Dynamic Economic Dispatch Incorporating Photovoltaic and Wind Generation using Hybrid FPA with SQP

ABSTRACT

This paper presents a hybrid approach to explore the effect of wind and photovoltaic energy on conventional power network using dynamic economic dispatch. This model deals with stochastic and unpredictable character of wind and solar power output while considering the gaps between the real and predicted output power. A hybrid flower pollination algorithm with sequential quadratic programming is applied to reduce the overall operating costs of generators, while allocating generation to the committed units. The proposed technique is applied on power system having 13 solar units and a wind plant connected with 3, 5, and 10 generating units, respectively. The results of algorithm simulations performed in MATLAB 2014b confirm the competence of the suggested method.

KEYWORDS:

• Economic dispatch
• Flower pollination algorithm
• Photovoltaic
• Solar
• Sequential quadratic programming
• Wind

Additional information

Notes on contributors

Anum Abid

Anum Abid received her BSc degree in electrical engineering from University of Engineering and Technology, Taxila in 2016 and currently enrolled in MSc electrical engineering (Power) in University of Engineering and Technology, Taxila. Her research interests include power system optimization problems, smart grid, renewable energy, economic dispatch, and power system engineering. Corresponding author. Email: [email protected]

Tahir Nadeem Malik

Tahir Nadeem Malik received his BSc and MSc degree in electrical engineering from University of Engineering and Technology, Lahore. He received PhD electrical engineering degree from University of Engineering and Technology, Taxila in 2009. His research interests include power system operation, unit commitment, economic dispatch, smart energy, machine modelling, and optimization techniques in power system. E-mail: [email protected]

Farah Abid

Farah Abid received her BE degree in computer engineering from Mirpur University of Science and Technology (MUST), AJK, Pakistan in 2014. She has done the MS at National University of Science and Technology, College of electrical and mechanical engineering, Pakistan in 2016. Her research interests include applications in energy, power generation, image processing, and brain computer interface. E-mail: [email protected]

Intisar Ali Sajjad

Intisar Ali Sajjad received his BSc and MSc degrees in electrical engineering from University of Engineering and Technology, Taxila. He received PhD electrical engineering degree from Politecnico Di Torino, Italy in 2015. His research interests include power system control, energy efficiency, smart grid, and power flow. E-mail: [email protected]