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The focus of this study is on solving the coordination problem between distance relays (DISRs) and directional overcurrent relays (DOCRs), which is a complex nonlinear problem with various constraints. Ensuring proper coordination between DOCRs and distance relays is critical for maintaining the security of electrical networks. The primary objective of employing optimization algorithms is to determine the optimal operating time for zone-2 of distance relays, as well as the DOCRs setting, time dial setting (TDS), and pickup current (Ipickup). The optimization techniques must also guarantee that the primary and backup relays operate in sequence without any violation. To this end, both recent and well-established optimization algorithms are evaluated using an 8-bus network, with the aim of determining the DOCRs setting and the optimal operating time for zone-2 of distance relays. Furthermore, a comparative analysis of different optimization algorithms, including both traditional and recent techniques, is conducted.

This paper proposes a modified version of a well-known optimization technique called Farmland Fertility Optimization algorithm (FFA). The modified FFA (MFFA) is developed in order to improve the performance of conventional FFA. It is mainly based on two stages. Firstly, the Levy flights are used to enhance the local searching capability in the exploitation phase and the global searching capability in the exploration phase. Secondly sine–cosine functions are used to create different solutions which fluctuate outwards or towards the best possible solution. The developed algorithm has been validated using ten benchmark functions and three mechanical engineering benchmark optimization problems. After that, the newly developed algorithm MFFA is used for extracting the effective unknown parameters of Proton Exchange Membrane Fuel Cells (PEMFCs) models. The optimal extraction of these parameters is essential to determine an accurate semi-empirical mathematical model for PEMFC. The sum of squared errors between the experimental data and the corresponding calculated ones is adopted as the objective function. Four different commercial PEMFC stacks are used to validate the effectiveness of the developed algorithm. The results obtained by MFFA are compared with those obtained by the conventional FFA and other well-known optimization techniques. Moreover, a comprehensive statistical analysis is performed to determine the accuracy and efficiency of the developed algorithm. The results prove the reliability and superiority of the developed algorithm compared with the conventional FFA and other state-of-the-art optimizers.

Due to the rapid development of photovoltaic (PV) system and spreading of its application, the accuracy of modelling of solar cells, as the main and basic element of PV systems, is gaining relevance. In this paper, an Enhanced Harris Hawk Optimization Algorithm (EHHO) is proposed and applied for estimating the required parameters of different PV models in an effective and accurate way. Harris Hawk Algorithm (HHO) is based on Hawks ways in hunting and catching their brays. The HHO utilizes two phases including exploration and exploitation. The main purpose of proposed enhancement is to improve the second phase of HHO. This enhancement is performed on the exploration phase by fluctuating towards or outwards the best optimal solution using sine and cosine functions. Both conventional and proposed algorithms are applied for single, double and triple diode PV models. In order to test the applicability and robustness of proposed algorithm, it is applied for estimating the parameters of different real PV systems and compared with other recent optimization algorithms. The results show that the proposed EHHO is more accurate than conventional HHO and other algorithms.

This paper proposes a new methodology for solving the coordination problem of DOCRs based on multi-objective grey wolf optimizer and fuzzy logic decision-making. In addition to the conventional objective function, a new objective function which aims to minimize the discrimination time between primary and backup relays is proposed. Moreover, the conventional objective function related to minimizing the total operating time of primary and backup relays is considered. The feasibility and performance of the proposed methodology for solving the coordination problem of DOCRs are investigated using two different systems (8-bus system and IEEE-30 bus system). The proposed methodology is compared with other reported methods. The results prove the viability and effectiveness of the proposed methodology to solve the DOCR coordination problem without any miscoordination between primary and backup relays.

