Simultaneous optimal integration of photovoltaic distributed generation and battery energy storage system in active distribution network using chaotic grey wolf optimization




photovoltaic distributed generation, battery energy storage system, active distribution network, optimal integration, multi-objective functions, chaotic grey wolf optimization algorithm


Goal. The integration of photovoltaic distributed generations in the active distribution network has raised quickly due to their importance in delivering clean energy, hence, participating in solving various problems as climate change and pollution. Adding the battery energy storage systems would be considered as one of the best choices in giving solutions to the mentioned issues due to its characteristics of quick charging and discharging, managing the quality of power, and fulfilling the peak of energy demand. The novelty of the proposed work is the development of new multi-objective functions based on the sum of the three technical parameters of total active power loss, total voltage deviation, and total operation time of the overcurrent protection relay. Purpose. This paper is dedicated for solving the allocation problem of hybrid photovoltaic distributed generation and battery energy storage systems integration in the standard IEEE 33-bus and IEEE 69-bus active distribution networks. Methodology. The optimal integration of the hybrid systems is formulated as minimizing the proposed multi-objective functions by applying a newly developed metaheuristic technique based on various chaotic grey wolf optimization algorithms. The applied optimization algorithms are becoming increasingly popular due to their simplicity, lack of gradient information needed, ability to bypass local optima, and versatility in power system applications. Results. The simulation results of both test systems confirm the robustness and efficiency of the chaotic logistic grey wolf optimization algorithm compared to the rest of the algorithms in terms of convergence to the global optimal solution and in terms of providing the best and minimum multi-objective functions-based power losses, voltage deviation and relay operation time values. Practical significance. Recommendations have been developed for the use of optimal allocation of hybrid systems for practical industrial distribution power systems with the renewable energy sources presence.

Author Biographies

N. Belbachir, University of Mostaganem, Algeria

PhD Student, Department of Electrical Engineering

M. Zellagui, University of Batna 2, Algeria

PhD, Associate Professor, Department of Electrical Engineering

S. Settoul, Mentouri University of Constantine 1, Algeria

PhD Student, Department of Electrotechnic

C. Z. El-Bayeh, Concordia University, Canada

PhD, Postdoctoral Research, Canada Excellence Research Chairs Team

B. Bekkouche, University of Mostaganem, Algeria

PhD, Professor, Department of Electrical Engineering


Lai C.S., Jia Y., Lai L.L. A comprehensive review on large-scale photovoltaic system with applications of electrical energy storage. Renewable and Sustainable Energy Reviews, 2017, vol. 78, pp. 439-451. doi:

Wong L.A., Ramachandaramurthy V.K., Taylor P., Ekanayake J.B., Walker S.L., Padmanaban S. Review on the optimal placement, sizing and control of an energy storage system in the distribution network. Journal of Energy Storage, 2019, vol. 21, pp. 489-504. doi:

Macedo L.H., Franco J.F., Rider M.J., Romero R. Optimal operation of distribution networks considering energy storage devices. IEEE Transactions on Smart Grid, 2015, vol. 6, no. 6, pp. 2825-2836. doi:

Hemmati R. Mobile model for distributed generations and battery energy storage systems in radial grids. Journal of Renewable and Sustainable Energy, 2019, vol. 11, no. 2, p. 025301. doi:

Home-Ortiz J.M., Pourakbari-Kasmaei M., Lehtonen M., Sanches Mantovani J.R. Optimal location-allocation of storage devices and renewable-based DG in distribution systems. Electric Power Systems Research, 2019, vol. 172, pp. 11-21. doi:

Santos S.F., Fitiwi D.Z., Cruz M.R.M., Cabrita C.M.P., Catalão J.P.S. Impacts of optimal energy storage deployment and network reconfiguration on renewable integration level in distribution systems. Applied Energy, 2017, vol. 185, pp. 44-55. doi:

Zafar R., Ravishankar J., Fletcher J.E., Pota H.R. Multi-timescale model predictive control of battery energy storage system using conic relaxation in smart distribution grids. IEEE Transactions on Power Systems, 2018, vol. 33, no. 6, pp. 7152-7161. doi:

Bai L., Jiang T., Li F., Chen H., Li X. Distributed energy storage planning in soft open point based active distribution networks incorporating network reconfiguration and DG reactive power capability. Applied Energy, 2018, vol. 210, pp. 1082-1091. doi:

Lei J., Gong Q. Operating strategy and optimal allocation of large-scale VRB energy storage system in active distribution networks for solar/wind power applications. IET Generation, Transmission & Distribution, 2017, vol. 11, no. 9, pp. 2403-2411. doi:

Alharthi H., Alzahrani A., Shafiq S., Khalid M. Optimal allocation of batteries to facilitate high solar photovoltaic penetration. 9th International Conference on Power and Energy Systems (ICPES 2019), Perth, Australia, 2019. doi:

Ahmed H.M.A., Awad A.S.A., Ahmed M.H., Salama M.M.A. Mitigating voltage-sag and voltage-deviation problems in distribution networks using battery energy storage systems. Electric Power Systems Research, 2020, vol. 184, art. no. 106294. doi:

Sardi J., Mithulananthan N., Gallagher M., Hung D.Q. Multiple community energy storage planning in distribution networks using a cost-benefit analysis. Applied Energy, 2017, vol. 190, pp. 453-463. doi:

