| 董砚,卢禹,雷兆明,康学斌.风光储制氢下多台制氢机组优化调度研究[J].高技术通讯(中文),2022,32(1):77~83 |
| 风光储制氢下多台制氢机组优化调度研究 |
| Research on optimal scheduling of multiple hydrogen production units under wind/photovoltaic/energy-storage hydrogen production |
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| DOI：10.3772/j.issn.1002-0470.2022.01.009 |
| 中文关键词: 风光储； 制氢； 调度； 时序差分算法(TDA)； 多目标粒子群优化算法(MOPSO) |
| 英文关键词: wind/photovoltaic/energy-storage， hydrogen production， scheduling， temporal-difference algorithm (TDA)， multi-objective particle swarm optimization algorithm (MOPSO) |
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| 摘要点击次数: 1791 |
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| 中文摘要: |
| 以风光储制氢系统中多台制氢机组和储能电池的优化调度为研究对象，目标是制氢的经济效益最大化。根据调度对象和目标函数的特征分别采用改进时序差分算法（TDA）和多目标粒子群优化算法(MOPSO)进行优化调度，其中储能电池的调度起辅助作用，用来使风光出力曲线匹配制氢出力曲线。算例分析表明，文中所述改进时序差分算法在解决多台制氢机组调度的问题上有更好的效果，对于时段扩大后的出力匹配问题，调度储能电池出力后也能很好地解决。风光储制氢系统在追求经济效益的同时也具备很好的消纳能力，能很好地适应风能和太阳能的间歇性和波动性。 |
| 英文摘要: |
| The study focuses on the optimal scheduling of multiple hydrogen production units and energy storage battery in wind/photovoltaic/energy-storage hydrogen production system. Its goal is to maximize the economic benefits of hydrogen production. According to the characteristics of the scheduling objects and objective functions, improved temporal-difference algorithm (TDA) and multi-objective particle swarm optimization algorithm (MOPSO) are adopted to optimize scheduling. The scheduling of energy storage battery plays an auxiliary role to match the wind-photovoltaic output curve with the hydrogen production units output curve. Analysis of calculation examples shows that the reinforcement learning described in this paper has a better effect in solving the scheduling problem of multiple hydrogen production units. The scheduling of energy storage battery can solve the output match problem after the increased number of period well. Wind/photovoltaic/energy-storage hydrogen production system has both economic benefits and good consumption capacity, and can adapt well to the intermittency and fluctuation of wind and solar energy. |
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