A proportion prediction model of terminal energy structure of IPS based on hidden markov chain

Abstract With the development of clean energy and advanced technologies, the application of industrial product-service system (IPS2) in power systems become possible. Accurate and scientific analysis of terminal energy consumption competitiveness is an important theoretical basis for regional development planning and energy investment decision-making, and effectively promotes coordinated and rapid development of energy, economy and environment. Therefore, how to predict the terminal energy development scientifically and accurately is of great significance to the company operation and development of industrial product service system. This paper proposes a hidden Markov chain prediction model. The hidden state probability matrix is modified by five factors, such as energy intensity, economic development scale and population size. The difficulty and poor accuracy of traditional probability transfer matrix are solved, so the model can mine more intrinsic information of time series. The power grid companies should change from pure power suppliers to terminal energy service providers. The model is described and can be used as a decision support system for smart grid planning.