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The research presented in this paper introduces a novel environmental energy‐harvesting technology that harnesses electricity from the evaporation of water using porous structural materials. Specifically, a strategy employing paper‐based hydroelectric generators (p‐HEGs) is proposed to capture the energy produced during water evaporation and convert it into usable electricity. The p‐HEGs offer several advantages, including simplicity in fabrication, low cost, and reusability. To evaluate their effectiveness, the water evaporation‐induced electrical output performance of four different p‐HEGs are compared. Among the variants tested, the p‐HEG combining wood pulp and polyester fiber exhibits the best output performance. At room temperature, this particular p‐HEG generates a short‐circuit current and open‐circuit voltage of ≈0.4 µA and 0.3 V, respectively, thereby demonstrating excellent electrical stability. Furthermore, the electrical current and voltage generated by the p‐HEG through water evaporation are able to power an LED light, both individually and in series and parallel connections. This study delves into the potential of electricity harvesting from water evaporation and establishes it as a viable method for renewable energy applications. [ABSTRACT FROM AUTHOR]

Metal-organic frameworks (MOFs) have the advantages of tunable pore sizes and porosity and have demonstrated unique advantages for various applications. This study synthesized composite MOF nanomaterials by modifying MOF801 or AlOOH with UIO66. The composite nanomaterials, UIO66/MOF801 and UIO66/AlOOH showed increased Zeta potential than their pristine form, AlOOH, UIO66 and MOF801. For the first time, the composite MOFs were used to fabricate filter paper-based evaporation-driven power generators for spontaneous electricity generation. The MOFs-KBF membrane was constructed by coating filter paper (10 × 50 mm) with composite MOFs and conductive Ketjen Black. The UIO66/MOF801 decorated device achieved a maximum open circuit voltage of 0.329 ± 0.005 V and maximum output power of 2.253 μW. The influence of salt concentration (0.1–0.5 M) on power generation was also analyzed and discussed. Finally, as a proof-of-concept application, the device was employed as a salinity sensor to realize remote monitoring of salinity. This work demonstrated the potential of flexible MOF composites for spontaneous power generation from water evaporation and provides a potential way to enhance the performance of evaporation-driven power generators. [ABSTRACT FROM AUTHOR]

Microbial fuel cell is a promising technology to harvest energy from wastewater, and effective anode catalysts are essential for its applications. In this study, zero-dimension nitrogen-doped carbon dots, as biocompatible efficient modifiers, were synthesized and decorated onto the carbon paper surface to prepare microbial fuel cell anode. The as-fabricated nitrogen-doped carbon dots decorated carbon paper anode was able to enhance electricity generation and efficient wastewater treatment. It was found that the as-fabricated electrode had a high hydrophilicity, which was favorable for the microbial immobilization. Compared with the carbon paper anode, the biofilm on the as-prepared anode was almost twice of thickness. After introducing nitrogen-doped carbon dots, the extracellular electron transfer process from the microorganisms to the anode was enhanced. The microbial fuel cell with the as-developed anode generated a remarkable power output of 0.32 mW, 1.1 times higher than that of the raw carbon paper anode with same measurement area. Moreover, 16 sRNA pyrosequencing analysis shows that the quantity of Pseudomonas on the electrode increased by ∼40%, which also promoted the electron transfer rate by excreting mediators like phenazines or phenazine derivatives. This work developed a new approach to design microbial fuel cell anode material and fabricate a high-efficiency and environmentally friendly anode for electricity generation from wastewater. Image 100697 • Notable power output was obtained from MFC with N-doped CDs@carbon paper electrode. • The carbon paper electrode was highly hydrophilic by decorating with N-doped CDs. • The EET efficiency was enhanced by modifying the electrode with N-doped CDs. • The relative abundance of Pseudomonas was enhanced with N-doped CDs' decoration. [ABSTRACT FROM AUTHOR]

The central role of electricity in shaping the worldwide economy is broadly acknowledged in the energy literature. Having identified the then ongoing crisis of the electricity sector, the present Awami League government initiated restructuring the energy sector since 2009 to quicken the pace of the developmental activities. All these efforts resulted in landmark achievements in the Bangladesh energy sector, especially in increasing the electricity generation capacity. However, the global Covid-19 pandemic and its aftermath effects on the Bangladesh economy require a policy revision in Bangladesh's energy sector and electricity generation mix. To our knowledge, there is no study to analyse the adverse consequences of the Covid-19 in Bangladesh energy sector. By employing a SARIMA forecasting model, we reveal that electricity demand will remain less than the actual generation in the upcoming two years. Also, the DGE model finds that due to Covid-19, the economic growth rate will be around 4.5 percent in the long-run. We further simulate that the steady-state electricity demand and standard consumption values would fall by 8-10 percent and 6 percent, respectively. We recommend that a review of the power sector master plan is needed for future energy security and economic stability in Bangladesh. [ABSTRACT FROM AUTHOR]

Highlights • We develop a novel portable and disposable paper-based biobattery. • Our biobattery is on-demand electricity generation activated by a drop of tap water. • A low-cost, simple-structure battery case is created by single layer of paper filter. • We proposed integrated air-cathode paper-based proton exchange membrane. • Proposed battery can be used for paper-based diagnostic devices. Abstract A novel, portable, and disposable paper-based microbial fuel cells (MFC) generating electricity from harmless strain of Escherichia coli (E. coli) has been developed. This MFC is on-demand electricity generation activated by a drop of tap water in a dry anode containing the biofilm of E. coli. A low-cost, simple-structure MFC case was created by a single layer of paper filter with high order of folding, which could support interchangeable dry bacteria-loaded anodes. The paper filter was innovatively engineered to make an integrated air-cathode proton exchange membrane (ACPEM) by coating carbon nanotube mixed with potassium ferricyanide on one surface and spraying hydrophobic solution on the other surface, respectively. The E. coli biofilm pre-inoculated in the anodes made of activated carbon sheet was simply dried in the air for the sake of long-term storage and usage. The dry anodes can be simply set in the MFC case with the readily prepared ACPEM, which can be used for on-demand power generation within seconds after adding water with maximum power density of 8.8μW/cm2. [ABSTRACT FROM AUTHOR]

