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Optimal allocation of hybrid renewable energy sources using progressive L-index method for voltage stability margin enhancement and impact of storage devices

  • Bharat Singh ORCID logo , Nitin Kumar Saxena ORCID logo EMAIL logo , Ashwani Kumar ORCID logo , Wenzhong Gao ORCID logo and Fuqi Ma ORCID logo
Published/Copyright: January 2, 2025
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International Journal of Emerging Electric Power Systems
From the journal International Journal of Emerging Electric Power Systems

Abstract

Distribution system networks (DSN) are presently gaining more concern in terms of security and stability due to the penetration of distributed energy resources (DERs) and the integration of microgrids. The active DSNs may have their operating point near the maximum power transfer capability due to the optimal asset utilization, which jeopardizes the stability of the network. The article presents a novel approach for optimizing the placement of solar PV, D-STATCOMs and energy storage in distribution networks. The method minimizes the L-Index for voltage stability, reduces voltage deviations, and lowers annual operating costs, ensuring enhanced performance and cost-efficiency for modern power systems. The article presents a novel approach of progressive L-Index to determine the suitable sites for optimal location of the DERs using Particle Swarm Optimization (PSO). It also utilizes the mixed-integer nonlinear programming using GAMS to compute the appropriate size of DERs, D-STATCOM and the energy storage. The studies have been performed on the standard IEEE-69 bus test DSN. The results exhibit that the proposed scheme enhances the overall voltage profile of the DSN, and the VSM is upgraded by 41.60 % with DER installation, as compared without DG.

Keywords: battery energy storage system; D-STATCOM; L-index; renewable energy sources; voltage stability margin
Corresponding author: Nitin Kumar Saxena, University of Denver, Denver, USA; and Teerthanker Mahaveer University, Moradabad, India, E-mail:

  1. Research ethics: Not applicable.

  2. Informed consent: Not applicable.

  3. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  4. Use of Large Language Models, AI and Machine Learning Tools: None declared.

  5. Conflict of interest: The authors state no conflict of interest.

  6. Research funding: There is no research funding for this work.

  7. Data availability: Not applicable.

List of symbol

δ i Voltage angle at bus i p f deg i Power factor of the diesel generator
δ b a t Depth of discharge for battery p f Power factor of the grid
η d i s Discharging efficiency P g e n i k Active power output for generating unit at ith bus
η c h Charging efficiency P d i k Active power demand at ith bus for kth time
η P V Solar PV efficiency P s o l a r Solar output power
η i n v Inverter efficiency P deg , i k Active power output from diesel generator
η r l Efficiency of renewable energy sources P grid i k Active power from the grid at ith bus for kth time
∆ k Time interval   P c h i k Charge power for ith bus at the kth time
λ b u s Loadability factor at bus   P d i s i k Discharge power for ith bus at kth time
Batt size Size of battery Q d i k Reactive power demand at ith bus for kth time
B i j Susceptance of the line between i and j Q g e n i k Reactive power output for generating unit
DOD max   _ bat Maximum depth of discharge of the battery Q solar , i k Reactive power from solar PV
G Solar irradiation ( w a t t m 2 ). Q grid i k Reactive power from grid at ith bus for kth time
G 0 Standard solar irradiation ( w a t t m 2 ). Q DST , i k Reactive power rating of D-STATCOM
G i j Condectence Q dis p p c s , i k Reactive power dispatch for the voltage source converter
h Number of hours for operation S p c s , i k Appreant power of the convertor
i , j Index for bus   S B Set of buses
k Index for time S T Set of time
l Index for line SOC min Minimum state of charge
n b Total number of buses SOC max Maximum state of charge
N D S T , i Number of D-STATCOMs at ith bus T c Temperature of PV cell
N wind Number of wind turbine T A Ambient temperature
N bat Number of batteries V Rated voltage

