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Energy Management in Distribution System Using Volt-VAr Optimization for Different Loading Conditions

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Abstract

In the current scenario, the major challenge among power utilities is to meet an exponential rise in energy demand. The major portion of increased demand is still fulfilled by coal-based power generators that impose a lot of security threats due to the exhaustible nature of fossil fuels, increased carbon footprints, negative environmental impacts like increased pollution level, environmental temperature rise and global warming. Therefore, the power utilities throughout the globe are adopting energy management techniques to tackle different issues related to supply–demand mismatching, hikes in energy prices and energy securities. Volt-VAr control is a widely used energy management technique that optimally coordinates voltage and VAr injection. Optimal reduction of a voltage produces a significant reduction in power consumption for voltage-dependent loads, which constitutes the major portion of the distribution system load. The VAr injection also ensures energy savings due to the compensation effect. Therefore, this article presented an algorithm for energy management through Volt-VAr optimization. To estimate energy savings using the proposed technique, different case studies have been considered and have been validated using IEEE 33 node system. Simulation results show that significant demand reduction during peak loading condition is possible through deeper voltage reduction while applying the proposed Volt-VAr control technique. Furthermore, the proposed technique also ensures reduction in total energy demand, line loss minimization, energy savings, power factor correction, capacity release and improvement in voltage profile.

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Data Availability

All data generated or analysed during this study are included in this published article [and its supplementary information files].

Abbreviations

P, Q:

Active and reactive power consumption at ith node

\({P}_{0},{Q}_{0}\) :

Rated active and reactive power at ith node

\({V}_{0},{V}_{i}\),:

Rated voltage and operating voltage at ith node

\({V}_{min},{V}_{max}\) :

Minimum and maximum permissible limit of voltage at ith node

\({Z}_{Pi},{I}_{Pi},{P}_{Pi}\) :

ZIP coefficients for real power at ith node

\({Z}_{Qi},{I}_{Qi},{P}_{Qi}\) :

ZIP coefficients for reactive power at ith node

\({P}_{Tloss} , { Q}_{Tloss}\) :

Total active, reactive power loss

\({Z}_{ij}={R}_{ij}+{X}_{ij}\) :

Impedance connecting line node i and j

\({P}_{eff/j}\),\({Q}_{eff/j}\) :

Total effective active and reactive power loads beyond node j

\({P}_{Lossij}\), \({Q}_{Lossij}\) :

Real and reactive power losses of line between node i and j

\({v}_{k}^{n}\) :

Velocity of kth particle at n iteration

\({x}_{k}^{n}\) :

Position of kthparticle at n iteration

\(w\),:

Coefficients of weight factor

\({w}_{min},{w}_{max}\) :

Upper and lower limits of w

\({p}_{bestk}\) :

Personal solution;

\(gbest\) :

Global solution

\({c}_{1},{c}_{2}\) :

Acceleration coefficient

\(rand1,rand2\) :

Random number [0–1]

\(ite\) :

Current number of iteration

\({ite}_{max}\) :

Maximum number of iteration

\({N}_{b}\) :

Total no. of nodes

\({\mathrm{F}}_{\mathrm{c}}\), :

Total energy cost

\({K}_{p}\) :

Annual power loss cost ($/kW)

\({K}_{c}\) :

Annual capacitor cost ($/KVAr)

\({N}_{q}\) :

No. of capacitors to be installed

\({\mathrm{F}}_{\mathrm{E}}\) :

Energy savings with the implementation of CVR

\({P}_{loss}^{1}, {P}_{loss}^{2}\) :

Active power losses before and after CVR applied

\({Q}_{loss}^{1}, {Q}_{loss}^{2}\) :

Reactive power losses before and after CVR applied

\({F}_{V}\) :

Voltage reduction limit;

\({F}_{D}\) :

Demand reduction benefits

\({F}_{1}\) :

Deviation in kW demand

\({F}_{2}\) :

Deviation in kVAr demand

\({{P}_{Di}^{1},P}_{Di}^{2}\) :

Active power demand at ith bus before and after CVR applied

\({Q}_{Di}^{1}, {Q}_{Di}^{2}\) :

Reactive power demand at ith bus before and after CVR applied

\({F}_{VD}\),:

Bus voltage deviation

\({N}_{cap}\) :

No. of optimal locations

\({N}_{cap}^{max}\) :

Maximum number of possible locations

\({V}_{no-control}\) :

Substation voltage during no control

\({V}_{CVR}\) :

Substation voltage during volt-VAr control

\({C}_{no-control}\) :

Total annual cost during no control

\({V}_{no-control}\) :

Total annual cost during volt-VAr control

References

  • Abdelaziz AY, Ali ES, Abd Elazim SM (2016) Flower pollination algorithm and loss sensitivity factors for optimal sizing and placement of capacitors in radial distribution systems. Int J Electr Power Energy Syst 78:207–214

    Article  Google Scholar 

  • Abou El-Ela AA, El-Sehiemy RA, Abbas AS (2018) Optimal placement and sizing of distributed generation and capacitor banks in distribution systems using water cycle algorithm. IEEE Syst J 12(4):3629–3636

    Article  Google Scholar 

  • Abou El-Ela AA, El-Sehiemy RA, Kinawy AM, Mouwafi MT (2016) Optimal capacitor placement in distribution systems for power loss reduction and voltage profile improvement. IET Gener Transm Distrib 10(5):1209–1221

    Article  Google Scholar 

  • American National Standard for Electrical Power Systems and Equipment Voltage Rating (60 Hz), American Standard Institute, C84.1–2006, December 2006.

