Community microgrid planning in Lombok Island: an Indonesian case study

Rural electrification, diesel generator replacement, and resilient electrification systems against natural disasters are among the main targets for Perusahaan Listrik Negara (PLN) in Indonesia to achieve a universally accessible, resilient, and environment-friendly electricity supply. Microgrids, therefore, become a popular and available way to achieve the aforementioned targets due to their flexibility and resiliency. This paper aims to provide a resilience-oriented planning strategy for community microgrids in Lombok Island, Indonesia. A mixed-integer linear program, implemented in the distributed energy resources customer adoption model (DER-CAM), is presented in this paper to find the optimal technology portfolio, placement, capacity, and optimal dispatch in a community microgrid. The multinode model is adopted for the planning, and hence, power flow constraints, N-1 contingency, and technology constraints are considered. The results show that the placement of photovoltaic (PV) arrays, battery energy storage systems (BESSs), and diesel generators (DGs) as backup sources in multi-node community microgrids lead to multiple benefits, including 100% rural electrification, over 25% cost savings, as well as over 22%, in particular CO2 emission reduction in multinode community microgrids.

Automated summary

Rural electrification, diesel generator replacement, and resilient electrification systems against natural disasters are important targets for Perusahaan Listrik Negara (PLN) in Indonesia. Microgrids are seen as a popular and flexible solution to achieve these goals. This paper presents a resilience-oriented planning strategy for community microgrids in Lombok Island, Indonesia, using a mixed-integer linear program implemented in the DER-CAM model. The results show that placing photovoltaic arrays, battery energy storage systems, and diesel generators in multi-node community microgrids can lead to multiple benefits, including 100% rural electrification, cost savings of over 25%, and CO2 emission reduction of over 22% in multinode community microgrids.