The recovery and utilisation of industrial excess heat has been identified as an important contribution for energy efficiency by reducing primary energy demand. Previous works, based on top-down studies for a few sectors, or regional case studies estimated the overall availability of industrial excess heat. A more detailed analysis is required to allow the estimation of potentials for specific heat recovery technologies, particularly regarding excess heat temperature profiles. This work combines process integration methods and regression analysis to obtain cogeneration targets, detailed excess heat temperature profiles and estimations of electricity generation potentials from low and medium temperature excess heat. The work is based on the use of excess heat temperature (XHT) signatures for individual sites and regression analysis using publicly available data, obtaining estimations of the technical potential for electricity generation from low and medium temperature excess heat (60–140 °C) for the whole Swedish kraft pulp and paper industry. The results show a technical potential to increase the electricity production at kraft mills in Sweden by 10 to 13%, depending on the level of process integration considered, and a lower availability of excess heat than previously estimated in studies for the sector. The approach used could be adapted and applied in other sectors and regions, increasing the level of detail at which industrial excess heat estimations are obtained when compared to previous studies. [ABSTRACT FROM AUTHOR]

An enormous gap exists between Africa's current electrification rate and the 2030 UN goal to ensure universal access to modern energy. A study by Sanoh et al. published in Renewable Energy in 2014 [1] is a rare example of finding a cost minimal solution for the Africa-wide generation and transmission network. Unfortunately, however, the paper exhibits a number of relatively serious flaws that demand attention given the alarming paucity of such research on Africa. Five issues of the study by Sanoh et al. are identified and discussed in this commentary paper. Specifically, the study does not account for capacity factors when deriving required capacity additions, misses transmission losses when sizing generation capacity, models country-level import constraints incorrectly, introduces a supply option redundancy, and reports optimisation results that can be shown to be mathematically sub-optimal. As a result of some of these issues, the Sanoh et al. significantly underreport the required capacity to meet additional African demand in 2025. In addition to discussing these flaws, this paper provides potential approaches to avoid each of the five issues. [ABSTRACT FROM AUTHOR]

Abstract: Alarmingly low pulp prices in early 2009 left pulp and paper mills across North America desperate for any way to improve thin profit margins. One solution that continues to gain popularity among the industry is improved energy management systems for cogeneration systems, which use steam for two purposes – to provide heat for the pulping process and to generate electricity for sale to regional providers. This paper presents an energy optimization algorithm for use in a pulp and paper mill cogeneration system. The algorithm is applicable to a number of popular mill configurations, power sale contracts, and fuel purchasing scenarios. The method is also extended to address weather-dependent cooling limitations encountered by a mill cogeneration facility, in which case an iterative solution is proposed in order to maintain convexity of the optimization problem. Results are presented in the form of three case studies. [ABSTRACT FROM AUTHOR]

Abstract: The possibility of co-processing paper sludge with coal in power plants for power production and useful products was investigated as an alternative to the disposal option. The thermal behaviour of the fuels and their blend during pyrolysis and combustion processes was studied, kinetic models were developed and the compatibility of each component in the blend was evaluated. The experiments were conducted in a thermogravimetric analysis system, at non-isothermal heating conditions, over the temperature range 25–850°C. The effect of the inorganic constituents of the fuels and their mixture on thermal conversion characteristics, reactivity, slagging and fouling propensities and environmental pollution was examined. The thermochemical reactivity of the two fuels was different in both nitrogen and air. Devolatilization of paper sludge occurred earlier and with a higher rate, while its combustion was hindered by the high content of ash. When the two fuels were mixed their pyrolysis or combustion reactivities did not substantially change. A first-order parallel reactions model for pyrolysis and a power low model for combustion fitted the experimental results accurately. The kinetic parameters of the blend could be predicted from the data of the individual components. Co-firing paper sludge with subbituminous coal might somehow improve the slagging/fouling potential of the coal. However, if the mineral matter of paper sludge is partly removed before use, then the combustion behaviour of the mixture could resemble that of coal alone and the overall efficiency of the process would increase. [Copyright &y& Elsevier]

[Display omitted] • Various carbon nanotube-based devices are developed for solar energy utilization. • The water evaporation system can generate freshwater (1.28 kg m−2h−1). • The solar-thermoelectric system can output a voltage and charge a cellphone. • The supercapacitor performs an areal specific capacitance of 19.6 mF cm−2. • The hybrid energy system can produce freshwater, generate and store electric power. Nowadays, multi-functional systems driven by solar energy have been explored to alleviate the crisis of energy and freshwater scarcity. However, it remains a great challenge to integrate multi-functions into one hybrid system with a monolithic material, which can harvest, convert and store solar energy synergistically. Here, we firstly propose a multi-functional carbon nanotube paper, which starts from a material level to solve these problems. The carbon nanotube paper is fabricated by vacuum filtration. It exhibits high efficiency of solar-thermal conversion. Secondly, three types of energy conversion/storage systems (e.g., solar-thermal evaporation system, solar-thermoelectric generation system, and supercapacitor) are constructed based on the carbon nanotube paper, which extend the research to a device level. The solar-thermal evaporation system shows an evaporation rate of 1.28 kg m-2h−1 under simulated sunlight irradiation of 1 kW m−2. The solar-thermoelectric generation system demonstrates a stable electric power generation with an output voltage of 100 mV under light irradiation of 1 kW m−2. The supercapacitors perform the energy storage function with an areal specific capacitance of 19.6 mF cm−2. These devices and systems can be used in freshwater generation (0.84 kg m-2h−1, sunlight irradiation of 1 kW m−2), water purification/desalination (inorganic ions rejection larger than 99.9%) and portable solar charging system (maximum output voltage of 5 V). Finally, a hybrid energy system is innovatively proposed from the system level to simultaneously produce freshwater, generate and store electric power. Through the synergetic coupling of solar conversion and storage technologies, the hybrid energy system can supply sustainable freshwater and electricity for remote areas in daily life, highlighting the superiority of multi-energy (thermal energy, electrical energy, and electrochemical energy) complementary. [ABSTRACT FROM AUTHOR]

