International Journal of Electrical and Computer Engineering (IJECE) Vol.
No.
October 2025, pp.
ISSN: 2088-8708.
DOI: 10.
11591/ijece.
Enhancing network resilience and energy efficiency in the El Abiodh Sidi Cheikh grid through load flow analysis Ali Abderrazak Tadjeddine1,2.
Soumia Djelaila1.
Ridha Ilyas Bendjillali1.
Sofiane Mohammed Bendelhoum1.
Abdelyamine Boukhobza1.
Salih Lachache1 LSETER Laboratory.
Technology Institute.
Nour Bachir University Center.
El-Bayadh.
Algeria SCAMRE Laboratory.
Maurice Audin National Polytechnic School of Oran.
Oran.
Algeria
Article Info
ABSTRACT
Article history:
This study investigates the performance of the El Abiodh Sidi Cheikh (ESC) electrical grid, focusing on energy efficiency, system stability, and the integration of renewable energy sources.
Numerical methods, including the Newton-Raphson (NR), accelerated Newton-Raphson (ANR), and fast decoupled (FD) load flow methods, were employed to evaluate power flow, voltage stability, and active power losses.
Key results reveal that the NR method achieves the lowest power loss, with a minimal value of 2.
32 MW,
while voltage violations at specific nodes, such as buses 4 and 13, emphasize the necessity for voltage regulation.
Analysis of the sun trajectory and temperature profiles highlights correlations between climatic conditions and energy demand, aiding renewable energy optimization.
Additionally, photovoltaic (PV) measurements demonstrate diurnal variations in energy output, critical for enhancing renewable energy integration.
These findings underscore the importance of advanced power flow analysis and strategic planning to ensure network resilience, energy efficiency, and reliability in the ESC region.
Received Feb 27, 2025 Revised Jun 22, 2025 Accepted Jul 12, 2025 Keywords:
Active power losses El Abiodh Sidi Cheikh Electrical grid Grid reliability Photovoltaic energy Power flow analysis This is an open access article under the CC BY-SA license.
Corresponding Author:
Ali Abderrazak Tadjeddine LSETER Laboratory.
Technology Institute.
Nour Bachir University Center El-Bayadh.
Algeria Email: atadj1@gmail.
INTRODUCTION
One essential piece of infrastructure that makes it easier to move electricity from power plants to consumers is the distribution electrical network .
, .
Nevertheless, many of the distribution systems in place today were built to satisfy the requirements of bygone eras, and they currently struggle to adjust to rising energy demands and changing operating environments .
Ae.
The challenges of updating outdated infrastructure to meet modern energy demands .
, .
are shown by the 30 kV distribution network of El Abiodh Sidi Cheikh (ESC), a region in southwest Algeria as shown in Figure 1.
Originally intended for far simpler energy needs, the ESC 30 kV grid was put into use prior to 2,000.
However, as economic activity soars and power needs in the area rise, the network has simply pushed itself beyond its capacity over the years.
The particular local conditions .
xtreme heat and very dry ai.
make things much more difficult.
These severe external conditions truly affect the functioning of the Almelec-conducted overhead lines.
Regrettably, this results in increased energy waste and shorter lifespans for important tools.
The network's simple AuradialAy design makes it particularly susceptible to power cuts.
Take El-Bnoud, for instance, which is about 90 kilometers from the main ESC substation as shown in Figure 1.
People there typically struggle with obvious voltage drops, which seriously compromise their power quality Journal homepage: http://ijece.
Int J Elec & Comp Eng
ISSN: 2088-8708
as shown in Figure 2.
Active and reactive power losses over those long transmission lines, exacerbated by the age of the equipment, produce these reductions .
Conversely, other parts of the grid may experience overvoltage problems, which often start when demand and power generation vary .
, .
These swings compromise the stability of the system and can damage linked electrical equipment .
, .
Figure 1.
El-Abiodh Sidi Cheikh (ESC) map Figure 2.
ESC distribution electrical grid (Area .
