Optimal Probabilistic Scheduling of a Proposed EH Configuration Based on Metaheuristic Automatic Data Clustering

Abstract

A combination of various energy conversion units offers a multi-carrier energy system, namely Energy Hub (EH). Optimal scheduling of EHs in the interconnected systems besides providing flexible management in input units stands as a challenging task. The uncertainties of input variables increase the complexity of this task. In this paper, an efficient EH structure is proposed and the conventional model is extended to tackle this issue in a short time operation interval. Moreover, a Metaheuristic Automatic Data Clustering (MADC) scheme used to solve the demand side uncertainty. This strategy omits the use of any additional variable needed for conventional techniques. The final solution is used to solve non differential, and high-dimension EH Economic Dispatch (EHED) problems. For best achievements an enhanced revised configuration by using a variable cost strategy for gas and electricity market simultaneously is proposed too. By comparing the effects of the EH feeding point on the objective function, a management side medium to reducing the computation burden proposed in the proceeding. The simulation results of the proposed model show an increase in EH benefit by reducing the cost. Considering mentioned issues as well as decreasing data dimensions due to reduced computing and probabilistic MADC scheduling of demands which could define the uncertainty. Besides, bypassing the need for a separate load management system, the results of this study are encouraging and warrant further analysis and research. The study is carried out in GAMS^© and is connected by MATLAB^© to implement the MADC.

KEYWORDS:

• EH configuration
• EH economic dispatch (EHED)
• Energy hub (EH)
• General algebraic modeling system (GAMS^©)
• Matrix laboratory MATLAB^©
• Metaheuristic automatic data clustering (MADC)
• Mixed integer linear programming (MILP)
• Optimal probabilistic scheduling

Additional information

Notes on contributors

Hadi Hosseinnejad

Hadi Hosseinnejad was born in West Azerbaijan, Iran in 1990. He received his BS degree from the University of Urmia, Urmia, Iran, in 2013, and his MS degree from the University of Islamic Azad University of Urmia, Urmia, Iran, in 2015. He is now a PhD candidate in electrical engineering at Islamic Azad University of Urmia, Urmia, Iran. His current research interests include optimal scheduling, energy hub and power systems include economic and reliability analysis. Email: [email protected]

Sadjad Galvani

Sadjad Galvani received his BS degree from the University of Tabriz, Tabriz, Iran, in 2005, and his MS degree from the University of Zanjan, Zanjan, Iran, in 2007, and a PhD degree in electrical engineering, from Urmia University, Urmia, Iran, in 2013. Currently, he is an associate professor in the Department of Power Engineering, faculty of Electrical and Computer Engineering, Urmia University, Urmia, Iran. His current research interests include probabilistic assessment of power systems, facts included operation of power systems, reliable and secure operation of power systems.

Payam Alemi

Payam Alemi was born in Tabriz, Iran, in 1982. He received his BS degree from the University of Tabriz, Tabriz, Iran, in 2005, and his MS degree from the science and research branch, Islamic Azad University, Tehran, Iran, in 2008, and PhD degree in electrical engineering, from Yeungnam University, Gyeongsan, Korea, in 2014. Then he joined Simon Fraser University, BC, Canada for his postdoctoral program until 2016. Currently he is an assistant professor in the Department of Electrical Engineering, Islamic Azad University, Urmia Branch, Urmia, Iran. His current research interests include the control of multilevel power converters, power loss analysis for converters, LCL filters, machine drives and DC-DC converters. Email: [email protected]