# Considering the Life-Cycle Cost of Distributed Energy-Storage Planning in Distribution Grids
## 1 Introduction
In a study by [PERSON] et al., considering the system economy, stability, carbon emissions, and renewable energy fluctuations at different time scales, the installation capacity of the battery and the supercapacitor, in the off-grid power system, was optimized and the optimal operation strategy of the system was proposed [10]. In a study by [PERSON] et al., the Life-Cycle Costs (LCCs) of different storage technologies (i.e., lead acid, NaS, and Li-ions) have been calculated to determine the capacity of distributed ESS with PV generation, but the coupling effect of the optimal location and operation of the system on the ESS capacity have not been taken into consideration [11]. In the environment of active distribution networks, with various types of DERs, ancillary services with novel trading schemes have also been proposed [12], to encourage active participation. A detailed literature survey leads to the understanding that the relevant short-life and high-cost of ESSs have been recognized as the main barriers to their wide-area deployment, therefore, the ESS planning with a detailed LCC model considering the impact of the charging/discharging cycles and the Depth of Discharging (DOD) levels etc., are crucial to carry out a comprehensive analysis from the life-cycle aspect. In addition, the network losses and voltage fluctuations affect the installation site and capacity of the ESSs, significantly, multiple-distributed ESSs coordination can reduce unnecessary ESS capacity, while ensuring optimal operation. In this paper, in order to improve the voltage profiles and network losses caused by PV integration and to improve the penetration level of PV in the future, a two-stage planning strategy which determines the optimal installation site and the optimal capacity of the multiple-distributed ESSs, utilizing the Genetic Algorithm (GA) combined with a Simulated Annealing (SA) is presented. Compared to the existing literature, the proposed method offers the following three main contributions. * The technical and economic characteristics of the various categories of ESSs are analyzed and the most suitable type of ESSs for a distribution network's optimal optimization, is selected. * The coupling effect between the sizing and sitting of the ESS are considered with a comprehensive LCC model, consequently, to achieve a distribution network optimization from the perspective of the whole project life with a minimum capacity and a limited infrastructure maintenance cost. * The two-stage heuristic optimization method utilizing GA combined with SA can achieve a good tradeoff among accuracy, convergence, and efficiency of optimization, and the SA can avoid the premature convergence of GA. The proposed method is demonstrated on a case study network to prove the feasibility and effectiveness in the ESS cost-reduction and the system economic performance improvement. The remaining of this paper is structured as follows: Section 2 describes the ESS characteristics and type selection; Section 3 presents the ESS installation site and a capacity optimization model; in Section 4, the sitting and sizing optimization method is described in details; in Section 5, a case study is carried out to verify the effectiveness and the concluding remarks are outlined in Section 6.