Skip to main content
SpringerLink
Log in

Analytical Approach to Power Dispatch in Distribution Systems

  • Chapter
  • First Online:
Reactive Power Support Using Photovoltaic Systems

Part of the book series: Springer Theses ((Springer Theses))

  • 408 Accesses

Abstract

In Chap. 2, the benefits of local reactive power provision using PV inverters have been demonstrated. The next logical step would be to assess the implementation of the power dispatch optimisation in the distribution system in the presence of other DERs that are becoming inseparable aspects of future power system. This chapter expands the work based on the insights from the previous chapter on reactive power compensation (RPC) using PV to include other inverter-based DERs and proposes a practical way to optimise the power dispatch.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 109.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 139.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 139.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Notes

  1. 1.

    This is true as long as the distribution system is a net importer of electricity at that period.

  2. 2.

    In Fig. 3.6, a sub-nadir refers to a period between the previous peak and the peak that a particular nadir is paired with, that has the next lowest \(c^{{\text {Pgrid}}}\). Similarly, a sub-peak is a period between the nadir that a particular peak is paired with and the subsequent nadir, that has the next highest \(c^{{\text {Pgrid}}}\). For example, in Fig. 3.5, if nadir 1 (04:30 a.m.) is paired with peak 3 (10:30 a.m.), the sub-nadir is at 04:00 a.m. and the sub-peak is at 11:00 a.m.

  3. 3.

    Assuming energy consumption of 6000 kWh per employee, there are about 3 EVs per 100 people in the industrial area.

References

  1. Liang RH, Wang JC, Chen YT, Tseng WT (2015) An enhanced firefly algorithm to multi-objective optimal active/reactive power dispatch with uncertainties consideration. Int J Electr Power Energy Syst 64:1088–1097, ISSN: 01420615. https://doi.org/10.1016/j.ijepes.2014.09.008

  2. Sousa T, Morais H, Vale Z, Castro R (2015) A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context. Energy 85:236–250, ISSN: 03605442. https://doi.org/10.1016/j.energy.2015.03.077

  3. Ziadi Z, Taira S, Oshiro M, Funabashi T (2014) Optimal power scheduling for smart grids considering controllable loads and high penetration of photovoltaic generation. IEEE Trans Smart Grid 5(5):2350–2359, ISSN: 19493053. https://doi.org/10.1109/TSG.2014.2323969

  4. Kim YJ, Kirtley JL, Norford LK (2015) Reactive power ancillary service of synchronous DGS in coordination with voltage control devices. IEEE Trans Smart Grid 8(2):515–527, ISSN: 1949-3053. https://doi.org/10.1109/TSG.2015.2472967

  5. Chen S, Hu W, Chen Z (2016) Comprehensive cost minimization in distribution networks using segmented-time feeder reconfiguration and reactive power control of distributed generators. IEEE Trans Power Syst 31(2):983–993, ISSN: 08858950. https://doi.org/10.1109/TPWRS.2015.2419716

  6. Mohseni-Bonab SM, Rabiee A (2016) Optimal reactive power dispatch: a review, and a new stochastic voltage stability constrained multi-objective model at the presence of uncertain wind power generation. IET Gener Transm Distrib 11:815–829, ISSN: 1751-8687. https://doi.org/10.1049/iet-gtd.2016.1545

  7. Zhao B, Guo C, Cao Y (2005) A multiagent-based particle swarm optimization approach for optimal reactive power dispatch. IEEE Trans Power Syst 20(2):1070–1078, ISSN: 0885-8950. https://doi.org/10.1109/TPWRS.2005.846064

  8. Kekatos V, Wang G, Conejo AJ, Giannakis GB (2014) Stochastic reactive power management in microgrids with renewables. IEEE Trans Power Syst PP (99):1–10, ISSN: 0885-8950. https://doi.org/10.1109/TPWRS.2014.2369452arXiv: 1409.6758

