Power Consumption Levels Research Articles

Synthesis, Properties, and Techno-economic Analysis of Highly Stable Biotransformer Oil Derived from Transesterification of Palm Oil Methyl Esters and Ditrimethylolpropane.

Currently, biotransformer oil (BTO) is in high demand due to the increasing level of electrical power consumption and environmental policy. Hence, this research aimed to prepare a highly stable BTO via basic transesterification of palm oil methyl ester (POME) and ditrimethylolpropane (Di-TMP) catalyzed by sodium methoxide (NaOCH3). Under the optimal conditions (POME/Di-TMP molar ratio = 5.0/1.0, NaOCH3 loading = 8 mol % based on the Di-TMP content under 3.5 mbar, and 300 rpm at 160 °C for 2 h), the POME conversion level and POME-Di-TMPTTE selectivity reached 90.3% and 96.6%, respectively. The obtained BTO with a high POME-Di-TMPTTE portion exhibited greater oxidation stability with a higher flash point and breakdown voltage in accordance with the IEC 62770 specification. A techno-economic analysis revealed the possibility of POME-Di-TMPTTE as a commercial BTO for its competitive cost and profit based on the current commercial price of BTO.

Experimental studies on the cooling and heating performance of a highly emissive coating

In this study, the cooling effect below ambient air temperature, heat dissipation properties and heating energy efficacy of a superomniphobic self-cleaning (SSC) highly emissive (HE) coating were systematically investigated. Except at midday, the SSC-HE coating with an extremely high solar reflectance of 0.985 showed a better cooling effect than a 10-cm-thick polyurethane insulation layer. The coating substantially reduced the interior air temperature of a well-insulated system by as much as 6.9 °C. The SSC-HE coating enabled the roof surface and room temperatures of the brick bungalow to be 3.4 and 10.2 °C below the ambient air temperature, respectively. Compared with the sunshade and spray water, the SSC-HE coating exhibited better cooling effect. The SSC topcoat allowed the battery cabinet of an HE-coated distributed telecommunication base station to remain its original sub-ambient cooling effect for a long time. Regardless of the location of the HE-coated metal facility, the ultrahigh emissivity of the coating enabled it to exhibit excellent heat dissipation performance during both day and night, even under adiabatic conditions. Additionally, under identical room temperature settings, the HE-coated electric oil heater not only showed faster heating but also had heating energy efficiency of 5.9 % and 4.4 % relative to heaters coated with aluminium- and black paints, respectively. Under identical heating power consumption levels, compared to black paint-coated heater, the HE-coated heater endowed the surrounding environment with a higher equilibrium air temperature, improving the thermal comfort of the indoor environment.

Energy-Efficient Algorithm for Data Path Selection in High-Density Wireless Sensor Networks

Relevance. Increasing the number of sensor devices per unit area consequently reduces the physical distance between the devices in the sensor network. Such networks are usually deployed over a large area and the sensor device that wants to transmit a data packet is located far away from the base station. In such a case, the source device is challenged to choose a transmission path that consumes the least amount of energy resources and satisfies the delivery time requirements. The objective of this study is to develop and validate the effectiveness of an empirical algorithm for selecting a transmission path that reduces the energy consumption of high-density wireless sensor networks. Methods of system analysis, analytical modeling, geometry and probability theories are used. Solution. It is assumed that the sensor network is deployed in a limited area and is a set of devices that are connected to each other informationally and energetically. When building data transmission routes, any sensor devices can be used as repeaters. At the same time, the increase in the number of repeaters leads to an increase in the time of data delivery. Novelty. It is assumed that the sensor network is deployed in a limited area and is a set of devices that are connected to each other informationally and energetically. Any sensor devices may be used as repeaters when constructing data transmission routes.Significance (theoretical). Dependences of power consumption level on various system parameters affecting the processes of functioning of high-density wireless sensor networks have been obtained. Significance (practical). The proposed empirical algorithm for selecting a rational data transmission route in a wireless sensor network allows us to determine, among all alternatives, the route to the coordinator that requires the least power. The effectiveness of the proposed empirical power-saving algorithm is confirmed by simulation modeling.

