Optimal Allocation and Economic Analysis of Battery Energy Storage Systems: Self-Consumption Rate and Hosting Capacity Enhancement for Microgrids with High Renewable Penetration

Muhyaddin Rawa, Abdullah Abusorrah, Yusuf Al-Turki, Saad Mekhilef, Mostafa H. Mostafa, Ziad M. Ali and Shady H. E. Abdel Aleem
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Muhyaddin Rawa: Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Abdullah Abusorrah: Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Yusuf Al-Turki: Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Saad Mekhilef: Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia
Mostafa H. Mostafa: Department of Electrical Power and Machines, International Academy for Engineering and Media Science, Cairo 12411, Egypt
Ziad M. Ali: Electrical Engineering Department, College of Engineering at Wadi Addawaser, Prince Sattam bin Abdulaziz University, Wadi Addawaser 11991, Saudi Arabia
Shady H. E. Abdel Aleem: ETA Electric Company, Power Quality Department, 410 Al-Haram St., El Omraniya, Giza 12111, Egypt

Sustainability, 2020, vol. 12, issue 23, 1-25

Abstract: Recent advances in using renewable energy resources make them more accessible and prevalent in microgrids (MGs) and nano grids (NGs) applications. Accordingly, much attention has been paid during the past few years to design and operate MGs with high renewable energy sources (RESs) penetration. Energy storage (ES) is the crucial enabler for reliable MG operation to help MGs become more resistant to disruptions, particularly with the increased penetration of RESs. In this regard, this paper formulates a two-stage optimization framework to improve a grid-connected MG performance. Firstly, the optimal allocation decisions of the battery ES systems (BESSs) are provided to enhance the self-consumption rate of the RESs and the hosting capacity (HC) of the MG. Secondly, an operation strategy with the results (number, location, and capacity) of the BESSs obtained from the first stage is handled as an objective function to minimize the MG’s total operation cost. The IEEE 33-bus radial system is modified to act as the MG with high RESs penetration. The problem is solved using a recent swarm intelligence optimization algorithm called the Harris hawks optimization (HHO) algorithm. The proposed optimal operation strategy considers numerous constraints, such as the charge-discharge balance, number and capacity limitations of the BESSs, and the different technical performance constraints of the MG. The results obtained verify the proposed optimization framework’s effectiveness for grid-connected MGs and validate the benefits gained from the appropriate allocation of BESSs. The results also indicate that oversized storage or using many unneeded storage units may adversely influence the MG’s total power losses.

Keywords: batteries; hosting capacity; decision-making; energy storage; optimization; microgrid; renewable energy sources; self-consumption (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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