Energy Storage Configuration of Distribution Networks Considering Uncertainties of Generalized Demand-Side Resources and Renewable Energies

With the growing proportion of advanced metering infrastructures and intelligent controllable equipment in power grids, demand response has been regarded as an effective and easily implemented approach to meet the demand–supply equilibrium. This paper innovatively proposes generalized demand-side resources combining the demand response with an energy storage system and constructs a configuration model to obtain scheduling plans. Firstly, this paper analyzes the characteristics of generalized demand-side resources and models the translational loads, reducible loads and energy storage system. Secondly, a deterministic energy storage configuration model aiming at achieving the lowest operation cost of distribution networks is established, from which the scheduling scheme of generalized demand-side resources can be obtained. Then, the fuzzy membership function and the probability density function are used to represent the uncertainty of the demand response, the prediction error of renewable energy output and the generalized demand-side resources that do not participate in the demand response. Therefore, this paper simulates daily operations to modify the capacity of energy storage. The problem is solved by using Monte Carlo simulation, fuzzy chance-constrained programming and mixed-integer programming. Finally, the effectiveness of this model is demonstrated with case studies in a 33-node distribution network. The results show that the uncertainty of this system is solved effectively. When only considering generalized demand-side resources, the total cost is reduced by 9.5%. After considering the uncertainty, the total cost is also decreased 0.3%. Simultaneously, the validity of the model is verified