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Alternatif Akım Mikro-şebekelerde Enerji Depolama Sistemlerinin Konum Optimizasyonu

Year 2024, , 662 - 671, 15.07.2024
https://doi.org/10.34248/bsengineering.1489516

Abstract

Bu çalışma, üretim yöntemleri ve tüketim davranışlarına göre elektrik üretim maliyetlerini en aza indirmek ve geleneksel üretim profilini düzleştirmek için alternatif akım (AA) mikro-şebekedeki enerji depolama sistemlerinin optimum konumlandırılması problemini ele almaktadır. Dağıtım şebekelerinin fiziksel ve operasyonel kısıtlarının yanında üretim santrallerindeki kısıtlarda probleme dahil edilmiştir. Geleneksel üretim santralleri gibi düzenli üretim aralıklarına sahip santrallerin yanı sıra rüzgâr türbinleri gibi düzensiz üretim aralıklarına sahip yenilenebilir enerji kaynakları da AA mikro-şebeke yapısına dahil edilerek enerji depolama sistemlerinin optimal konumlandırılması problemi genişletilmiştir. Problemin doğrusal ve konveks olmayan kısıtları göz önüne alındığında çözümünü mümkün kılmak için güç akış denklemlerinin bir üst boyut uzayında ifade edilmesi gerekmektedir. Konveks ve doğrusal olmayan güç akış denklemleri ve ikili karar değişkenini içeren enerji depolama sistemlerinin konumlandırılması için karmaşık tam sayılı doğrusal olmayan programlama çerçevesi geliştirilmiştir. Enerji depolama sistemlerinin konumlarının optimum olarak bulunması, geleneksel üreteçlerin üretim profillerinin düzleştirilmesini sağlar ve şebekede enerji sürekliliğinin sağlanmasında kritik rol oynar. Önerilen optimum enerji depolama sisteminin yerleşimi algoritması, IEEE 9-baralı test sistemine uygulanarak performansı doğrulanmıştır.

