Effective Energy Utilization Research Articles

ANFIS-BCMO technique for energy management and consumption of energy forecasting in smart grid with internet of things

This paper proposes an efficient energy management approach for managing the demand response and energy forecasting in a smart grid using Internet of Things (IoT). The proposed energy management approach is the hybrid technique that is the joint execution of adaptive neuro fuzzy inference system (ANFIS) and balancing composite motion optimization (BCMO), thus it is called ANFIS-BCMO technique. An energy management approach is developed using price-based demand response (DR) program for IoT-enabled residential buildings. Then, we devised a approach depends on ANFIS-BCMO technique to systematically manage the energy use of smart devices in IoT-enabled residential buildings by programming to relieve peak-to-average ratio (PAR), diminish electricity cost, and increase user comfort (UC). This maximizes effective energy utilization, which in turn increases the sustainability of IoT-enabled residential buildings on smart cities. The ANFIS-BCMO technique automatically responds to price-based DR programs to combat the main problem of DR programs that is the limitation of the consumer’s knowledge to respond when receiving DR signals. For consumers, the proposed ANFIS-BCMO based strategy programs appliances to exploit benefit based on reduced electricity bill. By then, the proposed method increases the stability of the electrical system by smoothing the demand curve. At last, the proposed model is executed on MATLAB/Simulink platform and the proposed method is compared with existing systems.

Broadband optical absorption and photothermal properties of partially disordered MoSe2 nanospheres

The new broadband light-absorbing material is essential for effective utilization of solar energy. However, the size-controllable MoSe2 nanospheres for the applications in broadband light-absorbing and photothermal fields, as well as the role of partially disordered features on the optical responses have not been well investigated. Here, we prepare the partially disordered MoSe2 nanospheres by a facile solvothermal synthesis method and investigate the random impacts of the spherical diameter on optical responses. The MoSe2 nanospheres reveal dark black color and broadband absorption from ultraviolet to near-infrared wavelength without obvious absorption edge. The photothermal properties with super-continuous laser irradiation demonstrate that MoSe2 nanospheres have high photothermal conversion efficiency of about 44.8% in water and even also reach about 30.7% in ethanol. The superior light absorption could originate from free-carriers absorption, defective state absorption and resonant absorption. The results not only pave the way of two-dimensional material for disordered photonic researches, but also widen the potential applications of MoSe2 in saturable absorber and photothermal agent.

Low-carbon development mechanism of energy industry from the perspective of carbon neutralization

Energy supply and environmental capacity are important material foundations for social and economic development and constraints for scientific and sustainable development, and with achieving the strategic goals of carbon peak and carbon neutral at an early date, too. Therefore, the international community generally regards energy-economic- environment (3E) as a necessary research direction. This paper studies the relationship among effective energy utilization, economic growth protection and ecological environment protection by establishing the contribution rate model of energy consumption factors to economic GDP growth. At the same time, this paper puts forward the government needs to use carbon trading market, carbon tax, such as low carbon management mechanism based on the Pareto Optimality of carbon trading market, prompts the excess money of the country or the region back to actively invest in low-carbon production, lets more energy companies to clean energy and low carbon production transformation, and helps to achieve the goal of regional energy industry carbon neutral.

Graphene–Silver Hybrid Nanoparticle based Organic Phase Change Materials for Enhanced Thermal Energy Storage

Due to the intermittent nature of solar energy, researchers and scientists are working to develop thermal energy storage (TES) systems for effective utilization of solar energy. Phase change materials (PCMs) are considered to be promising materials for TES. In this study, organic paraffin RT50 and graphene silver (Gr:Ag) nanopowder are adopted as TES material and thermal property enhancers. Microstructure and morphological behavior as well as chemical, optical, and thermal stability of the prepared composite PCM are visually investigated using scanning electron microscope (SEM), energy dispersive X-ray spectroscopy (EDX), Fourier transform infrared spectroscopy (FT-IR), UV-Vis spectroscopy, thermal conductivity analyzer, differential scanning calorimeter (DSC). and thermogravimetric analyzer (TGA). Furthermore, based on the outstanding thermal performance of the composite, an extended investigation on the thermal and chemical properties are evaluated for 500 thermal cycles to ensure their reliability. Results show the thermal conductivity of RT50 improved by 53.85% when Gr:Ag nanopowder is dispersed at a weight percent of 0.8 (RT50-0.8Gr:Ag). The change in latent heat value of the composite sample is less than 3%, which is significant for effective thermal energy storage. The thermal decomposition of RT50 is slightly improved from 300 °C to 330 °C. To ensure a reliable and passive technique for thermal energy storage within solar thermal application devices, such as solar air heaters and solar photovoltaic thermal systems, using nanoparticle enhanced PCMs at the range of a 50 °C melting point are a current research hotspot.