References

1. Ghatak, SR, Sannigrahi, S, Acharjee, P. Multi-objective approach for strategic incorporation of solar energy source, battery storage system, and DSTATCOM in a smart grid environment. IEEE Syst J 2019;13:3038–49. https://doi.org/10.1109/JSYST.2018.2875177.Search in Google Scholar

2. Gabash, A, Li, P. Active-reactive optimal power flow in distribution networks with embedded generation and battery storage. IEEE Trans Power Syst 2012;27:2026–35. https://doi.org/10.1109/TPWRS.2012.2187315.Search in Google Scholar

3. Kim, MK, Park, JK, Nam, YW. Market-clearing for pricing system security based on voltage stability criteria. Energy 2011;36:1255–64. https://doi.org/10.1016/j.energy.2010.11.019.Search in Google Scholar

4. Saxena, NK, Mekhilef, S, Kumar, A, Gao, DW. Marginal cost-based reactive power reinforcement using dynamic and static compensators. IEEE J Emerg Sel Top Power Electron 2022;10:4001–13. https://doi.org/10.1109/JESTPE.2022.3145871.Search in Google Scholar

5. Elsied, M, Oukaour, A, Youssef, T, Gualous, H, Mohammed, O. An advanced real time energy management system for microgrids. Energy 2016;114:742–52. https://doi.org/10.1016/j.energy.2016.08.048.Search in Google Scholar

6. Sharma, S, Chauhan, BK, Saxena, NK. Artificial neural network grid-connected MPPT-based techniques for hybrid PV-wind with battery energy storage system. J Inst Eng India Ser B 2023;104:1217–26. https://doi.org/10.1007/s40031-023-00922-y.Search in Google Scholar

7. Saxena, NK, Kumar, A. Estimation of dynamic compensation for renewable-based hybrid DG in radial distribution system using least error iterative method. Iran J Sci Technol – Trans Electr Eng 2020;45:15–28. https://doi.org/10.1007/s40998-020-00345-1.Search in Google Scholar

8. Barik, S, Das, D. A novel Q−PQV bus pair method of biomass DGs placement in distribution networks to maintain the voltage of remotely located buses. Energy 2020;194:116880. https://doi.org/10.1016/j.energy.2019.116880.Search in Google Scholar

9. Hong, YY, Chang, WC, Chang, YR, Der Lee, Y, Ouyang, DC. Optimal sizing of renewable energy generations in a community microgrid using Markov model. Energy 2017;135:68–74. https://doi.org/10.1016/j.energy.2017.06.098.Search in Google Scholar

10. Aman, MM, Jasmon, GB, Bakar, AHA, Mokhlis, H. A new approach for optimum simultaneous multi-DG distributed generation Units placement and sizing based on maximization of system loadability using HPSO (hybrid particle swarm optimization) algorithm. Energy 2014;66:202–15. https://doi.org/10.1016/j.energy.2013.12.037.Search in Google Scholar

11. Kettner, AM, Paolone, M. A generalized index for static voltage stability of unbalanced polyphase power systems including thévenin equivalents and polynomial models. IEEE Trans Power Syst 2019;34:4630–9. https://doi.org/10.1109/TPWRS.2019.2922073.Search in Google Scholar

12. Sharma, S, Kaur, D, Saxena, NK. Investigation for size and location of electric vehicle charging station accompanying VRP index and commissioning cost. Int J Emerg Elec Power Syst 2024;25:45–59. https://doi.org/10.1515/ijeeps-2023-0089.Search in Google Scholar

13. Aminudin, N, Rahman, TKA, Razali, NMM, Marsadek, M, Ramli, NM, Yassin, MI. Voltage collapse risk index prediction for real time system’s security monitoring. In: 2015 IEEE 15th international conference on environment and electrical engineering, EEEIC 2015 – conference proceedings. Rome, Italy; 2015:415–20 pp.10.1109/EEEIC.2015.7165198Search in Google Scholar