  9. Robbins BA, Domínguez-garcía AD (2016) Optimal reactive power dispatch for voltage regulation in unbalanced distribution systems. IEEE Trans Power Syst 31(4):1–11, ISSN: 08858950. https://doi.org/10.1109/TPWRS.2015.2451519

  10. Gabash A, Li P (2012) Active-reactive optimal power flow in distribution networks with embedded generation and battery storage. IEEE Trans Power Syst 27(4):2026–2035, ISSN: 08858950. https://doi.org/10.1109/TPWRS.2012.2187315. arXiv: 9605103 [cs]

  11. Zhu T, Luo W, Bu C, Yue L (2016) Accelerate population-based stochastic search algorithms with memory for optima tracking on dynamic power systems. IEEE Trans Power Syst 31(1):268–277, ISSN: 08858950. https://doi.org/10.1109/TPWRS.2015.2407899

  12. Hung DQ, Mithulananthan N, Lee KY (2014) Determining PV penetration for distribution systems with time-varying load models. IEEE Trans Power Syst 29(6):3048–3057, ISSN: 0885-8950. https://doi.org/10.1109/TPWRS.2014.2314133

  13. Hung DQ, Mithulananthan N, Bansal R (2014) Integration of PV and BES units in commercial distribution systems considering energy loss and voltage stability. Appl Energy 113:1162–1170, ISSN: 03062619. https://doi.org/10.1016/j.apenergy.2013.08.069

  14. Zhang L, Tang W, Liang J, Cong P, Cai Y (2016) Coordinated day-ahead reactive power dispatch in distribution network based on real power forecast errors. IEEE Trans Power Syst 31(3):2472–2480, ISSN: 0885-8950. https://doi.org/10.1109/TPWRS.2015.2466435

  15. Rabiee A, Feshki Farahani H, Khalili M, Aghaei J, Muttaqi KM (2016) Integration of plug-in electric vehicles into microgrids as energy and reactive power providers in market environment. IEEE Trans Ind Informatics 12(4):1312–1320, ISSN: 15513203. https://doi.org/10.1109/TII.2016.2569438

  16. Cheng B, Powell W (2016) Co-optimizing battery storage for the frequency regulation and energy arbitrage using multi-scale dynamic programming. IEEE Trans Smart Grid PP (99):1–10, ISSN: 19493053. https://doi.org/10.1109/TSG.2016.2605141

  17. Sanjari M, Karami H, Gooi HB (2017) Analytical rule-based approach to online optimal control of smart residential energy system. IEEE Trans Ind Informatics ISSN: 1551-3203. https://doi.org/10.1109/TII.2017.2651879

  18. Mehta R, Srinivasan D, Khambadkone AM, Yang J, Trivedi A (2016) Smart charging strategies for optimal integration of plug-in electric vehicles within existing distribution system infrastructure. IEEE Trans Smart Grid 3053 no. c:1–1, ISSN: 1949-3053. https://doi.org/10.1109/TSG.2016.2550559

  19. Sarker MR, Olsen DJ, Ortega-Vazquez MA (2016) Co-optimization of distribution transformer aging and energy arbitrage using electric vehicles IEEE Trans Smart Grid 1–11, ISSN: 19493053. https://doi.org/10.1109/TSG.2016.2535354

  20. Gandhi O, Zhang W, Rodríguez-Gallegos CD, Bieri M, Reindl T, Srinivasan D (2018) Analytical approach to reactive power dispatch and energy arbitrage in distribution systems with ders. IEEE Trans Power Syst 33(6):6522–6533, ISSN: 0885-8950. https://doi.org/10.1109/TPWRS.2018.2829527

  21. Wu L, Zhao Z, Liu J (2007) A single-stage three-phase grid-connected photovoltaic system with modified mppt method and reactive power compensation. IEEE Trans Energy Convers 22(4):881–886, ISSN: 08858969. https://doi.org/10.1109/TEC.2007.895461arXiv: z0024