In addition to these operational challenges, the region's extreme temperatures create further High temperatures increase the resistance in the conductors, therefore reducing their capacity to carry power and causing more losses that are technical .
, .
This raises important questions about the suitability of materials like Almelec conductors for long-term use in extreme weather, thereby adding another layer of fragility to the network .
, .
Including a 24 MWc solar (PV) plant in the system has clearly complicated things.
This renewable energy project presents difficulties maintaining voltage stability and guaranteeing general network dependability even if it exactly corresponds with the objectives of the area for an energy transition.
With an 3 kWh/kWp shown in Figure 3, the ESC region really has amazing solar potential and is obviously strategically important for solar energy harnessing.
But power from these distributed PV .
ources especially during low demand and peak sunshin.
may generate localized overvoltage issues.
The initial design of the infrastructure for a more centralized power system makes grid management considerably more Besides that, the area has unrealized wind energy potential in Figure 4.
Integrating wind energy might greatly increase the current renewable mix in some areas, where the average wind speed at 50 meters is 80 m/s.
However, adding wind power would require major technical adjustments to guarantee it runs well with the current infrastructure and does not further aggravate already existing issues.
Figure 3.
ESC PV potential: 1885.
3 kWh/kWp Figure 4.
ESC average wind: 1200 W/mA at 50 m Enhancing network resilience and energy efficiency in the A (Ali Abderrazak Tadjeddin.
A ISSN: 2088-8708 These all point clearly to the multi-layered challenges invading the ESC network: Technical challenges include addressing voltage problems .
oth drops and surge.
, optimizing current from existing infrastructure, and managing the impact of climate on energy systems .
, .
, .
Related to energy: It is about minimizing technical losses, improving network efficiency, and seamlessly introducing renewable energy sources .
, .
, .
This effort focuses especially on the ESC 30 kV network and is all about carefully assessing these We intend to do here: Particularly for those far-off loads like El-Bnoud, pinpoint voltage violations present challenges, find precisely how local climate variables influence overhead line performance, considering the new PV systems, compare the total energy losses of the network to its production, and provide doable technological fixes that increase the dependability, robustness, and energy efficiency of the The results of this study should truly help maximize the performance of the current network and provide specific advice on improved integration of renewable energy sources.
Emphasizing sustainable and financially wise solutions, this work should also contribute to a better understanding of how to modernize distribution networks under such conditions.
To get all this, the work employs three well-known numerical calculation techniques selected for their accuracy and efficiency in power flow analysis: Newton-Raphson (NR), adaptive Newton-Raphson (ANR), and fast decoupled (FD).
MATHEMATICAL FORMULATION
We truly depend on sophisticated modelling tools to tackle those challenging, complicated equations and large system computations.
They are necessary for ensuring our analysis is accurate and spot-on.
These advanced computer tools were crucial for our work.
They guided us in exploring the several configurations of the ESC distribution network and determining the optimal approaches to improve its performance in Figure 5.
Consider the single-line figure as our grid map.
It lets us examine how energy moves, how to reduce losses, and how to maintain voltage stability by precisely showing us how everything is linked.
Look at the single-line diagram for the first zone of the ESC distribution network in Figure 6.
Here are some salient features it emphasizes: simply said, radial arrangement is the way the medium-voltage wires branch from the main substation to every other distribution point, components of a network: It shows visually all the important parts: transformers, transmission lines, and where all the power is being consumed, and particularly in heavy demand, we can quickly identify places experiencing voltage drops or loss of electricity.
To address the stability and efficiency problems in the ESC distribution network, our research followed a quite regimented route.
Here is our approach: We compiled comprehensive data on the features of the network, normal usage patterns, and potential generating capacity.
This clarified just what was impeding its functioning .
, .
Constructing models and running simulations: We developed models of every network component with accepted techniques including FD.
ANR, and NR.
Key in determining voltage issues, power loss, and network general health was these simulations.
Finding solutions: We focused especially on places with dubious voltage levels and important electricity distribution points.
We proposed and implemented methods to offset reactive power in order to resolve voltage problems and get the network working as intended.
