Solar Photovoltaic Energy Systems Research Articles

A novel hybrid optimization framework for sizing renewable energy systems integrated with energy storage systems with solar photovoltaics, wind, battery and electrolyzer-fuel cell

This study proposes a novel approach to evaluate the integration of solar photovoltaic (PV) and wind turbine renewable energy systems (RES) with Electrolyzer-Fuel Cell Energy Storage System (EFCS) and Battery Energy Storage System (BESS). The objective is to minimize the weighted average cost of energy (waCOE) while maintaining a specific renewable energy fraction (FRES). To achieve this objective, a new hybrid optimization system that combines Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) is proposed to simultaneously optimize the capacity of PV, wind turbine, battery, electrolyzer, hydrogen tank, and fuel cell, which makes it a complex and nonlinear optimization problem. The proposed method produces more practical outcomes by implementing some constraints on PSO and strengthens its ability to exploit optimization opportunities. Six scenarios representing different integrated systems are investigated and compared technically and economically, including PV + BESS, PV + EFCS, Wind + BESS, Wind + EFCS, PV + Wind + BESS, and PV + Wind + EFCS. A case study is conducted on a university campus situated on a Mediterranean island, where electricity production relies on imported fossil fuel. The findings indicate that a PV-wind hybrid system consisting of a 1.15 MW wind turbine, a 2.89 MW PV, and a 2.31 MWh BESS has the lowest waCOE of 0.1838 €/kWh. This system is capable of providing a demand–supply fraction (DSF) of 44.63% with a FRES of 60.1%. The study found that a hybrid system consisting of PV and wind turbines showed promise in the examined region due to their complementary characteristics. Additionally, combining various RES with BESS with approximately 33–35% lower waCOE was found to be more economically viable and resulted in 16–20% higher DSF compared to EFCS.

Comparative analyses of solar photovoltaic, wind turbine, and solar photovoltaic and wind turbine hybrid systems: Case study of Thailand

Thailand is rapidly moving toward sustainable electricity generation by employing renewable energy systems, particularly solar photovoltaic systems and wind turbines. While various aspects of renewable energy resources in Thailand have been represented in the literature, the modeling of renewable energy systems, particularly hybrid solar photovoltaic and wind energy systems, have rarely been studied. To cover this gap, four renewable energy modeling tools, SAM, PVsyst, HOMER, and RETScreen, were used to model solar photovoltaic systems (PVS), wind turbine systems (WTS), and solar photovoltaic-wind turbine hybrid systems (PVWHS) for residential applications in Thailand. The developed models were validated to ensure their accuracy by comparing the estimated annual electricity generation to the actual energy yield from the real systems. The PVS modeling results from SAM, PVsyst, HOMER, and RETScreen contained errors of 3.6, 6.9, 5.5, and -3.9%, respectively. The WTS modeling results from HOMER and RETScreen had 15.7% and 18.1% deviations from the real system, respectively. The simulation results show that a 6.6 kW PVS is the most economical system in Chaiyaphum with high solar irradiance whereas a PVWHS (6.05 PVS and 1 kW WTS) is the best system in Sa Kaeo with a high wind speed and average solar irradiance. The PVS, WTS, and PVWHS simulations were also performed in seven different regions across Thailand; Chanthaburi, Nakhon Si Thammarat, Kanchanaburi, Ubon Ratchathani, Samutprakan, Chiang Rai, and Maha Sarakham. It was found that only Chanthaburi with a 7.7 m/s average wind speed is suitable to install PVWHS while PVS is the most economical system for the rest of the locations. A sensitivity analysis was conducted to create a diagram that can help to identify the most economically suitable system with respect to solar irradiance and wind speed. The results indicate that PVWHS is a viable option for some regions in Thailand.

