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Researchers are increasingly focusing on renewable energy due to its high reliability, energy independence, efficiency, and environmental benefits. This paper introduces a novel multi-objective framework for the short-term scheduling of microgrids (MGs), which addresses the conflicting objectives of minimizing operating expenses and reducing pollution emissions. The core contribution is the development of the Chaotic Self-Adaptive Sine Cosine Algorithm (CSASCA). This algorithm generates Pareto optimal solutions simultaneously, effectively balancing cost reduction and emission mitigation. The problem is formulated as a complex multi-objective optimization task with goals of cost reduction and environmental protection. To enhance decision-making within the algorithm, fuzzy logic is incorporated. The performance of CSASCA is evaluated across three scenarios: (1) PV and wind units operating at full power, (2) all units operating within specified limits with unrestricted utility power exchange, and (3) microgrid operation using only non-zero-emission energy sources. This third scenario highlights the algorithm's efficacy in a challenging context not covered in prior research. Simulation results from these scenarios are compared with traditional Sine Cosine Algorithm (SCA) and other recent optimization methods using three test examples. The innovation of CSASCA lies in its chaotic self-adaptive mechanisms, which significantly enhance optimization performance. The integration of these mechanisms results in superior solutions for operation cost, emissions, and execution time. Specifically, CSASCA achieves optimal values of 590.45 €ct for cost and 337.28 kg for emissions in the first scenario, 98.203 €ct for cost and 406.204 kg for emissions in the second scenario, and 95.38 €ct for cost and 982.173 kg for emissions in the third scenario. Overall, CSASCA outperforms traditional SCA by offering enhanced exploration, improved convergence, effective constraint handling, and reduced parameter sensitivity, making it a powerful tool for solving multi-objective optimization problems like microgrid scheduling.

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The development of DC microgrids is reliant on multi-input converters, which offer several advantages, including enhanced DC power generation and consumption efficiency, simplified quality, and stability. This paper describes the development of a multiple input supply based modified SEPIC DC-DC Converter for efficient management of DC microgrid that is powered by two DC sources. Here Multi-Input SEPIC converter offers both versatility in handling output voltage ranges and efficiency in power flow, even under challenging operating conditions like lower duty cycle values. These features contribute to the converter's effectiveness in managing power within a DC microgrid. In this configuration, the DC sources can supply energy to the load together or separately, depending on how the power switches operate. The detailed working states with equivalent circuit diagrams and theoretical waveforms, under steady-state conditions, are shown along with the current direction equations. This paper also demonstrates the typical analysis of large-signal, small-signal, steady-state modeling techniques and detailed design equations. The proposed configuration is validated through the conceptual examination using theoretical and comprehensive MATLAB simulation results. Detailed performance analysis has been done for different cases with various duty ratios. Finally, to show the competitiveness, the multi-input SEPIC topology is compared with similar recent converters.

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In this paper, an innovative transactive energy approach is proposed as viable option for coordinated distribution system planning across a certain horizon. The proposed approach is evaluated across a multi-looped (meshed) test system and is implemented with load growth having prosumers participating in the electrical market in transactive energy system aiming at evaluation on techno-economic basis. Apart from prosumer sensitivity analysis, evaluations have been carried across reducing total production cost of energy, reduction in per unit price, active power losses. Whereas improving voltage profile, cost of scheduling and consumer per kWh purchase and sales in comparison with traditional counterpart. The proposed framework includes optimization algorithm aiming at sources scheduling and IEEE 69 system for validation. The algorithm minimizes cost, maximizes energy efficiency, increases renewable energy mix and reduces consumers cost of energy purchase. Reduction of 51.44 % in cost of energy is achieved, whereas loss reduction of 12.6% is achieved. The comparison of IEEE 69-bus base case with the 10 %, 15% and 20% transactive energy applied with simulations to evaluate performance parameters that will directly benefit both prosumers and utility alike in-terms of low bills and further reduction of stress on the grid amid load growth across multiple years.

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Fingerprints hold evidential value for individual identification; a sensitive, efficient, and convenient method for visualizing latent fingermarks (LFMs) is of great importance in the field of crime scene investigation. In this study, we proposed an aggregation-induced emission atomization technique (AIE-AT) to obtain high-quality fingermark images. Six volunteers made over 1566 fingerprint samples on 17 different objects. The quality of fingermark development was evaluated using grayscale analysis for quantitative assessment, combining the fluency of fingermark ridges and the degree of level 2 and level 3 features. Both qualitative and quantitative methods were employed to explore the effectiveness of AIE molecule C27H19N3SO in developing fingermarks, its applicability to objects, and its individual selectivity. Additionally, the stability of the AIE molecule was examined. Comparative experimental results demonstrated the high stability of the AIE molecule, making it suitable for long-term preservation. The grayscale ratio of the ridges and furrows was at least 2, with high brightness contrast, the level 2 and level 3 features were clearly observable. The AIE-AT proved to be effective for developing fingermarks on nonporous, porous, and semiporous objects. It exhibited low selectivity on suspects who leave fingermarks and showed better development effects on challenging objects, as well as efficient extraction capability for in situ fingermarks. In summary, AIE-AT can efficiently develop latent fingermarks on common objects and even challenging ones. It locates the latent fingermarks for further accurate extraction of touch exfoliated cells in situ, providing technical support for the visualization of fingermarks and the localization for extraction of touch DNA.