IoT based Smart Electricity Monitoring and Control Using ESP-Mesh Networking

The "IoT-Based Smart Electricity Monitoring and Control System Using ESP-MESH Networking" is a state-of- the-art project that aims to transform the way we manage and consume electricity in our homes. In today's world, our homes are equipped with a wide range of electrical appliances, each with varying levels of power consumption. Without an effective system to monitor and control these appliances, they can lead to excessive electricity usage. This not only results in high energy bills but also contributes to a significant carbon footprint, which is harmful to our environment. The Power consumption by the overall house can be monitored using this device and control the other electronic devices, able to monitor the power consumption in different rooms and able to monitor the current power by specific devices. User can check their Power usage from anywhere and at any time interval. The information can be monitored from mobile applications and also be monitored even on a web page. The Main can be turned on/off using a relay from anywhere. The Home application can also be controlled from anywhere through the mobile application. Keywords— ESP-MESH Networking, Power Consumption, Energy efficiency, Carbon footprint, Relay control, Energy management

Measurement of cryoelectronics heating using a local quantum dot thermometer in silicon

Silicon technology offers the enticing opportunity for monolithic integration of quantum and classical electronic circuits. However, the power consumption levels of classical electronics may compromise the local chip temperature and hence the fidelity of qubit operations. Here, we utilize a quantum-dot-based thermometer embedded in an industry-standard silicon field-effect transistor (FET), to assess the local temperature increase produced by an active FET placed in close proximity. We study the impact of both static and dynamic operation regimes. When the FET is operated statically, we find a power budget of 45 nW at 100 nm separation whereas at 216 μm the power budget raises to 150 μW. When operated dynamically, we observe negligible temperature increase for the switch frequencies tested up to 10 MHz. Our work describes a method to accurately map out the available power budget at a distance from a solid-state quantum processor and indicate under which conditions cryoelectronics circuits may allow the operation of hybrid quantum-classical systems.

Variational quantum circuit learning-enabled robust optimization for AI data center energy control and decarbonization

As the demand for artificial intelligence (AI) models and applications continues to grow, data centers that handle AI workloads are experiencing a rise in energy consumption and associated carbon footprint. This work proposes a variational quantum computing-based robust optimization (VQC-RO) framework for control and energy management in large-scale data centers to address the computational challenges and overcome limitations of conventional model-based and model-free strategies. The VQC-RO framework integrates variational quantum circuits (VQCs) with classical optimization to enable efficient and uncertainty-aware control of energy systems in AI data centers. Quantum algorithms executed on noisy intermediate-scale quantum (NISQ) devices are used for value function estimation trained with Q-learning, leading to the formulation of a robust optimization problem with uncertain coefficients. The quantum computing-based robust control strategy is designed to address uncertainties associated with weather conditions and renewable energy generation while optimizing energy consumption in AI data centers. This work also outlines the computational experiments conducted at various AI data center locations in the United States to analyze the reduction in power consumption and carbon emission levels associated with the proposed quantum computing-based robust control framework. This work contributes a novel approach to energy-efficient and sustainable data center operation, promising to reduce carbon emissions and energy consumption in large-scale data centers handling AI workloads by 9.8 % and 12.5 %, respectively.

Co-design based FPGA implementation of an efficient new speech hyperchaotic cryptosystem in the transform domain

In this paper a new encryption system has been designed and implemented for real-time speech transmission to reduce bandwidth requirements, increase security and minimize residual intelligibility. To guarantee robustness and lightweight computation, the developed cryptosystem has been carried out in the wavelet transform domain based on a hyperchaotic model to generate mask and permutation keys. The cryptographic system has been designed using a hardware-software (HW/SW) co-design approach by developing several IP-cores in a relatively short development time. The performances and security evaluation of the system have been validated through simulation results followed by an experimental validation through the implementation of an encrypted speech signal transmission between two low cost Nexys-4 DDR FPGA platforms, operating in real-time for both wired and wireless communications. Compared to similar works, high performances have been obtained in terms of bandwidth efficiency due to the use of DWT, limited area of FPGA resources, low power consumption and high security level with a large keyspace that is sufficient to resist against brute force attacks. The designed system can be a very useful solution for many real-time secure integrated voice communication systems, multiple communication purposes, military, professional or personal high level of conversations security.

