A Multi-Objective Time - Series Optimization for Optimum Planning Design of Integrative Power System with the Effects of Multi-Dimensional Sources of Uncertainty

Time series aggregation (TSA) procedures are used to simplify data entry and enhance solution efficiency. This study suggested a two-step multi-objective optimization framework for TSA strategy determination. TSA methodologies for optimum MES design and operation were used to create the multi-energy system's preliminary design. In the second step, the system's total annual cost, as well as loss of load probability (LSLP), were used as objectives, or the optimal combination of the several objectives was found optimal TSA strategy for the MES's structure and performance. The ideal energy-storage MES design proved the method's efficacy. TSA techniques were compared and analyzed for architectural schemes & system performance variations. The findings show that the initial full-time series data may be used to verify the viability of the best MES design schemes and quantify the departure of outcomes from alternative TSA procedures. LSLP decrease raises expenses. The TAC of the framework improves from $9.79 x 10(7) to $1.56 x 10(8) when the LSLP reduces to 7.90% to zero in the numerous grids method (TG1) with 730-time steps (TS). To fulfill energy system demand, the minimal LSLP approach must be chosen. The best TSA tactics for MES design may be chosen based on unique needs.