In order to alleviate the burden of continuous increasing energy consumption falling on the power system and solve the complex calculation problem in the joint dispatching of large-scale electrical equipment, a hybrid decentralized optimization of dispatching the large-scale controllable appliances and energy storage equipment considering demand side response was proposed in this paper. Firstly, two mathematical models of controllable electrical equipment load and energy storage equipment were established. On this basis, a mixed integer non-linear centralized optimization model was mathematically formulated under the constraints of the operation characteristics of the system and equipment, with the objective of minimizing the sum of electricity purchase cost, users’ dissatisfaction cost and energy storage equipment loss cost. Secondly, for tackling the difficult nonlinear centralized optimization problems of high dimensionality, multi objectives and multiple constraints, the Lagrange relaxation method was used to decompose the problem into two sub-problems, namely, optimally scheduling the controllable electrical equipment load and optimizing the dispatch of the energy storage equipment. Then, the former was further decomposed into optimizing dispatch of each controllable electrical equipment and solved by the interior point method, while the latter was decomposed into a set of mixed integer linear optimization sub-problems of scheduling each energy storage equipment and solved in parallel by the Benders decomposition method. Thirdly, a series of numerical simulations together with comparison analysis were performed to verify the effectiveness and superiority of the proposed dispatch optimization method. For example, the optimization objective value and the optimal dispatch solution corresponding to the proposed method were illustrated and compared with those of the centralized method to demonstrate the effectiveness of the hybrid decentralized optimization method. And the influence of different numbers of dispatching equipment on the computation efficiency was investigated on the centralized and decentralized optimization method to show the superiority of the proposed hybrid decentralized optimization method. According to the numerical simulation results, the optimization objective value of the proposed method is basically consistent with that of the centralized. Moreover, the identified dispatch solution enables to efficiently respond to the time-of-use and results in good effect of peak-shaving and valley-filly. Besides, the calculation efficiency of the proposed hybrid decentralized optimization method is of high computation efficiency and not affected by the increasing number of the schedulable electrical equipments.