The number of plug-in electric vehicles (PEVs) has rapidly increased owing to the government’s active promotion policy worldwide. Consequently, in the near future, their charging demand is expected to grow enough for consideration in the planning process of the transmission system. This study proposes a stochastic method for modeling the PEV charging demand, of which the time and amount are uncertain. In the proposed method, the distribution of PEVs is estimated by the substations based on the number of electricity customers, PEV expansion target, and statistics of existing vehicles. An individual PEV charging profile is modeled using the statistics of internal combustion engine (ICE) vehicles driving and by aggregating the PEV charging profiles per 154 kV substation, the charging demand of PEVs is determined for consideration as part of the total electricity demand in the planning process of transmission systems. The effectiveness of the proposed method is verified through case studies in the Korean power system. It was found that the PEV charging demand has considerable potential as the additional peak demand in the transmission system planning because the charging time could be concentrated in the evening peak time.

As Korea aims to increase the extent to which renewable energy sources (RES) account for up to 20% of the total power generated in the country by 2030, the feasibility of this target is a major concern. This concern largely results from the Korean power system possessing unique characteristics, such as its electrical isolation and high density. To achieve the RES target, the reliable operation of the power system must coexist with an increased share of RES power generation. This study proposes a method to evaluate the penetration limit of RES in the Korean power system considering the existing plans for the long-term electricity supply and demand, as well as its operational requirements. The Korea electric power corporation (KEPCO) planning database of the Korean power system for the next 15 years was employed to determine the penetration limit of RES considering the reliability criteria, including the minimum power generation of conventional sources, primary frequency control requirement, 10-min reserve requirement, and frequency stability.

To fulfill the need of operating power systems more effectively through diverse resources, frequency control conditions for maintaining a balance between generators and loads need to be provided accurately. As frequency control is generally achieved via the governor responses from local generators and the automatic generation control (AGC) frequency control of the central energy management system, it is important to coordinate these two mechanisms of frequency control efficiently. This paper proposes a dynamic-model-based AGC frequency control simulation method that can be designed and analyzed using the governor responses of generators, which are represented through dynamic models in the planning stage. In the proposed simulation model, the mechanism of the AGC frequency control is implemented based on the dynamic models of the power system, including governors and generators; hence, frequency responses from the governors and AGC can be sequentially simulated to coordinate and operate these two mechanisms efficiently. The effectiveness of the proposed model is verified by simulating the AGC frequency control of the Korean power system and analyzing the coordination effect of the frequency responses from the governors and AGC.