Modeling Method of Multi-Energy Systems Based on LSTM Algorithm

Abstract

The development of the Energy Internet has improved the efficiency of energy utilization and promoted sustainable development of power and energy systems. The multi-energy system modeling considering the dynamic process of transmission line is one of the key research points of Energy Internet operation control. Through the energy circuit theory, the lumped parameter model of natural gas pipelines is built and the dynamic characteristic parameters under the control instruction are extracted. Combined with dynamic characteristic parameters, the long short-term memory (LSTM) neural network is designed to fit the natural gas pipeline dynamic process into discrete linear time-varying (LTV) equations. Combined with the equations, an energy hub method is used to build a control model of industrial parks with multi-energy distribution system. Using the rolling optimal control strategy given in this paper, the model is solved by the Matlab-Yalmip solver and rolling control instructions of each energy conversion unit are obtained. Finally, the case study demonstrates that the LSTM neural network-based modeling method presented in this paper can accurately fit the dynamic process of a natural gas pipeline system. The rolling control model of the multi-energy system can improve the efficiency of energy utilization, exhibit the transmission line status constraints during the optimization control process and improve reliability of the multi-energy system operation.

Keywords

• Energy hub
• LSTM
• multi-energy supply system
• pipeline system modeling