Zheng Y., Hill D.J., Dong Z.Y. Multi-agent optimal allocation of energy storage systems in distribution systems. IEEE Transactions on Sustainable Energy, 2017, vol. 8, no. 4, pp. 1715-1725. doi:

Zhang Y., Xu Y., Yang H., Dong Z.Y. Voltage regulation-oriented co-planning of distributed generation and battery storage in active distribution networks. International Journal of Electrical Power and Energy Systems, 2019, vol. 105, pp. 79-88. doi:

Gao J., Chen J.-J., Cai Y., Zeng S.-Q., Peng K. A two-stage Microgrid cost optimization considering distribution network loss and voltage deviation. Energy Reports, 2020, vol. 6, no. 2, pp. 263-267. doi:

Luo L., Abdulkareem S.S., Rezvani A., Miveh M.R., Samad S., Aljojo N., Pazhoohesh M. Optimal scheduling of a renewable based microgrid considering photovoltaic system and battery energy storage under uncertainty. Journal of Energy Storage, 2020, vol. 28, art. no. 101306. doi:

Chen J., Jiang X., Li J., Wu Q., Zhang Y., Song G., Lin D. Multi-stage dynamic optimal allocation for battery energy storage system in distribution networks with photovoltaic system. International Transactions on Electrical Energy Systems, 2020, vol. 30, no. 12, art. no. e12644. doi:

Khalid M., Akram U., Shafiq S. Optimal planning of multiple distributed generating units and storage in active distribution networks. IEEE Access, 2018, vol. 6, pp. 55234-55244. doi:

Wong L.A., Ramachandaramurthy V.K., Walker S.L., Taylor P., Sanjari M.J. Optimal placement and sizing of battery energy storage system for losses reduction using whale optimization algorithm. Journal of Energy Storage, 2019, vol. 26, art. no. 100892. doi:

Mukhopadhyay B., Das D. Multi-objective dynamic and static reconfiguration with optimized allocation of PV-DG and battery energy storage system. Renewable and Sustainable Energy Reviews, 2020, vol. 124, art. no. 109777. doi:

Qian X., Zhang S., Liu J., Zheng Y., Liu W. Hierarchical optimal planning of battery energy storage systems in radial distribution networks. 3rd IEEE Conference on Energy Internet and Energy System Integration (EI2 2019), Changsha, China 2019. doi:

Ahmadi B., Ceylan O., Ozdemir A. Voltage profile improving and peak shaving using multi-type distributed generators and battery energy storage systems in distribution networks. 55th International Universities Power Engineering Conference (UPEC 2020), Italy, 2020. doi:

Valencia A., Hincapie R.A., Gallego R.A. Optimal location, selection, and operation of battery energy storage systems and renewable distributed generation in medium–low voltage distribution networks. Journal of Energy Storage, 2021, vol. 34, art. no. 102158. doi:

Mirjalili S., Mirjalili S.M., Lewis A. Grey wolf optimizer. Advances in Engineering Software, 2014, vol. 69, pp. 46-61. doi:

Lu C., Gao L., Li X., Hu C., Yan X., Gong W. Chaotic-based grey wolf optimizer for numerical and engineering optimization problems. Memetic Computing, 2020, vol. 12, no. 4, pp. 371-398. doi:

Settoul S., Chenni R., Hassan H.A., Zellagui M., Kraimia M.N. MFO Algorithm for optimal location and sizing of multiple photovoltaic distributed generations units for loss reduction in distribution systems. 7th International Renewable and Sustainable Energy Conference (IRSEC 2019). Morocco, 2019. doi:

Zellagui M., Settoul S., Lasmari A., El-Bayeh C.Z., Chenni R., Hassan H.A. Optimal allocation of renewable energy source integrated-smart distribution systems based on technical-economic analysis considering load demand and DG uncertainties. Lecture Notes in Networks and Systems. 2021, vol. 174, pp. 391-404. doi:

Belbachir N., Zellagui M., Lasmari A., El-Bayeh C.Z., Bekkouche B. Optimal PV sources integration in distribution system and its impacts on overcurrent relay based time-current-voltage tripping characteristic. 12th International Symposium on Advanced Topics in Electrical Engineering (ATEE 2021), Romania, 2021. doi:

Lasmari A., Zellagui M., Hassan H.A., Settoul S., Abdelaziz A.Y., Chenni R. Optimal energy-efficient integration of photovoltaic DG in radial distribution systems for various load models. 11th International Renewable Energy Congress, (IREC 2020), Tunisia, 2020. doi:

Saleh K.A., Zeineldin H.H., Al-Hinai A., El-Saadany E.F. Optimal coordination of directional overcurrent relays using a new time-current-voltage characteristic. IEEE Transactions on Power Delivery. 2015, vol. 30, pp. 537-544. doi:

Saremi S., Mirjalili S.Z., Mirjalili S.M. Evolutionary population dynamics and grey wolf optimizer. Neural Computing and Applications, 2015, vol. 26, no. 5, pp. 1257-1263. doi:

Saremi S., Mirjalili S., Lewis A. Biogeography-based optimization with chaos. Neural Computing and Applications, 2014, vol. 25, no. 5, pp. 1077-1097. doi:




How to Cite

Belbachir, N., Zellagui, M., Settoul, S., El-Bayeh, C. Z., & Bekkouche, B. (2021). Simultaneous optimal integration of photovoltaic distributed generation and battery energy storage system in active distribution network using chaotic grey wolf optimization. Electrical Engineering & Electromechanics, (3), 52–61.



Power Stations, Grids and Systems