Adsorbent Coatings for Adsorption Heat Transformation: From Synthesis to Application

In recent years, growing energy demands and environmental pollution caused by the extensive use of fossil fuels have inspired considerable research interest in adsorptive heat transformation (AHT). This technology offers effective utilization of low-grade solar or waste thermal energy for cooling and heating with low environmental impact. Increasing the AHT power is a keystone for further development and dissemination of this emerging technology. The AHT power is mainly determined by ad/desorption dynamics, which is significantly hindered by slow heat transfer between the adsorbent and heat exchanger. Shaping the adsorbent bed as a coating on the heat exchanger surface is considered an effective route to enhance heat transfer and increase the AHT power. In this review, the technology of adsorbent coating for AHT is comprehensively surveyed, including coating synthesis, adsorption dynamics, and use in real AHT devices. The advantages of the coated bed configuration are considered, and its challenges are outlined. Finally, recommendations for better organization of the coating’s structure for rational control of the relative contributions of heat and mass transfer are considered.

Penerapan Sistem SCADA Audit Energi Listrik Berbasis Raspberry-Pi Codesys Dengan Komunikasi Modbus TCP Di Workshop Elektro Politeknik Enjinering Indorama.

The Covid-19 pandemic has an impact on almost all sectors of people's lives including the industrial sector.. According to Director of Energy Conservation Haryanto, the efforts that the industry can do to survive the current pandemic period is with conservation and energy efficiency, because when an industry has implemented an energy efficiency system, the industry will be able to reduce energy costs and reduce carbon dioxide (CO2) emissions. This research aims to create a prototype system that can support effective and efficient energy utilization efforts through the monitoring system of electricity use in the Politeknik Enjinering indorama Electrical department Workshop building so that it is expected to be used as a reference for energy audit systems both in the community environment and in the Politeknik Enjinering Indorama in order to aim for energy utilization. In this system Nodemcu ESP 8266 which acts as an RTU (Remote Transfer Unit) will send the results of processing data measurement sensor PZEM 004t to MTU (Master Transfer Unit) Raspberry pi using the Communication Protocol Modbus TCP, then the data received by MTU from RTU will be displayed to the display HMI (Human Machine Interface) Webvisu from Codesys so that sensor measurement data can be monitored in real time in the Politeknik Enjinering indorama Electrical department Workshop building either through the Computer or mobile phone. Based on the results of PZEM04T sensor testing for energy use for 30 days obtained the largest energy usage data, namely on line 1 of 83235.31 KWh, on line 2 of 79122.49 KWh and on line 3 of 26289.15 with accuracy rates for each line1, 2 and 3 which is 4.46%, 4.87% and 9.89%. The conclusion of this study that the system successfully functioned in accordance with the purpose of the study is to monitor the use of electrical energy in the Electrical Engineering wokshop building both through mobile phones and PCs in real time to be further referenced to the process of effective and efficient energy utilization in the future.Keywords: Energy Audit; PZEM04T; Raspberry Pi Codesys; Modbus TCP.

Overview of energy routers control strategies

In order to solve the problem of effective utilization of renewable energy, energy Internet technology came into being. As the key equipment of the energy Internet, the research on energy routers is of great importance. This paper introduces the energy router from the aspects of structure and operation mode, and summarizes a general energy router structure. At the same time, the control strategies of the energy router are systematically discussed. In view of the complex and diverse control strategies of the current energy router, this paper summarizes the research status of energy router control strategies and discusses the control strategies according to different classification methods.

