Abstract
This article describes a method to optimally allocate and size Battery Energy Storage System (BESS) to mitigate the costs incurred due to voltage deviation and power losses in a Renewable Energy Sources (RES) integrated Distribution Network. The optimum placement and sizing of BESS in RES connected distribution network is calculated by using a novel metaheuristic and nature inspired method called water cycle algorithm (WCA). The WCA influenced by the process of water sequence and the actions of rivers and their flows on the way to sea. Results are displayed for the application of proposed WCA optimization technique on IEEE 33 bus distribution system and IEEE 43 bus distribution network. Consequently the results come up with a considerable reduction in voltage deviations, power losses which were obtained with the installation of BESS units in a Distribution system using WCA. Besides, the proposed technique achieved the good results with less computational time. The results obtained from WCA are validated with GA, PSO and GSA. The outcomes disclose the efficacy and dominance of the WCA over GA, PSO and GSA.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Abbreviations
- BESS:
-
Battery Energy Storage System
- DOD:
-
depth of discharge
- ESS:
-
Energy storage system
- GA:
-
Genetic algorithm
- GSA:
-
Gravitational search algorithm
- Li–ion:
-
Lithium ion
- PSO:
-
Particle swarm optimization
- PV:
-
Photo voltaic
- RES:
-
Renewable energy sources
- VDI:
-
Voltage deviation index
- WCA:
-
water cycle algorithm
- WT:
-
Wind turbine
- C loss:
-
Power loss cost
- Cvr :
-
Voltage regulation cost
- EB - min :
-
Minimum capacity of the BESS
- Eb - max :
-
Maximum capacity of the BESS
- M:
-
Total branch number
- MVAbase :
-
Base power
- NaS:
-
Sodium sulphur
- Ni–Cd:
-
Nickel–cadmium
- \({\mathrm{N}}_{\mathrm{pop}}\) :
-
Number of population in WCA
- \({\mathrm{N}}_{\mathrm{var}}\) :
-
Number of variables in WCA
- PB-min :
-
Minimum power of BESS
- PB-max :
-
Maximum power of BESS
- \({\mathrm{P}}_{\mathrm{cha}}^{\mathrm{t}}\) :
-
Power charge rate
- \({\mathrm{P}}_{\mathrm{dis}}^{\mathrm{t}}\) :
-
Power discharge rate
- \({\mathrm{P}}_{\mathrm{L}}\) :
-
Active power loss
- Pmax :
-
Maximum active power at slack bus
- \({\mathrm{Q}}_{\mathrm{L}}\) :
-
Reactive power loss
- Randn:
-
Random number
- \({\mathrm{S}}_{\mathrm{L}}\) :
-
Apparent power loss
- \({\mathrm{\alpha }}_{\mathrm{VR}}\) :
-
Cost of voltage regulation
- \({\mathrm{\alpha }}_{\mathrm{Loss}}\) :
-
Rate of power loss cost
- \(\upmu\) :
-
Variance in WCA
- \(\sqrt{\upmu }\) :
-
Standard deviation
References
Ai WL, Shareef H, Ibrahim AA, Mohamed A (2014) Optimal battery placement in photovoltaic based distributed generation using binary firefly algorithm for voltage rise mitigation. In: Conference proceeding - 2014 IEEE international conference on power and energy, PECon 2014, 2014, pp 155–158. https://doi.org/10.1109/PECON.2014.7062432
Khaboot N, Srithapon C, Siritaratiwat A, Khunkitti P (2019) Increasing Benefits in High PV Penetration Distribution System by Using Battery Enegy Storage and Capacitor Placement Based on Salp Swarm Algorithm. Energies 12(24):4817. https://doi.org/10.3390/en12244817
Alzahrani A, Alharthi H, Khalid M (2019) Minimization of power losses through optimal battery placement in a distributed network with high penetration of photovoltaics. Energies. https://doi.org/10.3390/en13010140
Awad ASA, EL-Fouly, T. H. M., & Salama, M. M. A. (2017) Optimal ESS allocation for benefit maximization in distribution networks. IEEE Trans Smart Grid 8(4):1668–1678. https://doi.org/10.1109/TSG.2015.2499264