In this paper, an efficient optimization technique, called improved moth-flame optimization (IMFO) is proposed to improve the performance of conventional Moth-flame optimization (MFO). Then, both of MFO and IMFO are applied to solve the coordination problem of standard and non-standard directional overcurrent relays (DOCRs). In the proposed IMFO, the leadership hierarchy of grey wolf optimizer is used to improve the performance of conventional MFO with the aim of finding the best optimum solution. The major goal for optimal coordination of DOCRs is to minimize the total operation time for all primary relays as well as satisfy the selectivity criteria between relay pairs without any violation in the operating constraints. The performance and feasibility of proposed IMFO are investigated using three different networks (8-bus network, 9-bus network, and 15-bus). The proposed IMFO is compared with conventional MFO and other well-known optimization techniques. The results show the effectiveness of the proposed IMFO in solving both standard and non-standard DOCRs coordination problems without any violation between primary and backup relays. In addition, the results show the power of proposed IMFO in finding the best optimal relay settings and minimizing the total operating time of relays which its reduction ratio reaches more than 28% with respect to the conventional MFO. Furthermore, the reduction in the total operating time of primary relays reaches more than 50 % with the usage of the non-standard relay curve.

Optimal allocation of distributed generations (DGs) is vital to the proper operation of the distribution systems, which leads to power loss minimization and acceptable voltage regulation. In this paper, an Enhanced Artificial Ecosystem-based Optimization (EAEO) algorithm is proposed and used to solve the optimization problem of DG allocations to minimize the power loss in distribution systems. In the suggested algorithm, the search space is reduced using operator G and sine-cosine function. The G-operator affects the balance between explorative and exploitative phases. At the same time, it gradually decreases during the iterative process in order to converge to the optimal global solutions. On the other hand, the sine-cosine function creates different and random solutions. The EAEO algorithm is applied for solving the standard 33-bus 69-bus, and 119-bus distribution systems with the aim of minimizing the total power losses. Multiple DG units operating at various power factors, including unity-, fixed-, and optimal-power factors, are considered. Both single and multiple objectives are considered to minimize the total voltage deviation (TVD), maximize the system stability, and reduce the total power losses. The obtained results are compared with those obtained by the AEO and other algorithms. The results demonstrate a significant reduction of total power losses and improvement of the voltage profile of the network, especially for the DGs operating at their optimal power factors. Comparisons show the dominance of the proposed EAEO algorithm against other analytical, metaheuristic, or hybrid algorithms. Moreover, the EAEO outperforms the original AEO algorithm with a faster convergence speed and better system performance.

Recently, extracting the precise values of unknown parameters of the polymer electrolyte membrane fuel cell (PEMFC) is considered one of the most widely nonlinear and semi-empirical optimization problems. This paper proposes and applies a Modified Artificial Ecosystem Optimization (MAEO) algorithm to solve the problem of PEMFC parameters extraction. The conventional AEO is a novel optimization technique that is inspired by the energy flow in a natural ecosystem which is defined as abiotic, which includes non-living bodies and elements such as light, water and air. The proposed optimization algorithm, MAEO, is used to enhance the performance of conventional AEO and provide faster convergence rate as well as to be far away from falling into the local optima. In the proposed MAEO, an operator is suggested to improve the balance between exploitation and Exploration phases. The accurate estimation of PEMFC unknown parameters leads to develop a precise mathematical model which simulates the electrochemical and electrical characteristics of PEMFC. The objective function of the studied optimization problem is formulated as the sum of squared errors (SSE) between the measured and simulated stack voltages. To prove the reliability and capability of the proposed MAEO algorithm in solving this problem compared with other recent algorithms, it is tested on four different PEMFC stack models, namely, BCS-500W, SR-12 500W, 250W and Temasek 1 kW stacks. Moreover, statistical measures are performed to assess the superiority and robustness of the proposed algorithm. In addition, the accuracy of optimized parameters is assessed through the dynamic characteristics of PEMFCs under varying the reactants' pressures and temperature of the cell. However, the simulation results confirm that the proposed MAEO algorithm has high accuracy and reliability in extracting the PEMFC optimal parameters compared with the conventional AEO and other effective algorithms.