Ultrafast-response H2S MEMS gas sensor based on double phase In2O3 monolayer particle film

The regulation of crystal structure plays a crucial role in gas sensing. In this work, by precisely controlling the annealing temperature, we first synthesized rhombohedral corundum-type In2O3 (h-In2O3), cubic bixbyite-type In2O3 (c-In2O3) and double phase In2O3 (c/h-In2O3). The c/h-In2O3 possesses the heterostructures of double phases, the abundant oxygen vacancies (61.1 %), and the more adsorbed oxygen (35.9 %). Subsequently, by self-assembly method, the sensors with one monolayer In2O3 particle film were successfully fabricated. The c/h-In2O3 sensor shows excellent H2S sensing performances with high response of 54.4 (50 ppm), extremely fast response time of 3.3 s and low limit of detection (LOD) of 20 ppb at 160 °C. The reasons for the ultrafast response of the sensor were unveiled through the comparison experiment of 4 layers particle film sensor and the theoretical analysis. Additionally, the outstanding sensing performance could be attributed to the abundant oxygen vacancies, the double phase heterojunction and the monolayer particle film. This work provides a new idea for designing micro-electro-mechanical system (MEMS) gas sensors with high sensitivity, extremely fast response, low power consumption and high level of integration.

A value-based framework from Building Stock Model to Retrofit Model

The study has as its original database the decarbonization process initiated in Mexico by the National Commission for the Efficient Use of Energy (CONUEE) as part of its “Savings Program of Electric Power in Buildings of the Federal Public Administration” (PAEIAPF) of 1999. The primary purpose of PAEIAPF was to reduce the levels of electric power consumption in Federal Government buildings. The program has operated for 20 years; however, its scope only reaches operational carbon. Since 90% of existing buildings will be in use by 2050, the Retrofit Models will be the base to determine solutions for a more resilient living environment that fortifies and extends the grid’s capacity and meets climate change mitigation targets. Secondly, significant socioeconomic and profound environmental impacts are not calculated explicitly in existing tools and are often referred to as “secondary” or Non-Energy Benefits (NEB). “The goal is to give them a measurement value to be considered in the decision-making calculus. It is assumed that soon; such factors will enter the general climate change economy, not unlike carbon in the past decade.” In this context, the proposed research aims to develop a value-based framework that will support a Building Stock Model and subsequent Retrofit Models, documented in a web-tool platform. The framework has three main steps:A) Building Stock Model: Mapping of selected buildings of the program PAEIAPF in a GIS system. Documentation of the baseline energy consumption and embodied CO2-eq of the existing building.B) Retrofit Models: Involving a Whole Life Cycle Assessment (WLCA) and Non-Energy Benefits (resilience coefficient, health, productivity).C) Web Tool Platform: Application and toolset that allows for consistent documentation, environmental impact evaluation of existing building stock, and solution design in identifying energy reduction concepts.

FUZZY CONTROL OF POWER CONSUMPTION OF ELECTROMECHANICAL EQUIPMENT OF THE MAIN DRAINAGE COMPLEX AT IRON ORE MINE

The paper presents a fuzzy control system for the consumption of electric power by pumps of the main drainage complex of a mine based on the Mamdani fuzzy inference algorithm. The proposed system has a structure with two inputs, such as water inflow and electricity cost, and one output, the power of pumping units. The choice of the Mamdani method for building a fuzzy system is due to the fact that all these inputs and outputs are subject to preliminary expert evaluation. All quantities are fuzzificated by smooth membership functions - Gaussian and sigmoid. The input values of the system are represented by linguistic variables, each of which includes five fuzzy sets that define the membership in the very low, low, medium, high, and very high levels of the corresponding input value. The output of the system contains ten fuzzy sets. During the fuzzification, it was assumed that in order to avoid overloading the pump motors, only one option is considered: their operation at maximum power when there is a very high level of mine water inflow during heavy rains or for other reasons. In all other cases, the operation of at least one of the pumps with the highest permissible power is excluded. A base of 25 fuzzy rules was formed. When defining the rules, it is assumed that in all cases when there is a high water inflow into the mine, all three pumps must be put into operation, regardless of the electricity cost in force in the current period of time. This set of rules is of the highest importance due to the need to prevent flooding of the mine. For other values of water inflow, the output power consumption of drainage pumping units depends on the current cost. This set of rules has a lower priority. We simulated the operation of the dewatering pumping system with and without a fuzzy power consumption control system. The test signal for the "water inflow" input was represented as a random variable with a normal distribution. The test signal for the "electricity cost" input was formed on the basis of real data on the price determined by the operator for the day ahead market for 12/24/2023. It was found that the use of a fuzzy system can reduce the cost of purchasing electricity by 1.24% per day. It should also be noted that the economic effect is achieved not by reducing the level of power consumption, but by rationalizing the operation of the drainage complex, which ensures maximum groundwater drainage performance when the cost of electricity is high, and minimum when it is low.

