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Framework for optimal grounding system design concerning IEEE standard

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Abstract

This paper investigates the optimal grounding grid design using artificial intelligence techniques based on the empirical formula for grounding resistance (Rg), touch and step voltages (Et and Es), which are addressed in IEEE Std. 80-2013/Cor. 1-2015. The objective function is formulated based on the grid conductors’ material cost and the installation cost. Particle swarm optimization (PSO) and genetic algorithm (GA) are individually utilized to search for and confirm the global best solution of minimizing the grounding system cost with considering all operation constraints including the safety criteria. A modified objective function is constructed based on self-adaptive penalization utilized to account for constraint violations during the optimization process. The selection strategy for modifying the local best positions of particles and the global best position of the swarm is proposed to enhance the ability of PSO for fast convergence. Results proved that either PSO or GA settles on the global best solution, successfully. To perform the space domain investigation, the optimal grounding grid design is implemented using a finite element method, where the COMSOL Multiphysics program is selected to verify the settled optimal global solution. Using COMSOL, the grounding resistance and safety criteria are evaluated over the grid diagonally. The COMSOL results ensure the operating constraints satisfaction of the optimal grounding grid design. The performance evaluation reveals that the grounding potential rise limit, the available grid area, and the number of vertical rods greatly affect the optimization of the grounding system design. The results also illustrate a great significant effect of the fault current and upper surface resistivity on the optimal grid design.

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References

  1. Nedi F (2004) A new evolutionary method for designing grounding grids by touch voltage control. In: 2004 IEEE international symposium on industrial electronics, Ajaccio, France, 4–7 May 2004, vol 2, pp 1501–1505

  2. Kara S, Kalenderli O, Altay O (2015) Optimum grounding grid design by using genetic algorithms. In: 9th international conference on electrical and electronics engineering (ELECO), Bursa, Turkey, 26–28 November 2015, pp 1117–1121

  3. IEEE Guide for Safety in AC Substation Grounding. In IEEE Std 80-2013 (Revision of IEEE Std 80-2000/Incorporates IEEE Std 80-2013/Cor 1-2015), pp. 1–226, 15 May 2015

  4. Lee CY, Shen YX (2009) Optimal planning of ground grid based on particle swam algorithm. World Acad Sci Eng Technol 60:30–37

    Google Scholar 

  5. Otero AF, Cidrás J, Garrido C (2002) Grounding grid design using evolutionary computation-based methods. Electr Power Compon Syst 30(2):151–165

    Article  Google Scholar 

  6. Khodr HM (2009) Optimal methodology for the grounding systems design in transmission line using mixed-integer linear programming. Electr Power Compon Syst 38(2):115–136

    Article  Google Scholar 

  7. Naveen S, Kumar KS, Rajalakshmi K (2015) Distribution system reconfiguration for loss minimization using modified bacterial foraging optimization algorithm. Int J Electr Power Energy Syst 69:90–97

    Article  Google Scholar 

  8. Pegado R, Naupari Z et al (2019) Radial distribution network reconfiguration for power losses reduction based on improved selective BPSO. Electr Power Syst Res 169:206–213

    Article  Google Scholar 

  9. Gerez C, Silva LI, Belati EA et al (2019) Distribution network reconfiguration using selective firefly algorithm and a load flow analysis criterion for reducing the search space. IEEE Access 7:67874–67888

    Article  Google Scholar 

  10. Xing H, Sun X (2017) Distributed generation locating and sizing in active distribution network considering network reconfiguration. IEEE Access 5:14768–14774

    Article  Google Scholar 

  11. Chen G, Qian J, Zhang Z, Sun Z (2019) Applications of novel hybrid bat algorithm with constrained pareto fuzzy dominant rule on multi-objective optimal power flow problems. IEEE Access 7:52060–52084

