Active and Reactive Power Management in the Smart Distribution Network Enriched with Wind Turbines and Photovoltaic Systems

Abolfazl Mehbodniya, Ali Paeizi, Mehrdad Rezaie, Mahdi Azimian, Hasan Masrur and Tomonobu Senjyu
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Abolfazl Mehbodniya: Department of Electronics and Communication Engineering, Kuwait College of Science and Technology (KCST), Doha Area, 7th Ring Road, Kuwait City 20185145, Kuwait
Ali Paeizi: Department of Electrical Engineering, Shahid Beheshti University, Tehran 1983969411, Iran
Mehrdad Rezaie: Department of Electrical Engineering, Malayer University, Malayer 6571995863, Iran
Mahdi Azimian: Department of Electrical and Computer Engineering, Kashan Branch, Islamic Azad University, Kashan 8715998151, Iran
Hasan Masrur: Graduate School of Science & Engineering, Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara 903-0123, Okinawa, Japan
Tomonobu Senjyu: Graduate School of Science & Engineering, Faculty of Engineering, University of the Ryukyus, 1 Senbaru, Nishihara 903-0123, Okinawa, Japan

Sustainability, 2022, vol. 14, issue 7, 1-21

Abstract: The penetration of renewable energy sources has been intensified during the last decade to tackle the climate crisis by providing clean energy. Among various renewable energy technologies, wind turbines and photovoltaic systems have received increasing attention from investors. Generally, electronic power converters are used to control renewable generations. The present study discusses the power management of smart distribution networks enriched with wind and photovoltaic units. The model aims to minimize the expected network operating cost of the system formulated as an objective function regarding AC optimal power flow constraints. In addition, stochastic programming based on unscented transformation is adopted to model the probable behavior of loads, renewable generations, and energy market prices. The model employs a linear approximation model to burden the complexity of the problem and achieve the optimum solution. The problem is tested to a 33-bus system using the General Algebraic Modeling System (GAMS). The obtained results confirm the proposed model’s potential in reducing energy costs, power losses, and voltage deviations compared to conventional power flow studies. In the proposed scheme compared to network load distribution studies, the active and reactive power losses, network energy costs, and voltage deviations are improved by about 40.7%, 33%, 36%, and 74.7%, respectively.

Keywords: linear approximation; power scheduling; smart distribution network; renewable resources (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
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