Abstract
In recent years, distributed energy storage (DES) has experienced rapid growth and has been widely applied in active distribution networks (ADNs). Owing to the close correlation between the characteristics and the application scenarios, DES modeling needs to be parameterized separately for various application demands. In this paper, a parameterized model for optimal DES planning in ADNs is proposed. The typical scenarios for DES planning are generated by the clustering technique, containing the patterns of load demand, wind turbine output and photovoltaic output. Secondly, an optimal planning model of DES considering parameterized characteristics is established, which is essentially a mixed integer non-linear optimization problem. Then, the model is converted to a mixed-integer second-order cone programming model, which can be solved efficiently by available commercial software. Finally, case studies on the modified IEEE 33-node system and IEEE 123-node system verify the efficiency of the proposed method, and the effects of DES planning are validated by two evaluation indexes.
Highlights
With the integration of distributed generators (DGs) and flexible loads, traditional distribution systems are evolving into active distribution networks (ADNs) [1]
The typical scenarios for distributed energy storage (DES) planning are generated by a clustering technique, containing the patterns of load demand, wind turbine output and photovoltaic output
mixed-integer non-linear programming (MINLP) model is transformed into a mixed-integer second-order cone programming (MISOCP) model by convex conversion
Summary
With the integration of distributed generators (DGs) and flexible loads, traditional distribution systems are evolving into active distribution networks (ADNs) [1]. Many works in the literature have studied on the sizing and allocation of DES in ADNs. A combined genetic algorithm and sequential quadratic programming method is proposed in [19], and further testify the potential economic benefits of energy storage systems. For the reason that the cost of different DES types varies enormously, it is necessary to compare the costs of different types of energy storage in different scenarios and choose the optimal DES selection to maximize economic benefits. There is a need to propose a parameterized model, which can transform the efficiency, life cycle, and other characteristics of multiple DES types into parameterized representation. This paper proposes a parameterized model for optimal DES planning in ADNs. The main contributions are summarized as follows:. Parameterized Modeling of Optimal DES Planning in Active Distribution Networks (ADNs)
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