  22. Gandhi O, Rodríguez-Gallegos CD, Zhang W, Srinivasan D, Reindl T (2018) Economic and technical analysis of reactive power provision from distributed energy resources in microgrids. Appl Energy 210:827–841, ISSN: 03062619. https://doi.org/10.1016/j.apenergy.2017.08.154

  23. SMA, Sunny tripower inverter. https://usa.krannichsolar.com/fileadmin/content/dataSTPTL-US12-24EXP-DUS132533W.pdf

  24. Koller M, Borsche T, Ulbig A, Andersson G (2013) Defining a degradation cost function for optimal control of a battery energy storage system. In: 2013 IEEE Grenoble Conference, IEEE, Jun. 2013, pp 1–6, ISBN: 978-1-4673-5669-5. https://doi.org/10.1109/PTC.2013.6652329

  25. Ghosh S, Das D (1999) Method for load-flow solution of radial distribution networks. IEE Proc Gener Transm Distrib 146(6):641–648, ISSN: 13502360. https://doi.org/10.1049/ip-gtd:19990464

  26. Teng JH (2003) A direct approach for distribution system load flow solutions. IEEE Trans Power Delivery 18(3):882–887, ISSN: 0885-8977. https://doi.org/10.1109/TPWRD.2003.813818

  27. Baran ME, Wu FF (1989) Network reconfiguration in distribution systems for loss reduction and load balancing. IEEE Trans Power Delivery 4(2):1401–1407, ISSN: 0885-8977. https://doi.org/10.1109/61.25627

  28. Bieri M (2017) Methodology description: SERIS future power price scenarios

    Google Scholar 

  29. EMC, Energy market price information. https://www.emcsg.com/marketdata/priceinformation Visited on 04/01/2018

  30. Wei H, Sasaki H, Kubokawa J, Yokoyama R (1998) An interior point nonlinear programming for optimal power flow problems with a novel data structure. IEEE Trans Power Syst 13(3):870–877, ISSN: 08858950. https://doi.org/10.1109/59.708745

  31. Liu M, Tso S, Cheng Y (2002) An extended nonlinear primal-dual interior-point algorithm for reactive-power optimization of large-scale power systems with discrete control variables. IEEE Trans Power Syst 17(4):982–991, ISSN: 0885-8950. https://doi.org/10.1109/TPWRS.2002.804922

  32. Li YW, Kao CN (2009) An accurate power control strategy for powerelectronics- interfaced distributed generation units operating in a low-voltage multibus microgrid. IEEE Trans Power Electron 24(12):2977–2988, ISSN: 08858993. https://doi.org/10.1109/TPEL.2009.2022828

  33. Gandhi O, Zhang W, Rodríguez-Gallegos CD, Srinivasan D, Reindl T (2016) Continuous optimization of reactive power from PV and EV in distribution system. In: 2016 IEEE Innovative Smart Grid Technologies–Asia (ISGT-Asia), Melbourne. Nov. 2016, IEEE. pp 281–287. ISBN: 978-1-5090-4303-3. https://doi.org/10.1109/ISGT-Asia.2016.7796399

  34. Chelouah R, Siarry P (2000) A continuous genetic algorithm designed for the global optimization of multimodal functions. J Heuristics 6:191–213

    Google Scholar 

  35. Gandhi O, Rodríguez-Gallegos CD, Srinivasan D (2016) Review of optimization of power dispatch in renewable energy system. In: 2016 IEEE Innovative Smart Grid Technologies–Asia (ISGT-Asia), Melbourne. Nov. 2016. IEEE. pp 250–257. ISBN: 978-1-5090-4303-3. https://doi.org/10.1109/ISGT-Asia.2016.7796394

  36. Bhosekar A, Ierapetritou M (2018) Advances in surrogate based modeling, feasibility analysis, and optimization: a review. Comput Chem Eng 108:250–267, ISSN: 00981354. https://doi.org/10.1016/j.compchemeng.2017.09.017