A Comprehensive Review of Distributed MPPT for Grid-Tied PV Systems at the Sub-Module Level

Energy crises and the growth of the energy demand have increased the interest in utilizing unconventional power sources. Thus, renewable energy sources have become a topic of interest to mitigate rising energy concerns and cope with increased electricity demand. With remarkable merits including cleanness and abundance, photovoltaic (PV) solar energy systems are a key to solving these issues. The employed inverters should effectively utilize the maximum available power from the PV solar system and transfer this power to the utility grid without posing any further limitations. However, the unequal power generation of different PV systems caused by partial shading (PS) and other PV panel degradation factors leads to a reduction in generation capacity. One of the relatively new solutions to mitigate the mismatch concerns between the PV modules and sub-modules is to extract the maximum power of each sub-module individually. The main objective of this paper is to present a comprehensive review of such PV grid-connected inverters topologies associated with sub-module connection and control. It will classify the PV grid-tied inverters in accordance with the level where the maximum power point tracking (MPPT) system is implemented. A special focus has been placed on sub-module microinverters (MI) in terms of circuit topologies, conversion efficiency, and controller design. This paper provides a comprehensive analysis of employing the distributed MPPT (DMPPT) approach to maximize the power generation of PV systems by mitigating the mismatch issues inside the PV module. The circuit topology, PV system configuration, and MPPT algorithms used for applying DMPPT solutions in PV SMs are discussed in detail in this study.

AHREPS - Alternating Hybrid Renewable Energy Power System for Load Prioritization: A Case Study of Otokwu-Mmaku Community, Awgu, Enugu State, Nigeria

This paper presents the results of a research study using a novel Binary Data Driven Programming (BDDP) solution coined AHREPS (Alternating Hybrid Renewable Energy Power Systems) to alternate between a Solar Photovoltaic (Solar PV) Renewable Energy (RE) system and a Wind Turbine (WT) Renewable Energy system to provide continuous power supply in a rural-to-suburban household at Otokwu Mmaku Community, Awgu, Enugu State, Nigeria. The computational model for the Otokwu-Mmaku Solar PV (OMPV) and Otokwu-Mmaku Wind Turbine (OMWT) hybrid renewable energy (RE) systems are data-driven by a synthesis of data from simple function-fitted models to a generalized polynomial of order-1 for a 4-year duration (2018 to 2021). The results considering an average baseline load of 0.9kWh/day showed that using a 3-parallel connected 200W Solar PV modules and 5kW Wind turbine modules; the AHREPS employed the OMPV RE system for the months of January through June and the months of September through December all through the 4-year duration (2018-2021) but in the months of July (2021) and August (2020), the AHREPS employed the OMWT RE system in providing continuous power supply for the estimated load. This clearly shows that considering the model selection and alternating effects of the hybrid RE systems, the proposed AHREPS model can effectively meet the expected load demand of the aforementioned location.

Integrating Input/Output Analysis and Green Technological Innovation to Enhance Sustainable Performance in Economic Units

The research aimed to improve the level of sustainable performance in the economic units, especially the industrial ones. This is done by studying and analyzing the theoretical foundations and knowledge foundations for each of the input / output analysis and green technological innovation and evaluating the level of application of the Iraqi industrial economic units for them by choosing the Al-Zawraa General Company in Baghdad as a place for research. That company is one of the subsidiaries of the Iraqi Ministry of Industry and Minerals. An applied study was conducted on the company for the period (2020-2021). The extent of its use of green technology in its production and operational processes was evaluated by relying on sustainable performance indicators. The efficiency of natural and human resources, waste, air emissions, and water pollution were analyzed and diagnosed for solar photovoltaic energy systems, cost accounting by (IOA), and fault handling and sustainable performance improvement by (GTI). The research reached a set of conclusions, the most important of which was the suffering of the company under study from the lack of central government support for it and the failure to provide sufficient financial allocations for the application of green technology innovations. There are also no current or future visions for dealing with the waste and emissions caused by solar energy systems after the end of their lifespan. The application of (IOA) and (CTI) enables the economic unit in question to achieve many sustainable advantages, including: saving natural resources and improving the efficiency of their use, reducing costs, increasing market share and maximizing its profits, providing environmentally friendly products and services of high quality and efficiency, creating A supportive environment for creative ideas, supporting the process of sustainable decision-making, enhancing sustainable competitive advantages, contributing to preparing sustainable reports by diagnosing environmental, creative and other sustainable costs, and then improving its level of sustainable performance.