This paper presents an adaptive protection scheme (APS) for solving the coordination problem that deals with coordination directional overcurrent relays (DOCRs) and distance relays second zone time, in relation to coordination with DOCRs. The coordination problem becomes more complex with the impact of renewable energy sources (RES) when added to the distribution grid. This leads to a change in the grid topology, caused by the on/off states of the distribution generators (DG). The frequency of topological changes in distribution grids poses a challenge to the power system’s protection components. The change in the state of DGs leads to malfunction in reliability and miscoordination between protection relays, since that causes a direct effect to the short circuit currents. This paper used the school-based optimization (SBO) algorithm, which simulates the educational process, in order to deal with coordination problems. That algorithm is modified (MSBO) by modified both learning and teaching processes. The IEEE 8-bus test system and IEEE 14-bus distribution network are used to validate the proposed coordination system’s effectiveness when dealing with the coordination process between distance and DOCRs, at both the near- and far-end in the typical topological grid and with DGs in working order.

The network of the electrical system is one of the most complex structures that has developed by human civilization. The complexity of the operation of power systems is rising as the electric system is rapidly developing. Maintaining power system stability and preserve network reliability is the main task for protective relays. The main objective of protective relays is to isolate and disconnect only fault section rapidly and keep healthy sections in operation. In power system protection, directional overcurrent relays (DOCRs) are widely applied in distribution and sub-transmission systems. The problem of coordination is considered as a non-linear problem and this problem contains many constraints. In this chapter, the problem of coordination is expressed using various optimization techniques. Water cycle algorithm (WCA) and its modified-WCA (MWCA) are suggested to find a solution for the problem of coordination. In addition, moth-flame optimization (MFO) and improved-MFO (IMFO) are suggested to find a solution for the problem of coordination in case of conventional and non-conventional characteristic relay curve. The robustness and effectiveness of the suggested techniques are assessed using different networks and compared with other and recent optimization algorithms. The results prove the superiority of the suggested methods in solving DOCRs coordination problems without any miscoordination between relay pairs. Also, the reduction in the total operating time of primary relays reaches more than 59% with the usage of the non-standard characteristic relay curve.

Solar cell is one of the important renewable energy resources, and it is considered a promising source for energy challenges in the future. The identification of solar cell model parameters is very important due to the control and the simulation of PV systems. In this paper, an enhanced teaching–learning-based optimization (ETLBO) algorithm is proposed and applied to estimate the photovoltaic cells parameter. The ETLBO is proposed to improve the performance of conventional TLBO and reduce its search space by adjusting the parameters which control the explorative and exploitative phases to achieve the suitable balancing. The proposed algorithm is validated using real dataset of photovoltaic single-diode and double-diode models. In addition, the proposed algorithm is tested on the dataset of two real PV panels (polycrystalline and monocrystalline). The results obtained by the proposed algorithm are compared with those obtained by other well-known optimization algorithms. All results prove the effectiveness and superiority of proposed algorithm compared with other optimization techniques.

This paper proposes an enhanced version of grey wolf optimizer (EGWO) to solve the coordination problem of directional overcurrent relays (DOCRs). The EGWO is proposed to improve the convergence characteristics and computation time of the conventional grey wolf optimizer (GWO) by selecting a suitable balance between exploration and exploitation phases. This balance is achieved by exponential decreasing of the control parameter during the iterative process. The EGWO is explored in all search space during predetermined iterations, and then it fast converges to the best optimal solution by local exploitation around the optimal solutions. The proposed optimization technique is applied to solve the coordination problem of DOCRs. The main objective of optimal coordination of DOCRs is to minimize total operating time of all primary relays with sustaining the selectivity between relay pairs. The feasibility and performance of the proposed technique for solving the coordination problem of DOCRs are investigated using four different systems, compared with several well-known techniques. The obtained results prove the effectiveness and superiority of the proposed technique compared with these techniques. The proposed technique is able to find the optimal relay settings and minimize the total operating time of relays (with a reduction ratio about 19.3995% relative to the conventional GWO) without any miscoordination. In addition, DIgSILENT PowerFactory is used to validate the proposed technique.

In this article, a new hybrid metaheuristic optimization algorithm is proposed to solve the coordination problem of directional overcurrent relays (DOCRs). The proposed algorithm is constructed usi...

