System Configuration Research Articles

Experimental investigation of enhanced CO2 refrigeration systems at varying operating condi-tions

The efficiency of a CO2 refrigeration system depends mainly on the operating conditions and the system design. To increase the energy efficiency, advanced system designs include additional components and their combinations such as parallel compression, ejectors, and expansion machines. For a direct comparison of different system designs, measurements were performed on an advanced CO2 laboratory refrigeration system at different operating conditions. The system behaviour was investigated at different gas cooler outlet temperatures, varying cooling loads, different evaporation temperatures and amounts of superheating. The results of the measurements performed on a baseline system configuration and advanced system designs are presented. It was observed that the influence of operating conditions is less important for certain measures in terms of efficiency improvement than for others. For each system design, operating conditions were identified under which a particularly advantageous behaviour of the respective measures was found. In the future, this will allow the judgment of the efficiency enhancement of each of different respective features for each individual application.

A Time and Place to Land

Cooperation between an unmanned aerial vehicle (UAV) and unmanned surface vehicle (USV) can be critical in fields like search and rescue, marine ecology, and surveying. This is because, by landing a UAV on a USV for recharging, the agents can collaborate to eliminate their individual limitations; UAVs typically have a superior speed and vantage point compared to USVs, but can only remain airborne for short periods of time due to battery limitations, whereas USVs lack mobility and height but can remain at sea for extended periods of time and carry large batteries. The question our work this summer sought to answer is: how can we get a UAV-USV pair to seek out ”calm waters” and attempt a landing when and where the waves are most favorable? Due to the high risk associated with testing such a system on a real body of water, we developed a novel testbed that utilizes an unmanned ground vehicle (UGV) fitted with a custom-made 2-axis tilting landing pad that can pitch and roll to simulate the motion of a USV in a variety of wave conditions. We used this novel testbed with an indoor Crazyflie UAV to experimentally prove a cooperative model-predictive control (MPC) scheme. In essence, MPC works by optimizing control inputs using a model that encodes the dynamics of a system to pick the best series of control inputs from a finite set of valid inputs. Our work successfully proved the viability of a system where two agents use MPC to optimize their relative positions and the intensity of nearby waves to reach consensus on where and when to land. By landing 100+ times using a variety of system configurations, we were able to demonstrate a significantly increased likelihood of successful landings when using our control scheme.

Exploring the network structure of coupled green-grey infrastructure to enhance urban pluvial flood resilience: A scenario-based approach focusing on ‘centralized’ and ‘decentralized’ structures

Urban pluvial floods pose a significant risk to cities, occurring when precipitation exceeds the carrying capacity of the urban drainage network. Coupled green-grey infrastructure has emerged as a sustainable solution for mitigating urban pluvial floods. This study aims to explore best practices in the network configuration of urban drainage systems coupled with low-impact development (LID) to enhance flow distribution and stormwater infiltration. To do so, we focused on two competing key concepts in network analysis: (1) Centralization and (2) Decentralization. We integrated a one-dimensional stormwater model with a rapid flood spreading model to assess the flood mitigation performance of various centralized and decentralized network configurations in the Gangnam region of Seoul, South Korea. To further assess the combined effects of green and grey infrastructure, we compared the performance of each drainage network configuration with and without identical mixed LID practices. Here we show that the centralized drainage network scenario performed best in reducing flood volume by 40.3%, the decentralized drainage network scenario performed best in shortening flood duration by 47.8%, and the LID practices scenario performed best in mitigating peak flooding rates by 4.2%, each as independent scenarios. When all three scenarios were coupled together, flood volume could be reduced by 73.5%, flood duration by 54.7%, and peak flooding rates by 19.8% in the study area. This exploratory study underscores the potential of network analysis in urban flood research, particularly the effectiveness of loosely-connected network topology. Our findings contribute to the development of best practices for coupled green-grey infrastructure, facilitating sustainable stormwater management and urban flood resilience.