Development and Testing of Solar Powered Evaporative Air-Cooling System with an Improved Performance

This study proposes a new active direct evaporative cooling system that uses a bundle of cotton fibers as an evaporating surface and activated carbon as a moisture adsorbent. A two-stage evaporative cooling experimental setup consisting of an activated carbon adsorbent in between the cooling pad was designed, fabricated, and tested at Bahir Dar, Ethiopia. The fiber bundle (pad 1) was wetted with water and ambient air was forced through it using a fan then the air that exiting from pad 1 was forced through a bulk of activated carbon (moisture adsorbent), and then the air from the adsorbent passed through the second wetted fiber bundle (pad 2). The energy source for the fan and pump was the solar photovoltaic energy system. The average temperature drop of the cooler without the moisture adsorber was 9.33°C and with the inclusion of the moisture, the adsorber gave an additional temperature drop of 1.5°C to 4.95°C. During the hot dry season, the average relative humidity of the ambient air, pad 1 outlet, adsorbent outlet, and pad 2 outlets were 28.26%, 76.12%, 55%, and 88.2% respectively. The cooler with moisture adsorbent had a cooling capacity of 3653 W, an effectiveness of 94.25%, and a COP of 52.2. The developed solar evaporative cooling system can provide energy-efficient, sustainable, affordable cold air for different applications. The cooler could be used by small-scale farmers, wholesalers, and retailers for the cooling and storage of horticultural products to reduce the postharvest loss in fresh produces.

Investigation of Cost-Effective Electric Vehicle Charging Station Assisted by Photovoltaic Solar Energy System

The impact of increased power demand on electricity grids due to the projected expansion of electric vehicles (EVs) could be lessened by integrating renewable energy-fed EV charging stations. The study aims to evaluate different combinations of electric vehicle chargers’ technology for use in an EV charging station powered by a photovoltaic solar system. Then a technical, economic and environmental feasibility analysis of the EV charging station is presented in this paper.

Improved utilization of hybrid energy for low-income houses based on energy consumption pattern

<abstract> <p>The adoption of solar photovoltaic and small wind turbine hybrid energy systems in residential applications has picked up promising development around the globe. However, the uncertainty of renewable energy generation associated with the reliance on climate conditions is one of the factors which affect the reliability of the system. Therefore, there is a need to develop an energy management scheme for improving the reliability of the system. One of the drawbacks of hybrid renewable energy systems is the high investment cost, particularly looking at low-income family units. This present paper, an extension of the preceding work, focused on the development of an energy utilization scheme of a hybrid energy system particularly for low-income houses based on energy consumption patterns. The utilization scheme is developed using computational methods in a MATLAB environment. Energy storage systems considered in this work are electrochemical batteries and small-scale flywheel energy storage (kinetic energy storage). Utilizing hybrid energy based on consumption patterns has lowered the capacity of the system's components, resulting in a 0.00 investment cost. The flywheel energy storage is prioritized to supply high-wattage loads while the battery is prioritized to supply average loads, resulting in a 33.9% improvement in battery health. This hybrid system contains a high proportion of renewable energy and reduces annual electricity costs by 96.7%. The simulated results on MATLAB software showed an improvement in terms of energy utilization of a hybrid power system. The cost of utilizing energy is reduced by effectively utilizing more renewable energy sources, with a resultant reduction in electricity bills.</p> </abstract>

Design and Development of Wind-Solar Hybrid Power System with Compressed Air Energy Storage for Voltage and Frequency Regulations

The intermittent nature of wind and solar photovoltaic energy systems leads to the fluctuation of power generated due to the fact that the power output is highly dependent upon local weather conditions, which results to the load shading issue that led to the voltage and frequency instability. In additional to that, the high proportions of erratic renewable energy sources can lead to erratic frequency changes which affect the grid stability. In order to reduce this effect, the energy storage system is commonly used in most wind-solar energy systems to balance the voltage and frequency instability during load variations. One of the innovative energy storage systems is the compressed air energy storage system (CAES) for wind and solar hybrid energy system and this technology is the key focus in this research study. The aim of this research was to examine the system configuration of the CAES system through modelling and experimental approach with PID controller design for regulating the voltage and frequency under different load conditions. The essential elements and the entire system have been presented in this work as thorough modelling in the MATLAB/Simulink environment for different load conditions. The developed model was tested through an experimental workbench using the developed prototype of the compressed air storage in the Siemens Lab at DeKUT and explored the consequence of the working parameters on the system proficiency and the model accuracy. The performance of the system for the developed prototype of CAES system was validated using results from an experimental workbench with MATLAB/Simulink R2022b simulation. The modeling and experimental results, shows that the frequency fluctuation and voltage drop of the developed CAES system during load variations was governed by the I/P converter using a PID_Compact controller programed in the TIA Portal V17 software and downloaded into PLC S7 1200. Based on these results, the model can be applied as a basis for the performance assessment of the compressed air energy storage system so as to be included in current technology of wind and solar hybrid energy systems.