The optimization model of Directional Over Current Relays (DOCRs) coordination is considered non-linear optimization problem with a large number of operating constraints. This paper proposes a modified version for Water Cycle Algorithm (WCA), referred to as MWCA to effectively solve the optimal coordination problem of DOCRs. The main goal is to minimize the summation of operating times of all relays when they act as primary protective devices. The operating time of a relay depends on time dial setting and pickup current setting or plug setting, which they are considered as decision variables. In the proposed technique, the search space has been reduced by increasing the C-value of traditional WCA, which effects on the balance between explorative and exploitative phases, gradually during the iterative process in order to find the global minimum. The performance of proposed algorithm is assessed using standard test systems; 8-bus, 9-bus, 15-bus, and 30-bus. The obtained results by the proposed algorithm are compared with those obtained by other well-known optimization techniques. In addition, the proposed algorithm has been validated using benchmark DIgSILENT PowerFactory. The results show the effectiveness and superiority of the proposed algorithm to solve DOCRs coordination problem, compared with traditional WCA and other optimization techniques.

This paper presents an application of Harris Hawks Algorithm (HHA) as an intelligent method for optimal tuning of integral classical controllers to design the appropriate load frequency controllers. A mathematically model is presented for investigating the optimized controller parameters and enhancing the system performance. It consists of two-area interconnected power system with different participation of DFIG based wind turbine at the first area only. This article solves the load frequency control (LFC) problem under step load perturbation (SLP) by 2%. Simulation results confirm that, oscillation of frequency at both areas and tie-line power oscillation are effectively damped using HHA. Also, when DFIG participation level is high, the optimum performance of power system is achieved. All time domain simulation results are carried out using MATLAB program for investigating the effectiveness of this algorithm.

An optimization algorithm called modified evaporation rate water cycle algorithm (MERWCA) is proposed in this paper to find the optimal solutions for the coordination problem of directional overcurrent relays (DOCRs). The proposed MERWCA improves the performance of a conventional evaporation rate water cycle algorithm (ERWCA) by enhancing the balance between exploitation (search locally) and exploration (search globally) phases to find the best optimum solution. MERWCA includes the Opposition Based Learning (OBL) and Levy Flight (LF) component to address the shortcomings that the original ERWCA may exhibit, to avoid falling on the local optimal and improve the convergence rate. The proposed MERWCA is verified on the CEC’2017 test suite and its performance are compared with those of ten common metaheuristic algorithms (MAs). Both MERWCA and ERWCA are evaluated in the case of non-conventional and conventional relay curves. The feasibility of MERWCA technique is assessed using the conventional IEEE 39-bus meshed distribution test system. The results prove the viability of the MERWCA in solving DOCRs coordination problems in both cases (conventional and non-conventional characteristic relay curve) without any miscoordination between DOCRs pair. Moreover, the reduction ratio in minimizing the total operating using MERWCA reaches 46% with respect to the ERWCA and about 66% using the non-conventional relay characteristic. Finally, the MERWCA is assessed using benchmark DIgSILENT PowerFactory.

This paper describes an important topic regarding with stability of the electrical grid, it is the load frequency control (LFC) problem. At any interconnected-areas of power systems, LFC problem must be solved to ensure system stability without any disturbance. When the amount of generating power is insufficient to meet the electrical load needs, frequency deviation is appeared with instability in power system. Doubly fed induction generator (DFIG) has the ability to support the power system with an additional inertia by supplying it with an extra active power. The studied system in this paper is a two-area thermal-thermal power plants with different participation levels of DFIG at the first area. The exchanged power is flowing between neighboring areas in the studied system through a tie-line. The two power plants in each model are subjected to 2% load perturbations in each area. These load perturbations are applied for examining the ability of Grey Wolf Optimizer (GWO) to restore the stability of studied systems. The optimum performance of power system is achieved when DFIG participation level is high. All time domain simulation results are carried out using MATLAB (R2015a) program for investigating the effectiveness of this method.