Optimal Battery Storage Configuration for High-Proportion Renewable Power Systems Considering Minimum Inertia Requirements

With the continuous development of renewable energy worldwide, the issue of frequency stability in power systems has become increasingly serious. Enhancing the inertia level of power systems by configuring battery storage to provide virtual inertia has garnered significant research attention in academia. However, addressing the non-linear characteristics of frequency stability constraints, which complicate model solving, and managing the uncertainties associated with renewable energy and load, are the main challenges in planning energy storage for high-proportion renewable power systems. In this context, this paper proposes a battery storage configuration model for high-proportion renewable power systems that considers minimum inertia requirements and the uncertainties of wind and solar power. First, frequency stability constraints are transformed into minimum inertia constraints, primarily considering the rate of change of frequency (ROCOF) and nadir frequency (NF) indicators during the transformation process. Second, using historical wind and solar data, a time-series probability scenario set is constructed through clustering methods to model the uncertainties of wind and solar power. A stochastic optimization method is then adopted to establish a mixed-integer linear programming (MILP) model for the battery storage configuration of high-proportion renewable power systems, considering minimum inertia requirements and wind-solar uncertainties. Finally, through a modified IEEE-39 bus system, it was verified that the proposed method is more economical in addressing frequency stability issues in power systems with a high proportion of renewable energy compared to traditional scheduling methods.

Solvent optimization and fluorescein lasing for avidin biosensing

We report pulsed laser emission using fluorescein combined with avidin as an active medium matrix in a Littrow-like configuration system. The study covers testing several solvents and a range of excitation energies, aiming to get the narrowest bandwidth for stable peak emission wavelength. Initially, for 4 mM of fluorescein in 1:1 mixture of methanol-NSS, and excited with 20.80mJ of energy, a laser mission of 4.38 nm bandwidth is achieved. Then, different concentrations of thiolated avidin are mixed in the active medium, causing related red-shifts over the initial emission band. Substantial spectral changes are observed down to 0.3 μM of avidin, making apparent the stability conditions for this sort of laser system to work out as a biosensor.

A new modular neuroprosthesis suitable for hybrid FES-robot applications and tailored assistance

BackgroundTo overcome the application limitations of functional electrical stimulation (FES), such as fatigue or nonlinear muscle response, the combination of neuroprosthetic systems with robotic devices has been evaluated, resulting in hybrid systems that have promising potential. However, current technology shows a lack of flexibility to adapt to the needs of any application, context or individual. The main objective of this study is the development of a new modular neuroprosthetic system suitable for hybrid FES-robot applications to meet these needs.MethodsIn this study, we conducted an analysis of the requirements for developing hybrid FES-robot systems and reviewed existing literature on similar systems. Building upon these insights, we developed a novel modular neuroprosthetic system tailored for hybrid applications. The system was specifically adapted for gait assistance, and a technological personalization process based on clinical criteria was devised. This process was used to generate different system configurations adjusted to four individuals with spinal cord injury or stroke. The effect of each system configuration on gait kinematic metrics was analyzed by using repeated measures ANOVA or Friedman’s test.ResultsA modular NP system has been developed that is distinguished by its flexibility, scalability and personalization capabilities. With excellent connection characteristics, it can be effectively integrated with robotic devices. Its 3D design facilitates fitting both as a stand-alone system and in combination with other robotic devices. In addition, it meets rigorous requirements for safe use by incorporating appropriate safety protocols, and features appropriate battery autonomy, weight and dimensions. Different technological configurations adapted to the needs of each patient were obtained, which demonstrated an impact on the kinematic gait pattern comparable to that of other devices reported in the literature.ConclusionsThe system met the identified technical requirements, showcasing advancements compared to systems reported in the literature. In addition, it demonstrated its versatility and capacity to be combined with robotic devices forming hybrids, adapting well to the gait application. Moreover, the personalization procedure proved to be useful in obtaining various system configurations tailored to the diverse needs of individuals.

Measuring unit for synchronously collecting air dose rate and measurement position

This paper describes a measuring unit for synchronously collecting the air dose rate and measurement position for efficient dosimetry surveying and data logging. The developed prototype comprises a three-dimensional light detection and ranging-based mapping part and dosimetry part, which are integrated into a single measuring unit through an embedded computer that installs a ROS (robot operating system) framework. The unit can function as a standalone system with embedded batteries. Since it is portable, on-line data gathering in the workspace can be realized, thereby maintaining consistency between the air dose rate and measurement position. In this paper, we describe the functional requirements for the measuring unit, the prototype system configuration, and the experimental results obtained in the mockup environment and nuclear facility to discuss its performance.