Highly Efficient BBFIC for Grid-Connected Photovoltaic-Battery Energy Storage System Using Hybrid Optimization Assisted Framework

The conventional grid has been combined with a number of renewable energy solutions. As a result, the modern power system is constantly evolving with the help of various power electronics topologies. Due to the growing complexity and new system configuration, the modern power grid is subjected to many challenges and the risk factors are increasing exponentially. In order to evaluate the performance of grid-connected solar photovoltaic (PV) energy systems with battery energy storage system (BESS), highly efficient buck-boost-flyback integrated converter (BBFIC) experiments have been conducted. The whole cybernetics methodology utilized for real-time, closed-loop simulation, validation with other researchers, and numerous optimization techniques are applied in the research work. This paper is developing a new framework that focuses on increasing the voltage gain of the BBFIC for grid-tied PV-BESS. For enhancing the voltage gain of BBFIC, it is planned to optimize the duty cycle of the converter. For optimization purposes, this work deploys a hybrid algorithm termed as “alpha score based on salp-grey wolf optimization (AS-GWO)” that combines the concepts of both “grey wolf optimization (GWO) as well as salp swarm algorithm (SSA).” Finally, it has been demonstrated that the results are superior when compared to other approaches in terms of numerous aspects of measurements.

Feasibility of photovoltaic system in midi-lisy and panoramo equipment for pipeline rehabilitation

Changes in the availability and accessibility of alternative energy sources have been observed in recent years. This study analyzes the economic viability of the use of photovoltaic solar energy systems in equipment for the control and inspection of drinking water pipes. For this, the consumption, costs and operating times were reviewed using conventional sources and photovoltaic energy. The air conditioning system was found to be outdated and needs to be replaced with a leaner, more efficient one. However, portable electric generators should not be disabled, since they will serve as a backup on days when sunshine is the minimum necessary to recharge the batteries, with a contribution of close to 13.5% of the energy. These findings are useful for systems that are part of the jacket dipping process (rehabilitation of trenchless drainage pipes) used by municipal companies that provide home services.

Optimal sizing of standalone rural microgrid for sustainable electrification with renewable energy resources

Renewable energy is widely used in the cost-effective electrification of rural communities. This article discusses a better electricity option for the residents of Uttarakhand's (India) rural areas. The proposed technology is utilized to create a standalone microgrid that reliably fulfills the area's energy demands at a low cost of energy. The suggested system focuses on the hybrid energy model's optimal sizing and sensitivity analysis. The integrated model uses locally accessible energy resources such as solar photovoltaic, micro-hydropower, biogas, battery, biomass, and wind energy systems to meet the area's overall electrical energy requirement. In the simulation, the proposed energy framework considers the intermittent nature of renewable resources. The proposed microgrid model is optimized by utilizing differential evolution (DE) to reduce the overall cost of energy and sizing of the system. The effectiveness of DE is tested for optimization problems, and its results are compared against particle swarm optimization and genetic algorithms. Sensitivity analysis of the cost of energy and the total net present cost demonstrates the impact of modifying the input parameters. The simulation findings reveal that DE optimizes the system compared to its contemporaries, PSO and GA. According to the findings, the optimal configuration has a total net present cost of $ 7,12,532.00, and a cost of energy is 0.14$/kWh. The suggested model for the electrification of the rural community is quite effective in optimizing the system's cost and energy, and sizing.

Investigation of optimal power flow solution techniques considering stochastic renewable energy sources: Review and analysis

Increased penetration of renewable energy sources (RESs) in power system networks poses several challenges in system planning and management due to their uncertain and non-dispatchable nature. Consequently, this paper presents a thorough and precise review of recent solution methodologies for solving the optimal power flow (OPF) problems incorporated with stochastic RESs based on multiple peer-reviewed research publications in reputed journals. The Teaching Learning Based Optimization algorithm has been discussed and implemented to solve the OPF problem considering solar photovoltaic, wind turbine, and tidal energy systems. Weibull, Lognormal, and Gumbel probability density functions representing the uncertainty associated with the availability of wind speed, solar irradiance, and tidal energy systems, respectively. The results obtained from the proposed technique validate its novelty regarding OPF problems like minimization of operating cost, power loss in transmission lines, enhancement of voltage profile, and voltage stability. The proposed solution technique for OPF problems is tested on a modified IEEE 30-bus test system. Thus, this study assists in understanding the OPF problem for new researchers concerned with this domain and also gives the idea of implementing nature-inspired optimization algorithms on a defined test system to solve the OPF problem.