Design and development of solar assisted fluidized bed dryer integrated with liquid desiccant dehumidifier: Theoretical analysis and experimental investigation

Higher energy demand for ventilating higher mass flux of hot air in fluidized bed drying (FBD) and SDG-7 of the UN has been actuated the researchers towards solar energy intervention in FBD. However, the thumb rules and systematic design calculation of the solar system for FBD have not been reported in the literature. In view of that, a novel solar thermal system was designed and developed by thermo-hydrodynamic analysis, considering the variable physical properties of bioproducts and fluctuating weather. The key design parameters were fresh and desired dried product's moisture content, physical properties of products, dryer capacity, desired drying temperature, ambient conditions, etc. In order to enhance the drying effectiveness, state-of-the-art technology for air dehumidification was integrated by using an aqueous blend of LiCl (35 %) + CaCl (5 %) desiccant. A solar photovoltaic system was also estimated for recirculating the moisture-saturated desiccant over an unglazed solar absorber to regenerate it. From the experiment of ginger drying, it was explicitly found that the developed solar FBD could supply sufficient heat energy (173.06–604.12 W/hr.) compared to the required heat load (124.65 W/hr.), which justifies the operational flexibility. The obtained solar heat fraction (∼1) and solar fraction (0.52–0.64) imply that the solar energy could fulfill the heat energy demand by 100 % and total energy demand (heat + electrical) up to 64 %. The energy efficiency, exergy efficiency, and sustainability index of the solar thermal system were obtained up to 48 %, 2.96 %, and 1.03, respectively. Aiming for effective energy utilization, an intermittent heat supply strategy was associated. Compared to continuous drying, intermittent drying reduced the active drying time (2–2.5 hrs.) and specific energy consumption (33.47–43.83 %) and fortified the dried ginger by reducing shrinkage (11–12 %) and increasing the rehydratability (up to 22.15 %).

Industrial Cyber Blockchain Physical System for Microgrid in Data Based Predictive Analysis for Automatic Control Analysis

As an efficient distributed renewable energy utilization model, a microgrid is predictable to realize the higher incorporation of the industrial cyber-physical system (CPS) that has gained significant interest in the academia and industry fields. Electric grid is now facing exceptional variations in generation and load as rising number of distributed energy resources (DERs), typically interfaced via power electronics converter, have been positioned, which possess multifaceted technical problems. In the context of electric grid, Blockchain (BC) was primarily developed for peer-to-peer energy trading through cryptocurrency. This paper presents a deep learning based predictive model for automated control analysis (DLBPM-ACS) in BC assisted industrial CPS environment. The presented DLBPM-ACS technique aims to forecast the short-term energy requirement for reducing the delivery cost of electrical energy for consumers. In addition, the presented DLBPM-ACS technique employs BC for effective energy utilization monitoring and trading control. Moreover, the presented DLBPM-ACS technique employs deep belief network (DBN) model for energy prediction process. Furthermore, the artificial ecosystem optimizer (AEO) algorithm is applied for optimal tuning of the hyperparameters related to the DBN approach. A wide range of simulations was conducted and the outcomes demonstrate the better outcomes of the DLBPM-ACS technique.

A Review of Composite Phase Change Materials Based on Biomass Materials.

Phase change materials (PCMs) can store/release heat from/to the external environment through their own phase change, which can reduce the imbalance between energy supply and demand and improve the effective utilization of energy. Biomass materials are abundant in reserves, from a wide range of sources, and most of them have a natural pore structure, which is a good carrier of phase change materials. Biomass-based composite phase change materials and their derived ones are superior to traditional phase change materials due to their ability to overcome the leakage of phase change materials during solid–liquid change. This paper reviews the basic properties, phase change characteristics, and binding methods of several phase change materials (polyethylene glycols, paraffins, and fatty acids) that are commonly compounded with biomass materials. On this basis, it summarizes the preparation methods of biomass-based composite phase change materials, including porous adsorption, microencapsulation based on biomass shell, and grafting by copolymerization and also analyzes the characteristics of each method. Finally, the paper introduces the latest research progress of multifunctional biomass-based composite phase change materials capable of energy storage and outlines the challenges and future research and development priorities in this field.

