Study On The Optimization Method Of Wind Power Heat Pump Energy Storage System Based On GSA

Achieving "peak carbon emissions and carbon neutrality" is a crucial energy development goal for our country in the future.One of the key approaches to realizing this goal is the integration of wind energy,heat pumps,and energy storage systems.The rational allocation of capacities for various system components has a significant impact on the reliability and economy of wind power heat pump energy storage systems.This article briefly introduces the application background and research status of combining wind power and heating both domestically and internationally,designs an independent wind power heat pump energy storage system,and proposes an optimized capacity configuration scheme.The main research content is as follows:(1)First,the De ST software is utilized for building modeling in actual projects,performing hourly load calculations for buildings,and obtaining various data of the wind power system through actual measurements.Based on this,k-means clustering analysis is employed to derive the typical daily heat load curve and the typical daily wind power generation curve for the building and region.This information is then used to establish an integrated wind power heat pump energy storage system.(2)After preprocessing the wind power data of a wind farm in Shenyang,the Sobol global sensitivity analysis method is applied to conduct sensitivity analysis on input parameters,such as air pressure,wind deviation angle,70 m wind speed at the measurement tower,temperature,and humidity.Based on the analysis results,wind power output predictions are made using both BP neural networks and time series.It is found that neural network prediction is more suitable for wind power output forecasting,with predicted and measured values exhibiting similar trends and values,and a root mean square error of 18.23%.(3)This study introduces three typical application scenarios of energy storage systems and conducts sensitivity analysis on factors affecting the user-side economy of energy storage systems.It concludes that the unit capacity price and peak-valley price difference are the two main factors impacting the economy of user-side energy storage systems.Mathematical models are established for the main equipment of the wind power heat pump hybrid energy storage system,and different equipment is analyzed to lay the groundwork for subsequent simulation studies.(4)A particle swarm optimization algorithm is proposed for optimizing the capacity configuration of the wind power heat pump energy storage system.The system’s total cost and wind curtailment cost are set as objective functions,with wind power output,solid heat storage devices,and lithium battery units as constraints.The system is designed to achieve both wind power consumption and heating supply objectives.A practical project is used as an example for synchronized optimization calculations,and a sensitivity analysis is performed on the final optimization results.(5)Finally,the TRNSYS software is used to simulate the operational status of the wind power heat pump energy storage system.Parameters such as the COP of the water-source heat pump unit,the heating and heat absorption capacity of the heat pump unit,the state of charge and terminal voltage of the lithium battery unit,and the heat absorption and release capacity of the solid heat storage device are analyzed to verify the operational status of the wind power heat pump energy storage system.