency of one certain natural gas gathering and transportation system as the research object, this paper addresses these shortcomings by using the cloud model theory and the TOWA operator quadratic weighting method. Then, a dynamic comprehensive evaluation model of energy efficiency of natural gas gathering and transportation system is established by using the RS-entropy weighting method. Finally, each time sequence is evaluated by using Python programming language, and the dynamic comprehensive evaluation results of energy efficiency in the long-term dimension are obtained through dynamic dimension raising. The following results are obtained. First, the introduction of time weight vector allows for a better reflection of energy efficiency fluctuations in the long-term dimension and enriches the information content. Second, the dynamic comprehensive evaluation results show that the energy efficiency of the above mentioned gathering and transmission system is "average". The subsequent optimization efforts can focus on the boosting process which has a high proportion of energy consumption in the secondary indicators. Third, the analysis on the dynamic comprehensive evaluation results of energy efficiency of three gas fields verifies that the optimization model established in this paper are applicable to the comprehensive energy efficiency evaluation of most gas fields, demonstrating its extensive applicability. In conclusion, this model introduces uncertainty into energy efficiency evaluation to embody the dynamics and randomness of evaluation object over time, so as to identify the weak links of energy efficiency in the gathering and transportation system, strength the understanding on the energy efficiency system of natural gas gathering and transportation system, and provide more theoretical support for energy-saving and consumption-reducing decisions. [ABSTRACT FROM AUTHOR]
气田在进入开发中后期, 需要对能耗体系进行评价和优化, 但油气领域现有的静态能效评估方法大多忽略了模糊性与随机性, 且未考虑时间效应对评价结果的影响, 有必要对静态算法进行升级优化。为此, 以某天然气集输系统能效动态数据为研究对象, 利 用云模型理论以及 TOWA 算子二次加权法弥补上述缺点, 并结合 RS- 熵值赋权法, 构建了针对天然气集输系统的能效动态综合评价 模型, 最后利用 Python 编程语言对各时序进行评价, 并通过动态升维获得长时间维度下的能效动态综合评价结果。研究结果表明: ①随着时间权向量的引入, 更能反映长时间维度下的能效波动, 信息内容更加丰富详实; ②上述集输系统的能效动态综合评价结果 为 "-般", 后续优化可从二级指标中能耗占比较高的增压工艺入手; ③通过 3 个气田能效动态综合评价结果分析, 验证了所建立的 优化模型能适用于大多数气田能效综合评价, 方法具有广泛的适应性。结论认为, 该评价模型将不确定性介入能效评价研究中, 体 现评价对象随时间迁移的动态性以及随机性, 从而识别出该集输系统的能效薄弱环节, 可深化天然气集输系统能效体系的认识, 为 节能降耗决策提供更多理论支撑. [ABSTRACT FROM AUTHOR]
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