储能科学与技术2025，Vol.14Issue(5)：2057-2066,10.DOI:10.19799/j.cnki.2095-4239.2024.1127
基于集成神经网络的源-网-荷-储多能网络耦合优化调控研究
Research on coupled optimization and regulation of source network load storage multi energy networks based on integrated neural networks
摘要
Abstract
In multi-energy systems,the complexity of interconnections and the profound impact of system dynamics and uncertainties often lead to conflicts and trade-offs between components.These challenges make it difficult to maintain a dynamic balance between energy supply and demand.To address this challenge,a coupled optimization and control method for source network load storage multi-energy networks based on integrated neural networks is proposed.In addition,the proposed method considers the carbon emissions of multiple links in multi-energy systems,including source,grid,load,and storage,enabling comprehensive and accurate emission assessment.By combining a bidirectional weighted gated recurrent unit neural network with the Bagging ensemble algorithm,an ensemble neural network model can be constructed to capture contextual information about the time series data.By combining multiple weak learners,the proposed model significantly reduced the prediction error,achieving accurate carbon emission predictions in multi-energy networks.The regulation process focuses on three core optimization objectives:minimizing carbon emissions,and power generation costs,and maximizing the consumption of new energy.To address these challenges in complex multi-energy systems,the NSGA-II algorithm was applied to achieve comprehensive optimization regulation.The experimental results demonstrate that the proposed method accurately predicts carbon emissions.Furthermore,a regulation test demonstrated that the proposed method significantly improved the energy utilization efficiency,optimized the energy consumption,and enhanced the unit output stability.This research achievement is of great significance for sustainable development and efficient operation of multi-energy systems.关键词
集成神经网络/多能系统/源-网-荷-储/优化调控Key words
integrated neural network/multi energy system/source network load storage/optimizing regulation分类
信息技术与安全科学引用本文复制引用
赵爽,赵鹏远,丁万钦,刘斌,王文东,翟群芳,李小龙..基于集成神经网络的源-网-荷-储多能网络耦合优化调控研究[J].储能科学与技术,2025,14(5):2057-2066,10.基金项目
三峡金沙江川云水电开发有限公司永善溪洛渡电厂资助(Z412302062). （Z412302062）