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Traditional unidirectional power systems that produce large-scale electricity and supply it using an ultra-high voltage power grid are changing globally to increase efficiency. Current substations' protection relays rely only on internal substation data, where they are located, to detect changes. However, to more accurately detect changes in the system, various data from several external substations, including micro-grids, are required. As such, communication technology regarding data acquisition has become an essential function for next-generation substations. Data aggregators that use the GOOSE protocol to collect data inside substations in real-time have been developed, but data acquisition from external substations is challenging in terms of cost and security, so only internal substation data are used. This paper proposes the acquisition of data from external substations by applying security to R-GOOSE, defined in the IEC 61850 standard, over a public internet network. This paper also develops a data aggregator based on R-GOOSE, showing data acquisition results.

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In response to the rapid changes in the international energy environment, developing renewable energy (RE)-based distributed generation (DG) and various smart micro-grid systems is crucial for creating a robust electric power grid and new energy industries. In this aspect, there is an urgent need to develop hybrid power systems suitable for coexistent AC and DC power grids, integrated by high-performance wide ban gap (WBG) semiconductor-based power conversion interfaces and advanced operating and control strategies. Due to the intrinsic feature of variation in RE-based power generation, the design and integration of energy storage devices, real-time regulation of power flow, and intelligent energy control schemes are key technologies for further promoting DG systems and micro-grids. This paper investigates an integrated control scheme for multiple GaN-based power converters in a small- to medium-capacity, grid-connected, and RE-based power system. This is the first time that a complete design case demonstrating three GaN-based power converters with different control functions integrated with a single digital signal processor (DSP) chip to achieve a reliable, flexible, cost effective, and multifunctional power interface for renewable power generation systems is presented. The system studied includes a photovoltaic (PV) generation unit, a battery energy storage unit, a grid-connected single-phase inverter, and a power grid. Based on system operation condition and the state of charge (SOC) of the energy storage unit, two typical operating modes and advanced power control functions are developed with a fully digital and coordinated control scheme. Hardware of the GaN-based power converters and digital controllers are designed and implemented. The feasibility and effectiveness of the designed controllers and overall performance of the proposed control scheme are verified with results from simulation and experimental tests on a 1-kVA small-scale hardware system.

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Optimising energy use in systems and buildings is crucial to reduce climate change. This paper aims to address the gap in knowledge for pico-hydropower (<5 kW) that has been identified as an area of untapped potential in the water industries. A literature review and multivariate analysis are used to find a suitable pico-hydro turbine to install into a coral reef aquarium system in a government owned facility. Key findings from the literature review are untapped potential, gaps in knowledge and global quantification of small hydropower for energy recovery, and lack of enabling data contributing to slow uptake of small hydropower. The study showed a propeller pico-hydropower turbine could be used to recover approximately 10% of the energy used for pumping water through a filtration system. At 2.3 m available head, and 90 L/s water flow, power output up to 1.124 kW was achieved. The project was economically viable with financial and non-financial benefits for the life cycle of the product. There remain sparse case studies for energy recovery using small hydropower in the scientific literature. A growing number of authors see the potential of this renewable energy technology to reduce global greenhouse gas emissions and contribute to the UN Sustainable Development Goals to provide affordable clean energy and address climate change. This study helps to shine a light on opportunities to find value from waste using a novel application of hydropower in a water industry.

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The study made in this paper has been directed towards a novel load frequency management (LFM) scheme for solar-wind-based standalone micro-grid (SMG). For LFM, this brief deals with the introduction of proportional-integral-derivative with filter - (one plus integral), i.e., PIDF-(1+I) cascade controller. A maiden endeavor has been performed to employ a recently developed black widow optimization algorithm (BWOA) to obtain the supplementary controller parameters. The considered SMG consists of the wind turbine generator, diesel engine generator, solar photovoltaic as distributed generation unit, and flywheel and ultra-capacitor are considered as energy storage systems. Generation rate constraints and governor dead-band type power system's nonlinearities are also included in this study. This work aims to mitigate the effect of mismatch in demand and generation and minimize the change in frequency deviation (CFD). The maximum obtained CFD with the proposed controller is 0.048 Hz, which is entirely satisfactory and under the permissible limit of IEEE standard. A vivid comparative analysis of artificial bee colony and BWOA tuned controllers like conventional PID, PIDF, and PIDF-(1+I) is also performed. Finally, the detailed robustness assessment of the proposed controller with its real-time implementation through the standard New England IEEE 39 test bus system presents the controller's superiority.

