A critical review of distribution system planning : optimal placement and sizing of distributed generation and energy storage devices in microgrids

The transformation of the traditional distribution system into a microgrid concept of upgradation requires assessing and planning for infrastructure that delivers electricity with improved management, higher reliability, and security, along with economical energy consumption pricing and environmentally friendly energy generation. Several key factors, including demand forecasts, planning policies, condition monitoring, proper infrastructure integration, and reliability standards, significantly influence the planning process. The distribution generation (DG) placement and sizing, along with energy storage devices (ESD), play a critical role in distribution system planning, affecting not only the existing operational performance but also the future expansion of the network and handling uncertainties for a reliable and secure power supply and management. With this motivation, this paper provides an extensive review of distribution system planning based on the placement and sizing of DG and ESD. The effect of DG integrated with ESD placement and sizing in microgrids on distribution system planning is discussed extensively. In addition, various methods related to analytical, numerical, evolutionary, and advanced computational techniques are discussed, specifying the strengths and limitations of each individual method. Standards and policy issues in the present scenarios are highlighted, along with all the critical issues of distribution system planning with DG and ESD integration. Uncertainty handling in distribution system planning based on DG and ESD placement and sizing is another crucial influence elaborated in this review. At last, the significant findings and associated research gaps, as well as future scope in this area, are highlighted. This review aims to inform readers about distribution system planning based on the placement and sizing of DG and ESS, with technical analysis, an extensive summary of previous research, identification of possible research gaps, and key findings.