    Article  Google Scholar 

  12. Jia YH, Chen WN, Gu T, Zhang H, Yuan H, Lin Y, Yu WJ, Zhang J (2018) A dynamic logistic dispatching system with set-based particle swarm optimization. IEEE Trans Syst Man Cybern Syst 48(9):1607–1621

    Article  Google Scholar 

  13. Dustegor D, Poroseva SV, Hussaini MY, Woodruff S (2010) Automated graph-based methodology for fault detection and location in power systems. IEEE Trans Power Delivery 25(2):638–646

    Article  Google Scholar 

  14. Alik B, Teguar M, Mekhaldi A (2015) Minimization of grounding system cost using PSO, GAO and HPSGAO techniques. IEEE Trans Power Delivery 30(6):2561–2569

    Article  Google Scholar 

  15. Ghoneim SSM, Taha IBM (2016) Control the cost, touch and step voltages of the grounding grids design. IET Sci Meas Technol 10:943–951

    Article  Google Scholar 

  16. Elfergani A (2013) Accelerated particle swarm optimization-based approach to the optimal design of substation grounding grid. Przegląd Elektrotech 89:30–31

    Google Scholar 

  17. Opara K, Arabas J (2012) Decomposition and metaoptimization of mutation operator in differential evolution. In: Rutkowski L, Korytkowski M, Scherer R, Tadeusiewicz R, Zadeh LA, Zurada JM (eds) Swarm and evolutionary computation. Lecture notes in computer science, vol 7269. Springer, Berlin, pp 110–118. https://doi.org/10.1007/978-3-642-29353-5_13

    Chapter  Google Scholar 

  18. Derrac J, Garcia S, Molina D, Herrera F (2011) A practical tutorial on the use of nonparametric statistical tests as a methodology for comparing evolutionary and swarm intelligence algorithms. Swarm Evolut Comput 1(1):3–18. https://doi.org/10.1016/j.swevo.2011.02.002

    Article  Google Scholar 

  19. Gilbert G, Chow YL, Bouchard DE, Salama MMA (2011) Optimization of high voltage substations using a random walk technique. In: 2011 IEEE PES 12th international conference on transmission and distribution construction, operation and live-line maintenance (ESMO 2011), Providence, Rhode Island, USA, 16–19 May 2011, pp 1–7

  20. Tessema B, Yen GG (2006) A self adaptive penalty function based algorithm for constrained optimization. In: 2006 IEEE congress on evolutionary computation, CEC 2006,16–21 July 2006, Vancouver, BC, Canada, pp 246–253

  21. Hoballah A, Erlich I (2009) PSO-ANN approach for transient stability constrained economic power generation. In: PowerTech, 2009 IEEE Bucharest, Bucharest, Romania, 28 June–2 July 2009, pp 1–6

  22. Hoballah A, Erlich I (2012) Online market-based rescheduling strategy to enhance power system stability. IET Gener Transm Distrib 6(1):30–38

    Article  Google Scholar 

  23. Kennedy J, Eberhart R (1995) Particle swarm optimization. In: Proceedings of IEEE international conference on neural networks, Perth, WA, vol 4, pp 1942–1948

  24. Clerc M, Kennedy J (2002) The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Trans Evol Comput 6(1):58–73

    Article  Google Scholar 

  25. Clerc M (1999) The swarm and the queen: towards a deterministic and adaptive particle swarm optimization. Proc IEEE Congr Evolut Comput 3:1951–1957

    Google Scholar 

  26. AC/DC Module user’s guide, 1998–2015 COMSOL

  27. Sverak JG (1981) Sizing ground conductors against fusing. IEEE Trans Power Appar Syst PAS-100(1):51–59

    Article  Google Scholar 

  28. Sullivan JA (1998) Alternative earthing calculations for grids and rods. IEE Proc Transm Distrib 145(3):271–280

    Article  Google Scholar 

  29. Sverak JG (1984) Simplified analysis of electrical gradients above a ground grid, part I, how good is the present IEEE method? (A special report forWG 78.1). IEEE Trans Power Appar Syst PAS-103(1):7–25

    Article  Google Scholar 

  30. Thapar B, Gerez V, Balakrishnan A, Blank DA (1991) Simplified equations for mesh and step voltages in an AC substation. IEEE Trans Power Delivery 6(2):601–607

    Article  Google Scholar 

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Correspondence to Sherif S. M. Ghoneim.