Increased interest in sustainable agriculture and bio-based industries requires that we find more energy-efficient methods for treating cellulose-containing wastewaters. We examined the effectiveness of simultaneous electricity production and treatment of a paper recycling plant wastewater using microbial fuel cells. Treatment efficiency was limited by wastewater conductivity. When a 50 mM phosphate buffer solution (PBS, 5.9 mS/cm) was added to the wastewater, power densities reached 501 ± 20 mW/m2, with a coulombic efficiency of 16 ± 2%. There was efficient removal of soluble organic matter, with 73 ± 1% removed based on soluble chemical oxygen demand (SCOD) and only slightly greater total removal (76 ± 4%) based on total COD (TCOD) over a 500-h batch cycle. Cellulose was nearly completely removed (96 ± 1%) during treatment. Further increasing the conductivity (100 mM PBS) increased power to 672 ± 27 mW/m2. In contrast, only 144 ± 7 mW/m2 was produced using an unamended wastewater (0.8 mS/cm) with TCOD, SCOD, and cellulose removals of 29 ± 1%, 51 ± 2%, and 16 ± 1% (350-h batch cycle). These results demonstrate limitations to treatment efficiencies with actual wastewaters caused by solution conductivity compared to laboratory experiments under more optimal conditions. [ABSTRACT FROM AUTHOR]

We reported a novel, non-optical technique to analyse and quantify the transportation of bacterial cells in paper-based microfluidics. This approach was based on real-time measurement of the microbial electricity production. Our device was designed to have three hydrophilic regions linked by a channel on a paper layer by patterning hydrophobic barriers in the paper. Each region came into contact with an anodic electrode layer which was stacked with a cathodic compartment through a proton exchange membrane. When bacterial cells were transported to each region by capillary force, the bacteria cells were promoted to adhere onto the anode and the cells completed their respiration by transferring the electrons to the anode. A conductive load connected the anode and cathode to complete the external circuit through which the electrons flowed. The protons generated by the anodic reactions passed through the proton exchange membrane and travelled to the cathode, where they combined with electrons in the reduction process. By measuring the current through the load, bacterial cells’ transportation through the channels in paper was quantitatively investigated according to the pore size of the paper. Further understanding was made by analysing electron microscope examination of the hydrophilic regions. This work will determine more efficient cell movement within a paper material by controlling the paper's microfluidic dimensions and pore size. It will also provide a quantitative understanding of the flow of large organisms for use in paper-based diagnostics. [ABSTRACT FROM AUTHOR]

Electrical power generation in Oman depends mainly on natural gas, while in rural areas it is based mainly on diesel fuel. Oman has committed to net-zero emissions by 2050, in line with the Paris Agreement's goal of limiting global warming to 1.5°C. The objective of this paper is to propose an optimal energy mix model for electricity generation from various energy sources, such as gas, diesel, wind, and photovoltaic, that considers more renewable sources in the energy mix. The optimization model minimizes various costs such as construction cost, operation cost, fuel cost, and carbon emissions, while satisfying the load demand. In this paper, Masirah Island is selected to perform our analysis. Several scenarios are contemplated, including grid extension to the island. The results found that gas-powered generators with 20% PV and storage are the best option in terms of the levelized cost of electricity. The grid extension is an economically feasible option if the existing load is more than doubled. [ABSTRACT FROM AUTHOR]

Abstract: Integration of biomass gasification with a pulp and paper mill is a possible route to create more value-added products. This route facilitates, for example, more advanced electricity generation and production of biomass based transportation fuels or chemical feedstock. Each unit operation in such a process affects overall efficiency as well as possibilities for process integration. In this paper, the impact of different dryer types in a biomass gasification combined cycle (BIGCC) has been evaluated in terms of efficiency and economic performance. The BIGCC was sized so that the excess heat would replace the current steam production from bark and oil. The results show that the dryer type can have a significant impact on economic performance and efficiencies. A BIGCC with an integrated belt dryer, utilizing excess heat to heat the drying air from the mill, can result in electrical efficiencies of up to around 40%, while e.g. a steam dryer can reach 36–37%. Choice of oxidant, air or oxygen, in the gasifier affects both capital and operational cost. Air was proven to be the most cost efficient solution for the cases evaluated in this study. The investment of around 100 to 140 million Euros for a BIGCC facility is profitable for most evaluated cases for an annuity factor of 0.1, while the net annual profit is negative for most cases when the annuity factor was increased to 0.2, even when including financial support for renewable electricity. [Copyright &y& Elsevier]

Abstract: Gold is among the highly conductive and stable materials, which are ideal anodes for microbial fuel cells (MFCs). However, previous studies have shown that bare gold surface is recalcitrant for the colonization of some exoelectrogens, e.g., Shewanella putrefacians. In this work, the problem regarding the poor bio-compatibility of gold as an anode material was sorted out through coupling it with carbon paper. A new composite anode material was fabricated through sputtering gold layer homogeneously on carbon paper matrix. Results of cyclic voltammetry and electrochemical impedance spectroscopy in Fe(CN)6 3−/4− solution demonstrated better electrochemical performance of the carbon paper–gold (C–Au) composite than either carbon paper or bare gold, when they were used in MFCs. With Shewanella oneidensis MR-1 as the inoculum, the C–Au anode-based MFC produced total electric charges higher than the carbon-paper-anode-based MFC by 47%. The cyclic voltammetry analysis and the scanning electron microscopy observation showed that the MR-1 biofilm growth was accelerated when the carbon paper surface was sputtered with gold. Utilization of such a carbon paper–gold composite significantly enhanced the MFC performance. [ABSTRACT FROM AUTHOR]

Autonomous microgrid is known to lack appropriate inertia and damping for grid stabilization. Due to this, virtual synchronous machine (VISMA) has been introduced to provide necessary ancillary services through control of power converters. In a multi‐VISMA (n‐VISMA) microgrid, relative rotor angle stability of the power system is dependent on the active power balance after small perturbation. Thus, the use of relevant analytical models are essential issues for microgrid stability analysis. This paper presents a comprehensive small‐signal stability analysis to study inherent electromechanical oscillations in the virtual rotors. The subsystems of the microgrid consisting of VISMA, network, load and the outer power control were all modelled in Synchronous Reference Frame. The small‐signal model (SSM) was tested on IEEE‐9 bus system with VISMA replacing electromechanical synchronous machines on the network. To validate the developed numerical analytics, dynamic responses of the SSM are compared with those of the non‐linear (NL) system dynamics and the results reveal that the developed linearized SSM is sufficient to accurately characterize behaviour of the VISMA microgrid when operated in autonomous mode. Eigenvalues analysis and parameter sensitivities of the critical modes were investigated. Oscillatory participations of the VISMAs and steady state stability limit of the microgrid have also been investigated. [ABSTRACT FROM AUTHOR]