  • Bag, B., & Thakur, T., “Energy management using volt/var control of end-use appliances without affecting their performances and lives.” Journal of Renewable and Sustainable Energy, vol.9, no.3, pp: 035504, 2017.

  • Baran M, Wu FF (1989) Optimal sizing of capacitors placed on a radial distribution system. IEEE Trans Power Delivery 4(1):735–743

    Article  Google Scholar 

  • Bokhari, A., Alkan, A., Dogan, R., Diaz-Aguiló, M., De Leon, F., Czarkowski, D., ... & Uosef, R. E., “Experimental determination of the ZIP coefficients for modern residential, commercial, and industrial loads.” IEEE Transactions on Power Delivery, vol.29, no.3, pp: 1372–1381 2013.

  • Díaz P, Pérez-Cisneros M, Cuevas E, Camarena O, Martinez FAF, González A (2018) A swarm approach for improving voltage profiles and reduce power loss on electrical distribution networks. IEEE Access 6:49498–49512

    Article  Google Scholar 

  • Ellens, W., Berry, A., & West, S. (2012) A quantification of the energy savings by conservation voltage reduction. In 2012 IEEE International Conference on Power System Technology (POWERCON) (pp. 1–6). IEEE.

  • El-Shahat A, Haddad RJ, Alba-Flores R, Rios F, Helton Z (2020) Conservation voltage reduction case study. IEEE Access 8:55383–55397

    Article  Google Scholar 

  • Hossein ZS, Khodaei A, Fan W, Hossan MS, Zheng H, Fard SA, Bahramirad S (2020) Conservation voltage reduction and volt-VAR optimization: measurement and verification benchmarking. IEEE Access 8:50755–50770

  • Lakra, Neha Smitha, and Baidyanath Bag, “VAr optimization in mesh network during different loading conditions.” In 2021 7th International Conference on Electrical Energy Systems (ICEES). pp: 268–273, 2021

  • Milosevic B, Begovic M (2004) Capacitor placement for conservative voltage reduction on distribution feeders. IEEE Trans Power Delivery 19(3):1360–1367

    Article  Google Scholar 

  • Mtonga TP, Kaberere KK, Irungu GK (2021) Optimal shunt capacitors’ placement and sizing in radial distribution systems using multiverse optimizer. IEEE Canadian Journal of Electrical and Computer Engineering 44(1):10–21

    Article  Google Scholar 

  • Peskin, Melissa A., Phillip W. Powell, and Edmund J. Hall., “Conservation voltage reduction with feedback from advanced metering infrastructure.” In PES T&D, pp: 1–8, 2012.

  • Rajaram R, Kumar KS, Rajasekar N (2015) Power system reconfiguration in a radial distribution network for reducing losses and to improve voltage profile using modified plant growth simulation algorithm with Distributed Generation (DG). Energy Rep 1:116–122

    Article  Google Scholar 

  • Satsangi S, Kumbhar GB (2018) Effect of load models on scheduling of VVC devices in a distribution network. IET Gener Transm Distrib 12(17):3993–4001

    Article  Google Scholar 

  • Short, T. A., & Mee, R. W. (2012). Voltage reduction field trials on distributions circuits. In PES T&D 2012 (pp. 1–6). IEEE.

  • Shuaib YM, Kalavathi MS, Rajan CCA (2015) Optimal capacitor placement in radial distribution system using gravitational search algorithm. Int J Electr Power Energy Syst 64:384–397

    Article  Google Scholar 

  • Simulation Tool–OpenDSS,” [Online]. Available:http://smartgrid.epri.com/SimulationTool.aspx. Accessed 10 July 2020.

  • Singh, S., Singh, S. P., & Babu Pamshetti, V. (2020). Energy efficiency and peak load management via CVR and distributed energy storage in active distribution grid. International Transactions on Electrical Energy Systems, 30(3), e12224.

  • Sundhararajan S, Pahwa A (1994) Optimal selection of capacitors for radial distribution systems using a genetic algorithm. IEEE Trans Power Syst 9(3):1499–1507

    Article  Google Scholar 

  • Wang J, Raza A, Hong T, Sullberg AC, De León F, Huang Q (2017) Analysis of energy savings of CVR including refrigeration loads in distribution systems. IEEE Trans Power Delivery 33(1):158–168

    Article  Google Scholar 

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Acknowledgements

The authors express their gratitude to NIT Raipur for providing access to MATLAB used for validating the proposed methodology.

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  1. National Institute of Technology Raipur, Raipur, India

    Neha Smitha Lakra & Baidyanath Bag

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  1. Neha Smitha Lakra
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  2. Baidyanath Bag
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Correspondence to Neha Smitha Lakra.

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Lakra, N.S., Bag, B. Energy Management in Distribution System Using Volt-VAr Optimization for Different Loading Conditions. Process Integr Optim Sustain 6, 295–306 (2022). https://doi.org/10.1007/s41660-021-00214-2

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