Affiliation:
1. School of Electrical Engineering and Informatics, Bandung Institute of Technology, Bandung 40132, Indonesia
2. Perusahaan Listrik Negara, PT PLN Persero, Jakarta 12160, Indonesia
3. School of Business and Management, Bandung Institute of Technology, Bandung 40132, Indonesia
Abstract
In Indonesia, the power generation sector is the primary source of carbon emissions, largely due to the heavy reliance on coal-fired power plants, which account for 60% of electricity production. Reducing these emissions is essential to achieve national clean energy transition goals. However, achieving this initiative requires careful consideration, especially regarding the complex interactions among multiple stakeholders in the Indonesian electricity market. The electricity market in Indonesia is characterized by its non-competitive and heavily regulated structure. This market condition often requires the PLN, as the system operator, to address multi-objective and multi-constraint problems, necessitating optimization in the generation dispatch scheduling scheme to ensure a secure, economical, and low-carbon power system operation. This research introduces a multiparadigm approach for GS optimization in a regulated electricity market to support the transition to clean energy. The multiparadigm integrates multi-agent system and system dynamic paradigms to model, simulate, and quantitatively analyze the complex interactions among multiple stakeholders in the Indonesian regulated electricity market. The research was implemented on the Java–Madura–Bali power system using AnyLogic 8 University Researcher Software. The simulation results demonstrate that the carbon policy scheme reduces the system’s carbon emissions while increasing the system’s cost of electricity. A linear regression for sensitivity analysis was conducted to determine the relationship between carbon policies and the system’s cost of electricity. This research offers valuable insights for policymakers to develop an optimal, acceptable, and reasonable power system operation scheme for all stakeholders in the Indonesian electricity market.
Reference60 articles.
1. National Energy Council of Indonesia (2024, July 17). Indonesia Energy Outlook. Available online: https://den.go.id/publikasi/Outlook-Energi-Indonesia.
2. International Energy Agency (IEA) (2022). An Energy Sector Roadmap to Net Zero Emissions in Indonesia, IEA.
3. Optimal Scheduling of Integrated Energy System under the Background of Carbon Neutrality;LV;Energy Rep.,2022
4. Logenthiran, T., Srinivasan, D., Khambadkone, A.M., and Aung, H.N. (2010, January 6–9). Multi-Agent System (MAS) for Short-Term Generation Scheduling of a Microgrid. Proceedings of the 2010 IEEE International Conference on Sustainable Energy Technologies (ICSET), Kandy, Sri Lanka.
5. Alam, M.S., Hari Kiran, B.D., and Kumari, M.S. (October, January 28). Priority List and Particle Swarm Optimization Based Unit Commitment of Thermal Units Including Renewable Uncertainties. Proceedings of the 2016 IEEE International Conference on Power System Technology (POWERCON), Wollongong, NSW, Australia.