System sizing and transient simulation of a solar photovoltaic off-grid energy system in various climates with air heat pumps

Photovoltaic off-grid systems are essential in supplying power to areas remote from the grid. Mobile homes are used in various cases in remote areas, most of which are far from the power supply grid. It is not economically feasible to develop electricity networks in these areas. One of the best ways to supply power in such cases is to implement photovoltaic systems. These systems can produce electricity through solar irradiation and are environmental-friendly. However, due to the high capital cost of these systems, it is necessary to determine the optimal number of components, such as photovoltaic panels and batteries, to optimize the initial cost and achieve a desirable level of availability. In this study, the TRNSYS software is utilized to investigate the energy required by mobile homes for the ventilation system and power supply operation for different regions. A numerical method is developed to quantify the optimal photovoltaic system for each region for the optimal sizing of these systems. Also, generators have been considered in particular cases to ensure a continuous power supply. Finally, the cities are divided into different categories, showing the off-grid system performance in these regions. Results obtained for the city of Tehran, Iran, suggest that the Levelized energy cost is 0.23 USD/kWh. This system lacks 2.45%, equivalent to 118 h, of required energy and produces 56% surplus energy.

Modelling and techno-economic analysis of standalone SPV/Wind hybrid renewable energy system with lead-acid battery technology for rural applications

The present work discusses an enhanced optimal solution for electrifying an individual rural consumer in a northern Indian village. The optimisation and sizing assessment is based on the techno-economic and socio-environmental parameters. The real-time market-based design variables have been considered for the present investigation. The renewable resources are assessed by the PDAV tool from NASA linked to the HOMER-Pro software tool. A stand-alone hybrid renewable energy system is designed for the domestic load of 55.14 kWh/day and 11.71 kW peak demand. The comparative analysis finds the stand-alone Solar Photovoltaic and Wind energy hybrid renewable energy system suitable. The net present and energy costs are determined as $34,344 and 0.152$/kWh for an optimized Hybrid System. In the present work, the employment creation with social aspects of the renewable energy system is analysed in a distinguished manner. A novel approach is adapted for the environmental effect of hybrid energy systems. The sensitivity analysis and robustness viability has been performed for the optimized arrangement. In the scope of optimal sizing, an equivalent model of the hybrid energy system is recreated in Matlab/Simulink. Each Matlab/Simulink model section is analysed separately with better technical aspects for the different input parameters.

Hybrid Multi-Level Source Inverter Design and Validation in Solar Photo-voltaic Renewable Energy System

This paper proposes the hybrid multi-level source inverter in light of staggered coordinated framework for boosting photo voltaic power. Hybrid multi-level inverter (MLI) proposed to design less number of switches compare with other MLIs of diode clamped multi-level inverter, the smallest number of switches are required to accomplish the highest steps in staircase AC output voltage. HMLIs additionally include variable info voltage and carries out load guideline to keep up with consistent result voltage. The HMLIS intends to operate in multiple stages during shoot through stage exchanging beat width (PWM) adjustment keeps up with to work in buck and lift mode. The activity of proposed work implemented in MATLAB and discuss effectiveness with diminished sounds took care of inverter operation. Model of converter is planned and accomplished the most extreme effectiveness of 95.4% as information voltage goes from 10-60 volts and result of half breed staggered source inverter keeps up with steady of 230v dc. Trial results approve the exhibition of proposed half and half staggered source inverter for exchanged mode power supplies utilized in PC.

Thermo-ecological cost optimization of a solar thermal and photovoltaic integrated energy system considering energy level

Integrating renewable resources into traditional tri-generation systems helps to reduce fossil fuel use and emissions. A solar thermal and photovoltaic assisted integrated energy system is proposed here using high- performance cooling approaches to provide cooling, heating, and electricity. To find the best system configurations with a focus on the ecological performance, the specific thermo-ecological cost of the energy products considering energy level is optimized employing the cumulative exergy consumption over the whole life-cycle. The results show that the ideal specific costs for cooling, heating and electricity demands are 8.699, 7.129, and 1.970 J/J, respectively. Compared to the method without the energy level consideration, the specific cost of the hybrid system is 0.47 J/J higher due to the lower energy level of water products. Moreover, the specific thermo-ecological cost of natural gas has higher impacts on the performance of hybrid system than the other parameters.

