Skip to main content
Top

2021 | OriginalPaper | Chapter

Numerical Methods in Selecting Location of Distributed Generation in Energy Network

Authors : Reza Effatnejad, Mahdi Hedayati, Keyvan Choopani, Milad Chanddel

Published in: Numerical Methods for Energy Applications

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Integration of Distributed Generation (DG) units provide benefits to distribution systems. The presence of DG can affect various parameters of the distribution system such as reducing power losses and improving voltage profiles. But to maximize the profit from DG, the optimal location and the best amount of DG must be determined. Optimal placement and sizing of DG in the distribution network is a Complicated optimization problem. This paper presents a simple method for optimal sizing and optimal placement of distributed generators. This chapter of the book is about DG placement using numerical and innovative methods to solve the DG placement problem and comparing the two methods with each other. These methods are performed in a radial distribution system to minimize the total real power loss and improve the voltage profile. The proposed methods are tested on the standard IEEE 33-bus test system and the results are presented and compared with different approaches.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Puttgen HB, Macgregor PR, Lambert FC (2003) Distributed generation: Semantic hype or the dawn of a new era? IEEE Power Energ Mag 1(1):22–29CrossRef Puttgen HB, Macgregor PR, Lambert FC (2003) Distributed generation: Semantic hype or the dawn of a new era? IEEE Power Energ Mag 1(1):22–29CrossRef
2.
go back to reference Zhang X, Karady GG, Ariaratnam ST (2013) Optimal allocation of CHP-based distributed generation on urban energy distribution networks. IEEE Trans Sustain Energy 5(1):246–253CrossRef Zhang X, Karady GG, Ariaratnam ST (2013) Optimal allocation of CHP-based distributed generation on urban energy distribution networks. IEEE Trans Sustain Energy 5(1):246–253CrossRef
3.
go back to reference Kumar K, Kumar M (2020) Impacts of distributed generations on power system: transmission, distribution, power quality, and power stability. Handbook of research on new solutions and technologies in electrical distribution networks. IGI Global, pp 171–190 Kumar K, Kumar M (2020) Impacts of distributed generations on power system: transmission, distribution, power quality, and power stability. Handbook of research on new solutions and technologies in electrical distribution networks. IGI Global, pp 171–190
4.
go back to reference Freitas W et al. (2006) Comparative analysis between synchronous and induction machines for distributed generation applications. IEEE Trans Power Syst 21(1):301–311 Freitas W et al. (2006) Comparative analysis between synchronous and induction machines for distributed generation applications. IEEE Trans Power Syst 21(1):301–311
5.
go back to reference Barker PP, De Mello RW (2000) Determining the impact of distributed generation on power systems. I. Radial distribution systems. 2000 Power engineering society summer meeting (Cat. No. 00CH37134), vol 3. IEEE Barker PP, De Mello RW (2000) Determining the impact of distributed generation on power systems. I. Radial distribution systems. 2000 Power engineering society summer meeting (Cat. No. 00CH37134), vol 3. IEEE
6.
go back to reference Khan UN (2008) Impact of distributed generation on electrical power network. Wroclav University of Technology, Wroclav, Poland 1 Khan UN (2008) Impact of distributed generation on electrical power network. Wroclav University of Technology, Wroclav, Poland 1
7.
go back to reference Photovoltaics, Dispersed Generation, and Energy Storage (2009) IEEE application guide for IEEE Std 1547™. IEEE standard for interconnecting distributed resources with electric power systems Photovoltaics, Dispersed Generation, and Energy Storage (2009) IEEE application guide for IEEE Std 1547™. IEEE standard for interconnecting distributed resources with electric power systems
8.
go back to reference Series IRE (2009) Microgrids and active distribution networks. The institution of Engineering and Technology Series IRE (2009) Microgrids and active distribution networks. The institution of Engineering and Technology
9.
go back to reference Zakariazadeh A, Jadid S (2014) Smart microgrid operational planning considering multiple demand response programs. J Renew Sustain Energy 6(1):013134CrossRef Zakariazadeh A, Jadid S (2014) Smart microgrid operational planning considering multiple demand response programs. J Renew Sustain Energy 6(1):013134CrossRef
10.
go back to reference Zakariazadeh A, Jadid S, Siano P (2014) Smart microgrid energy and reserve scheduling with demand response using stochastic optimization. Int J Electr Power Energy Syst 63:523–533CrossRef Zakariazadeh A, Jadid S, Siano P (2014) Smart microgrid energy and reserve scheduling with demand response using stochastic optimization. Int J Electr Power Energy Syst 63:523–533CrossRef
11.
