Smart Grids and Machine Learning in Chinese and Western Intellectual Property Law

Abstract

Having huge power grids successfully integrate sustainable energy sources requires a smart and flexible power grid management system. Such smart systems have to adapt fast and accurately to a great amount of data input – a task which is made easier by applying modern machine learning technology. Solutions crafted by dynamic and powerful computing algorithms have the potential to surpass human cognitive capabilities. The question arises whether and how intellectual property law can be used to set the right incentives. This paper initially describes the basic functions of smart grids and the corresponding necessity of machine learning. Subsequently, it will analyze the current approaches of the most relevant patent offices in dealing with the challenges of AI-related smart grid inventions. Ultimately, it will be demonstrated that the contemporary discussions fail to focus on practical considerations of market entry possibilities that might be more promising than the approach of creating new exclusionary intellectual property rights.

Data-Driven Methods of Machine Learning in modeling the Smart Grids

“…ML-based algorithms also help in producing reliable data and the addition of other sources of information. This enhances the flow of information between different parts of the SG [7]. In intellectual property law, there are various legal issues in classifying and protecting ML systems, as well as the related target algorithms or other innovations [8].…”