Optimal Allocation of Storage Capacity in Distribution Network for Renewable Energy Expansion

Abstract

Today the integration of renewable energy production technologies into power systems brings a new challenge in terms of optimal usage of renewable. It is known that due to the discontinuous nature of renewable energy, the challenge can be associated with the presence of unwanted voltage fluctuations and power losses in power grids. This study performs optimization of the calculation of hosting capacity to determine the maximum amount of renewable energy that can be further expanded. This can be possible by energy storage deployment on the same power grids. The battery storages are expected to have power injection and absorption associated with discharging and charging of energy storages, respectively, to solve voltage fluctuations and power disturbances. Thus, to enhance the probability of distributed generation penetration, it is necessary to have optimal allocation and size during the renewable energy penetration in low-voltage distribution networks. Global optimization as a genetic algorithm (GA) method is used during hosting capacity assessment. The results show that using GA-based optimization, total cost and loss can be reduced by 38.8 and 73%, respectively. The practical results are verified by the IEEE-33 bus system.

Keywords:

• distributed generation
• energy storages
• hosting capacity
• optimal allocation
• overvoltage issues
• renewable energy integration

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research has been funded by the Ministry of Education and Science of the Republic of Kazakhstan (Grant No. BR10965311 “Development of the intelligent information and telecommunication systems for municipal infrastructure: transport, environment, energy, and data analytics in the concept of Smart City”).

Notes on contributors

Balzhan Azibek

Balzhan Azibek received the B.Sc. degree and M.Sc. degree in Electrical and Computer Engineering at Nazarbayev University, Kazakhstan. Her research area includes game theory approaches in power system modeling. Currently, she works as a senior lecturer at Astana IT University, Kazakhstan.

Nurkhat Zhakiyev

Nurkhat Zhakiyev is a PhD in Physics (L. Gumilyev Eurasian National University, Kazakhstan, 2015), worked in Nazarbayev University (2015–2020), Since 2020 he is a Senior Researcher, Director of the Department of Science and Innovation, Astana IT University, Kazakhstan. Supervisor of several research projects on the energy system modelling and integration of renewables. Computer modeler of energy systems and a Climate change mitigation expert.

Alman Kushekkaliyev

Alman Kushekkaliyev, PhD in Physics and Mathematical Science (2004), Associate Professor of M.Utemisov West Kazakhstan University, Uralsk. His research interests include design of advanced control systems and modeling in the physics.

Aidana Zhalgas

Aidana Zhalgas received the B.Sc. degree in Mathematics and M.Sc. degree in Mechanical Engineering at Nazarbayev University, Kazakhstan. Her research area includes optimization and analytics in power system modeling. Currently, she works as a senior lecturer at Astana IT University, Kazakhstan.

Bekzhan Mukatov

Bekzhan Mukatov, PhD in Power Plants and electricity systems (2016). His research interests in network stability, relay protection, automated control systems and power system modeling.