With the further advancement of electricity market reform, the introduction of policies such as time-of-use price has provided a favorable market environment for the development of demand response technology applications. Demand response equipment for cooling power loads, represented by cold storage air conditioning systems, can effectively alleviate the challenge of balancing power supply and demand. The demand response capability and potential benefits of cooling power loads are closely related to the investment planning and operation methods of demand response equipment. The existing investment planning methods for demand response equipment based on cooling storage technology mostly consider a single equipment type and carry out operational simulations based on fixed or simplified system operation strategies and equipment operation characteristics, which makes it difficult to optimize the combination of different types of equipment to suit the demand characteristics of the customer's cooling load, resulting in limited space for optimization of the system's demand response capability and failure to give full play to its economic value. Therefore, this paper investigates a unified investment planning modelling approach for cooling power load demand response equipment that considers the optimization of operating strategies. We take the cold storage air-conditioning system as the basis for the cooling load demand response equipment, and carry out research on the operation strategy optimization method and the optimal investment planning method of the cold storage air-conditioning system. Firstly, this paper briefly analyses the working principle and typical operation strategy of the cold storage air-conditioning system. Based on this, it proposes a model for optimizing the operation strategy of the cold storage air-conditioning system, or the demand response model for cooling loads, taking into account multiple types of chiller and cold storage equipment in the electricity market environment. Considering the switching characteristics of equipment working conditions, the proposed model indicates the working conditions of equipment by introducing integer variables, thus realizing flexible combination and switching of different working conditions of equipment; considering the non-linear relationship between the input power and output cooling capacity of chillers, the proposed model adopts segmental linearization technology to deal with the non-linear operating characteristics of chiller. Thus it constructs a mixed integer linear programming model to optimize the supply of the customer's cooling load demand, achieve a flexible response of the cooling power load to the electricity price signal and save electricity costs. Secondly, this paper constructs a demand response equipment investment planning model embedded with a unified operation strategy optimization model. The model takes the minimization of the total cost of customer investment and operation as the optimization objective, takes into account the tariff policy, the demand characteristics of the cold load, the investment cost and operating characteristics of the relevant equipment. It effectively resolves the coupling constraints between equipment investment and operation variables through a linear modelling method based on the Big M method, and finally establishes a mixed integer linear programming model, which can be efficiently solved by using a commercial solver. The example analysis compares the results of equipment investment considering different operating strategies. The results show that when the optimization strategy proposed in this paper is considered, the system can be flexibly adjusted according to the price and load characteristics of each operating scenario, with the lowest total system investment operating costs and the highest corresponding system investment benefits. Therefore, it is necessary to consider the optimization operation strategy in conjunction with the investment planning of the cold storage system, which can effectively reduce the total system investment and operation cost, optimize the electricity load curve and give full play to the application value of the ice storage air-conditioning technology.