go back to reference Mizani S, Yazdani A (2009) Optimal design and operation of a grid-connected microgrid. In: 2009 IEEE electrical power & energy conference (EPEC). IEEE Mizani S, Yazdani A (2009) Optimal design and operation of a grid-connected microgrid. In: 2009 IEEE electrical power & energy conference (EPEC). IEEE
12.
go back to reference Mohamed FA, Koivo HN (2010) System modelling and online optimal management of microgrid using mesh adaptive direct search. Int J Electr Power Energy Syst 32(5):398–407CrossRef Mohamed FA, Koivo HN (2010) System modelling and online optimal management of microgrid using mesh adaptive direct search. Int J Electr Power Energy Syst 32(5):398–407CrossRef
13.
go back to reference Kayal P, Chanda CK (2015) Optimal mix of solar and wind distributed generations considering performance improvement of electrical distribution network. Renew energy 75:173–186 Kayal P, Chanda CK (2015) Optimal mix of solar and wind distributed generations considering performance improvement of electrical distribution network. Renew energy 75:173–186
14.
go back to reference Hedayati H, Nabaviniaki A, Akbarimajd A (2008) A method for placement of DG units in distribution networks. IEEE Trans Power Delivery 23(3):1620–1628 Hedayati H, Nabaviniaki A, Akbarimajd A (2008) A method for placement of DG units in distribution networks. IEEE Trans Power Delivery 23(3):1620–1628
15.
go back to reference Ochoa LF, Padilha-Feltrin A, Harrison GP (2006) Evaluating distributed generation impacts with a multiobjective index. IEEE Trans Power Delivery 21(3):1452–1458CrossRef Ochoa LF, Padilha-Feltrin A, Harrison GP (2006) Evaluating distributed generation impacts with a multiobjective index. IEEE Trans Power Delivery 21(3):1452–1458CrossRef
16.
go back to reference Georgilakis PS, Hatziargyriou ND (2013) Optimal distributed generation placement in power distribution networks: models, methods, and future research. IEEE Trans Power Syst 28(3):3420–3428CrossRef Georgilakis PS, Hatziargyriou ND (2013) Optimal distributed generation placement in power distribution networks: models, methods, and future research. IEEE Trans Power Syst 28(3):3420–3428CrossRef
17.
go back to reference Costa PM, Matos MA (2009) Avoided losses on LV networks as a result of microgeneration. Electr Power Syst Res 79(4):629–634 Costa PM, Matos MA (2009) Avoided losses on LV networks as a result of microgeneration. Electr Power Syst Res 79(4):629–634
18.
go back to reference Gözel T, Hocaoglu MH (2009) An analytical method for the sizing and siting of distributed generators in radial systems. Electr Power Syst Res 79(6): 912–918 Gözel T, Hocaoglu MH (2009) An analytical method for the sizing and siting of distributed generators in radial systems. Electr Power Syst Res 79(6): 912–918
19.
go back to reference Lee SH, Park JW (2009) Selection of optimal location and size of multiple distributed generations by using Kalman filter algorithm. IEEE Trans Power Syst 24(3):1393–1400CrossRef Lee SH, Park JW (2009) Selection of optimal location and size of multiple distributed generations by using Kalman filter algorithm. IEEE Trans Power Syst 24(3):1393–1400CrossRef
20.
go back to reference Acharya N, Mahat P, Mithulananthan N (2006) An analytical approach for DG allocation in primary distribution network. Int J Electr Power Energy Syst 28(10):669–678CrossRef Acharya N, Mahat P, Mithulananthan N (2006) An analytical approach for DG allocation in primary distribution network. Int J Electr Power Energy Syst 28(10):669–678CrossRef
21.
go back to reference Hung DQ, Mithulananthan N (2011) Multiple distributed generator placement in primary distribution networks for loss reduction. IEEE Trans Indus Electron 60(4):1700–1708 Hung DQ, Mithulananthan N (2011) Multiple distributed generator placement in primary distribution networks for loss reduction. IEEE Trans Indus Electron 60(4):1700–1708
22.
go back to reference Rau NS, Wan Y (1994) Optimum location of resources in distributed planning. IEEE Trans Power Syst 9(4):2014–2020CrossRef Rau NS, Wan Y (1994) Optimum location of resources in distributed planning. IEEE Trans Power Syst 9(4):2014–2020CrossRef
23.