This paper describes an important topic regarding with stability of the electrical grid, it is the load frequency control (LFC) problem. At any interconnected-areas of power systems, LFC problem must be solved to ensure system stability without any disturbance. When the amount of generating power is insufficient to meet the electrical load needs, frequency deviation is appeared with instability in power system. Doubly fed induction generator (DFIG) has the ability to support the power system with an additional inertia by supplying it with an extra active power. The studied system is a two-area thermal-thermal power plants with different participation level of DFIG at the first area. An exchanging power is flowing between neighboring areas in the studied system through a tie-line. The two power plants in each model are subjected to 2% load perturbations in each area. These load perturbations are applied for examining the ability of Sine Cosine Algorithm (SCA) technique to restore the stability of studied systems. when DFIG participation level is high, the optimum performance of power system is achieved. All time domain simulation results are carried out by MATLAB (R2015a) program for investigating the effectiveness of this method.

Protective relays and circuit breakers are major components of the large interconnected power system. Protection system is used to isolate only faulted parts from the power system network in shortest possible time leaving healthy parts in service causing a minimum disturbance to the power system. The protective system should be able to discriminate between normal or abnormal or fault conditions which called the discrimination. Protection coordination is the important task in protection system. Without good protection coordination, the protection system will lose its features i.e. selectivity, dependability, and sensitivity. The protection mis-coordination is the main problem in the power system. This paper presents short circuit analysis and relay coordination between overcurrent relays of a 132/33/11kV substation which located in Upper Egypt. The short circuit analysis, and relays coordination are performed by ETAP 12.6 simulation program.

This paper proposes the application of Most Valuable Player Algorithm (MVPA) to find the optimal solution for directional overcurrent relays (DOCRs) coordination problem. The coordination problem of DOCRs is considered as a non-linear optimization problem. The decision variables for this problem are relay settings. Minimize the summation of the operating times of all primary relays with maintaining the coordination margin between relays pairs is the main goal of this study. The feasibility and performance of the proposed algorithm for solving the coordination problem of DOCRs are assessed in two test system (8-bus and IEEE-30 bus). The results show the ability of the proposed algorithm for solving DOCRs coordination problem without any miscoordination. The results of the proposed optimization algorithm are compared with other previously optimization techniques.

A novel application of the evaporation rate water cycle algorithm (ER-WCA) to solve the coordination problem of directional overcurrent releays (DOCRs) in power system networks is presented in this paper. Coordination problem of DOCRs has been considered as a non-linear optimization problem with many constraints. The relay settings are considered as the decision variables for this optimization problem. Minimize the summation of the operating times of all primary relays with maintaining the coordination margin between relays pairs is the main goal of this study. The performance of the ER-WCA is evaluated in a large distribution system. The results show the ability and reliability of the ER-WCA to solve DOCRs coordination problem without any miscoordination. The effectiveness of ER-WCA is compared with other previously optimization techniques. The results proved that ER-WCA is quite competent in dealing with such problems.

The optimal coordination of DOCRs becomes a very hard task as the power system becomes complex and larger. In this paper, the recent GWO technique is proposed to find the optimal settings for directional overcurrent relays (DOCR), minimize the total operation time for all primary relays, and maintain the relay coordination margin between relay pairs using GWO. The relay settings, pick up current (Ip) and time dial setting (TDS), are considered as decision variables. The operating time of a relay depends on these variables. The availability of the suggested technique is tested using fifteen bus network system using MATLAB. The results using GWO algorithm are compared with electromagnetic field optimization (EMF), Cuckoo Search Algorithm (CSA), and modified electromagnetic field optimization (MEFO). The results using GWO prove the viability of the proposed algorithms for solving DOCRs coordination problem compare with other optimization algorithms.