Brekken TKA, Yokochi A, Von Jouanne A, Yen ZZ, Hapke HM, Halamay DA (2011) Optimal energy storage sizing and control for wind power applications. IEEE Trans Sustain Energy 2(1):69–77. https://doi.org/10.1109/TSTE.2010.2066294
Bucciarelli M, Paoletti S, Vicino A (2018) Optimal sizing of energy storage systems under uncertain demand and generation. Appl Energy 225(3):611–621. https://doi.org/10.1016/j.apenergy.2018.03.153
Das CK, Bass O, Kothapalli G, Mahmoud TS, Habibi D (2018a) Optimal placement of distributed energy storage systems in distribution networks using artificial bee colony algorithm. Appl Energy 232(7):212–228. https://doi.org/10.1016/j.apenergy.2018.07.100
Das CK, Bass O, Kothapalli G, Mahmoud TS, Habibi D (2018b) Overview of energy storage systems in distribution networks: placement, sizing, operation, and power quality. Renew Sustain Energy Rev 91(11):1205–1230. https://doi.org/10.1016/j.rser.2018.03.068
De Lorenzo G, Andaloro L, Sergi F, Napoli G, Ferraro M, Antonucci V (2014) Numerical simulation model for the preliminary design of hybrid electric city bus power train with polymer electrolyte fuel cell. Int J Hydrog Energy 39(24):12934–12947. https://doi.org/10.1016/j.ijhydene.2014.05.135
De Luca D, Fragiacomo P, De Lorenzo G, Czarnetski WT, Schneider W (2016) Strategies for dimensioning two-wheeled fuel cell hybrid electric vehicles using numerical analysis software. Fuel Cells 16(5):628–639. https://doi.org/10.1002/fuce.201500174
de Sisternes FJ, Jenkins JD, Botterud A (2016) The value of energy storage in decarbonizing the electricity sector. Appl Energy 175:368–379. https://doi.org/10.1016/j.apenergy.2016.05.014
Dukpa A, Venkatesh B, El-Hawary M (2009) Application of continuation power flow method in radial distribution systems. Electr Power Syst Res 79(11):1503–1510. https://doi.org/10.1016/j.epsr.2009.05.003
Eskandar H, Sadollah A, Bahreininejad A, Hamdi M (2012) Water cycle algorithm—a novel metaheuristic optimization method for solving constrained engineering optimization problems. Comput Struct 110–111:151–166. https://doi.org/10.1016/j.compstruc.2012.07.010
Figgener J, Stenzel P, Kairies KP, Linßen J, Haberschusz D, Wessels O, Angenendt G, Robinius M, Stolten D, Sauer DU (2020) The development of stationary battery storage systems in Germany—a market review. J Energy Storage 29(12):101153. https://doi.org/10.1016/j.est.2019.101153
Fragiacomo P, Astorino E, Chippari G, De Lorenzo G, Czarnetzki WT, Schneider W (2017) Dynamic modeling of a hybrid electric system based on an anion exchange membrane fuel cell. Cogent Eng 4(1):1–16. https://doi.org/10.1080/23311916.2017.1357891
IRENA (2017) Electricity storage and renewables: costs and markets to 2030. In: International renewable energy agency (Issue October). http://irena.org/publications/2017/Oct/Electricity-storage-and-renewables-costs-and-markets%0Ahttps://www.irena.org/-/media/Files/IRENA/Agency/Publication/2017/Oct/IRENA_Electricity_Storage_Costs_2017.pdf
Jayasekara N, Masoum MAS, Wolfs PJ (2016) Optimal operation of distributed energy storage systems to improve distribution network load and generation hosting capability. IEEE Trans Sustain Energy 7(1):250–261. https://doi.org/10.1109/TSTE.2015.2487360
Karanki SB, Xu D (2017) Optimal capacity and placement of battery energy storage systems for integrating renewable energy sources in distribution system. In: 2016 National power systems conference, NPSC 2016. https://doi.org/10.1109/NPSC.2016.7858983
Ke BR, Ku TT, Ke YL, Chung CY, Chen HZ (2015) Sizing the battery energy storage system on a university campus with prediction of load and photovoltaic generation. IEEE Trans Ind Appl 52(2):1136–1147. https://doi.org/10.1109/TIA.2015.2483583