Improved Harris Hawks Optimization with Hybrid Deep Learning Based Heating and Cooling Load Prediction on residential buildings

In digital era, energy efficient building remains a hot research topic because of increasing concern regarding their environmental impact and energy consumption. Designing a suitable energy efficient building based on their layout namely overall areas, distribution of the glazing areas, orientation, height, and relative compactness. Such components directly impact the heating load (HL) and cooling load (CL) of residential buildings. A precise predicting of load facilitates effective management of energy consumption and improves the quality of life. Lately, several studies have been implemented to predict the CL and HL. The most significant and challenging parts of predictive are defining the effective input parameter and developing a higher accuracy predictive model. The accuracy of predictive model based on machine learning algorithm must be enhanced by hybrid model. With this motivation, this article introduces an Improved Harris Hawks Optimization with Hybrid Deep Learning Based Heating and Cooling Load Prediction (IHHOHDL-HCLP) model on Residential Buildings. The major aim of the IHHOHDL-HCLP model is to determine the CL and HL to accomplish effective energy utilization. To accomplish this, the IHHOHDL-HCLP primarily pre-processes the raw data in two levels namely min-max normalization and polynomial equation. In addition, the HDL model involves convolutional neural network (CNN) along with long short-term memory (LSTM) and bidirectional long short-term memory (BiLSTM) for HL and CL prediction process. Finally, the IHHO technique was applied for fine-tuning the hyperparameters related to the DL model. The IHHOHDL-HCLP model has demonstrated maximum prediction results with low RMSE values of 0.00874 and 0.00821, respectively, when applied to HL and CL, respectively. The experimental result analysis of the IHHOHDL-HCLP model demonstrates the better performance of the IHHOHDL-HCLP model over other DL models.

Research on the utilization of fuel cold energy for LNG powered container ships

Aiming at the problems that the fuel releases a lot of cold energy and the refrigerated containers consume a lot of electricity on large LNG powered container ships, a set of cold energy cascade utilization scheme that mainly uses LNG cold energy for refrigerated containers is designed. The simulation software Aspen HYSYS is used to establish and simulate the process of the ship’s cold energy cascade utilization system under five different working conditions, and the main parameters of the key nodes are obtained, according to the established exergy efficiency model, the exergy efficiency of the main equipment and the whole system is solved. Under the five working conditions, the maximum exergy efficiency of the refrigerated container system before optimization is 24.54%, at this time, the exergy efficiency of the entire cold energy utilization system is 24.86%. With the goal of improving the exergy efficiency of the entire system, using a hierarchical optimization method, the key parameters affecting the exergy efficiency of each cold energy utilization module are analyzed and optimized respectively, and the optimal operating parameters of different cold energy utilization module were determined. So as to realize the optimization of the whole cold energy cascade utilization system. The results show that the exergy efficiency of the optimized LNG cold energy cascade utilization system for ships under five working conditions is improved, under the 65% working condition, the exergy efficiency of the optimized refrigerated container system is 27.69%, and the exergy efficiency of the whole cold energy utilization system is 28.04%, which are increased by 3.15% and 3.18% respectively. Which proves that the LNG cold energy cascade utilization system can realize the effective utilization of LNG cold energy.

Effective removal of hexamethyldisiloxane using a citric acid modified three-dimensional graphene aerogel

Silica deposition resulting from methyl siloxane combustion represents a problem for the application and development of biogas energy, which creates the need to explore novel materials with high adsorption efficiency of methyl siloxane and excellent cycling performance. Here, citric acid (CA) was used to assist the hydrothermal reduction process and induce self-assembly with the final aim of obtaining three-dimensional reduced graphene oxide aerogels (rGOAs) from industrial-grade graphene oxide. The rGOAs were characterized by XRD, SEM, FTIR, Raman spectroscopy, and N2 adsorption/desorption techniques. The results showed that rGOAs had a significant removal capacity of hexamethyldisiloxane (L2), which could be attributed to the improvement of both texture and hydrophobic properties by CA. Among the rGOAs, the rGOA-2 showed the highest theoretical breakthrough adsorption capacity (QB, th, 337.3 mg g−1). The specific surface area (582.4 m2 g−1) and micropore volume (0.39 cm3 g−1) were the most key structural factors affecting QB, th. Appropriately decreasing the temperature and increasing the inlet concentration was beneficial to improving the adsorption capacity. In addition, the rGOA-2 exhibited excellent recyclability and reuse performance over five consecutive adsorption/regeneration cycles. Thus, our study provides a novel methodology with a high potential to overcome the problem of silica deposition using sustainable materials for the adsorption of methyl siloxane, to provide specific theoretical and technical support for the effective utilization of renewable energy.

