Problem Of Energy Consumption Research Articles

Can the Clean Heating Policy reduce carbon emissions? Evidence from northern China.

The Clean Heating Policy aims to solve the problems of excessive energy consumption and severe air pollution caused by central heating in northern China. Whether this policy can effectively reduce carbon emissions remains unexplored. Using panel data representing 65 cities in northern China from 2010 to 2019, this paper constructs a dynamic spatial DID model to empirically study the carbon reduction effect of the Clean Heating Policy and its influence channels. The results are summarized as follows. First, the Clean Heating Policy can significantly reduce carbon emissions, and this conclusion holds after multiple robustness tests. The policy has a lag effect, but its spatial spillover effect and long-term effect are not significant. Second, the carbon reduction effect of the Clean Heating Policy is mainly achieved by optimizing the energy structure and improving the thermal efficiency of heat consumer terminals. Third, the carbon reduction effect varies by city and emission field. It is significant only in low-subsidy cities, high-carbon cities, and household fields. Fourth, there is a synergistic reduction relationship between the Clean Heating Policy and the low-carbon city policy. Based on the results of this paper, we propose policy implications, such as promoting policies in multiple ways and improving subsidy efficiency, and provide a reference for other countries.

Auxiliary graph-based energy-efficient routing resource allocation algorithm in space division multiplexing elastic optical networks

Space division multiplexing elastic optical networks (SDM-EONs) are considered as a efficient solution for increasing the link’s capacity. However, the SDM-EONs brought challenges to be explored, notably the routing, core and spectrum assignment (RCSA) problem. For the real network, another important issue should be considered is the problem of energy consumption. The auxiliary graph (AG) can abstract node devices into elements in it and support various routing policies for different purposes by adjusting the weights of AG edges. Therefore, this paper proposes an auxiliary graph-based energy efficient routing resource allocation algorithm (AG-EERRA) to jointly optimize the energy consumption and RCSA. Each node of the auxiliary graph is abstracted from the devices of physical node. The intra edge weights of nodes set the function associated with the energy consumption model. The inter edge weights of node are composed link length, free frequency slots, modulation efficiency and the value of core crosstalk innovatively. Meanwhile, the impact of inter-core crosstalk on request is reduced by crosstalk avoidance strategy and crosstalk aware strategy. In the proposed auxiliary graph, the shortest weight path is selected to transmit requests that can reduce network energy consumption and blocking probability. Under the high-load network, request splitting is performed for the requests that cannot successfully find a route to improve energy efficiency. Simulation results show that the proposed algorithm can improve the network energy efficiency while reducing request blocking probability compared to comparison algorithms.

Grid-Connected Microbial Fuel Cell Modeling and Control in Distributed Generation

Water shortages and water pollution have seriously threatened the sustainable development of the community. The grid-connected microbial fuel cell is an effective way to control the cost of wastewater treatment plants. Moreover, it solves the problem of low efficiency and high energy consumption. In view of the characteristics of strong coupling, non-linearity, and internal load in the process of microbial fuel cell grid connection, it is necessary to design the grid-connected unit of power electronic device. Based on the establishment of the microbial fuel cell stack model, the stability control and the constant power control scheme were designed for the chopper and inverter, respectively. The simulation results showed that the control strategy with the combination of voltage stabilizer and constant power can make a grid-connected system of all phase voltage and frequency output. The three-phase voltage Uabc was steady at 7 h and the voltage amplitude was controlled at roughly 380 V, according to the output voltage waveform. The value was 50 Hz, which satisfies the criteria for grid connection.

MOF-derived LDH modified flame-retardant polyurethane sponge for high-performance oil-water separation: Interface engineering design based on bioinspiration.