References

  • Alsharif H, Jalili M, Hasan KN. 2022. Power system frequency stability using optimal sizing and placement of battery energy storage system under uncertainty. J Energy Storage, 50: 104610.
  • Byrne RH, Nguyen TA, Copp DA, Chalamala BR, Gyuk I. 2017. Energy management and optimization methods for grid energy storage systems. IEEE Access, 6: 13231-13260.
  • Calderaro V, Conio G, Galdi V, Massa G, Piccolo A. 2013. Optimal decentralized voltage control for distribution systems with inverter-based distributed generators. IEEE Trans Power Syst, 29(1): 230-241.
  • Carpentier J. 1977. Optimal power flows. Int J Electr Power Energy Syst, 1(1): 3-15.
  • Dui X, Zhu G, Yao L. 2017. Two-stage optimization of battery energy storage capacity to decrease wind power curtailment in grid-connected wind farms. IEEE Trans Power Syst, 33(3): 3296-3305.
  • Dutta S, Sharma R. 2012. Optimal storage sizing for integrating wind and load forecast uncertainties. In: Proceedings of IEEE PES Innovative Smart Grid Technologies, January 16-20, Washington DC, USA, pp: 1-7.
  • Fossati JP, Galarza A, Martín A, Fontan L. 2015. A method for optimal sizing energy storage systems for microgrids. Renew Energy, 77: 539-549.
  • Guo J, Zhang P, Wu D, Liu Z, Ge H, Zhang S, Yang X. 2021. A new collaborative optimization method for a distributed energy system combining hybrid energy storage. Sustain Cities Soc, 75: 103330.
  • Hannan MA, Faisal M, Ker PJ, Begum RA, Dong ZY, Zhang, C. 2020. Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications. Renew Sustain Energy Rev, 131: 110022.
  • Happ HH. 1977. Optimal power dispatch comprehensive survey. IEEE Trans Power App Syst, 96(3): 841-854.
  • Huang S, Wu Q, Wang J, Zhao H. 2016. A sufficient condition on convex relaxation of ac optimal power flow in distribution networks. IEEE Trans Power Syst, 32(2): 1359-1368.
  • Huang Y, Ju Y, Ma K, Short M, Chen T, Zhang R, Lin Y. 2022. Three-phase optimal power flow for networked microgrids based on semidefinite programming convex relaxation. Appl Energy, 305: 117771.
  • Karimi H, Ansari J, Gholami A, Kazemi A. 2014. A comprehensive well to wheel analysis of plug-in vehicles and renewable energy resources from cost and emission viewpoints. In: Proceedings of IEEE Smart Grid Conference, November 3-6, Venice, Italy, pp: 1-6.
  • Kayacık SE, Kocuk B. 2020. A misocp-based solution approach to the reactive optimal power flow problem. IEEE Trans Power Syst, 36(1): 529-532.
  • Kazemi M, Ansari MR. 2022. An integrated transmission expansion planning and battery storage systems placement-a security and reliability perspective. Int J Electr Power Energy Syst, 134: 107329.
  • Kekatos V, Wang G, Conejo AJ, Giannakis GB. 2014. Stochastic reactive power management in microgrids with renewables. IEEE Trans Power Syst, 30(6): 3386-3395.
  • Kim J, Dvorkin Y. 2018. Enhancing distribution system resilience with mobile energy storage and microgrids. IEEE Trans Smart Grid, 10(5): 4996-5006.
  • Li Y, Li T, Zhang H, Xie X, Sun Q. 2022. Distributed resilient double-gradient-descent based energy management strategy for multi-energy system under DoS attacks. IEEE Trans Netw Sci Eng, 9(4): 2301-2316.
  • Morstyn T, Hredzak B, Aguilera RP, Agelidis VG. 2017. Model predictive control for distributed microgrid battery energy storage systems. IEEE Trans Control Syst Technol, 26(3): 1107-1114.
  • Nick M, Cherkaoui R, Paolone M. 2017. Optimal planning of distributed energy storage systems in active distribution networks embedding grid reconfiguration. IEEE Trans Power Syst, 33(2): 1577-1590.
  • Nojavan S, Majidi M, Esfetanaj NN. 2017. An efficient cost-reliability optimization model for optimal siting and sizing of energy storage system in a microgrid in the presence of responsible load management. Energy, 139: 89-97.
  • Reddy KS, Mudgal V, Mallick TK. 2018. Review of latent heat thermal energy storage for improved material stability and effective load management. J Energy Storage, 15: 205-227.
  • Stecca M, Elizondo LR, Soeiro TB, Bauer P, Palensky P. 2020. A comprehensive review of the integration of battery energy storage systems into distribution networks. IEEE Open J Ind Electron Soc, 1: 46-65.
  • Tian Z, Wu W, Zhang B, Bose A. 2016. Mixed‐integer second‐order cone programing model for var optimisation and network reconfiguration in active distribution networks. IET Gener Transm Distrib, 10(8): 1938-1946.
  • Wong LA, Ramachandaramurthy VK, Taylor P, Ekanayake JB, Walker SL, Padmanaban, S. 2019. Review on the optimal placement, sizing and control of an energy storage system in the distribution network. J Energy Storage, 21: 489-504.
  • Yang L, Li X, Sun M, Sun C. 2023. Hybrid policy-based reinforcement learning of adaptive energy management for the energy transmission-constrained island group. IEEE Trans Industr Inform, 19(11): 10751-10762.
  • Yang Y, Bremner S, Menictas C, Kay M. 2018. Battery energy storage system size determination in renewable energy systems: A review. Renew Sustain Energy Rev, 91: 109-125.
  • Zia MF, Elbouchikhi E, Benbouzid M, Guerrero JM. 2019. Energy management system for an islanded microgrid with convex relaxation. IEEE Trans Ind Appl, 55(6): 7175-7185.
  • Zidar M, Georgilakis PS, Hatziargyriou ND, Capuder T, Škrlec D. 2016. Review of energy storage allocation in power distribution networks: applications, methods and future research. IET Gener Transm Distrib, 10(3): 645-652.

Optimal Location of Energy Storage Systems on Alternative Current Micro-grids

Year 2024, , 662 - 671, 15.07.2024
https://doi.org/10.34248/bsengineering.1489516

Abstract

This study addresses the problem of optimal positioning of energy storage systems in the AA micro-grids to minimize electrical generation costs and smooth the conventional generation profile based on generation methods and consumption behaviors. In addition to the physical and operational restrictions of distribution networks, restrictions in generation plants are also included in the problem formulation. The problem has been expanded by including power plants with regular generation intervals, such as traditional power plants, as well as renewable energy sources with irregular generation intervals, such as wind turbines, in alternative current (AC) micro-grids. In order to make the problem considering the non-convex and non-linear constraints solvable, reformulation of the power flow equations is needed to reformulate in higher dimensional space. A mixed-integer non-linear programming framework for handling the non-convex power flow equations, and binary decision variables accounting for the energy storage system placement has been developed. Obtaining optimal location of energy storage systems plays a critical role in smoothing the conventional generation profile and maintains energy reliability. The performance of the proposed optimal energy storage placement algorithm has been verified on IEEE 9-bus benchmark.

