Optimization of Distributed Generators in a Virtual Power Plan Using Mixed Integer Linear Programming Method

• Main Authors: Ahmed Abubakar, Elwan, Mohd Hafiz, Habibuddin, Yanuar Zulardiansyah, Arief, Siti Nur Aisyah, Mohd Sharan, Rasyidah, Mohamad Idris
• Other Authors: Hasmat, Malik
• Format: Book Chapter
• Language: English
• Published: Springer Nature Singapore Pte Ltd 2024
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://ir.unimas.my/id/eprint/44382/1/Optimization%20of.pdf; http://ir.unimas.my/id/eprint/44382/; https://doi.org/10.1007/978-981-99-6749-0_22
• Institution: Universiti Malaysia Sarawak

Power utilities worldwide face capacity expansion challenges due to costs, land availability, and environmental sustainability. Increased demand and the need to build a reliable and resilient network have compelled power utilities to organize competitively distributed generators to compensate for any supply surge. These distributed power generation units are small and dispersed, making control difficult. To find a solution that is both economical and sustainable, a virtual power plant is formed from diesel generators with a capacity of 5.6 MW, a waste-to-energy (WtE) power generating plant with a capacity of 1 MW, a wind power plant with a capacity of 0.6 MW, and a photovoltaic (PV) power plants with a capacity of 0.4 MW. The distributed generators were optimally integrated into a virtual power plant and for the best integration solution, a Deming wheel, also known as the plan, do, check, and act (PDCA) method and mixed integer linear programming (MILP) were used in an Excel solver. The simulation results show that the total VPP power generated from the sources is 6.33 MW, with renewable energy sources accounting for 1.6 MW (25% of the total) and a cost estimate of 0.5$/kW. Diesel and wind contribute the least in comparison with their capacities, while others contribute the most (100% of the capacities).