14. Nasiraghdam, H, Jadid, S. Optimal hybrid PV/WT/FC sizing and distribution system reconfiguration using multi-objective artificial bee colony (MOABC) algorithm. Sol Energy 2012;86:3057–71. https://doi.org/10.1016/j.solener.2012.07.014.Search in Google Scholar

15. Chen, G, Liu, L, Song, P, Du, Y. Chaotic improved PSO-based multi-objective optimization for minimization of power losses and L index in power systems. Energy Convers Manag 2014;86:548–60. https://doi.org/10.1016/j.enconman.2014.06.003.Search in Google Scholar

16. Du, L, Deng, Q. Impact of wind power and photovoltaic cell power on power system stability based on L index. In: Asia-Pacific power and energy engineering conference. APPEEC, Shanghai, China; 2012: 1-4 pp.10.1109/APPEEC.2012.6307008Search in Google Scholar

17. Mohseni-Bonab, SM, Rabiee, A, Mohammadi-Ivatloo, B. Voltage stability constrained multi-objective optimal reactive power dispatch under load and wind power uncertainties: a stochastic approach. Renew Energy 2016;85:598–609.10.1016/j.renene.2015.07.021Search in Google Scholar

18. Essallah, S, Bouallegue, A, Khedher, A. A comparative performances study of different indices for optimal DG placement in distribution system. In: International conference on green energy and conversion systems, GECS 2017, Hammamet, Tunisia; 2017:1-6 pp.10.1109/GECS.2017.8066233Search in Google Scholar

19. Mehta, P, Bhatt, P, Pandya, V. Optimal selection of distributed generating units and its placement for voltage stability enhancement and energy loss minimization. Ain Shams Eng J 2018;9:187–201. https://doi.org/10.1016/j.asej.2015.10.009.Search in Google Scholar

20. Essallah, S, Bouallegue, A, Khedher, A. Optimal placement of PV-distributed generation units in radial distribution system based on sensitivity approaches. In: 16th international conference on sciences and techniques of automatic control and computer engineering, STA 2015, Monastir, Tunisia; 2015:513-520 pp.10.1109/STA.2015.7505109Search in Google Scholar

21. Jalali, A, Aldeen, M. Modified modal analysis approach for distribution power systems. In: 2017 IEEE PES innovative smart grid technologies conference Europe, ISGT-Europe 2017 – proceedings. Turin, Italy; 2017:1-6 pp.10.1109/ISGTEurope.2017.8260103Search in Google Scholar

22. Pal, S, Nath, S. An intelligent on line voltage regulation in power distribution system. In: IEEE ICPCES 2010 – International conference on power, control and embedded systems, Allahabad, India; 2010:1-5 pp.10.1109/ICPCES.2010.5698695Search in Google Scholar

23. Li, H, Zhou, L, Zhang, Q. A two-layer strategy for reactive power and voltage control for improving the static voltage stability of PV power cluster. In: 2018 3rd international conference on smart and sustainable technologies, SpliTech 2018, Dali, China; 2023:84-94 pp.Search in Google Scholar

24. Liu, JH, Chu, CC. Long-term voltage instability detections of multiple fixed-speed induction generators in distribution networks using synchrophasors. IEEE Trans Smart Grid 2015;6:2069–79. https://doi.org/10.1109/TSG.2014.2379716.Search in Google Scholar

25. Rajendar, G, Banakara, B. Improvement of voltage stability by optimal capacitor placement using sensitivity matrix. In: International conference on signal processing, communication, power and embedded system, SCOPES 2016 – proceedings, Paralakhemundi, India; 2016:1991-6 pp.10.1109/SCOPES.2016.7955796Search in Google Scholar

26. Murty, VVSN, Kumar, A. Optimal placement of DG in radial distribution systems based on new voltage stability index under load growth. Int J Electr Power Energy Syst 2015;69:246–56. https://doi.org/10.1016/j.ijepes.2014.12.080.Search in Google Scholar