Microbial fuel cells (MFCs) have garnered significant attention due to their capacity to generate electricity using renewable and carbon-neutral energy sources such as wastewater. Extensive experimental work and modeling techniques have been employed to dissect these processes and understand their respective impacts on electricity generation. The driving force is to enhance MFC performance for practical applications commercially. Among the various statistical modeling approaches, one particularly robust tool is the Design of Experiments (DoE). It serves to establish the relationships between different variables that influence MFC performance and allows for the optimization of the MFC configuration and operation for scaled-up performances in terms of bioelectricity generation. This study focused on optimizing microbial fuel cells (MFCs) for bioelectricity production using industrial wastewater treatment, employing the Box–Behnken design (BBD) methodology. Through an analysis of response surface models and ANOVA tests, it was found that a combined approach of reduced quadratic, reduced two-factor interaction, and linear models yielded sound results, particularly in voltage yield, COD removal, and current density. Second-order regression models predicted optimal conditions for various parameters, with surface area, temperature, and catholyte dosage identified as critical input variables for optimization. Under these conditions, conducted by the four-factor and three-level Box–Behnken design methodology in a double-chamber MFC unit considering eight output variables—CCV yield, % COD removal, current density, power density, % TSS removal, % CE, and % P O 4 3 − —the optimum values were 700 mV, 54.4%, 54.4 mA/m2, 73.7 mW/m2, 99%, 21.2%, and 100%, respectively. At optimum operating conditions, the results revealed a desirability of 76.6% out of a total of 92 iterations. The paper highlights the effectiveness of statistical ANOVA fit-statistics modeling and optimization in enhancing DCMFC performance, recommending its use as a sustainable bioenergy source. Furthermore, validation results supported the above optimization output response findings and confirmed the viability of biorefinery wastewater as an anolyte for scaling up DCMFC bioelectricity generation. [ABSTRACT FROM AUTHOR]

Power load prediction is fundamental for ensuring the reliability of power grid operation and the accuracy of power demand forecasting. However, the uncertainties stemming from power generation, such as wind speed and water flow, along with variations in electricity demand, present new challenges to existing power load prediction methods. In this paper, we propose an improved Convolutional Neural Network–Bidirectional Long Short-Term Memory (CNN-BILSTM) model for analyzing power load in systems affected by uncertain power conditions. Initially, we delineate the uncertainty characteristics inherent in real-world power systems and establish a data-driven power load model based on fluctuations in power source loads. Building upon this foundation, we design the CNN-BILSTM model, which comprises a convolutional neural network (CNN) module for extracting features from power data, along with a forward Long Short-Term Memory (LSTM) module and a reverse LSTM module. The two LSTM modules account for factors influencing forward and reverse power load timings in the entire power load data, thus enhancing model performance and data utilization efficiency. We further conduct comparative experiments to evaluate the effectiveness of the proposed CNN-BILSTM model. The experimental results demonstrate that CNN-BILSTM can effectively and more accurately predict power loads within power systems characterized by uncertain power generation and electricity demand. Consequently, it exhibits promising prospects for industrial applications. [ABSTRACT FROM AUTHOR]

The government has set an ambitious target of renewable energy development in Malaysia. As a promising renewable energy source, wind energy plays an important role in the Malaysia renewable energy roadmap. Compared to onshore wind energy, offshore wind resources with better quality can be provided in the areas away from the coast, which has greater potential to contribute to electricity generation. Wind and bathymetry conditions are two important factors that determine the feasibility and economics of offshore wind turbines. In this paper, an investigation is conducted on wind and bathymetry conditions around Malaysia. The data source mainly originates from the Global Wind Atlas. The conditions of the coastal areas in different states and federal territories of both Peninsular Malaysia and East Malaysia are analysed, with a specific focus on wind speed, wind energy density, and bathymetry conditions in high-wind-speed regions. The data and survey are verified and compared with the past published literature. This paper aims to investigate the wind and bathymetry conditions around Malaysia, assess the potential of offshore wind energy, discuss the feasibility of offshore wind turbines, and provide references for offshore wind development in Malaysia. [ABSTRACT FROM AUTHOR]

In light of the growing integration of renewable energy sources in power systems, the adoption of DC microgrids has become increasingly popular, due to its simple structure, having no frequency, power factor concerns. However, the dependence of DC microgrids on cyber-networks also makes them susceptible to cyber-attacks. Potential cyberattacks can disrupt power system facilities and result in significant economic and loss of life. To address this concern, this paper presents an attack-resilient control strategy for microgrids to ensure voltage regulation and power sharing with stable operation under cyber-attack on the actuators. This paper first formulates the cyber-security problem considering a distributed generation based microgrid using the converter model, after which an attack-resilient control is proposed to eliminate the actuator attack impact on the system. Steady state analysis and root locus validation illustrate the feasibility of the proposed method. The effectiveness of the proposed control scheme is demonstrated through simulation results. [ABSTRACT FROM AUTHOR]

This paper analyzes five optimization algorithms for solving microgrid energy management problems. Network reconfiguration has become prevalent due to increased power demand in modern society. Microgrid energy management system has become a part of essential strategies to mitigate the total generation cost and electricity payment in the advanced smart electrical network. This study compared the performance of the optimization algorithm with total generation cost minimization and the total number of demand response programs while selecting the best approach as a suggestion. The effectiveness of the applied method is evaluated with fitness value, convergence rates, and robustness. Numerical simulation results are presented in paper, the five different methods are evaluated based on their performance and the resulting demand response program from the viewpoint of system cost-minimizing. [ABSTRACT FROM AUTHOR]

The safety and robustness of Deep Geological Repositories (DGRs) are of paramount importance for the long-term management of spent nuclear fuel from electricity generation. The introduction of a multi-barrier system, which includes the host rock formation and an engineered barrier system (including the bentonite buffer), has been a widely used approach to ensure the safety of DGRs. The assessment of the long-term safety of DGRs involves the mathematical modeling of the coupled thermal–hydraulic–mechanical–chemical (THMC) processes that occur in the near-field of the DGRs and their impact on the behaviour and engineering properties of the bentonite buffer. This paper presents a review of the THMC-coupled processes that arise in the bentonite buffer as well as a mathematical model governing such coupled processes. The model is verified against existing analytical solutions and validated against measured data of a thermal diffusion experiment in a sand bentonite column. Also, scoping analyses were performed to assess the influence of coupled THM processes on solute transport in clayrocks. The results of the numerical model closely matched those of the analytical solutions and experimental data demonstrating the capability of the provided mathematical model as well as the numerical approach in enhancing our comprehension of DGR behaviour. This enhanced comprehension will be valuable for safety prediction and assessment in the context of DGRs. The work presented in this paper is part of the Canadian Nuclear Safety Commission's (CNSC) regulatory research to gain independent knowledge on the safety of the geological disposal of radioactive waste. [ABSTRACT FROM AUTHOR]