Techno-economic evaluation of biogas-fed SOFC systems with novel biogas purification and carbon capture technologies

Small-scale biogas-fed solid oxide fuel cell (SOFC) systems, integrated with carbon capture storage (CCS) technologies, offer a sustainable solution for European farms’ heat and power demands with minimal carbon emissions. This study investigates different system configurations ranging from 20 to 200 kW, incorporating heat integration, fuel recirculation, biogas purification and CCS. Two scenarios are evaluated: an SOFC subsystem (1) with cryogenic biogas purification and a sodium carbonate loop for CCS, and (2) with dual sodium carbonate loops for biogas purification and CCS. Key performance metrics, such as system efficiency and levelized cost of electricity (LCOE), were assessed. At 60% recirculation ratio, 650 °C reforming temperature, and 85% fuel utilization, SOFC system electrical achieved the highest efficiency of 65%, with overall system efficiency of 53.6% (first configuration) and 57.4% (second configuration). Scaling effect reduced the LCOE of the first scenario from 0.165 €/kWh (20 kW) to 0.123 (200 kW), and the second scenario from 0.150 €/kWh (20 kW) to 0.116 €/kWh (200 kW). The cost breakdown reveals a significant investment cost from stack replacements. The study suggests that the optimized small-scale biogas-fed SOFC systems with CCS are viable for decentralized heat and power generation.

A case report of system configuration issue in medical imaging due to system upgrade- changes in hardware and software.

Although the rapid growth in the efficiency of medical imaging is undeniable, the expansion of health information technology (HIT) into medical imaging has not been as seamless or well-integrated as it was thought to be. The socio-technical complexities in medical imaging associated with HIT systems can cause risks to patient harm and inconvenience, both individually and collectively, often in new, unforeseen, and unexpected ways. This study reflects a retrospectively collected single incident report related to medical imaging HIT systems, aiming to develop a set of preventive and corrective strategies. A combination of multiple deductive approaches (existing frameworks), i.e., HIT Classification Systems and 18-step medical imaging process workflow and inductive method (content analysis), were used to analyze the incident. The incident was identified as a "system configuration"-related software issue, contributed by system upgrade- changes in hardware and software. The incident was determined to occur during steps 10-12, i.e., "study selection and retrieval," "calling up of patient's referral," and "image review and interpretation," causing severe disruptions in the clinical workflow for several weeks. We propose 16 preventive and corrective strategies grouped under four key areas based on the socio-technical aspects associated with HIT systems. The key areas are (i) preparation and integration for upgraded systems, (ii) training for medical imaging specialists, (iii) contingency planning/immediate backup system, and (iv) system design and configuration. These strategies are expected to help healthcare staff, analysts, reporters, researchers, and relevant stakeholders improve care delivery and patient safety in medical imaging in the context of any system upgrades.

State of the Art Synthesis of Ag-ZnO-Based Nanomaterials by Atmospheric Pressure Microplasma Techniques

Atmospheric pressure microplasma is a simple, cost-effective, efficient, and eco-friendly procedure, which is superior to the traditional nanomaterials synthesis techniques. It generates high yields and allows for a controlled growth rate and morphology of nanomaterials. The silver (Ag) nanomaterials, with their unique physical and chemical properties, exhibit outstanding antibacterial and antifungal properties. Similarly, zinc oxide (ZnO) nanomaterials, known for their low toxicity and relatively lower cost, find wide applications in wound repair, bone healing, and antibacterial and anticancer applications. The use of core–shell nanomaterials in certain situations where some nanoparticles can cause serious harm to host tissues or organs is a testament to their potential. A benign material is coated over the core to reduce toxicity in these cases. This review compares the numerous configurations of microplasma systems used for synthesizing nanomaterials and their use in producing Ag, ZnO, and their core–shell (Ag-ZnO) nanomaterials for biomedical applications. The summary also includes the effect of control parameters, including cathode diameter, gas flow rate, precursor concentration, voltage, and current, on the nanomaterial’s characteristics and applications. In addition, it provides a research gap in the synthesis of Ag, ZnO, and core–shell nanomaterials by this technique, as well as the development and limitations of this technique and the use of these nanoparticles for biomedical applications.