Frequent petrochemical spill accidents and secondary fire hazards have threatened the ecological environment and environmental safety. The traditional purification technology has the problems of high energy consumption and secondary pollution, which also brings new challenges to spill disposal. Herein, we demonstrate a biomimetic structure-based flame-retardant polyurethane (PU) sponge (FPUF@MOF-LDH@HDTMS) for continuous oil-water separation. Inspired by desert beetle and lotus leaf, the biomimetic micro-nano composite structure was constructed by in-situ growth of metal-organic framework-derived layered double hydroxide (MOF-LDH) on the surface of the PU sponge. After grafting MOF-LDH with hexadecyltrimethoxysilane, FPUF@MOF-LDH@HDTMS showed excellent superhydrophobic/superoleophilic performance (water contact angle=153° and oil contact angle=0°). FPUF@MOF-LDH@HDTMS can easily and quickly adsorb oily liquids suspended/settled in the water thanks to the unique bionic structure. FPUF@MOF-LDH@HDTMS has excellent oil/organic solvents absorption capacity; even after 20 cycles of use still maintains high adsorption capacity. More importantly, the continuous oil-water separation through FPUF@MOF-LDH@HTMS has achieved a separation efficiency of up to 99.1%. In addition, the bionic superhydrophobic sponge has excellent flame retardancy, which reduces the possibility of secondary fire caused by PU sponges. Thus, the biomimetic micro-nano composite structure provides a new design strategy for the more high-performance oil-water separation sponges.

Research on Underwater Wireless Acoustic Communication Routing Protocol

Due to the limitation of the communication range of sensor nodes, underwater nodes must transmit data to the water surface through routing mechanism. Therefore, the design of routing algorithm is related to the performance of the network, and the research of routing algorithm is necessary. However, underwater nodes are vulnerable to ocean turbulence and biological factors. The underwater environment is dynamic and complex, which greatly affects the acoustic channel, making the improvement of routing protocol a challenge. These factors lead to problems in underwater acoustic communication network, such as empty nodes, packet delivery rate, energy consumption, delay and other problems, and in the dynamic and complex seawater environment, the performance of acoustic network will be further reduced. This paper introduces some main routing algorithms, such as hollow node awareness algorithm, layer-based routing protocol; Opportunistic routing algorithm; Double-hop routing protocol, etc. These routing algorithms can solve some problems. Simulation shows that they have certain advantages in packet delivery rate, delay, network lifetime, etc.

Future Vehicle Trend: A Comparative Study of the Fuel Vehicle, Electrical Vehicle, and Hybrid Vehicles

As the second largest carbon emission industry in the world, the automobile industry faces serious energy consumption and environmental pollution problems. The development of a low-carbon economy requires cars to achieve low energy consumption, lower emissions require the development of more advanced and environmentally friendly technologies. Three dominant kinds of vehicles, fuel vehicles, electrical vehicles, and hybrid vehicles will be explored in this paper. Section one introduces the types of fuel vehicles, the factors that affect them, and their negative impact on the environment. Section two focuses on the advantages of hybrid vehicles over gasoline and pure electric vehicles in terms of their operation and driving costs. Section two discusses the advantages of hybrid vehicles compared to gasoline and electric vehicles in terms of their operation and driving costs. In section three, the characteristics of various types of electric vehicles are comprehensively evaluated, and the prospects of the exhibition of electric vehicles are discussed. Finally, the future development trend of electric vehicles is forecasted.

Thermodynamic and Economic Analysis of an Ammonia Synthesis Process Integrating Liquified Natural Gas Cold Energy with Carbon Capture and Storage

Ammonia, as a bulk chemical, is widely used in fertilizers and fuels and is also a promising hydrogen carrier. Aiming at reducing the high energy consumption of the ammonia synthesis process, this study innovatively proposed a low-carbon ammonia synthesis process based on the cold energy utilization of liquified natural gas regasification. In this process, the cold energy released from the regasification of liquified natural gas was used as the refrigeration source of the air separation unit and carbon capture and storage unit, which improves the comprehensive energy utilization efficiency of the whole process of synthetic ammonia. Based on Aspen Plus simulations, the process economy and exergy were comprehensively analyzed. The total efficiency of the low-carbon ammonia synthesis process was 42.69%, of which the ammonia production capacity was 35.07 t/h, and the total capital investment of the integrated process was 3.4 × 107 USD, and the product cost was 387.86 USD. Compared with three different ammonia plants, the levelized cost of ammonia in the low-carbon ammonia synthesis process was reduced to 324.03 USD/ton. The proposed process can well solve the problems of high energy consumption in the ammonia synthesis process and provide a valuable production route for the low-carbon ammonia synthesis process.

