A Multi-Objective VAR Planning Approach Considering Seasonal Variations of Wind Power and Solar PV

This paper proposes a stochastic multi-objective VAR planning technique that integrates seasonal variations in wind power, solar PV, and load and investigates their significant effect on the selection of VAR sources. To account for various system scenarios that could arise during the planning horizon, typical seasonal days that characterize seasonal variability associated with renewable energy sources (RES) and load are employed. The problem is described as an optimization problem with two conflicting objective functions that simultaneously yield the minimum possible investment and operating costs, as well as a sufficient VAR reserve that guarantees an appropriate security margin for all anticipated scenarios resulting from seasonal variations. The objective functions are optimized while maintaining a significant number of constraints at both the normal state and contingency situations for each hour of the typical seasonal days in the planning horizon. The problem is addressed using a hybrid strategy that combines conventional methods with the efficient multi-objective genetic algorithm NSGA-II. To demonstrate the viability of the presented methodology, it has been successfully tested on an IEEE 14-bus system.