Beyond resilience? A comparative sociological analysis of the impact of the Covid-19 pandemic on five European health care systems

Background The article questions the popularity of resilience as a concept and its application to health care systems as a main lens for understanding the impact the COVID-19 pandemic on them. Methods It develops a sociological definition following a thorough examination of the various proposed meanings for the term. Subsequently, it proposes a conceptual framework to analyze the vulnerability and sustainability of health care systems as a more comprehensive tool that moves beyond the limitations of resilience. This framework is then applied to evaluate its heuristic value in assessing the resilience strategies adopted in response to the COVID-19 pandemic in five European countries (France, Hungary, Italy, Sweden, and the United Kingdom), considered as problematic ‘sentinel cases’ within their health macro-regions. Adopting the six variables provided by the COVID-19 Health Systems Response Monitor of the European Observatory on Health Systems and Policies, a detailed comparative analysis is conducted. This analysis explores the resilience strategies of these countries in terms of the vulnerability outputs they produced and their consequent effects on the sustainability of their health care systems. Results The results show that the resilience strategies adopted during the pandemic were shaped by the different configurations of health care systems and policy decisions regarding resource mobilization. As such, these strategies produced various vulnerability outputs, resulting in different degrees of risk distribution and sustainability. Conclusions These results are pertinent for understanding that what matters from a sociological point of view is not simply how different health care systems cope with external shocks like a pandemic to retain control over their structure and functions (resilience), but the social consequences produced by their strategies.

Optimization of capacity configuration and comprehensive evaluation of a renewable energy electrolysis of water for hydrogen production system

The global green hydrogen industry is experiencing rapid growth, but the high production costs are hindering its widespread adoption. To address this challenge, it is particularly important to rationally configure a renewable energy hydrogen production system. For this purpose, the study proposes a model for capacity optimization configuration of a renewable energy hydrogen production system, which integrates wind power, photovoltaic (PV) power, and concentrating solar power (CSP) with alkaline electrolyzer. It conducts capacity optimization configuration and comprehensive evaluations of the hydrogen production system across various scenarios. To minimize the total daily consumption cost, the CPLEX solver is utilized to solve the objective function and determine the capacity configuration of the renewable energy electrolysis of water hydrogen production system generator set under various scenarios. This approach achieves a utilization rate of over 99% for renewable energy. Through comprehensive evaluation, research has found that renewable energy-coupled hydrogen production significantly reduces generator capacity and electricity generation costs compared to separate hydrogen production, enhancing the economic efficiency of the system. The Wind-PV-CSP coupling hydrogen production system has the smallest generator assembly capacity and the lowest hydrogen production cost, which is 18.84 CNY·kg−1, significantly lower than the cost of PV-CSP coupling hydrogen production (25.78 CNY·kg−1) and wind-PV coupling hydrogen production (25.86 CNY·kg−1). It has good development prospects and plays an important role in exploring the development path of large-scale on-site consumption of new energy.

Cylindrical Microwave Body Scanner—–Part I: System Configuration and Image Reconstruction

Cylindrical Microwave Body Scanner—–Part I: System Configuration and Image Reconstruction

Techno-Economic Analysis of Solar, Wind, and Biomass Hybrid Renewable Energy Systems to Meet Electricity Demand of a Small Village in Bihar State of India

This study examines the potential use of Hybrid Renewable Energy Systems (consisting of photovoltaic, wind, bio, and diesel sources) both with and without the inclusion of battery storage in the eastern region of India. An evaluation is conducted to determine the economic viability of several system configurations, and the most efficient system is selected using HOMER software. The investigation focused on six distinct scenarios to meet the energy needs of a village community. The goal was to satisfy a daily load need of 1093.7 kWh, with a peak demand of 153.63 kW. The study examined many factors, such as system efficiency, financial viability, and ecological consequences. The primary aim of the research was to compare the power costs associated with different designs of HRES. Detailed techno-commercial assessments were carried out to examine the energy production, consumption, and financial impacts of each scenario. This research provides valuable insights for individuals and organizations seeking reliable and long-lasting energy solutions by analyzing the potential benefits and drawbacks of implementing HRES in rural areas. An evaluation is conducted to determine the energy contribution of each element within an RES, as well as the influence of HRES on energy expenses and net present value. The findings of this study reveal that the optimized hybrid system comprises 133 kW photovoltaic arrays, a 130-kW wind turbine, a 0.2 kW biogas generator, a 100-kW diesel generator, a 540-kWh battery bank with nominal capacity, and a 58-kW converter. This system has a minimum COE of 0.347$/kWh and NPC of $1.71M. The research offers useful insights for designers, scholars, and policymakers on the existing design constraints and policies of biomass-based hybrid systems.

