Probabilistic Multi-objective Framework for Multiple Active Power Filters Planning

Abstract

In the real-world electrical distribution networks, entering of the non-linear loads, as main sources of harmonic generator, has probabilistic nature. In this paper, with a new point of view, a multi-objective framework is developed for multiple active power filters (APFs) with taking probabilistic features of non-linear loads into account. In the proposed probabilistic multi-objective framework, total harmonic distortion of voltage (THDV), motor load loss function, harmonic transmission line loss, and total APFs current are the four objectives considered in the optimization problem. At the same time, individual and THDV, and maximum allowable size of the APFs are modeled as constraints with predetermined admissible levels. The newly developed framework is a non-convex non-linear mixed-integer optimization problem. Hence, a new hybrid of melody search algorithm and augmented Powell heuristic method is employed and followed by a fuzzy satisfying method to obtain the final optimal solution. The feasibility and effectiveness of the offered framework has been implemented on the IEEE 18-bus distribution test system and IEEE 30-bus distribution test system. The obtained results show the profitableness of the newly developed framework in the APFs planning.

Keywords::

• active power filters (APFs)
• augmented Powell heuristic method (APHM)
• fuzzy satisfying method (FSM)
• harmonic transmission line loss (HTLL)
• harmony search algorithm (HSA)
• melody search algorithm (MSA)
• motor load loss function (MLLF)
• total current of active power filters
• total harmonic distortion of voltage (THDV)
• two-point estimation method (2-PEM)

Additional information

Notes on contributors

Mohammad Kiani-Moghaddam

Mohammad Kiani-Moghaddam received the B.S. degree with first class honors in electrical engineering from the Islamic Azad University of Najafabad, Isfahan, Iran, in 2010, and the M.S. degree with first class honors in Electrical Engineering from the Shahid Beheshti University, Tehran, Iran, in 2015. His research interests include operation and planning, reliability, and risk assessment in modern large-scale power systems, power quality planning, and advanced optimization methodologies applied to power systems.

Mojtaba Shivaie

Mojtaba Shivaie was born and brought up in Semnan, Iran. He obtained the B.Sc. degree with first class honors in electrical engineering from Semnan University, Semnan, Iran, the M.Sc. and Ph.D. degrees with first class honors in electrical engineering, from Shahid Beheshti University, Tehran, Iran. His research interests include power systems planning, competitive electricity markets analysis, power systems reliability, smart electrical grids applications, and optimization methodologies.

Ahmad Salemnia

Ahmad Salemnia received the B.Sc. and M.Sc. degrees from Iran University of Science and Technology, Tehran, Iran, in 1983 and 1990, respectively, and the Ph.D. degree from Polytechnic Institute of Lorraine (INPL), France, in 1996, all in electrical engineering. In 1990, he joined Shahid Abbaspour School of Engineering, Shahid Beheshti University, Tehran, Iran, where he is currently an Assistant Professor. His research interests include power quality, harmonics and active filtering, and applications of power electronics in power systems.

Mohammad T. Ameli

Mohammad T. Ameli received the B.Sc. degree in electrical engineering from Technical College of Osnabrueck, Osnabrueck, Germany, in 1988, and the M.Sc. and Ph.D. degrees from Technical University of Berlin, Berlin, Germany, in 1992 and 1997, respectively. Since then, he has been a Professor in EE Faculty, Shahid Beheshti University, Tehran, Iran. He was the General Director of the Iran Research and Technology Institute for Electric Machines for three years. His research interests include power system simulation, operation, planning, and control of power systems, renewable energy in power systems, and smart grids.