A two-stage optimal scheduling method for combined heat and power systems considering thermal inertia

Abstract

Combined heat and power (CHP) system has the outstanding advantages of environmental protection,economy and flexible operation mode,and has a better development prospect. Based on the different characteristics of electricity and heat in transmission and storage,a two-stage optimal scheduling method for CHP system considering thermal inertia is proposed. In the first stage,considering the structure and operation characteristics of the heating network,the optimal scheduling model of the CHP system based on model predictive control is established,and the strategy of intra-day controllable equipment output and grid interactive power is optimized. In the second stage,the goal is minimize the output adjustment of each unit in CHP system,and the real-time prediction error of renewable energy and load is taken into account to dynamically adjust the economic scheduling strategy in the first stage. The example shows that the two-stage optimal scheduling model can improve the economy of system operation and make up for the imbalance of supply and demand. Combined with the thermal inertia of the system,the building can store or release heat according to load demand and time-of-use electricity price,which can reduce the impact of renewable energy and load uncertainty on scheduling,smooth power fluctuations,and promote heat and power complementation.

Keywords

• combined heat and power (chp)
• thermal inertia
• model predictive control (mpc)
• two-stage optimization
• dynamic optimal scheduling
• convolutional neural network