Kudkelwar S, Sarkar D (2019) Online implementation of time augmentation of over current relay coordination using water cycle algorithm. SN Appl Sci. https://doi.org/10.1007/s42452-019-1661-3
Lazzeroni P, Repetto M (2019) Optimal planning of battery systems for power losses reduction in distribution grids. Electr Power Syst Res 167(7):94–112. https://doi.org/10.1016/j.epsr.2018.10.027
Li R, Wang W, Chen Z, Wu X (2018) Optimal planning of energy storage system in active distribution system based on fuzzy multi-objective bi-level optimization. J Mod Power Syst Clean Energy 6(2):342–355. https://doi.org/10.1007/s40565-017-0332-x
Lu L, Han X, Li J, Hua J, Ouyang M (2013) A review on the key issues for lithium-ion battery management in electric vehicles. J Power Sources 226:272–288. https://doi.org/10.1016/j.jpowsour.2012.10.060
Naidji I, Ben Smida M, Khalgui M, Bachir A, Li Z, Wu N (2019) Efficient allocation strategy of energy storage systems in power grids considering contingencies. IEEE Access 7:186378–186392. https://doi.org/10.1109/ACCESS.2019.2957277
Qing Z, Yu N, Xiaoping Z, You Y, Liu D (2013) Optimal siting & sizing of battery energy storage system in active distribution network. In: 2013 4th IEEE/PES innovative smart grid technologies Europe, ISGT Europe 2013, 2012, pp 1–5. https://doi.org/10.1109/ISGTEurope.2013.6695235
Sarkar D, Odyuo Y (2019) An ab initio issues on renewable energy system integration to grid. Int J Sustain Energy Plan Manag 23:27–38. https://doi.org/10.5278/ijsepm.2802
Selim A, Kamel S, Jurado F (2020) Efficient optimization technique for multiple DG allocation in distribution networks. Appl Soft Comput J 86:105938. https://doi.org/10.1016/j.asoc.2019.105938
Tsiropoulos I, Tarvydas D, Lebedeva N (2018). Li-ion batteries for mobility and stationary storage applications - scenarios for costs and market growth. https://doi.org/10.2760/8717
Venkatesh B, Ranjan R, Gooi HB (2004) Optimal reconfiguration of radial distribution systems to maximize loadability. IEEE Trans Power Syst 19(1):260–266. https://doi.org/10.1109/TPWRS.2003.818739
Wen S, Lan H, Fu Q, Yu DC, Zhang L (2015) Economic allocation for energy storage system considering wind power distribution. IEEE Trans Power Syst 30(2):644–652. https://doi.org/10.1109/TPWRS.2014.2337936
Wong LA, Ramachandaramurthy VK, Taylor P, Ekanayake JB, Walker SL, Padmanaban S (2019a) Review on the optimal placement, sizing and control of an energy storage system in the distribution network. J Energy Storage 21(12):489–504. https://doi.org/10.1016/j.est.2018.12.015
Wong LA, Ramachandaramurthy VK, Walker SL, Taylor P, Sanjari MJ (2019b) Optimal placement and sizing of battery energy storage system for losses reduction using whale optimization algorithm. Journal of Energy Storage 26(5):100892. https://doi.org/10.1016/j.est.2019.100892
Xiao J, Zhang Z, Bai L, Liang H (2016) Determination of the optimal installation site and capacity of battery energy storage system in distribution network integrated with distributed generation. IET Gener Transm Distrib 10(3):601–607. https://doi.org/10.1049/iet-gtd.2015.0130
Zhang B, Dehghanian P, Kezunovic M (2019) Optimal allocation of PV generation and battery storage for enhanced resilience. IEEE Trans Smart Grid 10(1):535–545. https://doi.org/10.1109/TSG.2017.2747136
Funding
This research did not receive any funds from any agencies in public, commercial or not from any profit sectors.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Barla, M.C., Sarkar, D. Optimal placement and sizing of BESS in RES integrated distribution systems. Int J Syst Assur Eng Manag 14, 1866–1876 (2023). https://doi.org/10.1007/s13198-023-02016-w
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13198-023-02016-w