High Voltage Electric Pulse Drilling: A Study of Variables through Simulation and Experimental Tests

With the deepening of drilling depth, the difficulty of drilling engineering increases gradually due to the complex geological conditions. The traditional mechanical drilling method shows the problems of high energy consumption, low efficiency, long cycle and high cost. Because of the characteristics of rock, the high abrasiveness of rock causes great wear to the bit, which becomes an important factor affecting the drilling rate. High voltage electric pulse (Abbreviated as HVEP later in this paper) drilling technology is a new technology developed in the past several decades. The technology uses plasma channel, water jet or shock wave generated by high voltage electric pulse discharge to break rock. It has the characteristics of environmental protection, directional breaking, easy control of rock breaking process and fast speed in the face of complex hard rock. In this paper, the mechanism and technology of rock breaking by high voltage electric pulse method in deep drilling are studied, and the functional test is carried out.

Reuse of Buffing Dust-Laden Tanning Waste Hybridized with Poly- Styrene for Fabrication of Thermal Insulation Materials

Air pollution, resulting from buffing dust waste produced by local leather tanning industry, has become a critical issue for the environment and public health. To promote a circular economy through resource recovery, this work developed a thermal insulation composite using buffing dust-laden tanning waste mixed with polystyrene and a blowing agent. To prepare the samples from leather tanning waste, different proportions of buffing dust (5–20% (w/w)) were blended with polystyrene in the presence of 3% (w/w) blowing agent. The composite material was processed in double-barreled with co-twin extruder to expose it to pressure and then heated at 200 °C. Different physico-chemical properties of composite samples were determined. The prepared composite materials had a good thermal conductivity (0.033–0.029 W/m-K), strong compression (5.21–6.25 ton), density (38–20 kg/m3), and water absorption (5–7.5%), as compared to conventional constructional insulation panels. The thermal conductivity of polystyrene was reduced to 10% after the addition of buffing dust (20% w/w). The presence of a blowing agent in the composite material enhanced its volume without compromising its physico-chemical properties. Thermo-gravimetric analysis showed that the thermal stability of the composite material ranged from 200–412 °C. FTIR analysis indicated that the composite had carbonyl and amino functional groups. The SEM images revealed the formation of voids with a decreasing homogeneity of the composite after the addition of the buffing dust waste. The EDX analysis revealed that the composite also had 62% of C and a tiny amount of Cr. This implies that the composite panels can be used for installation in buildings as thermal insulators in the construction sector. Overall, this work not only resolved the energy consumption problems during manufacturing, but it also brought positive impacts on the environment by recycling hazardous buffing dust and then reusing it as a thermal insulation material. Not only does this reduce the air pollution that results from the buffing dust waste, but this also promotes resource recovery in the framework of a circular economy.

Structure-activity relationship and experimental study of organic solvents and deep eutectic solvents in separation of cyclohexane-ethyl acetate

Selecting the appropriate extractant is of great significance for solving the problems of high energy consumption and difficult separation in the extractive distillation process. In this study, four deep eutectic solvents (DESs) were designed by combining menthol hydrogen bond acceptors with lauric acid and capric acid hydrogen bond donors and tetrabutylammonium bromide hydrogen bond acceptors with levulinic acid and ethylene glycol hydrogen bond donors. The interaction mechanism and structure–activity relationship between azeotropic system, hydrogen bond donor, hydrogen bond acceptor and deep eutectic solvent were studied. σ-profile, interaction energy, reduced density gradient, electrostatic potential, and natural bond orbital were used to study the microscopic mechanism and structure–activity relationship of azeotropes separated by DESs. On this basis, the vapor–liquid equilibrium experiments of separating ethyl acetate-cyclohexane azeotrope by DESs were carried out. The results showed that separating ethyl acetate-cyclohexane by using DESs is feasible and that the DES synthesized by using levulinic acid and tetrabutylammonium bromide is preferable for separation. Studying the relationship between DES structures and the azeotrope provides a theoretical basis for the screening and design of DES extractants for the separation of alkane-ester azeotropes using extractive distillation.

Event-Based Optical Flow Estimation with Spatio-Temporal Backpropagation Trained Spiking Neural Network.