Design, Greenhouse Emissions, and Environmental Payback of a Photovoltaic Solar Energy System

This study aims to design a 16.4 MW photovoltaic solar system located in the Brazilian Northeast and quantify the associated greenhouse gas emissions and environmental payback. The energy system was designed to minimize the Levelized Cost of Energy. The greenhouse gas emissions were quantified with the Life Cycle Assessment methodology, expressing the environmental impact in terms of generated energy (kg CO2-eq/kWh) and following ISO 14040 and 14044. The environmental payback considered the Brazilian electricity mix and degradation of the panels. The results indicated a system capable of producing 521,443 MWh in 25 years, with an emission factor of 0.044 kg CO2-eq/kWh and environmental payback of five years and eight months. The emission factor is at least ten times lower than thermoelectric natural gas power plants. The solar panels were the main contributors to the greenhouse gas emissions, representing 90.59% of overall emissions. It is concluded that photovoltaic energy systems are crucial in the search for emissions mitigation, even in a country that presents a predominantly renewable electricity matrix, with demonstrated environmental benefits.

Contributions of Solar Photovoltaic Systems to Environmental and Socioeconomic Aspects of National Development—A Review

Presently, the world is undergoing exciting haste to install photovoltaic (PV) systems in industry, residential/commercial buildings, transportation, deserts, street lights, and many other applications. Solar photovoltaic energy systems are clean and reliable energy sources that are unlimited, unlike their fossil fuel counterparts. The energy market is rapidly growing globally with newly and cumulative installed capacities of about 37.6 GW and 139.6 GW, accounting for 53% and 55%, respectively, in 2017, making it one of the fastest-growing industries. The cumulative photovoltaic installations are projected to have reached 600 GW worldwide and are projected to reach 4500 GW by 2050 because of the strategies and policies of many countries. In 2021, more than three-quarters of the developed countries are now home to one solar installation. This article evaluates a critical and extensive review of the contributions of solar photovoltaic systems to national development. The approach follows all steps, starting with capturing photovoltaics on the Earth’s surface, then price reduction, load management, and socioeconomic impact of solar photovoltaic systems. From the study, it is found that the policies and strategies adopted by the leading countries, such as tax credits, capital subsidies, net-metering, VAT reduction, feed-in tariffs (FiTs), and renewable portfolio standards (RPS), have significantly helped in more installations. Additionally, the significant drop in photovoltaic module prices from 4731 $/W in 2010 to 883 $/W in 2020 has boosted the move for more installations. Based on the findings, approximately 10 million permanent employments would be put in place by advancing solar power across the globe annually.

Musical chairs algorithm for parameters estimation of PV cells

Solar photovoltaic (PV) energy systems are representing the most attractive source of energy, especially with the continuous reduction of manufacturing costs. The new systems' sizing and cost estimation depend mainly on the accurate modeling of the PV cells. The modeling of the PV cells is based on one-diode modeling with five unknown parameters or the more accurate modeling based on two-diode modeling that have seven unknown parameters, or with a higher number of shunt diodes modeling with a higher number of unknown parameters. An accurate and fast estimation of the PV cell parameters will help designers to build their decision based on accurate results, where any small variation of these parameters can spoil the results obtained from the modeling and can produce an unwise decision. A high number of studies are introduced in the literature to estimate these parameters. These studies are different in the accuracy of results and the time consumed to get these results. Some of these studies used metaheuristic algorithms which are characterized by slow convergence and may cause inaccurate results. For this reason, a recent optimization algorithm called the musical chairs algorithm (MCA) is introduced in this paper to estimate these parameters faster and more accurately than many metaheuristic algorithms. The idea behind the use of MCA is to have a high number of search agents in the beginning to enhance the exploration and continuously reduce this number to enhance exploitation at the end of optimization and reduce the convergence time. The results obtained from using 10 optimization algorithms showed that the error associated with MCA is 20% of the average error of the other optimization algorithms. Moreover, the MCA never misses the global minimum of error which was not the case in other optimization algorithms. The MCA obtained these results in 40% of the time consumed by other optimization algorithms. These results of the MCA showed its superiority compared to other optimization algorithms.