This methodical methodology guarantees not only identification of actual issues but also generates useful, doable suggestions to guarantee everyone's dependability and efficiency of the ESC distribution network.
Particularly for the behavior of loads, dynamic load models .
hat which take frequency change.
are very vital when we require an accurate analysis.
These models enable us to precisely see how frequency changes the consumption of electricity.
This provides us with a far more realistic view of how loads interact with the complete system and their general effect on performance.
Maintaining a dependability, stability, and seamless operation of the network depends on this degree of detail .
, .
Common and efficient for both static and dynamic load behavior representation is the ZIP model:
ycIycnO .
= ycEycn .
Oe ycycEycn .
= ycOycnO O yaycn ycEycn .
= ycEi0 .
caycy ( ycn ) ycaycy ( ycn ) ycaycy ] {Q i ycO0 ycOycn 2 ycOycn = ycEi0 .
cayc ( ) ycayc ( ) ycayc ] In these equations, ycEycn and Q i represent the active and reactive power of the load at the operating voltage ycO, while ycEi0 and ycEi0 represent the active and reactive power of the load at the nominal voltage.
The coefficients of the ZIP model are ycaycy , ycaycy , ycaycy , ycayc , ycayc , and ycayc in per unit (P.
Int J Elec & Comp Eng.
Vol.
No.
October 2025: 4774-4784
Int J Elec & Comp Eng
ISSN: 2088-8708
Emphasizing how closely generation, transmission, and consumption are all interconnected inside the distribution network, this model really highlights the dynamic character of energy flow.
Finding the intricate nodal voltages is the primary objective of this whole method.
Once we have those, we can figure out everything else including line power flow, currents, and even energy losses.
Simply said, it all comes down to solving a series of challenging equations in which our major unknowns are the real and imaginary components of those nodal voltages.
Figure 6.
ESC Single-line diagram (Area .
Figure 5.
Bus ycn with production, transmission, and load in bus yc Power flow analysis Power flow analysis provides operators and planners with critical information, including line loads, bus voltages, generated power, losses and powers optimizations .
, .
This information highlights constraints and helps identify areas where limits are exceeded.
Modern computational tools make power flow calculations feasible for networks of virtually any size .
, .
Each ycaycyc ycn is characterized by six variables: ycOycn , yuycn , ycEyaycn , ycEyaycn , ycEyaycn , and ycEyaycn .
For a system with ycu nodes, this results in 6ycu variables .
To ensure the system is solvable, 2ycu unknowns and 4ycu known parameters must be defined.
Non-generating busses, ycE.
= ycE.
= 0, and ycOycn and yuycn are unknown.
The Table 1 present the constraints with formulation mathematical.
Table 1.
Constraints with formulation mathematical Constraints Generation and load balance:
Generation limits:
Voltage constraints:
Angle constraints:
Mathematical formulation ycA OcycA ycn=1 ycEyaycn Oe (Ocycn=1 ycEyaycn ycEycycn ) = 0 { ycA Ocycn=1 ycEyaycn Oe (OcycA ycn=1 ycEyaycn ycEycycn ) = 0 ycEyaycn O ycEycn O ycEyaycn { ycoycnycu ycEyaycn O ycEycn O ycEyaycn ycOycn O ycOycn O ycOycn yuEycnycycoycnycu O .
uEycn Oe yuEyc ) O yuEycnycoycaycu Generating busses: for generating nodes, the following relationships apply:
ya = Ocycu ycU ycO { O ycn O ycn=ycoycu ycnyco yco ycIycn = ycOycn O (Ocycn=yco ycUycnyco ycOyco ) .
The active and reactive power injected at a node are defined as:
ycE = (Ocycuycn=yco ycUycnyco ycOyco ycOycn ) O ycaycuyc.
uyco Oe yuycn yuEycnyc.
{ ycn ycEycn = (Ocycuycn=yco ycUycnyco ycOyco ycOycn ) O ycycnycu.
uyco Oe yuycn yuEycnyc.