The advantages of an event camera, such as low power consumption, large dynamic range, and low data redundancy, enable it to shine in extreme environments where traditional image sensors are not competent, especially in high-speed moving target capture and extreme lighting conditions. Optical flow reflects the target's movement information, and the target's detailed movement can be obtained using the event camera's optical flow information. However, the existing neural network methods for optical flow prediction of event cameras has the problems of extensive computation and high energy consumption in hardware implementation. The spike neural network has spatiotemporal coding characteristics, so it can be compatible with the spatiotemporal data of an event camera. Moreover, the sparse coding characteristic of the spike neural network makes it run with ultra-low power consumption on neuromorphic hardware. However, because of the algorithmic and training complexity, the spike neural network has not been applied in the prediction of the optical flow for the event camera. For this case, this paper proposes an end-to-end spike neural network to predict the optical flow of the discrete spatiotemporal data stream for the event camera. The network is trained with the spatio-temporal backpropagation method in a self-supervised way, which fully combines the spatiotemporal characteristics of the event camera while improving the network performance. Compared with the existing methods on the public dataset, the experimental results show that the method proposed in this paper is equivalent to the best existing methods in terms of optical flow prediction accuracy, and it can save 99% more power consumption than the existing algorithm, which is greatly beneficial to the hardware implementation of the event camera optical flow prediction., laying the groundwork for future low-power hardware implementation of optical flow prediction for event cameras.

CL‐HPWSR: Cross‐layer‐based energy efficient cluster head selection using hybrid particle swarm wild horse optimizer and stable routing in IoT‐enabled smart farming applications

AbstractIn the recent days, the Internet of Things (IoT) has assumed a significant role in automized farming applications. The farmers can receive frequent information corresponding to the soil moisture, water used, humidity, temperature, moisture, etc., by utilizing actuators and sensor nodes. Various clustering techniques used in wireless sensor network (WSN) applications have achieved energy‐efficient results. However, IoT‐enabled smart farming (SF) applications require scalable networks and long‐distance communication. The existing clustering techniques cannot provide SF solutions, and work related to communication overhead, end‐to‐end delay, latency etc., has not been taken up exhaustively. Therefore, in this article, a cross‐layer‐based hybrid particle Swarm wild horse optimizer (PSWHO) and stable routing technique (CL‐HPWSR) is designed to minimize energy consumption, communication delay, latency etc. in SF applications. Initially, the network is designed to be Bi‐concentric Hexagons. The cross‐layer‐based optimal cluster head (CH) selection mechanism is designed using the hybrid optimization algorithm‐named PSWHO to mitigate excess energy consumption problems in WSN. While clustering, cross‐layer parameters from different layers such as physical, medium access control, and network are used to compute the probability of each sensor node. Moreover, the deep learning‐based routing algorithm extended deep golden eagle neural network (EDGENN) is introduced to explore the optimal route for transmitting the data. The performance of CL‐HPWSR is implemented in Matlab by focusing energy‐efficiency, computational‐efficiency and QoS‐efficiency factors. Finally, in comparison with state‐of‐the‐art‐based SF approaches such as CL‐IoT, FEEC‐IIR, BiHCLR, PSO‐ECHS, and PSO‐C, the CL‐HPWSR has performed better in terms of energy‐efficiency, QoS‐efficiency and computational‐efficiency.

Deep Non-Orthogonal Multiple Access Network Assisted by Intelligent Reflecting Surface

The intelligent reflecting surface (IRS) assisted non-orthogonal multiple access (NOMA) symbiotic communication technology is expected to enhance the access performance, energy efficiency and spectrum efficiency of the communication network, and is regarded as an important candidate technology to support the evolution of the sixth-generation (6G) towards large-scale, high-capacity and sustainable development. However, the relevant research of this technology is still at the initial stage, and many key challenges have not been fully studied. Therefore, it is urgent to open up relevant research ideas and methods to promote its development and early implementation, so as to make it an effective 6G technology. In view of this, this paper intends to carry out the research on the theory and method of IRS assisted NOMA symbiotic transmission, starting from the analysis of the active and passive symbiotic mechanism of NOMA transmission protocol. Based on this, we further study the efficient symbiotic modulation transmission technology and multi-dimensional resource optimization allocation method. The research content of this paper is to explore the transmission theory and technology of high energy efficiency and high frequency spectrum efficiency for 6G, and break through the bottleneck problem of spectrum and energy consumption encountered by wireless communication, which has important practical significance for the wireless communication.