Superalloys are extensively used in the design of combustor components of aero engines because they can withstand high temperature oxidizing environments, while maintaining their strength. This investigation aims at assessing the tribological characteristic of some combustor components candidate cobalt-based and nickel-based superalloys. Three combinations of the alloys were tested at different operating conditions and temperatures; CP1 (Cobalt 1/Cobalt 2), CP2 (Cobalt 2/Nickel 1) and CP3 (Cobalt 1/Nickel 1). The investigation showed that the increase in temperature from 350 °C to 550 °C was associated with a decrease in the coefficient of friction for all tested contact pairs, a decrease in wear coefficient (wear damage) for CP1, and an increase in wear coefficient for CP2 and CP3. Samples analysis using SEM-EDS and Raman Spectroscopy showed that the least wear coefficient exhibited by CP1 at 550 °C, and by CP2 at 350 °C is due to the development of a compacted protective layer of chromium oxide Cr2O3, known for its favourable tribological characteristic, which contributes to load bearing, precludes the metal-metal contact, and reduces the friction and wear damage. On the other hand, the decrease in friction was associated with an increase in wear coefficient for CP2 and CP3 due to the formation of a porous oxide layer with high tungsten trioxide (WO3) content which makes the oxide softer, decreases friction and increases the wear damage in the oxide layer. Material selection maps are presented to aid aero-engine designers.

Several optimization techniques are applied to distribution system reconfiguration such as particle swarm optimization technique (PSO), genetic algorithm optimization (GAO) and grey wolf optimization technique (GWO). In this paper, grasshopper optimization algorithm is used to simulate distribution network reconfiguration to determine the optimal switches combination for maximizing power losses reduction taking into account the constraints of the system structure. The proposed technique mathematically simulates feeder reconfiguration inspired from behavior of grasshopper in nature, and then it is used to find the optimal configuration of network. The proposed method is tested on IEEE 33-bus radial distribution system and gave the optimal solution in a reasonable time of computation. The proposed simulation results proved reasonable computing time and high performance of the proposed method when compared with other optimization techniques.

Cobalt-based superalloys are used in aero-engine combustor components due to their high strength and wear resistance at elevated temperatures. The objective of this investigation is to study the role of the surface oxide formed during the fretting process on the tribological behavior of this class of materials, at temperatures up to 550°C. The investigation, which was carried out using a specially designed tribometer, showed that the wear coefficient and the coefficient of friction (COF) generally decrease with the increase of temperature at different work rates. When the work rate was fixed at relatively high value (350mJ/s), the wear coefficient was found to decrease monotonically with temperature, while the COF experienced a peak at 200°C. Analysis of the specimen fretted at 200°C showed that the hard wear debris promoted abrasive wear and caused an increase in the COF. In addition, the formed oxide was thin, non-continuous and contained mainly cobalt monoxide (CoO), which contributed to the increase in the COF. Analysis of the specimen fretted at 550°C showed that the wear damage decreased due to the formation of a continuous thick protective oxide containing mainly chromium (III) oxide (Cr2O3), known for its good tribological characteristics. It has also been observed that delamination wear took place within this oxide layer. When the oxide composition and thickness inside and outside the fretted area were compared, it was concluded that the real contact temperature exceeded 600°C due to the frictional heat.

Process selection for repair of mechanical components due to wear and corrosion, e.g. damage of aluminum casting housings of fuel injection systems, is based on cost and response time factors, provided that the mechanical performance is maintained within acceptable limits. One of the promising and emerging repair technologies is Cold Gas-Dynamic Spray (CGDS) coating, where a high-pressure gas propels fine powder particles to very high velocities to produce surface coating. It is essential to identify the optimum process conditions and powder composition to produce repaired surfaces with tribological properties close to those of the originally manufactured part (without coating). The objective of this work is to compare the dynamic friction and fretting wear properties of the repaired surfaces using various types of coating composition and spraying techniques. Eight types of CGDS coatings, applied to AMS 4260 aluminum specimens, were fretted against 440C stainless steel specimens at low and high nominal loads to assess their fretting wear resistance, dynamic friction properties and damping capacity. The optimum coating composition and process conditions were identified. In comparison to the uncoated specimen, this optimum coating offered tribological characteristics close to the uncoated material and even better dynamic friction properties. © 2010 Elsevier Ltd. All rights reserved.