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The goal of this study is to introduce an effective load frequency control scheme with the integration of tidal turbines in a standalone microgrid (µG) system. As standalone µG experiences lower inertia and lacks primary frequency control, the use of variable tidal turbines in the de-loaded region may be accepted as one of the feasible solutions for managing frequency regulation issues. In this condition, the de-load region alludes to an area where tidal turbines liberate their accumulated kinetic energy in rotational parts pursuing frequency fluctuations. An effectual cascade fractional order fuzzy PID-integral double derivative (CFOFPID-IDD) controller suggested for efficient utilization of tidal turbines, whose design variables are tuned through a recently appeared Jaya algorithm. An investigation is made between the acquired outcomes of the studied CFOFPID-IDD droop controller with fractional order fuzzy PID droop control to analyze the proposed strategy performance in various load conditions, with different physical constraints like time delay, dead zone, and generation rate constraints. Moreover, the sensitivity test reveals that the Jaya-optimized CFOFPID-IDD controller can undergo ± (10-25) % variation in various coefficients without retuning the design variable values. The simulation outcomes validate the effectiveness and adequacy of the proposed regulator.

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The use of renewable energy sources in energy distribution networks as distributed generation sources for dispersed and low consumption loads in remote areas such as remote villages and islands with low population can be a proper solution for reducing economic costs, reducing environmental pollutions and increasing energy efficiency. The purpose of this paper is optimal operation management of micro-grids by considering the existing capacities in the electricity market. In fact the microgrid operator, which is responsible for the safe operation of the network, should consider a process for planning in the network that takes into account all benefits of micro-grid's components. In other words, enough reliability for generation resources in these networks should be created in order to reduce costs and environmental pollution from energy production. In this paper, the artificial bee colony (ABC) algorithm has been used to minimize the costs and environmental pollutions by providing the optimal production power of distributed generation.

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A micro-grid consisting of distributed generation resources (DGRs) with a hybrid energy storage system (HESS) composed of batteries and super-capacitors was studied. A control strategy based on the particle swarm optimization (PSO) and energy management algorithms was proposed to facilitate power distribution in the micro-grid and to improve the reliability, control levels, and penetration of micro-grids in the current electrical grids. The proposed operational strategy is based on the power predicted using the load profile and power generation resources. Energy management strategies were then presented by solving a multi-objective problem by the PSO algorithm and submitting the optimization results to the fuzzy controller and power distribution management (PDM) unit. The optimizer, the PDM unit, and the fuzzy controller provide a comprehensive operating procedure for the islanded and grid-connected micro-grids, taking into account their stability against grid fluctuations. In another part of this strategy, an auxiliary power control unit (APCU) was proposed for supporting the HESS and increasing the reliable performance of this unit. The proposed structure was applied to the net power (Pnet) of the islanded and grid-connected micro-grids. The net power was divided into high-frequency (super-capacitor) and low-frequency (battery and APCU) components. The proposed algorithm and simulation results were analyzed using MATLAB/Simulink.

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The design and control of an intelligent integrated standalone micro-grid (I-ISMG) have been proposed in this study. The ISMG system consists of solar photovoltaic (SPV), wind turbine generator (WTG), diesel engine generator (DEG) as distributed power generation (PG), and battery and flywheel as energy storage systems (ESSs). An improved incremental conductance (I-InC) maximum power point (MPP) tracking (MPPT) scheme, and a fuzzy wind power generation model (FWPGM) are utilized to obtain the power from solar, and wind energy systems respectively. The key contribution of this work is to control the power flow for synchronous micro-grid (MG) operation, which in turn resolves the problem of load frequency control (LFC). In this control strategy, an intelligent, i.e. fuzzy logic-based adaptive control scheme is proposed for the coordinated power flow among the generation, demand, and storage system. To minimize the frequency deviation (Δf) and control of PG from WTG and DEG, frequency support (FS) fuzzy logic-based droop characteristic is employed. For the droop control in WTG and DEG, fuzzy logic-based proportional-integral-derivative (F-PID), and self-tuned-fuzzy PID (STF-PID) control schemes are utilized respectively. Apart from droop controls, a fuzzy observer (FO) is designed to manage power flow to/from the storage systems. Further, the proposed control scheme has been benchmarked using single area power system (SAPS) and modified New England IEEE 39 bus system.

