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首页> 外文期刊>Energy Conversion & Management >Modeling and configuration optimization of the natural gas-wind-photovoltaic-hydrogen integrated energy system: A novel deviation satisfaction strategy
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Modeling and configuration optimization of the natural gas-wind-photovoltaic-hydrogen integrated energy system: A novel deviation satisfaction strategy

机译:天然气风光 - 光伏 - 氢气集成能系统的建模与配置优化:一种新型偏差满足策略

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摘要

The integrated energy system (IES) coupled with renewable energy power generation and hydrogen energy storage (HES) is an effective way to achieve clean and low-carbon energy consumption, with great development potential. How to reasonably determine the system configuration scheme is a critical issue that needs to be solved urgently. This paper constructs a configuration optimization model. First, the mathematical model, objective function, optimization strategy, and constraints are given. Then, this study innovatively proposes an optimization strategy based on deviation satisfaction to construct the objective function, which can simultaneously optimize the two goals of annual comprehensive cost (ACC) and annual carbon emissions (ACE); the weight coefficients are introduced to reflect the different optimization preferences of decision-makers. The entire optimization model belongs to mixed integer linear programming and the case study gives the results under the same emphasis on ACC and ACE (W1 = 0.5, W2 = 0.5). The initial purchase cost structure shows that the cost of gas turbines, hydrogen storage tanks, and photovoltaic accounts for more than 70%. The cost of HES is high but the carbon emissions reduction effect of the system is considerable, and the ACE is only 6.63% of the traditional supply system. In the third part, sensitivity analysis results show that different optimization preferences could significantly affect the configuration results and the "cost-effectiveness" performance corresponding to each preference is different. The optimal optimization strategy interval is (W1 = 0.3, W2 = 0.7) to (W1 = 0.4, W2 = 0.6). The comparative analysis shows that the simulation results are reliable. Further analysis reveals that the current carbon tax base price is extremely unsatisfactory for the stimulus effect of the IES. Therefore, it is recommended to increase the base price of the current carbon tax.
机译:综合能源系统(IE)与可再生能源发电和氢能存储(HES)相结合,是实现清洁和低碳能耗的有效途径,具有巨大的发展潜力。如何合理地确定系统配置方案是需要紧急解决的重要问题。本文构建了配置优化模型。首先,给出了数学模型,客观函数,优化策略和约束。然后,本研究创新了基于偏差满足的优化策略来构建目标函数,可以同时优化年度综合成本(ACC)和年度碳排放(ACE)的两个目标;引入重量系数以反映决策者的不同优化偏好。整个优化模型属于混合整数线性编程,案例研究在ACC和ACE相同的强调下给出了结果(W1 = 0.5,W2 = 0.5)。初始购买成本结构表明,燃气轮机,储氢罐和光伏占70%以上的成本。 HES的成本很高,但系统的碳排放效果很大,ACE只有6.63%的传统供应系统。在第三部分中,敏感性分析结果表明,不同的优化偏好可能会显着影响配置结果,并且对应于每个偏好的“成本效益”性能不同。最佳优化策略间隔(W1 = 0.3,W2 = 0.7)至(W1 = 0.4,W2 = 0.6)。比较分析表明,仿真结果是可靠的。进一步的分析表明,对于IES的刺激效应,目前的碳税基本价格极为不满意。因此,建议增加当前碳税的基本价格。

著录项

  • 来源
    《Energy Conversion & Management》 |2021年第9期|114340.1-114340.18|共18页
  • 作者单位

    North China Elect Power Univ Sch Econ & Management Beijing 102206 Peoples R China|North China Elect Power Univ Beijing Key Lab New Energy & Low Carbon Dev Beijing 102206 Peoples R China;

    North China Elect Power Univ Sch Econ & Management Beijing 102206 Peoples R China|North China Elect Power Univ Beijing Key Lab New Energy & Low Carbon Dev Beijing 102206 Peoples R China;

    Univ Arizona Dept Syst & Ind Engn Tucson AZ 85721 USA;

    North China Elect Power Univ Sch Econ & Management Beijing 102206 Peoples R China|North China Elect Power Univ Beijing Key Lab New Energy & Low Carbon Dev Beijing 102206 Peoples R China;

    Jinan Univ Energy & Elect Res Ctr Zhuhai 519070 Peoples R China;

    North China Elect Power Univ Sch Econ & Management Beijing 102206 Peoples R China|North China Elect Power Univ Beijing Key Lab New Energy & Low Carbon Dev Beijing 102206 Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Integrated energy system; Multi-energy complementary; Configuration optimization; Optimal sizing; Deviation satisfaction strategy; Optimization preference;

    机译:集成能量系统;多能量互补;配置优化;最优施胶;偏差满意度策略;优化偏好;

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