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Appendix A

Appendix A

The grounding system parameter Eqs. (1) to (6) presented in Sect. 2 are as follows, where the complete description is reported in IEEE Std 80-2013/Cor 1-2015 [3]. The cross-sectional area A (mm2) of the conductors is calculated by [27];

$$ A = I_{\text{G}} /\sqrt {\frac{{{\text{TCAP}} \cdot 10^{ - 4} }}{{t_{\text{C}} \cdot \alpha_{\text{r}} \cdot \rho_{\text{r}} }}\ln \left( {\frac{{K_{0} + T_{\text{m}} }}{{K_{0} + T_{\text{a}} }}} \right)} $$
(A1)

where IG is the maximum fault current in kA, Ta and Tm are the ambient and maximum temperatures in °C; respectively. The thermal coefficient of resistivity αr and the resistivity of the ground conductors ρr are at the reference temperature Tr, K0 is a constant equal to (1/α0) or (1/αr) at Tr and eventually, the TCAP refers to the thermal capacity per unit volume that is obtained from Table 1 in [3] in (J/cm3 °C). The IG is defined by:

$$ I_{\text{G}} = D_{\text{f}} \times I_{\text{g}} $$
(A2)

where Df is the decrement factor that determines the rms equivalent of the asymmetrical current wave at the entire duration of fault (tf) that is given in s. The Df can be computed by:

$$ D_{\text{f}} = \sqrt {1 + \frac{{T_{\text{a}} }}{{t_{\text{f}} }}\left( {1 + e^{{\frac{{ - 2t_{\text{f}} }}{{T_{\text{a}} }}}} } \right)} $$
(A3)

Df can be calculated for specific X/R ratios and fault duration. Ta is the dc offset time constant in s (Ta = X/120πR for 60 Hz).

The effective rms value of the approximate asymmetrical current IF for the entire duration of the fault in A is computed by:

$$ I_{\text{F}} = D_{\text{f}} \times I_{\text{f}} $$
(A4)

where If represents the rms symmetrical current which is 3I0, where I0 is the zero-sequence fault current in A.

The rms symmetrical current Ig that flows between the grounding grid and the surrounding earth is given by:

$$ I_{\text{g}} = S_{\text{f}} \times I_{\text{f}} $$
(A5)

where Sf is the fault current division factor which represents the relation between the symmetrical fault current to that portion of the fault current that flows between the grounding grid and the surrounding earth (\( S_{\text{f}} = I_{\text{g}} /I_{\text{f}} \)).

The difference between one-layer and two-layer soil is the resistivity. In case of two-layer soil, the apparent resistivity (ρa) of the two-layer soil is computed based on (ρ1, ρ2) as follows [15, 28]:

$$ \rho_{\text{a}} = \frac{{\rho_{1} }}{{\left[ {1 + \left( {\left( {{\raise0.7ex\hbox{${\rho_{1} }$} \!\mathord{\left/ {\vphantom {{\rho_{1} } {\rho_{2} }}}\right.\kern-0pt} \!\lower0.7ex\hbox{${\rho_{2} }$}}} \right) - 1} \right)\left( {1 - e^{{\frac{1}{{K\left( {d_{0} + 2h} \right)}}}} } \right)} \right]}}(\rho_{2} < \rho_{1} ) $$
(A6)
$$ \rho_{\text{a}} = \rho_{1} \times \left[ {1 + \left( {\left( {{\raise0.7ex\hbox{${\rho_{1} }$} \!\mathord{\left/ {\vphantom {{\rho_{1} } {\rho_{2} }}}\right.\kern-0pt} \!\lower0.7ex\hbox{${\rho_{2} }$}}} \right) - 1} \right)\left( {1 - e^{{\frac{1}{{K\left( {d_{0} + 2h} \right)}}}} } \right)} \right](\rho_{1} < \rho_{2} ) $$
(A7)

where K is the reflection factor, h is the grid depth, d0 is the thickness of the top layer, and ρ1 and ρ2 refer to the resistivity of the upper and bottom layer, respectively.