Airfoil friction drag reduction based on grid-type and super-dense array plasma actuators

To improve the cruise flight performance of aircraft, two new configurations of plasma actuators (grid-type and super-dense array) were investigated to reduce the turbulent skin friction drag of a low-speed airfoil. The induced jet characteristics of the two actuators in quiescent air were diagnosed with high-speed particle image velocimetry (PIV), and their drag reduction efficiencies were examined under different operating conditions in a wind tunnel. The results showed that the grid-type plasma actuator was capable of producing a wall-normal jet array (peak magnitude: 1.07 m/s) similar to that generated in a micro-blowing technique, while the super-dense array plasma actuator created a wavy wall-parallel jet (magnitude: 0.94 m/s) due to the discrete spanwise electrostatic forces. Under a comparable electrical power consumption level, the super-dense array plasma actuator array significantly outperformed the grid-type configuration, reducing the total airfoil friction drag by approximately 22% at a free-stream velocity of 20 m/s. The magnitude of drag reduction was proportional to the dimensionless jet velocity ratio (r), and a threshold r = 0.014 existed under which little impact on airfoil drag could be discerned.

A Hybrid Chaotic Encryption ASIC With Dynamic Precision for Internet of Things

With the rapid development of the Internet of Things (IoT), device and data security has attracted huge academic attention in recent years since conventional security methods are barely feasible in IoT circumstances. Traditional encryption methods require extensive computation complexity, which requires several hardware resources and power consumption. Meanwhile, due to the low power requirement, most IoT devices are lightweight with limited computing and storage capabilities. The dilemma leads to the need for a lightweight encryption method with decent data protection strength. Chaotic encryption can be applied in the IoT because of the characteristics of determinacy and strong randomness. However, its safety and hardware overhead are positively correlated with implementation precision. Therefore, this paper performs a quantitative analysis of the system under different precision conditions. Then, a hybrid chaotic encryption scheme with dynamic precision is proposed, which balances power consumption and security protection level. Finally, the proposed design is implemented by Verilog and synthesized using SMIC 65nm CMOS technology. The evaluation results proved that the proposed ASIC provides decent encryption strength under diverse precision, effectively overcoming the influence of limited precision with low hardware resources and power consumption.

Hardware and software for automated examination of defects of hard tissues of teeth after endodontic intervention for fatigue and destruction

The work developed circuit engineering, design and software of the loading machine for automated examination of dental hard tissue defects after endodontics intervention for fatigue and destruction. The advantage of this development is the combination as cyclic loading methods simulating chewing movements and force effects on compression in a compact small-sized case, with low power consumption and small noise level. Thanks to the use of a screw transmission and a stepper motor in combination with a sensitive tensoresistive force sensor, it was possible to achieve high accuracy and resolution of 0.1 microns.
 A series of tests was conducted on real samples of endodontically treated teeth restored using fiberglass pins and cast metal stump inserts. It is shown that methods of restoring incisors and premolars of the upper jaw with the help of fiberglass pins have an advantage when the residual structure of the tooth is lacking due to a more uniform distribution of deformation stresses, since their elastic modulus is close to the elastic modulus of dentin.

Influence of the Electrical Characteristics of Pulsed Microwave Magnetron Power Supply on the Conditions for Plasma Formation in the Vacuum Chamber of Resonator-Type Plasmatron

The paper presents the research results of the influence of the electrical characteristics of a pulsed microwave magnetron power supply on the microwave discharge generation conditions, determined by the operating mode of the generating system as a whole. Plasma was formed in a vacuumized reaction-discharge volume located inside a rectangular resonator chamber. Depending on the operating modes of the microwave magnetron power supply, studies have been conducted for three modes of microwave discharge plasma generation: pulsed mode with a duty factor S ≈ 2; pulsed mode with a duty factor S ≈ 1.15; continuous mode. Probe measurements of the microwave power in the microwave discharge plasma volume and its local conductivity have been carried out. The paper presents the dependence of the power of microwave energy in the central area of the reaction-discharge quartz chamber of a microwave plasmotron on the amount of power consumed by the microwave magnetron, as well as the distribution of the electrical component of the microwave discharge plasma along the length and cross-sectional plane of the working volume. It has been established that for all studied modes of operation of the power source, with an increase in the power consumption of the microwave generator system, an increase in the microwave power recorded in the central region of the plasma discharge is characteristic. The continuous generation mode is characterized by a decrease in the uneven distribution of electromagnetic energy along the axis of the discharge chamber. It is shown that the transition from a pulsed to a continuous mode of microwave plasma discharge generation at the same level of power consumption by the generating system is characterized by a decrease in the value of the registered microwave power in the microwave discharge plasma volume and an increase in its local conductivity in particular areas of the reaction-discharge volume.

