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

Ahmed Abubakar, Elwan and Mohd Hafiz, Habibuddin and Yanuar Zulardiansyah, Arief and Siti Nur Aisyah, Mohd Sharan and Rasyidah, Mohamad Idris (2024) Optimization of Distributed Generators in a Virtual Power Plan Using Mixed Integer Linear Programming Method. In: Renewable Power for Sustainable Growth : Proceedings of ICRP 2023. Lecture Notes in Electrical Engineering, 1086 . Springer Nature Singapore Pte Ltd, pp. 355-365. ISBN 978-981-99-6749-0

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Abstract

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).

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