The parameters of Em defined by (1) are formulated as follows. Sverak [29] proposed the geometrical factor Km;

$$ K_{\text{m}} = \frac{1}{2\pi }\left( {\ln \left( {\frac{{D^{2} }}{{16 \cdot h \cdot d_{\text{c}} }} + \frac{{\left( {D + 2h} \right)^{2} }}{{8 \cdot D \cdot d_{\text{c}} }} - \frac{h}{{4d_{\text{c}} }}} \right) + \frac{{K_{\text{ii}} }}{{K_{\text{h}} }}\left( {\frac{8}{{\pi \left( {2n - 1} \right)}}} \right)} \right) $$
(A8)

where D is the spacing between parallel conductors (m), Kii is the corrective weighting factor that adjusts for the effects of inner conductors on the corner mesh, Kh is the corrective weighting factor that emphasizes the effects of the grid depth and n is a geometric factor composed of factors na, nb, nc, and nd. If the vertical rods are at the perimeter or at the corner of the grid, then Kii is equal 1. Otherwise, it is computed by:

$$ K_{\text{ii}} = \frac{1}{{\left( {2 \cdot n} \right)^{2/n} }} $$
(A9)

The factor Kh is calculated by:

$$ K_{\text{h}} = \sqrt {1 + \frac{h}{{h_{0} }}} $$
(A10)

where h0 is the reference depth and equal to 1. In [3, 30], the effective number of parallel conductors n is:

$$ n = n_{\text{a}} \cdot n_{\text{b}} \cdot n_{\text{c}} \cdot n_{\text{d}} $$
(A11)

where \( n_{\text{a}} = \frac{{2 \cdot L_{\text{C}} }}{{L_{\text{p}} }} \), nb = 1 for square grids, nc = 1 for square and rectangle grids, and nd = 1 for square, rectangle and L-shaped grids. Lp is the peripheral length of the grid. If the conditions of the grounding grid differ, the next relationships \( n_{\text{b}} = \frac{{L_{\text{p}} }}{4 \cdot \sqrt A } \), \( n_{\text{c}} = \left[ {\frac{{L_{x} \cdot L_{y} }}{A}} \right]^{{\frac{0.7A}{{L_{x} \cdot L_{y} }}}} \), and \( n_{\text{d}} = \frac{{D_{\text{m}} }}{{\sqrt {L_{x} .L_{y} } }} \) are utilized, where Lx and Ly are the maximum length of the side length of the grid in x and y directions, respectively, and Dm is the maximum distance between any two points on the grid in m, i.e., the length of the diagonal of the grid. The irregularity factor, Ki, is determined by:

$$ K_{\text{i}} = 0.644 + 0.148 \cdot n $$
(A12)

If there were a few vertical rods at locations neither the corner nor the perimeter, the effective conductor burial length Lm can be calculated as follows,

$$ L_{\text{m}} = L_{\text{C}} + L_{\text{r}} $$
(A13)

where, LC is the total length of grid conductor. Otherwise, the Lm was computed as follows;

$$ L_{\text{m}} = L_{\text{C}} + \left[ {1.55 + 1.22\left( {\frac{{L_{\rm{r}}^{ '} }}{{\sqrt {L_{x}^{2} + L_{y}^{2} } }}} \right)} \right]L_{\rm{r}} $$
(A14)

where, \( L_{\rm{r}}^{\prime } \) is the length of each ground rod in m.