Design of small volume and low power consumption logic gates based on 4-terminal multilevel magnetic cell

Spintronics is an emerging technology for designing logic circuits. The non-volatile logic based on the magnetic tunnel junction (MTJ) cell is a suitable solution to overcome the leakage power problem, which has become a major obstacle for CMOS technology. Here, we introduce a new style of magnetic gate (mGate) logic, which is built by a four-terminal cell. This cell operated by motion of domain wall that is based on spin transfer torque (STT) in a multi-level cell (MLC) structure. To reduce the complexity, a static circuit with a resistive load in ratioed logic style has been used. The use of MLC Gate logic in the static ratioed logic circuit is a suitable solution to reduce the complexity level of structure and power consumption in logic circuits in the field of spintronics. The performance of different magnetic logic gates have been investigated by simulations. The simulation results show that the MLC Gates offer a smaller area and lower power consumption and lower energy in comparison with the previous mGate and magnetic computing in memory.

Equipment- and Time-Constrained Data Acquisition Protocol for Non-Intrusive Appliance Load Monitoring

Energy behaviours will play a key role in decarbonising the building sector but require the provision of tailored insights to assist occupants to reduce their energy use. Energy disaggregation has been proposed to provide such information on the appliance level without needing a smart meter plugged in to each load. However, the use of public datasets with pre-collected data employed for energy disaggregation is associated with limitations regarding its compatibility with random households, while gathering data on the ground still requires extensive, and hitherto under-deployed, equipment and time commitments. Going beyond these two approaches, here, we propose a novel data acquisition protocol based on multiplexing appliances’ signals to create an artificial database for energy disaggregation implementations tailored to each household and dedicated to performing under conditions of time and equipment constraints, requiring that only one smart meter be used and for less than a day. In a case study of a Greek household, we train and compare four common algorithms based on the data gathered through this protocol and perform two tests: an out-of-sample test in the artificially multiplexed signal, and an external test to predict the household’s appliances’ operation based on the time series of a real total consumption signal. We find accurate monitoring of the operation and the power consumption level of high-power appliances, while in low-power appliances the operation is still found to be followed accurately but is also associated with some incorrect triggers. These insights attest to the efficacy of the protocol and its ability to produce meaningful tips for changing energy behaviours even under constraints, while in said conditions, we also find that long short-term memory neural networks consistently outperform all other algorithms, with decision trees closely following.

A novel approach for minimising anti-aliasing effects in EEG data acquisition.

Electroencephalography (EEG) waves and other biological signals can be deciphered with a deeper understanding of the human body. The benefits of EEG are growing. EEG studies have expanded globally. Research on EEG covers data gathering, analysis, energy renewal, and more. EEG-gathering devices include encoding, digital transfer, head sensor placement, and separate amplifiers. The EEG detects periodic noise. Head movement, sensor lines, and hair sweat produce low-frequency noise. Low-frequency noise alters EEG signals over time. Muscle actions and electromagnetic waves create high-frequency noise (especially in the facial and neck muscles). EEG shifts are saw-toothed by high-frequency noise. High- and low-frequency noises are usually lower and higher than human EEG, respectively. Lowering signal power above and below the testing level without altering the signs of interest lowers noise. Aliasing may affect low-frequency impacts in the original data because high-frequency noise is mirrored in the data. This work designed a non-binary Complementary metal oxide semiconductor (CMOS) Consecutive guesstimate register (CGR) reconfigurable analogue-to-digital converter (ADC) integrated with the instrumental amplifier. CGR ADC model comprises the bio-signal device monitoring for the EEG signals. This study focused on acquiring the EEG signals for amplification. The model uses the AC-coupled chopper stabilisation model with 1 A low power with a noise level of 1 A. The neural amplifier uses an optimised current technique to maximise the transconductance for a good noise efficiency factor. The simulation analysis estimates a bandwidth range of 0.05-120 Hz with a power consumption level of 0.271 µW. The computed noise level is observed as 1.1 µVrms and a gain of 45 dB. The comparative analysis of the proposed ADC model achieves the minimal energy consumption value of ∼12%, which is minimal than the nonlinear and switch-end capacitor. Also, the time consumed is ∼9% less than the nonlinear and switch-end Capacitor.18 nm CMOS technology is used to implement the proposed data acquisition system for low-power and density-optimised applications.