Development and application of graphene silk solar panel concept in smart bus stop design

With the continuous growth of the population, with the expansion of the urban area. Human activities and behavior are depleting limited resources, a large number of these private vehicles occupy our roads, it also causes various environmental problems. With the increasing awareness of environmental protection, the way of green travel has gradually become the way of travel advocated by people who living in the metropolis. Convenience and environmental protection are a major advantage of public transport, but unfortunately, the functions, services and environment of many bus stops are not convenient and friendly; Therefore, the smart bus stop was born, it can not only provide real-time bus information, but also provide a safe and comfortable waiting space. However, with the upgrading of service functions, the problem of energy consumption has become increasingly prominent. Powering through solar panels can naturally provide a sustainable energy source for smart bus stops, but many studies have found that solar panels themselves are not environmentally friendly, regardless of their materials and recyclability. The author’s investigation found that relevant studies have confirmed that spraying an aqueous solution containing carbon nanotubes or graphene on mulberry leaves for feeding silkworms doubles the toughness of the silk spit, and the conductivity of carbonized silk is 10 times higher. In addition, the robotic fiber spinning technology will allow silkworms to independently complete the production of silk objects without killing the silkworms. Through the research on graphene silk materials and robotic fiber spinning technology, this paper proposes a biologically autonomous solution to the production of graphene silk thin-film solar panels, so as to seek to solve the pollution problem of solar panels in the smart stop.

Simulation Analysis and Experiments for Blade-Soil-Straw Interaction under Deep Ploughing Based on the Discrete Element Method

The desirable sowing period for winter wheat is very short in the rice-wheat rotation areas. There are also lots of straw left in harvested land. Deep rotary tillage can cover rice straw under the surface to increase soil organic matter. Clarifying the effect of the rotary tillage blade on the soil and straw, as well as analyzing the movement patterns and forces on the straw and soil, are essential to investigate the deep rotary tillage process in order to solve the problems of energy consumption and poor straw burial effect of deep tillage and deep burial machinery. In this study, we built the interaction model of rotary blade-soil-straw through the discrete element method to conduct simulation and identified the factors that affect the power consumption and operation quality of the rotary blade. The simulation process reflects the law of rotary blade-soil-straw interaction, and the accuracy of the simulation model has been verified by field trials. The simulation test results show that the optimized structural parameters of the rotary tillage blade were 210 mm, 45 mm, 37° and 115° (R, H, α and β) designed based on this theoretical model can cultivate to a depth of 200 mm. The operating parameters were 8π rad/s for rotational speed and 0. 56 m/s for forward speed, respectively; the simulated and field comparison tests were conducted under the optimal combination of parameters, and the power, soil breaking rate, and straw burial rate were 1.73 kW, 71.34%, and 18.89%, respectively; the numerical error rates of simulated and field test values were 6.36%, 5.42%, and 8.89%, respectively. The accuracy of the secondary model was verified. The simulation model had good accuracy at all factor levels. The model constructed in this study can provide a theoretical basis and technical reference for the interaction mechanism between rotary tillage and soil straw, the optimization of machine geometry, and the selection of operating parameters.

Hydrothermal synthesis of a novel expanded vermiculite/xonotlite composite for thermal insulation

Natural disasters caused by global warming are threatening the survival of mankind. Reducing carbon emissions is an effective way to prevent global warming. In recent years, the construction industry is playing a dominant role in global energy consumption. Aimed to solve the problem of high energy consumption in the construction industry, a novel expanded vermiculite/xonotlite thermal insulation composite was successfully prepared via the hydrothermal method. The microstructure and thermal performance of the composite were systematically analyzed using field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), X-ray diffraction (XRD), thermogravimetric analysis (TGA), laser flash analysis (LFA), and infrared thermal imaging. The test results indicated that xonotlite fibers could be inserted well into the interlayers of expanded vermiculite. And the intercalation of xonotlite greatly improved the thermal insulation performance of expanded vermiculite at high temperature. The thermal conductivity of this composite decreased with intercalation rate increasing. The composite with intercalation rate of 51.43 % had the lowest thermal conductivity of 0.2116 W/mK at 800 °C which was 55.36 % lower than the expanded vermiculite sample. Meanwhile, this composite had good thermal stability and high temperature resistance. In addition, the thermal expansion of vermiculite and the synthesis of nano-xonotlite fibers were comprehensively studied and discussed. This study will provide a new perspective and ideas for developing vermiculite-based thermal insulating materials.