The second parameter for the safety criterion is the maximum step voltage (Es) that is defined in (2), where the effective buried length, Ls, is computed by;

$$ L_{\text{s}} = 0.75 \cdot L_{\text{C}} + 0.85 \cdot L_{\text{r}} $$
(A15)

where Lr is the total length of all vertical rods connected to the grid and it is

$$ L_{\text{r}} = N_{\text{r}} \times L_{\text{r}}^{\prime } $$
(A16)

where Nr is the number of vertical rods and \( L_{\text{r}}^{\prime } \) is the vertical rod length.

The factor Ks for calculating the step voltage can be determined by:

$$ K_{\text{s}} = \frac{1}{\pi }\left[ {\frac{1}{2 \cdot h} + \frac{1}{D + h} + \frac{1}{D}\left( {1 - 0.5^{n - 2} } \right)} \right] $$
(A17)

The above equation is valid when the grid depth h subjects to the following constraint:

$$ 0.25\,{\text{m}} \le h \le 2.5\,{\text{m}} $$
(A18)

For the safe limits of Et and Es defined in (3) and (4), the factor Cs is obtained by the following formula:

$$ C_{\text{s}} = 1 - \frac{{0.09\left( {1 - \frac{\rho }{{\rho_{\text{s}} }}} \right)}}{{2h_{\text{s}} + 0.09}} $$
(A19)

where hs is the thickness of the protective surface and if there is no protective surface, then, Cs = 1 and ρ = ρs.

As defined in (6), the grounding resistance is a function of R1, R2 and Rm that are formulated as follows:

$$ R_{1} = \frac{\rho }{{\pi L_{\text{C}} }}\left[ {\ln \left( {\frac{{2L_{\text{C}} }}{{a^{\prime}}}} \right) + \frac{{k_{1} \times L_{\text{C}} }}{\surd A} - k_{2} } \right] $$
(A20)
$$ a^{\prime} = \left\{ {\begin{array}{*{20}l} {\sqrt {d_{\text{c}} \times 2h} } \hfill &\quad {{\text{conductors }}\,{\text{buried}}\,{\text{at}}\,{\text{depth}}\,\,h} \hfill \\ {d_{\text{c}} } \hfill &\quad {{\text{conductors}}\,{\text{on}}\,{\text{the}}\,{\text{earth}}\,{\text{surface}}} \hfill \\ \end{array} } \right. $$
(A21)

where ρ is the soil resistivity, LC is the total length of grid conductors, A is the grid area, dc is the grid conductor diameter, h is the grid depth, and the coefficients k1 and k2 are determined in [3].

$$ R_{2} = \frac{\rho }{{\pi N_{\text{r}} \cdot L_{\text{r}} }}\left[ {\ln \left( {\frac{{2L_{\text{r}} }}{{0.5 \cdot d_{\text{r}} }}} \right) - 1 + \frac{{2k_{1} \times L_{\text{r}} }}{\surd A} \times \left( {\sqrt {N_{\text{r}} } - 1} \right)^{2} } \right] $$
(A22)

where Lr is the total length of rods, dr is the rods diameter, and Nr is the rods number.

The value of the mutual resistance between the ground resistance of the grid conductors R1 and the ground resistance due to the effect of vertical rods R2 is obtained by:

$$ R_{\text{m}} = \frac{\rho }{{\pi L_{\text{C}} }}\left[ {\ln \left( {\frac{{2L_{\text{C}} }}{{L_{\text{r}} }}} \right) + \frac{{k_{1} \times L_{\text{C}} }}{\surd A} - k_{2} + 1} \right] $$
(A23)

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Ghoneim, S.S.M., Hoballah, A. & Sabiha, N.A. Framework for optimal grounding system design concerning IEEE standard. Electr Eng 101, 1261–1276 (2019). https://doi.org/10.1007/s00202-019-00864-z

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