A Study On Optimal Power System Reinforcement Measures Following Renewable Energy Expansion

Renewable energy generation capacity in Korea is expected to reach about 63.8 GW by 2030 based on calculations using values from a power plan survey (Korea's renewable energy power generation project plan implemented in September 2017) and the "3020" implementation plan prescribed in the 8th Basic Plan for Long-Term Electricity Supply and Demand that was announced in 2017. In order for the electrical grid to accommodate this capacity, an appropriate power system reinforcement plan is critical. In this paper, a variety of scenarios are constructed involving renewable energy capacity, interconnection measures and reinforcement measures. Based on these scenarios, the impacts of large-scale renewable energy connections on the future power systems are analyzed and a reinforcement plan is proposed based on the system assessment results. First, the scenarios are categorized according to their renewable energy interconnection capacity and electricity supply and demand, from which a database is established. A dynamic model based on inverter-based resources is applied to the scenarios here. The transmission lines, high-voltage direct current and flexible alternating current transmission systems are reinforced to increase the stability and capabilities of the power systems considered here. Reinforcement measures are derived for each stage of renewable penetration based on static and dynamic analysis processes. As a result, when large-scale renewable energy has penetrated some areas in the future in Korean power systems, the most stable systems could be optimally configured by applying interconnection measure two and reinforcement measure two as described here. To verify the performance of the proposed methodology, in this paper, comprehensive tests are performed based on predicted large-scale power systems in 2026 and 2031. Database creation and simulation are performed semi-automatically here using Power System Simulator for Engineering (PSS/E) and Python.