A Study on Design Method of Synchronous Reluctance Motor Based on Nonlinear MEC Using Newton-Raphson Method

Recently, policies for carbon reduction are being implemented worldwide to solve environmental and energy consumption problems. Minimum Energy Performance Standard (MEPS) is a carbon reduction policy for reducing energy consumption by regulating the efficiency of industrial induction motors. The induction motors have a low manufacturing cost and a simple structure, and it can be operated without control and have great advantages in maintenance so it is applied in various industrial fields. However, compared with other types of motors, there is a limit to improving the efficiency due to the additional loss generated in the cage of rotor. Synchronous reluctance motors (SynRMs) are attracting the most attention as an alternative to an induction motor since they are composed of only a copper winding and a core, manufacturing cost and durability are excellent Moreover, unlike induction motors, there is no secondary loss; therefore, it is evaluated as a high-efficiency industrial motor corresponding to MEPS. However, because of their complex rotor shape composed of multiple barriers and segments, SynRMs are typically designed using finite-element analysis, requiring a significant amount of time and trial and error. In this paper, a basic design method for a synchronous reluctance motor based on a nonlinear magnetic equivalent circuit using the Newton-Rapson method is presented. Finally, the design method of the synchronous reluctance motor is validated through performance tests using a prototype.

Research on optimal operation model of multi-energy complementary energy system considering multi-type peak shaving costs

The vigorous development of clean energy is an important way to achieve “Carbon peak, Carbon neutral”, but the inherent intermittent and uncontrollable power generation characteristics of clean energy such as scenery and other comprehensive factors make the energy consumption problem more prominent, and the multi-energy complementary can solve the energy consumption problem more effectively. However, the current study of multi-energy complementary operation only considers the fuel cost, load shedding and wind and solar abandonment cost, and does not consider enough the peaking cost of thermal power units and the life loss of batteries. To address these problems, a multi-energy complementary energy system operation optimization model considering multiple types of peaking costs is established, and the peaking costs of regulating units are modeled more finely and solved by a dynamic inertia weighted particle swarm algorithm. The results demonstrate that the addition of energy storage system can effectively reduce the total operating cost of the system under the condition of large-scale clean energy grid connection, and the addition of creeping cost and low load operating cost can reflect the cost of conventional units more realistically, which can better provide the dispatching strategy for the decision of multi-energy complementary operation of power system.

Economically and thermodynamically efficient pressure-swing distillation with heat integration and heat pump techniques

• Pressure-swing distillation is intensified with heat integration and heat pump. • Designs are evaluated from economic, thermodynamic, and environmental perspectives. • Heat pump-assisted pressure-swing distillation gives the best performance. • Reliability of compression process in heat pump working process is analysed. The recovery of isopropanol from wastewater is of significance in the industry in light of sustainable development and public health. In this study, the separation has been investigated in the pressure-swing distillation process to avoid contamination by the additional solvent. To address the problem of tremendous energy consumption in conventional pressure-swing distillation, three energy-efficient pressure-swing distillation processes were proposed based on heat integration and heat pump techniques. For each scheme, the sequential iterative optimisation was performed targeting the minimum total annual cost. The temperature-enthalpy diagrams were employed to analyse the energy consumption of the proposed configurations. The reliability of the compression process in the compressor was ensured by means of the temperature-entropy diagrams. All pressure-swing distillation designs were compared from the economic, thermodynamic, and environmental perspectives. In comparison with the proposed conventional pressure-swing distillation, the heat integration and heat pump can save 31.44% and 51.30% total annual cost with a capital payback period of 3 years, respectively. Special attention was paid to evaluating a combined utilization of heat integration and heat pump techniques which can reduce 38.30% of the total annual cost. The savings in the total annual cost of all intensified designs were expected enhanced for a longer payback period. Besides, all alternative designs were found with good performance in decreasing CO 2 emissions and enhancing thermodynamic efficiency. The present study can serve as a reference for designing other azeotrope separations to achieve sustainable development.

Exploring the analysis of key factors of new energy consumption and measures to solve them

In order to achieve sustainable and healthy development, power companies must gradually abandon traditional energy sources and actively develop new energy sources, which could achieve green energy-saving and environmental protection effects. This requires an analysis of the key factors of new energy consumption, to clarify the causes of this problem and to take effective countermeasures to solve it. The application of new energy generation technology in power grids is a reasonable solution to the problem of new energy consumption, ensuring a continuous and sufficient supply of electricity resources to meet demand. This paper focuses on the key factors for the consumption of new energy and the measures to address them.