Doaa Khalil Ibrahim

In fast-growing isolated microgrids (IMGs), load frequency control (LFC) ensures optimal power quality for end
users. Stochastic grids, notably with renewable energy resources (RESs), require robust and intelligently designed LFC schemes. Thus, this research presents a novel cascade-loop controller combining a fractional order proportional derivative with a filter and a fractional order-proportional tilt integral derivative (FPDN-FPTID)
to improve LFC for single and multi-area IMGs. Recent dandelion optimization adjusts FPDN-FPTID controller
settings. Anti-windup keeps the controller out of the non-linear zone for low inertia IMGs. It concerns various
sources’ maximum generating rates. The two-area IMG model shows its potential and scalability. Extensive
MATLAB/Simulink simulations show that the FPDN-FPTID controller outperforms numerous published controllers, either single or cascade-loop, in minimum error criteria, undershoots/ overshoots/settling times, frequency, and tie-line power deviation following load and RES variations. Finally, the sensitivity study indicates
the suggested controller stabilizes the system despite ±25 % parameter changes.

Load frequency control (LFC) is vital for isolated microgrids (IMGs), especially when uncertain renewable energy sources (RESs) are present. Enhancing LFC schemes relies mainly on three tracks. Adding new resources to IMG structures is the first track, designing novel controller structures for LFC schemes is the second, and the third is improving controller tuning procedures in the LFC schemes. This research suggests an innovative multi-objective formula (MOF) for controller tuning that combines a novel error criterion termed the integral-square time absolute error of frequency change with the integral-square of IMG controllers' signals. Tested IMG includes multi-sources of diesel engine generators, fuel cells, battery energy storage technologies, and RESs (like photovoltaic and wind turbines). The proposed MOF tuning is evaluated compared to four different objective functions, which are the integral-absolute error (IAE), integral-time absolute error (ITAE), integral-square error (ISE), and integral-time square error (ITSE). The proportional-integral-derivative (PID), fractional-order, and cascade PID controllers are implemented to appraise the proposed MOF extensively against all these single objectives. Statistical analyses are accomplished comprehensively to verify the effectiveness of the artificial rabbits' optimization algorithm (ARO) in competition with other recent optimization algorithms to tune different controllers utilized in the LFC schemes of the examined IMG based on tested objectives. Therefore, ARO is applied to optimize controller settings by combining system nonlinearities with IMG sources' maximal generation rate constraints. The comparative analysis considers settling times, overshoots, IAE, ITAE, ISE, and ITSE performance indices. MATLAB/Simulink simulations confirmed the ability of the suggested MOF tuning to stabilize the system and keep improving performance indices, significantly attaining the minimum settling time even for massive three-type load fluctuations. The first type is step disturbances ranging between 0.1 and 0.25 p.u, the second is varying step disturbances every 5 s, and the third is severe dynamic random load shifts from −0.2 to 0.2 p.u. In addition, the MOF outperforms other competitors' tuning formulas while adding fluctuations of RESs with load disturbances. Furthermore, the robustness analysis is conducted for the applied controllers based on the proposed MOF tuning approach by changing the IMG nominal parameters with ±25 % and adding system nonlinearities. The analysis ensured its efficacy in preserving system stability. Finally, the stability test in the frequency domain using the MATLAB/control design tool verified system stability when different LFC controllers were tuned based on the proposed MOF tuning.

In rapidly expanding isolated microgrids (IMGs), load frequency control (LFC) should ensure optimal power
quality for end users. In particular, renewable energy sources (RES) require robust and intelligently designed LFC systems for their stochastic nature. This study presents a novel single-loop
controller that combines a fractional order-proportional beside a tilt integral derivative with fractional order (FPTID) to improve the LFC of multi-source IMGs. Diesel generators, fuel cells, battery storage devices, and RES (solar and wind power generation) are included in the evaluated IMG. Recent geometric mean optimization adjusts FPTID controller parameters. Extensive MATLAB/Simulink simulations reveal that the FPTID controller outperforms numerous previously published controllers regarding the minimum error criteria, undershoots/overshoots/settling times, and frequency deviation in response to load and RES variations.

