基于深度强化学习的柔性移动微电网设计与规划
Design and Planning of Flexible Mobile Micro-Grids Using Deep Reinforcement Learning
摘要：
气候变化带来的持续风险已经影响到全球游牧社区的生计，并可能导致未来几年移民流动的增加。因此，在能源系统规划中，特别是在发展中国家实现能源获取方面，流动性考虑变得越来越重要。先进的即插即用控制策略最近已经开发出这样一个分散的框架，更容易允许游牧社区相互之间以及与主电网的互连。基于此，本文研究了游牧社区移动式多能源供应系统的设计与规划策略。受相关不确定性的规模和维度的影响，在30年的规划范围内影响所有主要的设计和决策变量，深度强化学习（DRL）被用于解决设计和规划问题。基于DRL的解决方案以几种刚性基线设计选项为基准，以比较不确定性下的预期性能。蒙古蒙古包社区的一项案例研究结果表明，流动游牧能源系统在技术上和经济上都是可行的，特别是在考虑到灵活性时，尽管家庭之间的空间分散程度是一个重要的限制因素。对成本、等效排放量和未满足总负荷等关键经济、可持续性和弹性指标进行了测量，表明与现有基线相比，潜在的改善分别高达25%、67%和76%。最后，分解的灵活性和即插即用操作的价值是使用实物期权理论的变化，游牧社区和政策制定者的重要影响，重点是使他们的能源获取。
英文摘要：
Ongoing risks from climate change have impacted the livelihood of global nomadic communities, and are likely to lead to increased migratory movements in coming years. As a result, mobility considerations are becoming increasingly important in energy systems planning, particularly to achieve energy access in developing countries. Advanced Plug and Play control strategies have been recently developed with such a decentralized framework in mind, more easily allowing for the interconnection of nomadic communities, both to each other and to the main grid. In light of the above, the design and planning strategy of a mobile multi-energy supply system for a nomadic community is investigated in this work. Motivated by the scale and dimensionality of the associated uncertainties, impacting all major design and decision variables over the 30-year planning horizon, Deep Reinforcement Learning (DRL) is implemented for the design and planning problem tackled. DRL based solutions are benchmarked against several rigid baseline design options to compare expected performance under uncertainty. The results on a case study for ger communities in Mongolia suggest that mobile nomadic energy systems can be both technically and economically feasible, particularly when considering flexibility, although the degree of spatial dispersion among households is an important limiting factor. Key economic, sustainability and resilience indicators such as Cost, Equivalent Emissions and Total Unmet Load are measured, suggesting potential improvements compared to available baselines of up to 25%, 67% and 76%, respectively. Finally, the decomposition of values of flexibility and plug and play operation is presented using a variation of real options theory, with important implications for both nomadic communities and policymakers focused on enabling their energy access.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
