| Penulis/Author |
Chico Hermanu Brillianto Apribowo (1); Prof. Dr. Ir. Sasongko Pramonohadi, DEA. (2); Prof. Dr. Eng. Ir. F. Danang Wijaya, S.T., M.T., IPM. (3); Dr. Ir. Mokhammad Isnaeni Bambang Setyonegoro, M.T. (4); Prof. Ir. Sarjiya, S.T., MT., Ph.D., IPU. (5) |
| Abstrak/Abstract |
Indonesia is a tropical climate country with considerable renewable electrical energy source prospects, including
photovoltaic (PV) and wind energies. Nevertheless, several variable renewable energy sources (VREs) have
exhibited uncertain attributes and substantial reliance on natural conditions, leading to unstable load-related
power supply risks. Hence, integrating battery energy storage systems (BESSs) with VRE generators is a
dependable approach to bolster renewable energy generator applications on a large-scale grid while providing
load demand flexibility. This study determined adequate sizing and placement of the BESS to achieve maximum
VRE generator penetration while considering the demand response flexibility. Key indicators, including technical
minimum load and system ramp capacity, were identified to achieve maximum penetration of thermal gener-
ators. This study also combined a unit commitment procedure with direct current optimal power flow (DC-OPF)
as a novel approach to determine the maximum VRE penetration level. An optimization problem model con-
cerning mixed integer linear programming (MILP) was subsequently employed in this study using the CPLEX
solver in the general algebraic modeling system (GAMS). The study is based on the IEEE RTS-24 system modified
and a real-life case study of the Lombok energy system in Indonesia. Results from the simulated Lombok power
system highlighted that optimal sizing and placement of the BESS could lower system costs by 37.66%, 33.63%,
and 22.26% compared to the current system conditions during the weekday, weekend, and the lowest day
scenarios, respectively. The VRE penetrations of the generators were also higher than the current system con-
ditions by 83%, 51%, and 39% during the weekday, weekend, and the lowest day scenarios, respectively. |