Capacity configuration of compressed air energy storage systems with consideration of variable operating conditions

Abstract The extensive integration of high proportions of new energy poses difficulties to the secure and stable operation of power systems. Compressed air energy storage (CAES) technology, as a large-scale, long-duration energy storage technology, has garnered significant attention. However, CAES systems often work in off-nominal conditions, leading to the issue that capacity configured based on nominal conditions may struggle to meet the demands of wind and solar energy consumption. This paper conducts an in-depth study of the off-nominal operation characteristics of CAES systems, constructs a variable operation condition configuration model for CAES systems, and proposes a configuration method for scenarios involving wind and solar energy consumption. Numerical examples have proven that the proposed configuration method can effectively mitigate the fluctuation of new energy output and satisfy the demand for combined heat and power supply.

Study of two thermally integrated pumped thermal electricity storage systems using distinct working fluid groups: Performance comparison

As a competitive new energy storage technology, the thermally integrated pumped thermal electricity storage (TI-PTES) system has received much attention. In this work, two TI-PTES systems are constructed: the RHP-BORC system, which consists of a heat pump cycle (HP) with a regenerator and a basic organic Rankine cycle (BORC), and the RHP-EOFC system, which consists of a HP with a regenerator and an organic flash cycle with ejectors. Meanwhile, R1233zd(E) and Cis-butene are selected to form R1233zd(E)/R1233zd(E) (denoting the working fluid used in the charge and discharge cycles, respectively), R1233zd(E)/Cis-butene, Cis-butene/Cis-butene, and Cis-butene/R1233zd(E) groups. Thermodynamic and economic analyses as well as multi-objective optimization are performed for both systems. The results indicate that for the two systems with different working fluid groups, different parameters have distinct effects on the system performance, and the thermodynamic and economic performance of the RHP-BORC system is better than those of the RHP-EOFC system. For the RHP-BORC system, with the variations of thermal storage temperature, evaporation temperature of heat pump and pinch point temperature difference, the values of different performance metrics of the system with different working fluid groups are close respectively, such as power-to-power efficiency, energy storage density and annual emission reduction. For the RHP-EOFC system under different parameter conditions, when the system uses R1233zd(E)/Cis-butene and Cis-butene/Cis-butene, the performance is better. From the results of the multi-objective optimization, the optimal working fluid group of the RHP-BORC and RHP-EOFC systems are Cis-butene/Cis-butene and R1233zd(E)/Cis-butene, and the values of the power-to-power efficiency and the levelized cost of storage under the optimal solution conditions are 75.76 %, 0.234 $·kWh−1, and 84.31 %, 0.227 $·kWh−1, respectively. The results of the exergy destruction analysis under the optimal solution conditions show that the largest exergy destruction in the RHP-BORC and RHP-EOFC systems are in the condenser (480 kW) and compressor (1275 kW) of the HP cycle. This work expands the configuration of the TI-PTES system, showing promising development prospects. It also provides theoretical support for the further advancement of the TI-PTES system and offers valuable guidance for the design of such systems.

Reliability and criticality analysis of a large-scale solar photovoltaic system using fuzzy-fault tree analysis approach

Over time, solar Photovoltaic (PV) systems experience a decline in performance and reliability due to various environmental factors. Fault Tree Analysis (FTA) can be used to assess the reliability of these systems and identify faults and failure modes that can significantly impact the entire PV system’s performance. However, in practice, obtaining accurate failure probability values for the components of a solar PV system is challenging since systems operate in an ever-changing environment, resulting in a scarcity of data for statistical estimation. This paper proposes a fuzzy theory-based FTA approach to obtain the failure probabilities of the faults more accurately. The Fuzzy-FTA methodology converts experts’ subjective opinions expressed in linguistic terms into a Failure Possibility Score (FPS), which is then converted into a failure probability value. The results of the proposed approach are compared to those obtained through the conventional FTA to assess its effectiveness, applicability, feasibility, and efficiency. Soiling, dust accumulation, inadequate system maintenance, bad system configuration, bird dropping, delamination, improper installation, shading, grounding, and discoloration are the most critical faults and impact on the performance and reliability of solar PV systems.