27. Mistry, KD, Roy, R. Enhancement of loading capacity of distribution system through distributed generator placement considering techno-economic benefits with load growth. Int J Electr Power Energy Syst 2014;54:505–15. https://doi.org/10.1016/j.ijepes.2013.07.032.Search in Google Scholar

28. Ranjan, R, Venkatesh, B, Das, D. Voltage stability analysis of radial distribution networks. Elec Power Compon Syst 2003;31:501–11. https://doi.org/10.1080/15325000390127011.Search in Google Scholar

29. Hamada, MM, Wahab, MAA, Hemdan, NGA. Simple and efficient method for steady-state voltage stability assessment of radial distribution systems. Elec Power Syst Res 2010;80:152–60. https://doi.org/10.1016/j.epsr.2009.08.017.Search in Google Scholar

30. Thangaraj, Y, Kuppan, R. Multi-objective simultaneous placement of DG and DSTATCOM using novel lightning search algorithm. J Appl Res Technol 2017;15:477–91. https://doi.org/10.1016/j.jart.2017.05.008.Search in Google Scholar

31. Murty, VVSN, Kumar, A. Impact of D-STATCOM in distribution systems with load growth on stability margin enhancement and energy savings using PSO and GAMS. Int Trans Electr Energy Syst 2018;28:1–24. https://doi.org/10.1002/etep.2624.Search in Google Scholar

32. Saxena, NK, Kumar, A, Wenzhong Gao, D. Review of excitation techniques for squirrel cage induction generator based micro grid using dynamic compensation. Elec Power Compon Syst 2022;50:149–65. https://doi.org/10.1080/15325008.2022.2135645.Search in Google Scholar

33. Raja, P, Selvan, MP, Kumaresan, N. Enhancement of voltage stability margin in radial distribution system with squirrel cage induction generator based distributed generators. IET Gener, Transm Distrib 2013;7:898–906. https://doi.org/10.1049/iet-gtd.2012.0579.Search in Google Scholar

34. Kayal, P, Chanda, CK. Placement of wind and solar based DGs in distribution system for power loss minimization and voltage stability improvement. Int J Electr Power Energy Syst 2013;53:795–809. https://doi.org/10.1016/j.ijepes.2013.05.047.Search in Google Scholar

35. Singh, B, Sharma, AK. Impact of battery storage with DG integration in distribution network using combined dispatch strategy for loss minimisation. Int J Comput Digital Syst 2022;11:289–302. https://doi.org/10.12785/ijcds/110124.Search in Google Scholar

36. Gözel, T, Eminoglu, U, Hocaoglu, MH. A tool for voltage stability and optimization (VS&OP) in radial distribution systems using matlab graphical user interface (GUI). Simulat Model Pract Theor 2008;16:505–18. https://doi.org/10.1016/j.simpat.2008.02.003.Search in Google Scholar

37. Fu, R, Remo, T, Margolis, R, Fu, R, Remo, T, Margolis, R. U. S. Utility-scale photovoltaics- plus-energy storage system costs benchmark. USA: National Renewable Energy Laboratory; 2018:32 p.10.2172/1483474Search in Google Scholar

38. Denholm, P, O’Connell, M, Brinkman, G, Jorgenson, J. Overgeneration from solar energy in California: a field guide to the duck chart (NREL/TP-6A20-65023). Tech Report 2015:46.10.2172/1226167Search in Google Scholar

39. Aman, MM, Jasmon, GB, Mokhlis, H, Bakar, AHA. Optimal placement and sizing of a DG based on a new power stability index and line losses. Int J Electr Power Energy Syst 2012;43:1296–304. https://doi.org/10.1016/j.ijepes.2012.05.053.Search in Google Scholar
Received: 2024-05-27
Accepted: 2024-12-06
Published Online: 2025-01-02

© 2024 Walter de Gruyter GmbH, Berlin/Boston

https://doi.org/10.1515/ijeeps-2024-0165
Keywords for this article
battery energy storage system; D-STATCOM; L-index; renewable energy sources; voltage stability margin
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