Enhancing network resilience and energy efficiency in the A (Ali Abderrazak Tadjeddin.
A ISSN: 2088-8708 Power flow in transmission lines Once the iterative voltage solution is complete, line flows can be calculated.
The current between nodes ii and yco is:
yaycnyco = .
cOycn Oe ycOyco ) O ycUycnyco ycOycn O ( ycnycoAE.
ycIycnyco = ycEycnyco Oe ycycEycnyco = ycOycnycoO O .
cOycn Oe ycOyco ) O ycUycnyco ycOycn O ( ycnyco ) .
Where ycUycnyco is line admittance and ycUycnycoA is shunt admittance.
System losses are represented as:
ycIycycn = (Ocycuycn=0 ycIyaycn ) Oe (Ocycuycn=0 ycIyaycn ) { ycEycycn = (Ocycuycn=0 ycEyaycn ) Oe (Ocycuycn=0 ycEyaycn ) ycEycycn = (Ocycuycn=0 ycEyaycn ) Oe (Ocycuycn=0 ycEyaycn ) .
Where ycIyc represents total network losses.
These constraints ensure that the system operates safely, avoiding damage, instability, or Figure 7 outlines the process of evaluating power flow results, which are applied in investment planning and operational.
The Figure 7 illustrates the step-by-step process for evaluating power flow results, highlighting the sequence of data input, computation, and analysis phases.
It is a critical tool for understanding the integration of power flow computations into system planning, including the identification of constraints, optimization of network operations, and assessment of reliability and efficiency.
Figure 1.
Flowchart of power flow result evaluation process The lower at 0.
9 p.
and upper at 1.
1 p.
voltage limits are used in our study.
The NewtonRaphson (NR) method is widely used for solving nonlinear power flow problems due to its efficiency and fast convergence .
Ae.
Below is a detailed explanation of the mathematical process.
To solve a nonlinear equation yce.
= 0, the Newton-Raphson method relies on successive approximations of the solution x.
If OIycu 0 is the correction applied to the initial value ycu 0 , the solution is expressed as:
ycu = ycu 0 OIycu 0 Using the Taylor series expansion around ycu 0, the equation yce.
= 0 becomes:
Int J Elec & Comp Eng.
Vol.
No.
October 2025: 4774-4784
Int J Elec & Comp Eng
ISSN: 2088-8708
cu 0 yuuycu 0 ) = yce.
cu 0 ) yce A .
cu 0 )yuuycu 0 = 0 cu 0 ) Neglecting higher-order derivative terms .
ince yuuycu 0 is assumed smal.
, we obtain: yuuycu 0 = Oe A.
cu 0 ) .
yce The updated solution and the general iterative form is:
ycu 1 = ycu 0 iycu 0 = ycu 0 Oe ycu yco 1 = ycu yco Oe yce.
cu 0 ) yce A .
cu 0 ) yce.
cu yco ) .
yce A .
cu yco ) Convergence criteria: The iterations stop when the following conditions are satisfied:
ycu yco | < yuA1 ycaycuycc yce.
cu yco )| < yuA2 where: yuA1 and yuA2 are small positive numbers representing the desired accuracy.
Extension to systems of nonlinear equations: For a system of ycu nonlinear equations:
cu1 , ycu2 .
A , ycuycu ) = 0 cu1 , ycu2 .
A , ycuycu ) = 0 cu1 , ycu2 .
A , ycuycu ) = 0 The method is extended to calculate corrections yuuycu10 , yuuycu20 .
A , yuuycuycu0 .
Using the Taylor expansion and neglecting higher-order terms, the system can be written in matrix form as:
cu yco ) = Oeyayco yuuycu yco where: ya is the vector of functions .
ce1 , yce2 .