go back to reference Vovos PN, Bialek JW (2005) Direct incorporation of fault level constraints in optimal power flow as a tool for network capacity analysis. IEEE Trans Power Syst 20(4):2125–2134CrossRef Vovos PN, Bialek JW (2005) Direct incorporation of fault level constraints in optimal power flow as a tool for network capacity analysis. IEEE Trans Power Syst 20(4):2125–2134CrossRef
24.
go back to reference Rao SS (1996) Engineering optimization: theory and practice. John, New York, p 903 Rao SS (1996) Engineering optimization: theory and practice. John, New York, p 903
26.
go back to reference AlHajri MF, AlRashidi MR, El-Hawary ME (2010) Improved sequential quadratic programming approach for optimal distribution generation deployments via stability and sensitivity analyses. Electr Power Comp Syst 38(14):1595–1614CrossRef AlHajri MF, AlRashidi MR, El-Hawary ME (2010) Improved sequential quadratic programming approach for optimal distribution generation deployments via stability and sensitivity analyses. Electr Power Comp Syst 38(14):1595–1614CrossRef
27.
go back to reference Ochoa LF, Dent CJ, Harrison GP (2009) Distribution network capacity assessment: variable DG and active networks. IEEE Trans Power Syst 25(1):87–95CrossRef Ochoa LF, Dent CJ, Harrison GP (2009) Distribution network capacity assessment: variable DG and active networks. IEEE Trans Power Syst 25(1):87–95CrossRef
28.
go back to reference Dent CJ, Ochoa LF, Harrison GP (2010) Network distributed generation capacity analysis using OPF with voltage step constraints. IEEE Trans Power Syst 25(1):296–304CrossRef Dent CJ, Ochoa LF, Harrison GP (2010) Network distributed generation capacity analysis using OPF with voltage step constraints. IEEE Trans Power Syst 25(1):296–304CrossRef
29.
go back to reference Atwa YM et al (2009) Optimal renewable resources mix for distribution system energy loss minimization. IEEE Trans Power Syst 25(1):360–370CrossRef Atwa YM et al (2009) Optimal renewable resources mix for distribution system energy loss minimization. IEEE Trans Power Syst 25(1):360–370CrossRef
30.
go back to reference Kumar A, Gao W (2010) Optimal distributed generation location using mixed integer non-linear programming in hybrid electricity markets. IET Gener Transm Distrib 4(2):281–298CrossRef Kumar A, Gao W (2010) Optimal distributed generation location using mixed integer non-linear programming in hybrid electricity markets. IET Gener Transm Distrib 4(2):281–298CrossRef
31.
go back to reference Esmaili M (2013) Placement of minimum distributed generation units observing power losses and voltage stability with network constraints. IET Gener Transm Dist 7(8):813–821CrossRef Esmaili M (2013) Placement of minimum distributed generation units observing power losses and voltage stability with network constraints. IET Gener Transm Dist 7(8):813–821CrossRef
32.
go back to reference Kaur S, Kumbhar G, Sharma J (2014) A MINLP technique for optimal placement of multiple DG units in distribution systems. Int J Electr Power Energy Syst 63:609–617CrossRef Kaur S, Kumbhar G, Sharma J (2014) A MINLP technique for optimal placement of multiple DG units in distribution systems. Int J Electr Power Energy Syst 63:609–617CrossRef
33.
go back to reference Leyffer S (2001) Integrating SQP and branch-and-bound for mixed integer nonlinear programming. Comput Optim Appl 18(3):295–309MathSciNetCrossRef Leyffer S (2001) Integrating SQP and branch-and-bound for mixed integer nonlinear programming. Comput Optim Appl 18(3):295–309MathSciNetCrossRef
34.
go back to reference Khalesi N, Rezaei N, Haghifam M-R (2011) DG allocation with application of dynamic programming for loss reduction and reliability improvement. Int J Electr Power Energy Syst 33(2):288–295 Khalesi N, Rezaei N, Haghifam M-R (2011) DG allocation with application of dynamic programming for loss reduction and reliability improvement. Int J Electr Power Energy Syst 33(2):288–295
35.
go back to reference Bellman RE, Dreyfus SE (1962) Applied dynamic programming. Princeton UniversityPress, Princeton, New Jersey, 1962. Bellman Applied Dynamic Programming Bellman RE, Dreyfus SE (1962) Applied dynamic programming. Princeton UniversityPress, Princeton, New Jersey, 1962. Bellman Applied Dynamic Programming
36.
go back to reference Jabr RA, Pal BC (2009) Ordinal optimisation approach for locating and sizing of distributed generation. IET Gener Transm Distrib 3(8):713–723CrossRef Jabr RA, Pal BC (2009) Ordinal optimisation approach for locating and sizing of distributed generation. IET Gener Transm Distrib 3(8):713–723CrossRef
37.
