|
| 矿井水耦合废弃矿洞复合储能的矿区综合能源系统DQN优化模型 |
| DQN optimisation model for mine integrated energy system with composite energy storage in mine water coupled to abandoned mine caverns |
| 投稿时间：2025-01-27 修订日期：2025-06-25 |
| DOI： |
| 中文关键词: 废弃矿洞 压缩空气储能 抽水蓄能 深度Q网络算法 综合能源系统 |
| 英文关键词: abandoned mine compressed air energy storage pumped storage DQN algorithm integrated energy systems |
| 基金项目:黑龙江省省属高校基本科研业务费项目(2024-KYYWF-1055) |
|
| 摘要点击次数: 24 |
| 全文下载次数: 0 |
| 中文摘要: |
| 针对矿区废弃资源浪费和规模化储能的迫切需求问题，充分利用矿区废弃地下矿洞空间资源，结合矿井涌水巨大位势落差的储蓄能力及其所蕴含的低焓值地热能量，采用多层级能量回收方式减小资源浪费，将抽水蓄能、压缩空气储能和水源热泵技术耦合，提出复合储能型矿区综合能源系统架构。为克服传统优化建模方法的局限，将综合能源系统运行优化问题转化为马尔可夫决策过程，以系统运行净利润、风电消纳、低碳排放为目标，基于深度Q网络强化学习算法建立矿区综合能源系统优化调度模型。最后利用不同场景进行算例仿真分析，验证了DQN优化模型能够较好解决系统非线性和风电、负荷的不确定性问题，并保障了调度策略的实时响应能力。而且，提出的系统模型能够有效节约能量，提高储能密度，获得较好的经济和环境效益。 |
| 英文摘要: |
| Aiming at the waste of waste resources in mining areas and the urgent demand for large-scale energy storage， we make full use of the space resources of the waste underground mines in mining areas， combine the saving capacity of the huge potential difference of the mine water and the low-enthalpy geothermal energy contained in it， adopt a multi-level energy recovery method to reduce the waste of resources， and couple pumped storage， compressed air energy storage and water-source heat pump technology， and put forward the architecture of the composite energy storage type comprehensive energy system of the mining areas.In order to overcome the limitations of traditional optimisation modelling methods， the integrated energy system operation optimisation problem is transformed into a Markov decision-making process， and the integrated energy system optimisation scheduling model for mining area is established based on the deep Q-network reinforcement learning algorithm with the objectives of net profit of the system operation， wind power consumption， and low carbon emission. Finally， different scenarios are used to carry out example simulation analysis， which verifies that the DQN optimisation model is able to better solve the system nonlinearity and uncertainty of wind power and load， and guarantees the real-time responsiveness of the scheduling strategy. Moreover， the proposed system model can effectively save energy， improve the energy storage density， and obtain better economic and environmental benefits. |
|
View Fulltext
查看/发表评论 下载PDF阅读器 |
| 关闭 |