  37. Queipo NV, Haftka RT, Shyy W, Goel T, Vaidyanathan R, Tucker PK (2005) Surrogate-based analysis and optimization. Prog Aerosp Sci 41(1):1–28. https://doi.org/10.1016/j.paerosci.2005.02.001

  38. Trivedi A, Sanyal K, Verma P, Srinivasan D (2017) A unified differential evolution algorithm for constrained optimization problems. 2017 IEEE Congress on Evolutionary Computation CEC 2017 - Proceedings, pp 1231–1238. https://doi.org/10.1109/CEC.2017.7969446

  39. Trivedi A, Biswas N, Chakroborty S, Srinivasan D (2017) Extending unified differential evolution with a new ensemble of constraint handling techniques. In: 2017 IEEE Symposium Series on Computational Intelligence (SSCI). Nov. 2017, IEEE. pp 1–8, ISBN: 978-1-5386-2726-6. https://doi.org/10.1109/SSCI.2017.8285446

  40. Mirjalili S, Gandomi AH, Mirjalili SZ, Saremi S, Faris H, Mirjalili SM (2017) Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Adv Eng Softw 114:163–191, ISSN: 18735339. https://doi.org/10.1016/j.advengsoft.2017.07.002

  41. Savier JS, Das D (2007) Impact of network reconfiguration on loss allocation of radial distribution systems. IEEE Trans Power Delivery 22(4):2473–2480, ISSN: 08858977. https://doi.org/10.1109/TPWRD.2007.905370

  42. Zhang D, Fu Z, Zhang L (2007) An improved TS algorithm for loss-minimum reconfiguration in large-scale distribution systems. Electr Power Syst Res 77(5–6):685–694, ISSN: 03787796. https://doi.org/10.1016/j.epsr.2006.06.005

  43. EMC (2016) Use of system charges https://www.mypower.com.sg/documents/ts-usc.pdf Visited on 04/01/2018

  44. Braun M (2008) Provision of ancillary services by distributed generators, Ph.D Thesis, Kassel University, p 273, ISBN: 9783899586381

    Google Scholar 

  45. Zhang W, Quan H, Gandhi O, Rodríguez-Gallegos CD, Sharma A, Srinivasan D (2017) An ensemble machine learning based approach for constructing probabilistic PV generation forecasting. In: 2017 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC). Nov. 2017, IEEE. pp 1–6. ISBN: 978-1-5386-1379-5. https://doi.org/10.1109/APPEEC.2017.8308947

  46. Wu W, Hu Z, Song Y (2016) A new method for OPF combining interior point method and filled function method. In: 2016 IEEE Power and Energy Society General Meeting (PESGM). Jul. 2016, IEEE. pp 1–5. ISBN: 978-1-5090-4168-8. https://doi.org/10.1109/PESGM.2016.7741321

  47. Kelner V, Capitanescu F, Léonard O, Wehenkel L (2008) A hybrid optimization technique coupling an evolutionary and a local search algorithm. J Comput Appl Math 215(2):448–456, ISSN: 03770427. https://doi.org/10.1016/j.cam.2006.03.048

Download references

Author information

Authors and Affiliations

  1. Solar Energy Research Institute of Singapore, National University of Singapore, Singapore, Singapore

    Dr. Oktoviano Gandhi

Authors
  1. Dr. Oktoviano Gandhi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Oktoviano Gandhi .

Rights and permissions

Reprints and permissions

Copyright information

© 2021 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Gandhi, O. (2021). Analytical Approach to Power Dispatch in Distribution Systems. In: Reactive Power Support Using Photovoltaic Systems. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-030-61251-1_3

Download citation

  • DOI: https://doi.org/10.1007/978-3-030-61251-1_3

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-61250-4

  • Online ISBN: 978-3-030-61251-1

  • eBook Packages: EnergyEnergy (R0)

Publish with us

Policies and ethics

Search

Navigation