Ethical Statement

Bu araştırmada hayvanlar ve insanlar üzerinde herhangi bir çalışma yapılmadığı için etik kurul onayı alınmamıştır.

References

  • Alsharif H, Jalili M, Hasan KN. 2022. Power system frequency stability using optimal sizing and placement of battery energy storage system under uncertainty. J Energy Storage, 50: 104610.
  • Byrne RH, Nguyen TA, Copp DA, Chalamala BR, Gyuk I. 2017. Energy management and optimization methods for grid energy storage systems. IEEE Access, 6: 13231-13260.
  • Calderaro V, Conio G, Galdi V, Massa G, Piccolo A. 2013. Optimal decentralized voltage control for distribution systems with inverter-based distributed generators. IEEE Trans Power Syst, 29(1): 230-241.
  • Carpentier J. 1977. Optimal power flows. Int J Electr Power Energy Syst, 1(1): 3-15.
  • Dui X, Zhu G, Yao L. 2017. Two-stage optimization of battery energy storage capacity to decrease wind power curtailment in grid-connected wind farms. IEEE Trans Power Syst, 33(3): 3296-3305.
  • Dutta S, Sharma R. 2012. Optimal storage sizing for integrating wind and load forecast uncertainties. In: Proceedings of IEEE PES Innovative Smart Grid Technologies, January 16-20, Washington DC, USA, pp: 1-7.
  • Fossati JP, Galarza A, Martín A, Fontan L. 2015. A method for optimal sizing energy storage systems for microgrids. Renew Energy, 77: 539-549.
  • Guo J, Zhang P, Wu D, Liu Z, Ge H, Zhang S, Yang X. 2021. A new collaborative optimization method for a distributed energy system combining hybrid energy storage. Sustain Cities Soc, 75: 103330.
  • Hannan MA, Faisal M, Ker PJ, Begum RA, Dong ZY, Zhang, C. 2020. Review of optimal methods and algorithms for sizing energy storage systems to achieve decarbonization in microgrid applications. Renew Sustain Energy Rev, 131: 110022.
  • Happ HH. 1977. Optimal power dispatch comprehensive survey. IEEE Trans Power App Syst, 96(3): 841-854.
  • Huang S, Wu Q, Wang J, Zhao H. 2016. A sufficient condition on convex relaxation of ac optimal power flow in distribution networks. IEEE Trans Power Syst, 32(2): 1359-1368.
  • Huang Y, Ju Y, Ma K, Short M, Chen T, Zhang R, Lin Y. 2022. Three-phase optimal power flow for networked microgrids based on semidefinite programming convex relaxation. Appl Energy, 305: 117771.
  • Karimi H, Ansari J, Gholami A, Kazemi A. 2014. A comprehensive well to wheel analysis of plug-in vehicles and renewable energy resources from cost and emission viewpoints. In: Proceedings of IEEE Smart Grid Conference, November 3-6, Venice, Italy, pp: 1-6.
  • Kayacık SE, Kocuk B. 2020. A misocp-based solution approach to the reactive optimal power flow problem. IEEE Trans Power Syst, 36(1): 529-532.
  • Kazemi M, Ansari MR. 2022. An integrated transmission expansion planning and battery storage systems placement-a security and reliability perspective. Int J Electr Power Energy Syst, 134: 107329.
  • Kekatos V, Wang G, Conejo AJ, Giannakis GB. 2014. Stochastic reactive power management in microgrids with renewables. IEEE Trans Power Syst, 30(6): 3386-3395.
  • Kim J, Dvorkin Y. 2018. Enhancing distribution system resilience with mobile energy storage and microgrids. IEEE Trans Smart Grid, 10(5): 4996-5006.
  • Li Y, Li T, Zhang H, Xie X, Sun Q. 2022. Distributed resilient double-gradient-descent based energy management strategy for multi-energy system under DoS attacks. IEEE Trans Netw Sci Eng, 9(4): 2301-2316.
  • Morstyn T, Hredzak B, Aguilera RP, Agelidis VG. 2017. Model predictive control for distributed microgrid battery energy storage systems. IEEE Trans Control Syst Technol, 26(3): 1107-1114.
  • Nick M, Cherkaoui R, Paolone M. 2017. Optimal planning of distributed energy storage systems in active distribution networks embedding grid reconfiguration. IEEE Trans Power Syst, 33(2): 1577-1590.
  • Nojavan S, Majidi M, Esfetanaj NN. 2017. An efficient cost-reliability optimization model for optimal siting and sizing of energy storage system in a microgrid in the presence of responsible load management. Energy, 139: 89-97.
  • Reddy KS, Mudgal V, Mallick TK. 2018. Review of latent heat thermal energy storage for improved material stability and effective load management. J Energy Storage, 15: 205-227.
  • Stecca M, Elizondo LR, Soeiro TB, Bauer P, Palensky P. 2020. A comprehensive review of the integration of battery energy storage systems into distribution networks. IEEE Open J Ind Electron Soc, 1: 46-65.
  • Tian Z, Wu W, Zhang B, Bose A. 2016. Mixed‐integer second‐order cone programing model for var optimisation and network reconfiguration in active distribution networks. IET Gener Transm Distrib, 10(8): 1938-1946.
  • Wong LA, Ramachandaramurthy VK, Taylor P, Ekanayake JB, Walker SL, Padmanaban, S. 2019. Review on the optimal placement, sizing and control of an energy storage system in the distribution network. J Energy Storage, 21: 489-504.
  • Yang L, Li X, Sun M, Sun C. 2023. Hybrid policy-based reinforcement learning of adaptive energy management for the energy transmission-constrained island group. IEEE Trans Industr Inform, 19(11): 10751-10762.
  • Yang Y, Bremner S, Menictas C, Kay M. 2018. Battery energy storage system size determination in renewable energy systems: A review. Renew Sustain Energy Rev, 91: 109-125.
  • Zia MF, Elbouchikhi E, Benbouzid M, Guerrero JM. 2019. Energy management system for an islanded microgrid with convex relaxation. IEEE Trans Ind Appl, 55(6): 7175-7185.
  • Zidar M, Georgilakis PS, Hatziargyriou ND, Capuder T, Škrlec D. 2016. Review of energy storage allocation in power distribution networks: applications, methods and future research. IET Gener Transm Distrib, 10(3): 645-652.
There are 29 citations in total.