Increased innovation on finding new ways to generate energy from different sources to meet the growing demand of consumers has led to various challenges in controlling the power network when it faces different disruptions. To address these challenges, a new approach has been proposed in this research paper, which combines a controller with a soft computing technique called Particle Swarm Optimization (PSO). The study considers a power system with four units, where three different energy sources are utilized and distributed across two areas. Each area has two power sources, with one area having a combination of thermal and gas power plants, and the other area consisting of a nuclear power plant and a gas power plant. Transmitting power from the nuclear power plant is particularly complex due to its high sensitivity to disturbances. Therefore, an intelligent and efficient controller is needed to ensure robust control in this type of power network that includes nuclear power. The paper also conducts a thorough analysis of the harmful emissions associated with electricity generation from the different power plants considered. The goal is to reduce the carbon footprint associated with power generation. The proposed work and analysis in the paper are implemented using the MATLAB/SIMULINK environment. [ABSTRACT FROM AUTHOR]

There is a large global effort to improve microbial fuel cell (MFC) techniques and advance their translational potential toward practical, real-world applications. Significant boosts in MFC performance can be achieved with the development of new techniques in synthetic biology that can regulate microbial metabolic pathways or control their gene expression. For these new directions, a high-throughput and rapid screening tool for microbial biopower production is needed. In this work, a 48-well, paper-based sensing platform was developed for the high-throughput and rapid characterization of the electricity-producing capability of microbes. 48 spatially distinct wells of a sensor array were prepared by patterning 48 hydrophilic reservoirs on paper with hydrophobic wax boundaries. This paper-based platform exploited the ability of paper to quickly wick fluid and promoted bacterial attachment to the anode pads, resulting in instant current generation upon loading of the bacterial inoculum. We validated the utility of our MFC array by studying how strategic genetic modifications impacted the electrochemical activity of various Pseudomonas aeruginosa mutant strains. Within just 20 minutes, we successfully determined the electricity generation capacity of eight isogenic mutants of P. aeruginosa. These efforts demonstrate that our MFC array displays highly comparable performance characteristics and identifies genes in P. aeruginosa that can trigger a higher power density. [ABSTRACT FROM AUTHOR]

SUMMARY Previous studies by the authors have shown that energy savings in pulp and paper mills offer opportunities for increased electricity production on-site or wood fuel export. The energy export implies reductions in CO2 emissions off-site, where fossil fuel or fossil-fuel-based electricity is replaced. To assess this potential and the related profitability for a future situation, four energy market scenarios were used. For a typical Scandinavian mill, the potential for CO2-emission reductions was 15-140 kton year−1 depending on the scenario and the form of energy export. Extrapolated to all relevant mills in Sweden, the potential was 0.4-3.1 Mton year−1, which is in the order of percent of the Swedish CO2 emissions. Wood fuel export implies larger reduction in CO2 emissions in most scenarios. In contrast, electricity export showed better economy in most of the cases studied; with annual earnings of 5-6 M€, this is an economically robust option. In the market pulp mill investigated, the wood fuel export was in the form of lignin. Lignin could possibly be valued as oil, regarding both price and potential for CO2-emission reduction, making lignin separation an option with good profitability and large reductions of CO2 emissions. Copyright © 2011 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An introduction is presented in which the editor discusses articles in the issue on topics including photovoltaics (PV), silicon-based solar cells and electricity generation.

A new paper‐based anti‐reflection coating for solar cells is presented showing a large reduction in the reflection over the entire solar spectrum for a wide range of angles. This process is simple and inexpensive, requiring no high temperature or vacuum‐based processing, and is made from renewable cellulose fibers. [ABSTRACT FROM AUTHOR]

Chile has a very ambitious energy transition agenda and massive challenges ahead to accomplish it. To integrate the high solar energy potential in the north an the high wind power potential of the south of the country, considerable investments in the electrical grid and new balancing mechanism and storage capacities are necessary. This study addresses the potential of individual industries, particularly the paper industry, to provide flexibility to the electrical system on-site. To achieve this, an optimization model that minimizes energy provision costs is proposed. The model considers the demand of a company including its demand side management potential, combined heat and power generation capacities, as well as on-site renewable energy generation location potential from photovoltaics and wind power. The model is computed under multiple parametrization scenarios to estimate under which conditions it would be advantageous for the company to use renewable electricity. This allows to evaluate how much of the renewable electricity produced in high peaks can be used by the company, and in how far, demand side management and combined heat and power can compensate low generation periods of renewable electricity. The model is feeded with typical hourly electricity and heat demand profiles of a prototypic paper producing company, which were statistically derived from one and a half years of measurements. Moreover, electricity generation time series from photovoltaics and wind power are derived from physical models that rely on ERA5 reanalysis data. The latter data set allows to compute the model in locations all around Chilean territory in a 30 km x 30 km spatial grid. Results are presented in the form of maps of the shares of renewables that would be enabled at avery location by industries of the same characteristics. [ABSTRACT FROM AUTHOR]

This paper performs a technoeconomic analysis of the wind power potential and evaluates the cost of wind power generation in Evodoula, comparing two methods, the conventional method and the uncertainty method based on a comparative spatiotemporal approach using the geographic information system (GIS) software tool. This study is based on satellite wind data measured at 10 m above ground level (AGL) over a 40-year period (1980-2019), by the meteorological service NASA (National Aeronautics and Space Administration)/Goddard Space Flight Center (GSFC). The main objectives are to obtain an appropriate design for a proven optimal location and to assess the viability of wind power at Evodoula. For this type of study, there is little literature available. The optimization of an onshore wind farm and deployment in the wind energy development interest area (ZIDEE) is carried out to obtain a minimum and parsimonious discounted cost production unitary (CPU) of the electricity produced. The results showed that in Okok, a location with a large energy deficit, an onshore wind farm with an electricity generation capacity of 12.5 MW with 5 NORDEX N100-2.5MW wind turbines would have a total energy production (TEP) of about 64.0254825 TWh and a selling price of electricity that would be 0.0034 CAD$/kWh, which is very low compared to the utility price (about 98% cheaper). The total cost of the wind farm would be about $11 million, with a net present cost of about $218 million. The annual profit generated by the wind farm would be over $6 billion. The return on investment (ROI) of the project is estimated at 2880.882%. The constructed onshore wind farm would avoid CO2 emission at over 11 Mt CO 2 , eq /year as the energy generated is from the atmosphere. The wind farm would realize an average annual cash flow estimated at nearly $30 million after 20 years of operation. These savings would allow the installation of CO2 capture systems in conventional power plants. In addition, the analysis of uncertainties and risks was identified and quantified to estimate the confidence levels of the project development results. The risks have been assessed, and we recommend that the total uncertainty of the project is around 15%. The energy values in P 75 and P 90 are 10.08% and 19.22%, respectively, lower than the energy value in P 50 of 11.60 GWh/An. Finally, the main policy recommendations for an inclusive design process are highlighted. The contribution of this study is to assist policy makers in making appropriate decisions in the development and implementation of energy and environmental policy in Cameroon and in many continental areas. [ABSTRACT FROM AUTHOR]

