In response to the current problems of high volatility in wind and photovoltaic power generation and difficulties in consumption in typical areas

a new hybrid energy system optimization scheduling method for promoting wind and solar consumption through geothermal power generation is proposed by incorporating reliable and rapidly climbing geothermal power generation into the hybrid energy system. Taking into account both operational costs and risks

and constrained by physical characteristics of the power units

a multi-objective optimization dispatch model for the new hybrid energy system is established. A rolling repair strategy is introduced to correct the initial values of the population

and the model is solved based on the adaptive trade-off model and the non-dominated sorting genetic algorithm Ⅱ. This algorithm is more suitable for solving high-dimensional

complex constraint problems compared with the conventional algorithms and offers a faster convergence rate. Through a comparative analysis of two scenarios during typical winter days in a specific region of Tibet

geothermal power is found to enhance the absorption rates of wind and solar energy by 8.0% and 7.9%

respectively. Simultaneously

the system's operating costs decreases by 2.5%

and risk indices decreases by 7.1%.These findings underscore the role of geothermal power in promoting the integration of wind and solar energy and improving the overall reliability of the power system. The research provides valuable theoretical support for decision-making and scheduling in hybrid energy systems.