In order to meet the growth in demand and the renewable energy integration target, the Sulawesi Electricity System (SES) should be expanded. Currently, the SES is divided into two systems, namely South and North Sulawesi. These two systems have different characteristics, such as the system size, reliability and operational cost. North Sulawesi is smaller, weaker and more expensive than the South System. In order to improve the system reliability, generation and transmission expansion planning should be executed simultaneously to meet the economical investment cost and satisfy the reliability standard. For this purpose, the necessity of a backbone system with a higher voltage level than the existing 150 kV system should be considered, including the interconnection option between the two existing systems in Sulawesi. A methodology based on economic and technical criteria was developed to determine the backbone voltage level. Two voltage level options were considered, namely 275 and 500 kV. Several criteria were considered in order to determine the backbone voltage level, including the economic voltage, the line-loading limit, N-1 contingency, short circuiting, transient stability, voltage stability and small signal stability. The backbone voltage candidates should fulfil all of the criteria. The simulation was conducted in base- and high-demand scenarios, considering the fluctuation of future economic growth. The load flow and the dynamic analysis were simulated in a DIgSILENT Power Factory environment. The results showed that the 275 kV backbone, which was built in 2022, would violate three criteria: the economic voltage, N-1 contingency and voltage stability. On the other hand, the 500 kV backbone voltage level fulfills all of the criteria. The result of this research was considered in the electricity planning documents in Sulawesi. From a technical and economical perspective, the 500 kV backbone was chosen for the SES.
Generation expansion planning considering renewable energy integration and optimal unit commitment: A case study of Afghanistan