go back to reference Singh D, Misra RK, Singh D (2007) Effect of load models in distributed generation planning. IEEE Trans Power Syst 22(4):2204–2212 Singh D, Misra RK, Singh D (2007) Effect of load models in distributed generation planning. IEEE Trans Power Syst 22(4):2204–2212
38.
go back to reference Kotamarty S, Khushalani S, Schulz N (2008) Impact of distributed generation on distribution contingency analysis. Electr Power Syst Res 78(9):1537–1545CrossRef Kotamarty S, Khushalani S, Schulz N (2008) Impact of distributed generation on distribution contingency analysis. Electr Power Syst Res 78(9):1537–1545CrossRef
39.
go back to reference Khan H, Choudhry MA (2010) Implementation of Distributed Generation (IDG) algorithm for performance enhancement of distribution feeder under extreme load growth. Int J Electr Power Energy Syst 32(9):985–997 Khan H, Choudhry MA (2010) Implementation of Distributed Generation (IDG) algorithm for performance enhancement of distribution feeder under extreme load growth. Int J Electr Power Energy Syst 32(9):985–997
40.
go back to reference Moradi MH, Abedini M (2012) A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. Int J Electr Power Energy Syst 34(1):66–74 Moradi MH, Abedini M (2012) A combination of genetic algorithm and particle swarm optimization for optimal DG location and sizing in distribution systems. Int J Electr Power Energy Syst 34(1):66–74
41.
go back to reference Gomez-Gonzalez M, López A, Jurado F (2012) Optimization of distributed generation systems using a new discrete PSO and OPF. Electr Power Syst Res 84(1):174–180CrossRef Gomez-Gonzalez M, López A, Jurado F (2012) Optimization of distributed generation systems using a new discrete PSO and OPF. Electr Power Syst Res 84(1):174–180CrossRef
42.
go back to reference Pandi VR, Zeineldin HH, Xiao W (2012) Determining optimal location and size of distributed generation resources considering harmonic and protection coordination limits. IEEE Trans Power Syst 28(2):1245–1254 Pandi VR, Zeineldin HH, Xiao W (2012) Determining optimal location and size of distributed generation resources considering harmonic and protection coordination limits. IEEE Trans Power Syst 28(2):1245–1254
43.
go back to reference Taşgetiren MF, Liang Y-C (2003) A binary particle swarm optimization algorithm for lot sizing problem. J Econ Soc Res 5(2):1–20 Taşgetiren MF, Liang Y-C (2003) A binary particle swarm optimization algorithm for lot sizing problem. J Econ Soc Res 5(2):1–20
44.
go back to reference Singh RK, Goswami SK (2009) Optimum siting and sizing of distributed generations in radial and networked systems. Electr Power Comp Syst 37(2):127–145CrossRef Singh RK, Goswami SK (2009) Optimum siting and sizing of distributed generations in radial and networked systems. Electr Power Comp Syst 37(2):127–145CrossRef
45.
go back to reference Singh D, Singh D, Verma KS (2009) Multiobjective optimization for DG planning with load models. IEEE Trans Power Syst 24(1):427–436 Singh D, Singh D, Verma KS (2009) Multiobjective optimization for DG planning with load models. IEEE Trans Power Syst 24(1):427–436
46.
go back to reference Shukla TN et al (2010) Optimal sizing of distributed generation placed on radial distribution systems. Electr Power Comp Syst 38(3):260–274CrossRef Shukla TN et al (2010) Optimal sizing of distributed generation placed on radial distribution systems. Electr Power Comp Syst 38(3):260–274CrossRef
47.
go back to reference Singh RK, Goswami SK (2010) Optimum allocation of distributed generations based on nodal pricing for profit, loss reduction, and voltage improvement including voltage rise issue. Int J Electr Power Energy Syst 32(6):637–644 Singh RK, Goswami SK (2010) Optimum allocation of distributed generations based on nodal pricing for profit, loss reduction, and voltage improvement including voltage rise issue. Int J Electr Power Energy Syst 32(6):637–644
48.
go back to reference Shaaban MF, Atwa YM, El-Saadany EF (2012) DG allocation for benefit maximization in distribution networks. IEEE Trans Power Syst 28(2):639–649CrossRef Shaaban MF, Atwa YM, El-Saadany EF (2012) DG allocation for benefit maximization in distribution networks. IEEE Trans Power Syst 28(2):639–649CrossRef
49.