A , yceycu ]ycN , ya is the Jacobian matrix containing partial derivatives:
yuiycu1 ycu 0 yuiycu2 ycu 0
| A
ya = yuiycu1 ycu10 yuiycu2 ycu20
| A
uiycu1 ycu10 yuiycu2 ycu20 yuiycuycu ycu 0 yuiycuycu ycu 0 yuiycuycu ycu 0 ] ycu Iterative solution: The iterative update equations are:
uuycu yco 1 Oe1 = Oe(J k ) F.
cu k ) ycu yco 1 = ycu yco yuuycu yco here, ycu yco represents the solution vector at iteration k, and J k is the Jacobian matrix evaluated at ycu yco .
RESULTS (ESC GRID AREA .
The results obtained from the ESC network demonstrate the effectiveness of the three applied numerical methods and the identification strategies employed.
Thus, providing important information to improve the energy efficiency and resilience of the ESC network.
Improving network performance relies in particular on the identification of active power losses and the accurate detection of bus voltage fluctuations, ranging from slight to significant.
One-hours evolution load shape peak Analysis of ESC's secondary grid sector reveals substantial demand variance in Figure 8, with Bus 12 .
ndustrial/residential hybri.
71 MW versus Bus 15's minimal 0.
87 MW residential load, demonstrating the critical balancing challenge between heavy industrial and light domestic loads within a unified distribution network.
Enhancing network resilience and energy efficiency in the A (Ali Abderrazak Tadjeddin.
A ISSN: 2088-8708 ESC average temperature Figure 9 presents the hourly variation in average temperature throughout the study day for the ESC This profile helps establish potential correlations between climatic conditions and energy consumption The average temperature measured on November 5, 2024, is 14.
98 AC.
ESC Trajectory of the Sun Figure 10 depicts the sun's trajectory in the ESC region, providing essential data on solar angles critical for evaluating solar energy potential.
The sun path aligns well with global benchmarks for June and December, confirming the suitability of the measurements for optimizing PV installations and solar trackers.
ESC park photovoltaic analysis Figure 11 tracks 24-hour PV generation in area 2 of ESC park (November 05, 2.
, showing characteristic daytime production curves.
These diurnal patterns are key for predicting renewable contribution and planning storage/grid compensation strategies.
ESC voltages profiles Three load-flow methods (NR.
ANR.
FD) were applied to analyze grid voltages as shown in Figure 12.
Consistent violations detected at Bus 4 and 13.
ESC gain and losses Figures 13 analyze active power gains and losses within the ESC electrical grid using the NR.
ANR, and FD methods.
The NR method exhibits the lowest power loss, with a minimal loss of 2.
32 MW,
highlighting its effectiveness.
Figure 8.
One-hour ESC load curve (MW) Figure 9.
ESC average temperature over the study day Int J Elec & Comp Eng.
Vol.
No.
October 2025: 4774-4784
Int J Elec & Comp Eng
ISSN: 2088-8708
Figure 10.
Horizon and sun path diagram in the ESC region Figure 2.
Daily PV output (Area 2.
ESC Par.
Figure 12.
Voltage comparison with NR/ANR/FD methods Enhancing network resilience and energy efficiency in the A (Ali Abderrazak Tadjeddin.
A ISSN: 2088-8708 Figure 13.
Comparative analysis of power gains and losses for NR.
ANR, and FD methods CONCLUSION This paper assessed the electricity grid in area 2, using three load flow methodologies NR.
ANR, and FD by an in-depth examination in ESC.
Algeria.
The NR technique proved best with low active power losses of 2.
32 MW, therefore verifying its better power flow management capacity than the ANR and FD Significant deviations at busbars 4 and 13 were found by voltage stability analysis over the sixteen buses of the grid, therefore indicating important buses needing quick voltage fixes.
These findings suggest that either through transformer Tap changes (TLC) or reactive power compensation, voltage correction determines dependability of grid operation.
During the investigation of environmental impacts on grid functioning, close linkages between temperature oscillations, solar irradiation patterns, and load demand fluctuations were also underlined.
Particularly these connections determine the optimization of renewable energy integration strategies.
Furthermore, the analysis of the energy generation of PV systems indicated normal diurnal production patterns, which provide required data for enhancing storage capacity and solar energy resource management.
REFERENCES