Optimization of emission/economic dispatch using euclidean affine flower pollination algorithm (eFPA) and binary FPA (BFPA) in solar photo voltaic generation

Highlights

Economics dispatch has been solved using the proposed algorithm with inclusion of solar power plants.

Static case studies have been considered.

Cloud effects for full solar radiation and reduced solar radiation have been considered.

Simulation results are tested with IEEE 30 bus and IEEE 57 bus system.

Comparison has been made with existing algorithm to provide better results.

Abstract

Economic dispatch is the optimal output for a number of electricity generating units, to meet the system load, at the lowest possible cost, subject to transmission and operational constraints. The different Economic Dispatch (ED) methods have been developed in order to deal with the challenge of continuous and sustainable power at an improved cost. The increase in cost depletion of non-renewable sources has forced us to use the renewable energy resource as an alternative energy source. For optimizing the Economic Dispatch problem, a new algorithm is proposed based on Combined Emission Economic Dispatch (CEED) for Photo Voltaic (PV) plants and thermal power generation units. In CEED approach for improvising the Economic Dispatch Euclidean Affine Flower Pollination Algorithm (eFPA) and Binary Flower Pollination Algorithm (BFPA) has been used for solving the optimization problem for twenty PV and five thermal generators are done with full solar radiations and with reduced solar radiation. Power demand data has been taken from India in the district of Tuticorin Thermal Power Station (TTPS). Simulation results are tested with IEEE 30 bus and IEEE 57 bus systems and the comparison has been made with existing algorithm to provide better results.

Keywords

  • Solar photo voltaic generation;
  • Economic dispatch;
  • Combined emission economic dispatch (CEED);
  • Euclidean Affine Flower Pollination Algorithm (eFPA);
  • Binary Flower pollination Algorithm (BFPA)

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