Paying close attention to the environmental risks associated with traditional forms of energy, particularly the serious issue of global warming caused by the release and concentration of greenhouse gases, has become a paramount concern. This growing awareness has prompted governments worldwide to prioritize the benefits of alternative energy sources and develop comprehensive plans accordingly. Moreover, it is crucial to thoroughly consider and explore existing potentials in our quest for sustainable energy solutions. One such potential lies in the energy loss experienced due to gas pressure reduction in urban gas reduction stations. Furthermore, as we increase the amount of natural gas preheating, we observe a corresponding rise in the temperature within the expansion turbine, ultimately resulting in a significant boost in power generation. In this paper, we delve into the exciting possibility of harnessing electricity generation by utilizing a turbo expander within a municipal gas pressure reduction station. To maximize the work generation capacity, we propose preheating the gas input to the turbo expander using geothermal energy. Our study reveals that the turbo expander exhibits optimal performance, boasting an impressive isentropic efficiency of 92.3%, when the inlet temperature is maintained at 84 °C and the amount of preheating reaches 192.3 kJ/kg. [ABSTRACT FROM AUTHOR]

Electricity market violations affect the overall operations of the electricity market. This paper explores the evolutionary stability strategies of electricity generation enterprises and electricity consumers under two modes: traditional regulation and blockchain regulation to analyze blockchain technology's mechanism and conditions in solving electricity market violations. The experimental results indicate that the likelihood of consumers accepting electricity and the regulatory capacity of regulatory agencies play a crucial role in determining the violation approach adopted by electricity generation enterprises. Under traditional regulatory models, due to information asymmetry, regulatory agencies may not be able to detect violations promptly. Meanwhile, electricity consumers may choose to accept violations by power generation companies due to high appeal costs. Blockchain technology enables regulatory agencies to improve their regulatory capabilities by eliminating information asymmetry, reducing the cost of complaints from electricity consumers, thereby elevating the risk for enterprises engaging in market violations and optimizing the evolutionary game towards an optimum state. [ABSTRACT FROM AUTHOR]

As electric hot water cylinders (HWCs) have a large capacity for thermal storage, they are well-suited for Demand Side Management (DSM). This paper compares different methods of HWC temperature control and presents a methodology to assess the amount of thermal storage available in HWCs for demand side management based on use behaviour in different household types. Simple stochastic methods for domestic hot water (DHW) demand prediction were employed to design a smart controller that produced lower rates of unmet DHW demand and higher available storage than setpoint and ripple controllers. The average storage available for DSM from the use of this smart controller is predicted to be between 3.63 and 7.20 kWh per household. These results indicate the use of HWCs for thermal storage is a low-cost viable option for peak-shaving of power system load and could decrease power system greenhouse gas (GHG) emissions in countries such as Aotearoa New Zealand, where GHG-emitting electricity generation is primarily used to meet peak loads. [ABSTRACT FROM AUTHOR]

Floating photovoltaic (FPV) systems have generated much interest in the literature, due to the potential synergies with existing hydropower reservoirs. This is of particular relevance to Aotearoa New Zealand, where the national grid's heavy reliance on hydro resources has left the country prone to energy shortages during dry years. This paper investigates the potential implications of a 1-gigawatt peak fleet of distributed FPV systems on seven hydro schemes around the country. The results show that an FPV fleet in Aotearoa New Zealand could provide additional electricity generation when the controlled hydropower storage is low. A larger, wider rollout would allow for the reservoirs to replenish after the country's unique winter peak in electricity demand. [ABSTRACT FROM AUTHOR]

Wave energy, as a significant renewable and clean energy source with vast global reserves, exhibits no greenhouse gas or other pollution during real-sea operational conditions. However, throughout the entire lifecycle, wave energy convertors can produce additional CO2 emissions due to the use of raw materials and emissions during transportation. Based on laboratory test data from a wave energy convertor model, this study ensures consistency between the model and the actual sea-deployed wave energy convertors in terms of performance, materials, and geometric shapes using similarity criteria. Carbon emission factors from China, the European Union, Brazil, and Japan are selected to predict the carbon emissions of wave energy convertors in real-sea conditions. The research indicates: (1) The predicted carbon emission coefficient for unit electricity generation ( E F co 2 ) of wave energy is 0.008–0.057 kg CO2/kWh; when the traditional steel production mode is adopted, the E F co 2 in this paper is 0.014–0.059 kg CO2/kWh, similar to existing research conclusions for the emission factor of CO2 for wave energy convertor (0.012–0.050 kg CO2/kWh). The predicted data on carbon emissions in the lifecycle of wave energy convertors aligns closely with actual operational data. (2) The main source of carbon emissions in the life cycle of a wave energy converter, excluding the recycling of manufacturing metal materials, is the manufacturing stage, which accounts for 90% of the total carbon emissions. When the recycling of manufacturing metal materials is considered, the carbon emissions in the manufacturing stage are reduced, and the carbon emissions in the transport stage are increased, from about 7% to about 20%. (3) Under the most ideal conditions, the carbon payback period for a wave energy convertor ranges from 0.28 to 2.06 years, and the carbon reduction during the design lifespan (20 years) varies from 238.33 t CO2 (minimum) to 261.80 t CO2 (maximum). [ABSTRACT FROM AUTHOR]

