journal article·2022-08-18Open access

Optimization of PV and Battery Energy Storage Size in Grid-Connected Microgrid

Selahattin Garip, Saban Ozdemir

Applied Sciences· Volume 12· Issue 16

Abstract

This paper proposes a new method to determine the optimal size of a photovoltaic (PV) and battery energy storage system (BESS) in a grid-connected microgrid (MG). Energy cost minimization is selected as an objective function. Optimum BESS and PV size are determined via a novel energy management method and particle swarm optimization (PSO) algorithm to obtain minimum total cost. The MG was designed to use its own energy as much as possible, which is produced from renewable energy resources. Since it is a grid-connected system, it can demand energy from the grid within the determined limit with penalty. It differs from the studies in the literature in terms of optimizing both parameters such as PV and BESS size, being a grid-connected self-contained MG structure and controlling the grid energy by an energy management algorithm and optimizing the parameter via PSO with an energy management system (EMS). Results are compared for different PV and BESS. Moreover, effectiveness of the novel energy management method with PSO is compared with the genetic algorithm, which is the one of the well-known optimization algorithms. The results show that the proposed algorithm can achieve optimum PV and BESS size with minimum cost by using the new energy management method with the PSO algorithm.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Microgrid Control and Optimization · Hybrid Renewable Energy Systems · Smart Grid Energy Management

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Smart Grids, Graduate School of Natural and Applied Sciences, University of Gazi, Ankara 06500, Turkey

Department of Electrical and Electronic Engineering, Faculty of Technology, University of Gazi, Ankara 06500, Turkey

References (33)

