Optimal Power Flow with Uncertain Renewable Energy Sources Using Flower Pollination Algorithm

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Abstract

Optimal power flow (OPF) problem has become more significant for operation and planning of electrical power systems because of the increasing energy demand. OPF is very important for system operators to fulfill the electricity demand of the consumers efficiently and for the reliable operation of the power system. The key objective in OPF is to reduce the total generating cost while assuring the system limitations. Due to environmental emission, depletion of fossil fuels and its higher prices, integration of renewable energy sources into the grid is essential. Classical OPF, which consider only thermal generators is a non-convex, non-linear optimization problem. However, incorporating the uncertain renewable sources adds complexity to the problem. A metaheuristic algorithm which solves the OPF problem with renewable energy sources is to be implemented on a modified IEEE 30-bus system.

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Abdullah, M., Javaid, N., Khan, I. U., Khan, Z. A., Chand, A., & Ahmad, N. (2020). Optimal Power Flow with Uncertain Renewable Energy Sources Using Flower Pollination Algorithm. In Advances in Intelligent Systems and Computing (Vol. 926, pp. 95–107). Springer Verlag. https://doi.org/10.1007/978-3-030-15032-7_8

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