Quantitative comparison between the effective energy utilization efficiency of triboelectric nanogenerator and electromagnetic generator post power management

Triboelectric nanogenerator (TENG) is an energy technology that produces an output of high voltage but low current, and its output power is proportional to operation frequency (f). While the electromagnetic generator (EMG) gives an output of high current but low voltage, and its output power is proportional f2. Since both TENG and EMG gives an alternating current (AC), which has to be rectified into direct current (DC) for practical use. With considering the different degree of voltage and power losses at the rectification circuit owing to the threshold operation voltage of a diode, this is the first quantitative comparison between the effective energy utilization efficiency of TENG and EMG. The results demonstrate that the frequency range in which the maximum peak power of TENG outperforms EMG is expanded after rectification due to the more severe power loss of EMG than that of TENG. Besides, the average power loss rate of TENG is consistently lower than that of EMG, and it is especially obvious at low frequencies. Moreover, the energy utilization efficiency of TENG is always superior to that of EMG after rectification, with a maximum of 98.84 % for TENG while only 66.36 % for EMG. This study reveals that the loss caused by the rectification circuit of TENG is much lower than that of EMG, which lays a solid foundation for the applications of DC-TENG.

Day-ahead economic optimization scheduling model for electricity–hydrogen collaboration market

This paper presents a day-ahead economic optimization scheduling model for Regional Electricity–Hydrogen Integrated Energy System (REHIES) with high penetration of renewable energies. The electricity–hydrogen coupling devices are modelled with energy storage units and Insensitive Electrical Load (ISEL). The proposed objective function is able to capture the maximum benefits for REHIES in terms of economic benefits and can be summarized as a Quadratic Programming (QP) problem. The simulation verification is performed by MATLAB/CPLEX solver. The simulation results show that the proposed optimization model adapts the market requirement by contributing flexible collaboration between electricity and hydrogen. Also, the translational properties of ISEL can implement higher economic profits and more effective utilization of renewable energy.

Palladium-Supported Polydopamine-Coated NiFe2O4@TiO2: A Sole Photocatalyst for Suzuki and Sonogashira Coupling Reactions under Sunlight Irradiation.

The effective utilization of solar energy in synthetic organic chemistry has gained extensive attention owing to its enormous energy and environmentally benign nature. In this context, we designed and synthesized a magnetically retrievable, sole palladium (Pd)-supported polydopamine-coated core@shell (NiFe2O4@TiO2) heterogeneous nanophotocatalyst for Suzuki and Sonogashira coupling reactions under sunlight irradiation. The synthesized catalyst was characterized by powder X-ray diffraction (PXRD), Fourier-transform infrared, UV–vis, scanning electron microscopy, energy-dispersive X-ray spectroscopy, transmission electron microscopy, X-ray photoelectron spectroscopy, and vibrating sample magnetometer analysis. The photocatalytic activity of the synthesized nanocatalyst under sunlight irradiation was assessed for both Suzuki and Sonogashira coupling reactions, where it worked excellently well with a high yield of the product up to 98 and 96%, respectively. Its efficacy was also investigated in the conversion of substituted substrates in both the coupling reactions into desired biaryls and diarylacetylenes. Unique features of the synthesized catalyst are (i) its effective performance for both the aforesaid coupling reactions under ambient reaction conditions for a short reaction time in polar protic solvents (ethanolic water/EtOH) with good yield without any byproduct, (ii) magnetic retrieval of the catalyst from the reaction mixture employing an external magnet is an added advantage, and (iii) the retrieved catalyst could potentially be reutilized for up to five consecutive runs without appreciable diminution of catalytic efficacy, and its stability was confirmed by inductively coupled plasma optical emission spectroscopy analysis and XRD.

Enhanced Charge Separation for Efficient Photocatalytic H2 Production by Long-Lived Trap-State-Induced Interfacial Charge Transfer.

Photogeneration of charge carriers in semiconductors provides the scientific fundamental for photocatalytic water splitting. However, an ongoing challenge is the development of a new mechanism promoting charge carrier separation. Here we propose a trap-state-induced interfacial charge-transfer transition mechanism (TSICTT), in which electrons in long-lived trap states recombine with holes on the valence band (VB) of the semiconductor, thus prolonging the electron lifetime. We demonstrate this concept in the Sr4Al14O25:Eu2+, Dy3+/CdS (SAO/CdS) heterostructure, where trapped electrons with a lifetime of up to several hours in the SAO persistent luminescence phosphor (PLP) can continuously consume holes on the VB of CdS nanoparticles (NPs). We discover that the interfacial interaction and the work function difference between SAO and CdS are crucial for the TSICTT, which finally contributes to the improved H2 production from 34.4 to 1212.9 μmol gCdS-1 h-1 under visible-light irradiation. This model introduces a new strategy to manipulate charge carrier transport for the effective utilization of solar energy.