go back to reference Golshan MEH, Arefifar SA (2007) Optimal allocation of distributed generation and reactive sources considering tap positions of voltage regulators as control variables. Eur Trans Electr Power 17(3):219–239 Golshan MEH, Arefifar SA (2007) Optimal allocation of distributed generation and reactive sources considering tap positions of voltage regulators as control variables. Eur Trans Electr Power 17(3):219–239
50.
go back to reference Novoa C, Jin T (2011) Reliability centered planning for distributed generation considering wind power volatility. Electr Power Syst Res 81(8):1654–1661CrossRef Novoa C, Jin T (2011) Reliability centered planning for distributed generation considering wind power volatility. Electr Power Syst Res 81(8):1654–1661CrossRef
51.
go back to reference Wang L, Singh C (2008) Reliability-constrained optimum placement of reclosers and distributed generators in distribution networks using an ant colony system algorithm. IEEE Trans Syst Man Cybern C (Appl Rev) 38(6):757–764 Wang L, Singh C (2008) Reliability-constrained optimum placement of reclosers and distributed generators in distribution networks using an ant colony system algorithm. IEEE Trans Syst Man Cybern C (Appl Rev) 38(6):757–764
52.
go back to reference Abu-Mouti FS, El-Hawary ME (2011) Optimal distributed generation allocation and sizing in distribution systems via artificial bee colony algorithm. IEEE Trans Power Delivery 26(4):2090–2101 Abu-Mouti FS, El-Hawary ME (2011) Optimal distributed generation allocation and sizing in distribution systems via artificial bee colony algorithm. IEEE Trans Power Delivery 26(4):2090–2101
53.
go back to reference Arya LD, Koshti A, Choube SC (2012) Distributed generation planning using differential evolution accounting voltage stability consideration. Int J Electr Power Energy Syst 42(1):196–207 Arya LD, Koshti A, Choube SC (2012) Distributed generation planning using differential evolution accounting voltage stability consideration. Int J Electr Power Energy Syst 42(1):196–207
54.
go back to reference Rao RS et al. (2012) Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation. IEEE Trans Power Syst 28(1):317–325 Rao RS et al. (2012) Power loss minimization in distribution system using network reconfiguration in the presence of distributed generation. IEEE Trans Power Syst 28(1):317–325
55.
go back to reference Sharma D, Gaur P, Mittal AP (2014) Comparative analysis of hybrid GAPSO optimization technique with GA and PSO methods for cost optimization of an off-grid hybrid energy system. Energy Technol Policy 1(1):106–114 Sharma D, Gaur P, Mittal AP (2014) Comparative analysis of hybrid GAPSO optimization technique with GA and PSO methods for cost optimization of an off-grid hybrid energy system. Energy Technol Policy 1(1):106–114
56.
go back to reference Choopani K, Hedayati M, Effatnejad R (2020) Self-healing optimization in active distribution network to improve reliability, and reduction losses, switching cost and load shedding. Int Trans Electr Energy Syst 30(5):e12348CrossRef Choopani K, Hedayati M, Effatnejad R (2020) Self-healing optimization in active distribution network to improve reliability, and reduction losses, switching cost and load shedding. Int Trans Electr Energy Syst 30(5):e12348CrossRef
57.
go back to reference Choopani K, Effatnejad R, Hedayati M (2020) Coordination of energy storage and wind power plant considering energy and reserve market for a resilience smart grid. J Energy Storage 30:101542CrossRef Choopani K, Effatnejad R, Hedayati M (2020) Coordination of energy storage and wind power plant considering energy and reserve market for a resilience smart grid. J Energy Storage 30:101542CrossRef
58.
go back to reference Vazinram F et al. (2020) Self-healing model for gas-electricity distribution network with consideration of various types of generation units and demand response capability. Energy Conver Manage 206:112487 Vazinram F et al. (2020) Self-healing model for gas-electricity distribution network with consideration of various types of generation units and demand response capability. Energy Conver Manage 206:112487
59.
go back to reference Vazinram F et al. (2019) Decentralised self-healing model for gas and electricity distribution network. IET Gener Transm Distrib 13(19):4451–4463 Vazinram F et al. (2019) Decentralised self-healing model for gas and electricity distribution network. IET Gener Transm Distrib 13(19):4451–4463
Metadata
Title
Numerical Methods in Selecting Location of Distributed Generation in Energy Network
Authors
Reza Effatnejad
Mahdi Hedayati
Keyvan Choopani
Milad Chanddel
Copyright Year
2021
DOI
https://doi.org/10.1007/978-3-030-62191-9_34