Analyzing the Effect of the Uncertainty Parameters on the Technical Virtual Power Plant's Optimal Operating Schedule

N owadays, due to the strong integration of renewable energy sources (RES) into distributed grids, Virtual Power Plants (VPPs) have been motivated and have gained significant attention. A concept of VPP is the Technical Virtual Power Plant (TVPP), which considers both commercial and technical aspects when participating in the electricity market. When considering a TVPP, the objective is to optimize profit when participating in the day-ahead (DA) market while ensuring compliance with the technical constraints of the power grid. However, it is difficult to achieve both requirements due to the uncertainty and unpredictability of the RES power output. This paper analyzes the effects of the uncertainty parameters, in this case, the photovoltaic (PV) power output, on the TVPP's operation schedule. Two-Stage Stochastic Optimization Model (TSSOM) and Two-Stage Chance - Constrained Optimization Model (TSCCOM) are applied to determine the optimal scheduling of a TVPP, including PVs, energy storage systems (ESS), and local loads. The TVPP's network is assumed to be the IEEE 15-bus test system. This paper solves the optimization models using GAMS and CPLEX. The results present that when the input of the optimization problem is uncertain, using the TSCCOM optimization program for scheduling operation problems of a TVPP gains better results in maximizing profits while ensuring compliance with technical constraints.