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Even though solar power generation has become an emerging trend in the world, its penetration into the utility grid as a distributed generation source is not a satisfactory measure due to the inherent issues related to solar photovoltaic systems (SPVSs). In addressing these issues, microgrids have been identified as suitable integrating platforms for distributed, clean energy resources such as SPV. Different SPV and microgrid architectures are available for different applications depending on the resource availability and controllability. Reconfigurability is a concept that makes a system adaptable to two or more different environments by effectively utilizing the available resources. The review explains the applications of reconfigurable approaches on solar PV systems such as reconfigurable PV arrays, power conditioning unit (DC/DC converter, DC/AC inverter), microgrid controller and topology of distribution network with relevant studies. An analysis is also presented considering the unique features of reconfigurable systems in comparison to the static systems.

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Micro-grids consist of distributed power generation systems (DGs), distributed energy storage devices (DSs), and loads. Micro-grids are small-scale networks at low voltage levels that are use to provide thermal and electrical loads of small locations where there is no access to the main electrical grid. Given the environmental and economic issues for these areas, micro-grids can be a good solution for energy production. In this paper, determining the size and location of optimal electrical energy storage systems is presented. In other side, a new method based on the cost benefit analysis for optimal sizing of an energy storage system in a microgrid (MG) is proposed. The uncertainties associated with renewable energy sources and the occurrence of defects in the grid connection network and the effect of the contribution of load responses in a micro-grid are taken into account. The combined system consists of wind turbines and fuel cells. Basically, wind power is not definitively available. The new proposed method is based on two-stage randomization design (TSRD) for modeling the effect of wind power uncertainty so that the predicted wind energy error is considered as the main random parameter in the model. A standard probability distribution function is used to represent the error variations. Given the continuity of the mentioned function, the probability error function is extracted using the new discrete method and a certain number of scenarios with a certain probability. Finally, the problem has been transformed into an optimization problem, and a gray wolf optimization (GWO) algorithm has been used to solve it. In the proposed developed model based on local and global search, the algorithm tries to reach the final result in the shortest possible time and with the most precision. The results of the simulation show the efficiency of the proposed method in solving the micro-grid problem.

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This paper proposed the distributed moving horizon coordinated control scheme for the power balance and economic dispatch problems of micro-grid based on distributed generation. We design the power coordinated controller for each subsystem via moving horizon control by minimizing a suitable objective function. The objective function of distributed moving horizon coordinated controller is chosen based on the principle that wind power subsystem has the priority to generate electricity while photovoltaic power generation coordinates with wind power subsystem and the battery is only activated to meet the load demand when necessary. The simulation results illustrate that the proposed distributed moving horizon coordinated controller can allocate the output power of two generation subsystems reasonably under varying environment conditions, which not only can satisfy the load demand but also limit excessive fluctuations of output power to protect the power generation equipment.

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The modified flux-coupling-type superconducting fault current (SFCL) is a high-efficient electrical auxiliary device, whose basic function is to suppress the short-circuit current by controlling the magnetic path through a high-speed switch. In this paper, the high-speed switch is based on electromagnetic repulsion mechanism, and its conceptual design is carried out to promote the application of the modified SFCL. Regarding that the switch which is consisting of a mobile copper disc, two fixed opening and closing coils, the computational method for the electromagnetic force is discussed, and also the dynamic mathematical model including circuit equation, magnetic field equation as well as mechanical motion equation is theoretically deduced. According to the mathematical modeling and calculation of characteristic parameters, a feasible design scheme is presented, and the high-speed switch's response time can be less than 0.5 ms. For that the modified SFCL is equipped with this high-speed switch, the SFCL's application in a 10 kV micro-grid system with multiple renewable energy sources are assessed in the MATLAB software. The simulations are well able to affirm the SFCL's performance behaviors.

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Galvanic growth of Ag nano/micro-structures on Cu micro-grid was systematically studied for surface-enhanced Raman scattering (SERS) applications. Detailed characterizations via FE-SEM and HR-TEM showed that processing parameters, (reaction time, Ag(+) concentration, and PVP addition) all substantially affect thermodynamics/kinetics of the replacement reaction to yield substrates of significantly different microstructures/homogeneities and thus varied SERS performances (sensitivity, enhancement factor, and reproducibility) of the Ag substrates in the detection of R6G analyte. PVP as an additive was shown to notably alter nucleation/growth behaviors of the Ag crystals and promote the deposition of dense and uniform Ag films of nearly monodisperse polyhedrons/nanoplates through suppressing dendrites crystallization. Under optimized synthesis (50mM of Ag(+), 30s of reaction, and 700 wt.% of PVP), Ag substrates exhibiting a high Raman signal enhancement factor of ~1.1 × 10(6) and a low relative standard deviation of ~0.13 in the repeated detection of 10 µM R6G were obtained. The facile deposition and excellent performance reported in this work may allow the Ag microstructures to find wider SERS applications. Moreover, growth mechanisms of the different Ag nano/micro-structures were discussed based on extensive FE-SEM and HR-TEM analysis.

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