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Optimization of microenergy grid including adiabatic compressed air energy storage by considering uncertainty of intermittent parameters
Energy Science & Engineering ( IF 3.5 ) Pub Date : 2021-09-06 , DOI: 10.1002/ese3.970 Fei Hu 1 , Xisheng Zhan 1 , Behdad Arandian 2
Energy Science & Engineering ( IF 3.5 ) Pub Date : 2021-09-06 , DOI: 10.1002/ese3.970 Fei Hu 1 , Xisheng Zhan 1 , Behdad Arandian 2
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In recent years, zero-carbon energy resources such as adiabatic compressed air energy storage with thermal energy storage have been interested due to growing concerns over global warming. This study proposes a microenergy grid including heat and power networks connected through adiabatic compressed air energy storage with thermal energy storage, which can be considered hybrid energy storage supplying power for both networks. The power network is supplied with the main grid and wind turbine systems, and the heat network is provided with heat pumps. The objective function minimizes power purchased from the main grid and power demand of heat pumps in the heat network. Since uncertainty plays a key role in the operation of integrated energy systems, the uncertainty of intermittent parameters such as active and reactive load and wind speed data has been considered in this study. Therefore, predicted values are used in the optimization problem instead of using deterministic values for such uncertain parameters. To do this, an efficient 2-level corrective forecasting algorithm is proposed to have an accurate prediction for the day-ahead operation of the microenergy grid. Different scenarios are presented to show the importance of the forecasting method and the utilization of adiabatic compressed air energy storage with thermal energy storage in the system’s structure. The results indicate that corrective actions on the predicted load and wind speed data decrease the operation cost of the microenergy grid from 57.13% to 13.21%. Also, it is found that neglecting adiabatic compressed air energy storage with thermal energy storage in the structure of the microenergy grid increases operation cost to 3423 US$. Other obtained results also indicate the importance of coutilization of compressed air energy storage with thermal energy storage and 2-level corrective forecasting method leading to optimal operation of the microenergy grid.
中文翻译：
考虑间歇参数不确定性的含绝热压缩空气储能的微能源网优化
近年来，由于对全球变暖的担忧日益加剧，诸如具有热能存储的绝热压缩空气储能等零碳能源备受关注。本研究提出了一个微能源电网，包括通过绝热压缩空气储能和热储能连接的热电网络，可以认为是混合储能为这两个网络供电。电网由主电网和风力涡轮机系统供电，热网配备热泵。目标函数最小化从主电网购买的电力和热网中热泵的电力需求。由于不确定性在综合能源系统的运行中起着关键作用，本研究考虑了间歇性参数的不确定性，例如有功和无功负载以及风速数据。因此，在优化问题中使用了预测值，而不是对此类不确定参数使用确定性值。为此，提出了一种高效的 2 级校正预测算法，以准确预测微能源电网的日前运行。提出了不同的方案，以显示预测方法的重要性以及系统结构中绝热压缩空气储能和热储能的利用。结果表明，对预测的负荷和风速数据采取纠正措施将微电网的运行成本从 57.13% 降低到 13.21%。还，结果表明，在微能网结构中忽略带热能存储的绝热压缩空气储能使运行成本增加到3423美元。其他获得的结果也表明压缩空气储能与热储能的协同利用和两级校正预测方法导致微电网优化运行的重要性。
更新日期：2021-11-02
中文翻译：
考虑间歇参数不确定性的含绝热压缩空气储能的微能源网优化
近年来，由于对全球变暖的担忧日益加剧，诸如具有热能存储的绝热压缩空气储能等零碳能源备受关注。本研究提出了一个微能源电网，包括通过绝热压缩空气储能和热储能连接的热电网络，可以认为是混合储能为这两个网络供电。电网由主电网和风力涡轮机系统供电，热网配备热泵。目标函数最小化从主电网购买的电力和热网中热泵的电力需求。由于不确定性在综合能源系统的运行中起着关键作用，本研究考虑了间歇性参数的不确定性，例如有功和无功负载以及风速数据。因此，在优化问题中使用了预测值，而不是对此类不确定参数使用确定性值。为此，提出了一种高效的 2 级校正预测算法，以准确预测微能源电网的日前运行。提出了不同的方案，以显示预测方法的重要性以及系统结构中绝热压缩空气储能和热储能的利用。结果表明，对预测的负荷和风速数据采取纠正措施将微电网的运行成本从 57.13% 降低到 13.21%。还，结果表明，在微能网结构中忽略带热能存储的绝热压缩空气储能使运行成本增加到3423美元。其他获得的结果也表明压缩空气储能与热储能的协同利用和两级校正预测方法导致微电网优化运行的重要性。
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