可解释机器学习在电网调控领域中的应用OACSTPCD

Data driven machine learning is the core technology of the new generation of artificial intelligence.Although this technology has achieved significant results in the field of power grid dispatching and control,its poor interpretability hinders its practical engineering application in the field of power grid dispatching and control,which requires extremely high safety and reliability.Therefore,improving the interpretability of machine learning technology in the field of power grid dispatching and control is crucial for enhancing its practicality.Firstly,from the perspective of power grid dispatch operators,the definition,objectives,and significance of machine learning interpretability are analyzed.Then,the process of applying machine learning considering interpretability in the field of power grid dispatching and control is proposed,and typical machine learning interpretation techniques and their applications in power system prediction and stability assessment scenarios are introduced.The feasibility of applying this technology in the field of power grid dispatching and control is verified through practical cases.Finally,an analysis and outlook are conducted on the challenges faced by machine learning interpretable technologies in the field of power grid dispatching and control.Through this study,ideas and references are provided to solve the inexplicable problem of machine learning applications in the field of power grid dispatching and control,further promoting the practical engineering application of machine learning technology in this field.