Performance enhancement of PV array using successive ring adder algorithm based reconfiguration techniques

The photovoltaic array’s output is decreased due to increase of mismatch losses (ML) under partial shading condition. Different row currents begin to flow from the PV modules as a result. Therefore, the panels must be reconfigured to minimize the row current differential in order to get the most power possible from the PV panel. This paper suggests Successive Ring Adder Algorithms (SRAA) to minimize the difference of row current. Under various shading patterns, the proposed scheme’s superiority is evaluated and contrasted with series-parallel (SP) and Total-Cross-Tied (TCT) configurations. The numerical outcomes demonstrate the superiority of the suggested algorithm. Additionally, unlike the recently reported reconfiguration techniques, it may be used with both square (9 × 9) and non-square (9 × 6) PV arrays. In comparison to SP and TCT configuration system, the maximum power generation has improved by 4.04% and 9.25%, respectively. In comparison to TCT (30.96%) and SP (37.52%), the ML was obtained with the lowest value i.e. 25.87%. The efficiency for a 9 × 9 PV array is measured at 13.18%, the highest among TCT (12.67%) and SP (12.07%) configurations. For non-squared (9 × 6) PV array arrangement, similar types of enhanced outcomes are produced.

The Influence of the Assembly Line Configuration and Reliability Parameter Symmetry on the Key Performance Indicators

In the context of the demand for mass customization of products, a trade-off between highly efficient automated systems and flexible manual operators is sought. The linear arrangement of workstations made it possible to divide the process into many simple operations, which increases production efficiency, but also results in an increase in the number of workstations and a significant extension of the line. A human operator is usually treated as a quasi-mechanical object, and a human error is considered, similarly, as a failure of a technical component. However, human behavior is more complex and difficult to predict. A mathematical model of a new production organization is presented, including dividing the traditional production line into shorter sections or replacing the serial assembly line with a U-line with cells. Moreover, the reliability of operator and technical means are distinguished. Work-in-progress inventories are located between line sections to improve system stability. The stability of the assembly line is examined based on the system configuration and probabilistic estimates of human failure. The influence of the symmetry of reliability parameters of people on key performance indicators (KPI (headcount), KPI (surface) and KPI (Overall Equipment Effectiveness) is examined. KPI (solution robustness) and KPI (quality robustness) are also presented in order to evaluate the impact of a disruption on the assembly line performance. New rules for assigning tasks to stations are proposed, taking into account the risk of disruptions in the execution of tasks. For comparison of assembly problems, heuristic methods with newly developed criteria are used. The results show the impact of symmetry/asymmetry on assembly line performance and an asymmetric distribution of manual assembly times that is significantly skewed to the right due to human errors. On the assembly line, the effects of these errors are cumulative and lead to longer assembly times and lower KPIs.

Data-driven study/optimization of a solar power and cooling generation system in a transient operation mode and proposing a novel multi-turbine modification concept to reduce the sun's intermittent effect

This study explores the integration of solar energy via parabolic trough collectors (PTC) with the Goswami cycle, focusing on evaluating life cycle costs (LCC) and energy performance in both steady-state and transient conditions. A suitable system configuration of a single-turbine Goswami cycle is designed for integration with PTC. Then, in the system's steady-state, a parametric study is performed based on the change in the design components. Subsequently, a multi-objective optimization method using energy and lifetime cost objectives are defined to identify the best system performance. This optimization technique utilizes artificial neural network (ANN) and the grey wolf optimizer (GWO) algorithm. Accordingly, the transient performance of the system is investigated during its optimal operating point using the TRNSYS software. Suitable controllers are considered for regulating power production and cooling system. Annual transient performance graphs of the systems are obtained. Following these investigations, a novel multi-turbine system is proposed. This configuration aims to enhance system reliability and diminish the reliance on storage devices by optimizing performance. The proper configuration of the five-turbine system with the required controllers is also provided. Hence, the method of dividing the turbine into similar turbines with lower capacity is a new concept proposed in this study. In the optimal state, it is observed that for 100 kW of net power output, 161 kW of effective cooling load can be achieved. At this configuration, the system's LCC amounts to 2.91 M. Moreover, during transient operation, an average power of 90 kW is attainable with a cooling load of 120 kW. The findings indicate that modifying the system from single turbine to five-turbines incurs an additional cost of approximately 9.2 % and reduces power output by 6 %. However, this modification significantly mitigates the transient impact of solar fluctuations.