Show source-provided references
1. Optimal sizing of a wind/solar/battery hybrid grid-connected microgrid system10.1049/iet-rpg.2017.0010 ↗
2. Wave of net zero emission targets opens window to meeting the Paris Agreement10.1038/s41558-021-01142-2 ↗
3. Sizing battery energy storage systems: Using multi-objective optimization to overcome the investment scale problem of annual worth10.1109/TSTE.2019.2954673 ↗
4. Zhang, T., Gooi, H.B., Chen, S., and Goh, T. (2015, January 3–6). Cost-effectiveness studies of the BESSs participating in frequency regulation. Proceedings of the IEEE Innovative Smart Grid Technologies—Asia (ISGT ASIA), Bangkok, Thailand.10.1109/ISGT-Asia.2015.7387077 ↗
5. Penetration rate and effectiveness studies of aggregated BESS for frequency regulation10.1109/TSG.2015.2426017 ↗
6. A new approach for optimal sizing of battery energy storage system for primary frequency control of islanded microgrid10.1016/j.ijepes.2013.07.005 ↗
7. Battery energy storage system models for microgrid stability analysis and dynamic simulation10.1109/TPWRS.2017.2740163 ↗
8. Kerdphol, T., Qudaih, Y., and Mitani, Y. (2014, January 12–15). Battery energy storage system size optimization in microgrid using particle swarm optimization. Proceedings of the IEEE PES Innovative Smart Grid Technologies, Istanbul, Turkey.10.1109/ISGTEurope.2014.7028895 ↗
9. A hybrid energy management and battery size optimization for standalone microgrids: A case study for Flinders Island, Australia10.1016/j.enconman.2018.08.076 ↗
10. Battery energy storage system size determination in renewable energy systems: A review10.1016/j.rser.2018.03.047 ↗
11. Optimally sizing of battery energy storage capacity by operational optimization of residential PV-Battery systems: An Australian household case study10.1016/j.renene.2020.07.022 ↗
12. Choi, Y., and Kim, H. (2016, January 5–8). Optimal scheduling of energy storage system for self-sustainable base station operation considering battery wear-out cost. Proceedings of the Eighth International Conference on Ubiquitous and Future Networks (ICUFN), Vienna, Austria.10.3390/en9060462 ↗
13. Moghimi, M., Garmabdari, R., Stegen, S., and Lu, J. (2018, January 7–10). Battery energy storage cost and capacity optimization for university research center. Proceedings of the IEEE/IAS 54th Industrial and Commercial Power Systems Technical Conference (I&CPS), Niagara Falls, ON, Canada.10.1109/ICPS.2018.8369968 ↗
14. Fedjaev, J., Amamra, S., and Francois, B. (2016, January 25–28). Linear programming based optimization tool for day ahead energy management of a lithium-ion battery for an industrial microgrid. Proceedings of the IEEE International Power Electronics and Motion Control Conference (PEMC), Varna, Bulgaria.10.1109/EPEPEMC.2016.7752032 ↗
15. Optimal storage scheduling using markov decision processes10.1109/TSTE.2015.2497718 ↗
16. Optimal battery sizing of a grid-connected residential photovoltaic system for cost minimization using pso algorithm10.48084/etasr.3094 ↗
17. Determination with Linear Form of Turkey’s Energy Demand Forecasting by the Tree Seed Algorithm and the Modified Tree Seed Algorithm10.4316/AECE.2020.02004 ↗
18. An improved genetic algorithm-based optimal sizing of solar photovoltaic/wind turbine generator/diesel generator/battery connected hybrid energy systems for standalone applications10.1080/01430750.2019.1587720 ↗
19. Optimal sizing of battery energy storage for micro-grid operation management using a new improved bat algorithm10.1016/j.ijepes.2013.10.019 ↗
20. Nimma, K.S., Al-Falahi, M.D.A., Nguyen, H.D., Jayasinghe, S.D.G., Mahmoud, T.S., and Negnevitsky, M. (2018). Grey Wolf optimization-based optimum energy-management and battery-sizing method for grid-connected microgrids. Energies, 11.10.3390/en11040847 ↗
21. Optimal sizing and operation of battery storage for economic operation of hybrid power system using artificial bee colony algorithm10.1002/etep.2685 ↗
22. Optimal sizing of an autonomous photovoltaic/wind/battery/diesel generator microgrid using grasshopper optimization algorithm10.1016/j.solener.2019.06.050 ↗
23. Optimization of a battery energy storage system using particle swarm optimization for stand-alone microgrids10.1016/j.ijepes.2016.02.006 ↗
24. Optimization of microgrid battery capacity using pso with considering islanding operation
25. Bashir, M., and Sadeh, J. (2012, January 18–25). Size optimization of new hybrid stand-alone renewable energy system considering a reliability index. Proceedings of the 11th International Conference on Environment and Electrical Engineering, Venice, Italy.10.1109/EEEIC.2012.6221521 ↗
26. Optimal Design of Grid-Connected Solar Photovoltaic System Using Selective Particle Swarm Optimization10.1155/2021/6632859 ↗
27. Using electrical energy storage in residential buildings—Sizing of battery and photovoltaic panels based on electricity cost optimization10.1016/j.apenergy.2019.02.021 ↗
28. Optimal sizing and energy scheduling of grid-supplemented solar PV systems with battery storage: Sensitivity of reliability and financial constraints10.1016/j.energy.2021.121780 ↗
29. Beltran, A., Hughes, C., and Das, S. (2019, January 16–21). Improved maximum power point tracking of partially shaded pv arrays using particle swarm optimization with zone initialization. Proceedings of the IEEE 46th Photovoltaic Specialists Conference (PVSC), Chicago, IL, USA.10.1109/PVSC40753.2019.8980469 ↗
30. Kennedy, J., and Eberhart, R. (December, January 27). Particle swarm optimization. Proceedings of the International Conference on Neural Networks, Perth, WA, Australia.
31. Particle swarm optimization algorithm: An overview10.1007/s00500-016-2474-6 ↗
32. Day-Ahead Scheduling, Simulation, and Real-Time Control of an Islanded Microgrid10.4316/AECE.2021.04010 ↗
33. Stochastic Algorithms for Controller Optimization of Grid Tied Hybrid AC/DC Microgrid with Multiple Renewable Sources10.4316/AECE.2019.02007 ↗