In an environment marked by dual carbon goals and substantial fluctuations in coal market prices, coal power generation enterprises face an urgent imperative to make scientifically informed decisions regarding production management amidst significant market uncertainties. To tackle this challenge, this paper proposes a methodology for optimizing electricity generation side market decisions and assessing risks using quantile data-driven information-gap decision theory (QDD-IGDT). Initially, a dual-layer decision optimization model for electricity production is formulated, taking into account coal procurement and blending processes. This model optimizes the selection of spot coal and long-term contract coal prices and simplifies the dual-layer structure into an equivalent single-layer model using the McCormick envelope and Karush–Kuhn–Tucker (KKT) conditions. Subsequently, a quantile dataset is generated utilizing a short-term coal price interval prediction model based on the quantile regression neural network (QRNN). Interval constraints on expected costs are introduced to develop an uncertainty decision risk measurement model grounded in QDD-IGDT, quantifying decision risks arising from coal market uncertainties to bolster decision robustness. Lastly, case simulations are executed by using real production data from a power generation enterprise, and the dual-layer decision optimization model is solved by employing the McCormick–KKT–Gurobi approach. Additionally, decision risks associated with coal market uncertainties are assessed through a one-dimensional search under interval constraints on expected cost volatility. The findings demonstrate the effectiveness of the proposed research methodology in cost optimization within the context of coal market uncertainties, underscoring its validity and economic efficiency. [ABSTRACT FROM AUTHOR]

Several northern European countries have announced ambitious plans to become carbon neutral already before the year 2050. Recent research has, however, highlighted how potential bottlenecks in raw material and resource availability could significantly delay or hinder wind and solar photovoltaic (PV) expansion and continued biomass usage in parts of Europe. To address this issue, this paper assesses how exposed the national energy and climate plans (NECPs) of Finland, Estonia, Germany, Sweden, and Denmark are to resource limitations and techno-economic risks by reviewing and analysing 2030 NECP targets compared to statistical energy use data in these countries. The results indicate that the NECPs of Denmark and Germany are particularly exposed to risks related to global raw material availability, as Denmark plans to rapidly grow the share of wind and solar PV in electricity generation to 81% and 13% by 2030, respectively, followed by Germany, which outlines a 39% and 16% share of wind and solar PV in its national climate strategy. The NECPs of Finland and Germany are also shown to be vulnerable to limitations in biomass availability, as there is a significant disparity between the projected biomass usage and legally binding European Union (EU) targets for land use, land use change, and forestry (LULUCF) sector emissions in 2030 in these countries. [ABSTRACT FROM AUTHOR]

Solar‐based Distributed Generation (DG) powered Electric Vehicles (EVs) charging stations are widely adopted nowadays in the power system networks. In this process, the distribution grid faces various challenges caused by intermittent solar irradiance, peak EVs load, while controlling the state of charge (SoC) of batteries during dis(charging) phenomena. In this paper, an intelligent energy management scheme (IEMS)‐based coordinated control for photovoltaic (PV)‐based EVs charging stations is proposed. The proposed IEMS optimizes the PV generation and grid power utilization for EV charging stations (EVCS) by analysing real‐time meteorological and load demand data. The coordinated control of EMS provides power flow between PV generation, distribution grid, and EVs battery storage in a manner which results in the reduction of peak power demand by a factor of two. Further, the adaptive neuro‐based fuzzy control approach includes forecasting solar‐based electricity generation and EVs loads demand predictions to optimize IEMS according to the Indian power scenario. The proposed IEMS optimally utilizes the buffer batteries system for reducing the peak electricity demand with low system losses and reducing the impact of EVs charging load on distribution grid. The results are analysed using the digital simulation model and validated with real‐time hardware‐in‐loop experimental setup. [ABSTRACT FROM AUTHOR]

Ubiquitous energy harvesting technologies require new types of renewable, sustainable, and clean energy to solve the problems of fossil fuels. Although various nanogenerators have been developed over the last decade, low current density, requirements for complicated management circuits, generation of direct current (DC) outputs, and significant performance degradation under humid atmospheres have been problems limiting practical applications. This paper reports that the tribovoltaic and moisture‐enabled electricity generation effects can be achieved in a layered double hydroxide (LDH) by applying a metal brushing mode. The ZnAl‐LDH shows enhanced tribovoltaic nanogenerator (TVNG) performance even in a high‐humidity environment coupled with the moisture‐enabled electricity generated by the concentration gradient of a water molecule through the interlamellar structures of the LDHs. The spontaneous dissociation of water in the interior of LDHs removes the hole generated by the tribovoltaic effect, allowing high efficiency of an output voltage of 693.38 mV and current density of 65.48 mA m−2 even under low‐applied force (≈3.5 mN) at relative humidity 80%. The proposed TVNG provides a proof of concept for an all‐in‐one device consisting of a generator and capacitor because the LDH reveals a spontaneous charging performance similar to that of a capacitor. [ABSTRACT FROM AUTHOR]

PV(photovoltaic) systems have been deployed more in the recent years to support green energy generation. In the recent era, grid tied PV has been sparked by the emergence of the electricity market and offers an alternative solution to traditional fossil fuel-based electricity generation. A few of the potential impacts of solar PV on grid are false tripping of feeders, unwanted tripping, unnecessary islanding, and blind protection. In this research paper, different artificial intelligence techniques are tested in order to overcome the protection challenges. The PSCAD/EMTDC software package is used to analyze a section of the power system, and an algorithm has been constructed using Python v3.8 and MATLAB 2018. On an IEEE-9 BUS power system connected to a PV source, the Artificial Neural Network, Naive Bayes, Support Vector Machine, Random Forest, and Convolution Neural Network (CNN) algorithms are implemented to classify the faults. The suggested methods are proven effective for both in-zone and out-of-zone problems on power lines interconnected with solar park. The proposed techniques have been validated using total 16,320 internal and external fault cases with a wide range of system parameters alteration. In the proposed system, the effectiveness of several machine learning and deep learning techniques is compared. The obtained results demonstrate that CNN provides greater accuracy in the presence of a PV source, but at the same time, it is appropriate for a large number of data sets. The fault classification accuracy acquired is adequate and demonstrates the adaptability of the proposed approach. [ABSTRACT FROM AUTHOR]