Details

Primary Language Turkish
Subjects Electrical Energy Storage, Electrical Energy Generation (Incl. Renewables, Excl. Photovoltaics), Power Plants
Journal Section Research Articles
Authors

Tuncay Altun 0000-0003-1499-3384

Publication Date July 15, 2024
Submission Date May 24, 2024
Acceptance Date June 23, 2024
Published in Issue Year 2024

Cite

APA Altun, T. (2024). Alternatif Akım Mikro-şebekelerde Enerji Depolama Sistemlerinin Konum Optimizasyonu. Black Sea Journal of Engineering and Science, 7(4), 662-671. https://doi.org/10.34248/bsengineering.1489516
AMA Altun T. Alternatif Akım Mikro-şebekelerde Enerji Depolama Sistemlerinin Konum Optimizasyonu. BSJ Eng. Sci. July 2024;7(4):662-671. doi:10.34248/bsengineering.1489516
Chicago Altun, Tuncay. “Alternatif Akım Mikro-şebekelerde Enerji Depolama Sistemlerinin Konum Optimizasyonu”. Black Sea Journal of Engineering and Science 7, no. 4 (July 2024): 662-71. https://doi.org/10.34248/bsengineering.1489516.
EndNote Altun T (July 1, 2024) Alternatif Akım Mikro-şebekelerde Enerji Depolama Sistemlerinin Konum Optimizasyonu. Black Sea Journal of Engineering and Science 7 4 662–671.
IEEE T. Altun, “Alternatif Akım Mikro-şebekelerde Enerji Depolama Sistemlerinin Konum Optimizasyonu”, BSJ Eng. Sci., vol. 7, no. 4, pp. 662–671, 2024, doi: 10.34248/bsengineering.1489516.
ISNAD Altun, Tuncay. “Alternatif Akım Mikro-şebekelerde Enerji Depolama Sistemlerinin Konum Optimizasyonu”. Black Sea Journal of Engineering and Science 7/4 (July 2024), 662-671. https://doi.org/10.34248/bsengineering.1489516.
JAMA Altun T. Alternatif Akım Mikro-şebekelerde Enerji Depolama Sistemlerinin Konum Optimizasyonu. BSJ Eng. Sci. 2024;7:662–671.
MLA Altun, Tuncay. “Alternatif Akım Mikro-şebekelerde Enerji Depolama Sistemlerinin Konum Optimizasyonu”. Black Sea Journal of Engineering and Science, vol. 7, no. 4, 2024, pp. 662-71, doi:10.34248/bsengineering.1489516.
Vancouver Altun T. Alternatif Akım Mikro-şebekelerde Enerji Depolama Sistemlerinin Konum Optimizasyonu. BSJ Eng. Sci. 2024;7(4):662-71.

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