A Novel Real-Time Deterministic Scheduling Mechanism in Industrial Cyber-Physical Systems for Energy Internet

As an effective distributed renewable energy utilization paradigm, a microgrid is expected to realize the high integration of the industrial cyber-physical systems (CPS), which has attracted extensive attention from academia and industry. However, the real-time interaction and feedback loop between physical systems and cyber systems have posed severe challenges to the reliability, determinacy, and energy efficiency of the multiway flow of information and communication transmission. In order to solve the problem of slot scheduling and data transmission (SSDT) in the microgrid, a novel real-time deterministic scheduling (RTDS) scheme for industrial CPS is proposed in this article. First, the SSDT is formulated as a multiway flow scheduling problem, and it is theoretically proved that the SSDT problem is NP-hard. Then, the RTDS scheme designs two heuristic algorithms: scheduling request preprocessing and greedy-based multichannel time slot allocation for an optimal scheduling solution. Practical experimental results demonstrate that the proposed RTDS scheme has significant advantages in packet loss rate, deadline guarantee rate, and energy consumption compared with the traditional schemes, and thus, is more suitable for deployment in microgrid systems.

Liquid air energy storage with effective recovery, storage and utilization of cold energy from liquid air evaporation

Liquid air energy storage (LAES), as a promising grid-scale energy storage technology, can smooth the intermittency of renewable generation and shift the peak load of grids. In the LAES, liquid air is employed to generate power through expansion; meanwhile cold energy released during liquid air evaporation is recovered, stored and later utilized for air liquefaction enhancement. However, it is challenging for effective cold recovery from liquid air in the evaporator and cold utilization to compressed air in the cold box. The current cold recovery fluids are exergy-inefficient, and thus the most suitable cold recovery fluids should be determined. In this paper, a practically dynamic LAES system with cold/heat storage packed beds is studied from the startup to stability. Some common cold recovery fluids, such as air, propane, and methanol/propane, are investigated and compared in terms of heat transfer characteristics in the heat exchangers (i.e., evaporator and cold box) and cold storage packed bed. Simulation results show that using pressurized air (10 MPa) as cold recovery fluid results in high heat transfer coefficients in the heat exchangers and cold storage packed bed. Compared to other fluids, the pressurized air leads to a larger exergy efficiency of 78.2% in the cold box, and a comparable exergy efficiency of 89.6% in the evaporator. It is found that pressurized air and methanol/propane are both good cold recovery fluids in view of the heat transfer performance in the cold box and evaporator, achieving similar idealistic round trip efficiency of 53%. However, the consideration of exergy destruction in packed beds will decline the round trip efficiency to 43% for pressurized air and 38% for methanol/propane. The cold storage packed beds with methanol/propane as cold recovery fluids are easier to be penetrated by thermoclines at the same size of pebbles, which causes a lower round trip efficiency. This study gives new insights into the effective cold recovery, storage and utilization process of LAES for industrial applications.

Research on the investment decisions of PV micro‐grid enterprises under carbon trading mechanisms

AbstractAchieving carbon neutrality targets requires substantial financial support. Effective utilization of renewable energy is an essential means of promoting energy‐saving and emission reduction to realize a green and circular economy. This paper combines carbon trading mechanisms with the operational mode of Chinese micro‐grid enterprises. This method uses the real options theory to construct an investment decision model for photovoltaic (PV) micro‐grid enterprises. The study aims to analyze the impact of carbon trading revenue on a numerical simulation of PV micro‐grid enterprise investment decisions. The findings demonstrate that when projected growth rates, volatility standard deviations, and risk‐free interest rates rise in the carbon trading market, the carbon price threshold rises, causing businesses to seek out investment opportunities with higher future carbon prices. The increase of micro‐grid generation technology acceptance probability, the availability of resources to meet generation investment requirements, and the generation project cycle will decrease the carbon price threshold and accelerate enterprise investment. Studying the influence of carbon trading prices on micro‐grid investment has specific guidance and practical significance for future government subsidy policies and the investment strategies of grid enterprises.