Research on dynamic optimization of electric thermal integrated energy system with high proportion of new energy access

The fluctuation of new energy is large, and predictive control is difficult, challenging the scheduling of electric heating energy systems. Therefore, it is necessary to design dynamic optimization algorithms to adapt to unstable inputs. This study explores dynamic optimization methods for electric heating systems with a high proportion of new energy integration. Based on the integrated structure of photovoltaic wind electric heating system, the relationship between energy and power of energy storage equipment and the influencing factors of operation strategy were analyzed. Based on this, calculate the target fluctuation power, construct an optimization objective function, and achieve system oscillation control optimization. The experiment shows that this method can stabilize the load state, reduce the charging and discharging frequency, and improve the capacity utilization and power stability of the electric heating system.