Converting from a complete fossil fuel energy system to a decarbonized one is crucial to mitigating climate
change and protecting human health. Hybrid energy sources are better than producing energy from a single
technology. The combination of renewable energy and fuel generators allows users to cover seasonal fluctuations of resources and protects them from the unpredictability of fuel prices and supply. Nonetheless, the large-scale industrial demand presents a real challenge due to its consistency throughout the day and the intermittent nature of renewable sources. This research proposes a novel approach for optimal hybrid energy decarbonization for any demand type in general and industrial demand in particular. The proposed framework is developed by integrating the Hybrid Optimization of Multiple Energy Resources (HOMER) for the simulations of Hybrid Configurations (HCs), the Electrical Transient Analysis Program (ETAP) for the stability studies, and the Potentially All Pairwise RanKings of all possible Alternatives (PAPRIKA) method to rank the resulting configurations.
An industrial oil and gas complex with high wind and solar resource availability is adopted as a study case. It is
located in Abu Rudeis, Egypt, and currently utilizes only 11 Gas Turbine Generators (GTGs) to generate electricity. Five different HCs are investigated, including PV and wind systems. The proposed approach considers technical, environmental, economic, and socio-political criteria, with a total of 21 sub-criteria, and reveals that incorporating a wind farm of nine 2-MW wind turbines with the GTGs is the Optimal Hybrid Configuration (OHC).

Digital filters of electrical protective relays play primary roles in calculating the fundamental phasors of electrical power signals. In most fault cases, large amounts of decaying DC components are included in the current signals during the fault period. Decaying DC component significantly reduces the precision and convergence speed of all conventional frequency-domain filters such as Fourier and Walsh filters. In this investigation, this paper introduces a new frequency-domain filtering algorithm to remove the decaying DC components and accurately capture the fundamental power system phasors for digital protective relays. This is executed by means of a mathematical procedure using digital signal processing techniques. The proposed filter is tested for a wide variety of current signals during different fault conditions to assess its performance. The simulation results show that the proposed filtering algorithm has a superior performance at a wide range of decaying components.

The presence of DGs in power system networks tends to negatively affect the protective relays coordination. The proposed method introduces an approach to minimize the numbers of relays that acquire new settings on contrary to their original settings (case without DG), to achieve relays coordination in case of adding DG, since relays coordination with minimum number of relays of readjusted settings represents economical target, especially in networks containing mixture of electromechanical and adaptive digital relays. The scheme decides the possible minimum number of re-adjusted relays and their locations in an optimum manner to achieve proper relays coordination in case of adding DGs. The proposed approach is divided into two successive phases; the first phase is stopped when the first relays coordination solution is achieved. The second phase increases the possibility to keep higher number of relays at their original settings than that obtained in first phase through achieving multi solutions of relays coordination. The proposed approach is implemented and effectively tested on the well-known IEEE-39 bus test system.