Study on accurate regulation of power consumption in self-supporting time of off-grid system in Haikou

In practical engineering, Off-grid PV systems have failed to meet user requirements due to the absence of precise local weather parameters and unverified battery charging times. In this study, off-grid solar street lights in a village in Haikou were taken as an example. A three-year monitoring period was conducted using a local PV station. It was observed that in this area, the lowest solar radiation is typically recorded from December to January. Over three years, there were four instances of continuous overcast and rainy weather, with the longest period lasting up to 9 days. During these 9 days, the daily average power generation per kilowatt of PV module fluctuated between 0.46 and 0.92 kW. Based on this data, a theoretical formula for the optimal daily power consumption was derived, and it was determined that 180W and 240W were the optimal power consumption levels for continuous overcast and rainy weather. The charging time for the batteries was verified to be 4 days. Finally, practical validation was conducted using the village's solar street lights, confirming that the optimal power consumption during continuous overcast and rainy days was 180W, and during continuous overcast days, it was 230W. These research findings hold significant importance. Highlights Through theory and demonstration, it is concluded that: Based on years of meteorological monitoring, it has been determined that the maximum self-sufficient duration for the off-grid power station system in the Haikou area is 9 days. Under the condition of satisfying SST, the formula of optimal daily power consumption of off-grid PV system load and optimal days of battery full charge is derived through theoretical analysis. The actual engineering demonstration shows that the optimal daily consumption power of the street light off-grid system is about 180W when the load is in continuous rainy days. Under continuous overcast conditions, the optimal daily consumption power of the load is about 240 W. The best time for a fully charged battery is four days.

Technical, Qualitative and Energy Analysis of Wireless Control Modules for Distributed Smart Home Systems

Distributed smart home systems using wireless communication are increasingly installed and operated in households. Their popularity is due to the ease of installation and configuration. This paper presents a comprehensive technical, quality, and energy analysis of several popular smart home modules. Specifically, it focuses on verifying their power consumption levels, both in standby and active mode, to assess their impact on the energy efficiency of building installations. This is an important aspect in the context of their continuous operation, as well as in relation to the relatively lower power of loads popular in buildings, such as LED lighting. The author presents the results of measurements carried out for seven different smart home modules controlling seven different types of loads. The analysis of the results shows a significant share of home automation modules in the energy balance; in particular, the appearance of reactive power consumption due to the installation of smart home modules is noteworthy. Bearing in mind all the threads of the analysis and discussion of the results of measurement experiments, a short SWOT analysis is presented, with an indication of important issues in the context of further development of smart systems and the Internet of Things with wireless communication interfaces, dedicated to home and building applications.

Research on Two-Stage Regulation Method for Source–Load Flexibility Transformation in Power Systems

Under the premise of continuously increasing the grid-connected capacity of new energy, the fluctuation and anti-peak shaving characteristics of wind power have always constrained the development of green power systems. Considering the characteristics of power system flexibility resources, this paper introduces a two-stage regulation approach for power systems with enhanced source–load flexibility. In the day-ahead stage, an advanced peak regulation transformation is employed, leveraging the combined heat storage device of conventional thermal power units to enhance their peak regulation capability. Additionally, the Energy Intensive Load (EIL) is integrated into the regulation system. A two-level coordinated optimization model is developed, incorporating wind power integration and dispatching power allocation, with the aim of optimizing wind power integration and achieving the optimal allocation of dispatching power. In the intra-day stage, the connection of wind plants and energy storage devices is utilized to minimize the wind power fluctuations and improve the control ability over wind power variations. Compared with traditional methods, the wind power consumption in Scenario 1 and Scenario 2 increases by 2741.1 MW/h and 2478.5 MW/h respectively. Furthermore, the inclusion of an energy storage device in the intra-day stage significantly reduces the wind power fluctuations, maintaining a stable fluctuation rate within ±1%. Therefore, this method can effectively improve the level of wind power consumption and reduce the impact of real-time fluctuations on the power system.