Tidal stream turbines (TST) are a promising option for electricity generation to meet the ever-increasing demand for energy. The actuator disk (AD) method is often employed to represent a TST, to evaluate the TST operating in a tidal flow. While this method can effectively reduce the computational cost and provide accurate prediction of far-wake flow conditions, it falls short of fully characterising critical hydrodynamics elements. To address this limitation, a hybrid method is implemented by coupling AD with the blade element momentum (BEM) theory, using detailed performance data, such as thrust, to enhance the prediction of the wake effects. This work focuses on the development of a hybrid BEM–AD method using Reynolds-Averaged Navier–Stokes (RANS) turbulence models within computational fluid dynamics (CFD). Two variations and a hybrid modification of an AD model are presented in this paper. The first modified variation is a velocity variation that takes into account velocity profile inflow into the disk's configuration. The second modified variation is a radial variation that integrates the blade element theory into the disk's configuration. The hybrid modified model combines both the velocity profiles influenced and blade element theory in the design and analysis of the actuator disk. Several key investigations on some of the pre-solver parameters are also investigated in this research such as the effect of changing velocity and radial distance on the porosity and loss coefficient of the actuator disk performance. Importantly, this work provides an improved method to evaluate the key wake effects from a TST array which is crucial to determine the power performance of the TST array. [ABSTRACT FROM AUTHOR]

This paper presents a numerical algorithm for environmental/economic load dispatch (EELD) with emissions constraints, which takes into account the emissions trading system's effect on electricity generation cost and is implemented using a Python computer program. The developed program is applied to a power system of six (6) fossil-fueled electricity generating units with NOx, SO2 and CO2 constraints and proved to be significantly beneficial not only for the environment but also for the power company and the consumers. The proposed algorithm uses multi-objective optimization and incorporates both fuel and emissions allowances costs. The schedule of generating units is calculated and the testing of all possible weighting factor combinations with resolution of 0.01 is carried out showing that the proposed algorithm is fast, cost effective and environmentally friendly. [ABSTRACT FROM AUTHOR]

As an instrument supporting the realization of EU climate neutrality targets by 2050 and encouraging decarbonization outside its borders, the current proposed Carbon Border Adjustment Mechanism (CBAM) is facing opposition from some countries. Focusing on Brazil, this paper evaluates the impacts of the CBAM on the Brazilian economy through a comprehensive analysis of various scenarios based on the potential EU implementation of the CBAM and Brazil's climate scenarios. Results obtained in this research alleviate concerns of detrimental and competitiveness losses from Brazilian industries. Rather, the implementation of the EU CBAM improves the trade balance of Brazil's Energy-Intensive Industries (EII). The relatively low CO2 contents of Brazilian EII are elemental to this result, while contributions of carbon-free technologies in electricity generation are also critical factors in maximizing this trade surplus. Other consequential factors affecting these results are the contributions of CO2 removal from Brazil's forestry of land used, and homogeneity of CBAM-imposed products. [ABSTRACT FROM AUTHOR]

The electrical power distribution parts include the distribution transformer responsible for reducing high voltage (HV) 11 Kv to low voltage (LV) 416/240 volts, and the power distribution lines (PDLs), which are the source of electrical power supply for residential neighborhoods. Any malfunction of these parts, result in a power outage. Currently, any faults are reported, detected, and alert in a primitive way, and this mechanism certainly takes a lot of time and effort. In this paper, an automatic approach for detection, report and alert has been suggested. This approach process is carried out by continuously checking the status of the three output feeders (power distribution lines), which is the low voltage side of the distribution transformer, when a malfunction occurs in any one or more of these feeders, it will generate an alert signal in the form of a text message using short message service (SMS). The maintenance center is notified by receiving this SMS via SIM900 modem through the global system for mobile (GSM) communications network. The SMS text message includes feeder number, fault type and location address (street number and distribution transformer number). In this design, time and effort are shortened and the maintenance center enables fully automatic monitoring of electric power distribution parts within the sector of responsibility. [ABSTRACT FROM AUTHOR]

We need energy. But what are potential solutions to achieving net zero? This paper presents a Christian perspective and overview of nuclear energy in the UK, and other countries, within the context of government policies to achieve net-zero emissions while ensuring national security. The growth of renewables is well-known but nuclear energy’s positive contribution is often unrecognised in our energy mix for producing electricity. Nuclear provides clean, low-carbon baseload electricity and has its place alongside variable renewables in tackling climate change. Besides large reactors, small modular reactors (SMRs) are being considered within energy strategies. Beyond electricity generation, future nuclear plants offer cogeneration. Furthermore, nuclear plants do not create the air pollution associated with fossil-fuel emissions. This paper encourages people to become more informed about the place of nuclear energy by looking at an evidence-based approach and encourages discussion in an open, honest, and respectful way about its merits in protecting people and our planet. [ABSTRACT FROM AUTHOR]

Increased innovation on finding new ways to generate energy from different sources to meet the growing demand of consumers has led to various challenges in controlling the power network when it faces different disruptions. To address these challenges, a new approach has been proposed in this research paper, which combines a controller with a soft computing technique called Particle Swarm Optimization (PSO). The study considers a power system with four units, where three different energy sources are utilized and distributed across two areas. Each area has two power sources, with one area having a combination of thermal and gas power plants, and the other area consisting of a nuclear power plant and a gas power plant. Transmitting power from the nuclear power plant is particularly complex due to its high sensitivity to disturbances. Therefore, an intelligent and efficient controller is needed to ensure robust control in this type of power network that includes nuclear power. The paper also conducts a thorough analysis of the harmful emissions associated with electricity generation from the different power plants considered. The goal is to reduce the carbon footprint associated with power generation. The proposed work and analysis in the paper are implemented using the MATLAB/SIMULINK environment. [ABSTRACT FROM AUTHOR]

The daily production and life of human beings are inseparable from electricity. As the power supplier, electric power enterprises provide power demand for the majority of users. In the new era, electric power enterprises are also facing market-oriented reform. The focus of reform is electric power marketing. The formulation of electric power marketing strategy needs scientific decision-making analysis as guidance. With the increase of power demand, the scale of power grid is also expanding continuously. With the introduction of new energy equipment, the power system is becoming more and more complex, and it is difficult for relevant staff to effectively monitor and analyze the system. Combined with the above situation, this paper combined Bayesian network to build a power marketing decision analysis system, and combined Bayesian algorithm to test the power marketing real-time cost control system. The experimental results showed that the average judgment accuracy was 91.90 %, and the average warning time was 0.39 s. From the above data, it can be seen that this algorithm can play a good optimization effect on the performance of the system. In this paper, the elasticity test of the power system was also carried out from the aspect of wind speed, and the results showed that the maximum elasticity value can reach 0.94. It can be seen that the elasticity effect of the power system is good as a whole under different wind speeds. [ABSTRACT FROM AUTHOR]