The presence of DGs in power networks tends to negatively affect relays coordination. Adding fault current limiters FCLs is one of the possible solutions to mitigate negative impacts of DGs addition on protection systems. Traditional schemes have estimated the minimum value of FCL to restore relays coordination when adding DGs without resetting of any relays. That minimum value of FCL in such case is called a critical value, where below this value the relays coordination will be lost.
Nowadays, designing FCL to simultaneously achieve two conflicted objectives of good performance and low cost is considered a great challenge. The paper introduces a new scheme to determine to what extent we could decrease FCL impedance value below its critical value with re-adjusting the original settings of only one adaptive relay to get relays coordination. Decreasing FCL value below its critical value will reduce the cost especially for superconductivity FCL. The proposed scheme can determine the location of that selected relay to be an adaptive one and estimate its re-adjusted new settings to be applied when DGs are added while inserting the reduced value of FCL.
Actually the proposed scheme can be applied for any networks irrespective of the number of added DGs and their capacities; while having an adaptive relay is the only requirement to implement it. The proposed approach is implemented and effectively tested on the large well-known interconnected IEEE-39 bus test system with 84 relays. Its results are compared with other approaches where, no readjusted relays settings are applied. A noteworthy advantage of the proposed scheme is the ability to implement a reduced FCL value than the critical value, by adjusting only one relay settings in the whole network. The proposed scheme may also be extended to re-adjust settings of more than one relay and get further reduced value of FCL. Furthermore, it is also shown that a more optimum value of the total operating time of all primary relays for near end faults is achieved when applying the proposed method rather than other traditional schemes.

This paper proposes an analytical impedance-based fault location scheme for distribution systems. The approach is based on voltage and current measurements extracted at only one-end feeding substation.Modal transformation is implemented to decompose the coupled three phase equations due to mutual effects into decoupled ones, and hence directly calculating fault distance in each section without iterative processes. The proposed approach considers various aspects of distribution systems: intermediate loads along the feeder, tapped laterals and sub-laterals at various nodes, time varying loads, and unbalanced operations. The proposed algorithm is extensively investigated on a typical real 11 kV distribution system,South Delta electricity sector, Egypt using MATLAB environment. Different cases are studied considering various loading conditions, varied fault resistance values and different fault types. The achieved results ensure the effectiveness of the proposed fault locator irrespective to fault conditions. Besides, the robustness of the proposed scheme against unbalanced loading, network topology change and non homogeneous network sections is also confirmed.

By 2017, Egypt is expected to finish its sixth hydropower plant which is associated with the new Assiut barrage. Based on any hydraulic structure's design, there is enormous kinetic energy created downstream of the gates. This super power water jet generated under dams/barrage gates creates a destructive scouring effect downstream of the gates. In this work, a novel approach for hydrokinetic energy application is presented. The new approach proposes installing a farm of hydrokinetic turbines on the stilling basin of the spillways of the barrage's gate. This approach does not only magnify the total electric energy which was untapped in the past but also dissipates the enormous kinetic energy downstream of the gates. The total expected captured electric power from the barrage reaches 14.88 MW compared to 32 MW rated value of the existing hydropower plant.

High impedance faults (HIFs) are difficult to be detected or classified by overcurrent or distance relays. This paper presents a scheme for high impedance fault detection and classification in extra high voltage transmission line. The scheme recognizes the distortion of the current waveforms caused by the arcs usually associated with HIF using a discrete wavelet transform (DWT) based pattern recognition. The scheme uses a recursive method to sum the absolute values of the high frequency signal generated of line current signals measured at one substation end over one cycle. Proposed detector and classifier are tested under a variety of fault conditions on Egyptian 500 kV transmission line system by extensive simulation studies using HIF model of distribution system that modified to transmission lines. In addition, a real time HIF data recorded is used to validate the performance of the proposed scheme. All achieved results clearly reveal that the proposed scheme can accurately detect and classify HIFs in the transmission lines unaffected by fault type, fault inception angle, fault resistance, and fault location.

The coupling capacitor voltage transformers transient response during faults can cause protective relay mal-operation or even prevent tripping. This paper presents the CCVT transient response errors and the use of artificial neural network (ANN) to correct the CCVT secondary waveform distortion. In this paper, an ANN program is developed to recover the primary voltage from the distorted secondary voltage. The ANN is trained to achieve the inverse transfer function of the coupling capacitor voltage transformer (CCVT), which provides a good estimate of the true primary voltage from the distorted secondary voltage. The neural network is developed and trained using MATLAB simulations. The accuracy of the simulation program is
confirmed by comparison of its response with that of the target value from the simulation data.