Abstract:

In the coastal power grid with a high proportion of nuclear power units and new energy power generation equipment,the pressure of peak regulation on system is severe. In order to achieve the demand of system peak regulation and fully explore the capacity of nuclear power peak regulation,the optimized dispatch model of nuclear-photovoltaic-electrochemical energy storage-pumped storage-thermal multi-source combined operation with flexible output of nuclear power to participate in peak regulation is established. Firstly,0-1 variables are used to accurately linearize the flexible address to nonlinear output of nuclear power. Secondly,complete system operation constraints is established,considering the operating characteristics and cost composition of each power unit. Finally,based on traditional economic optimization goal,different carbon trading mechanisms are introduced,considering the system's new energy level. The simulation example verifies the effectiveness of the proposed model. The results show that the proposed scheduling model effectively alleviates the system's peak pressure and reduces the frequent start-stop of thermal power units by the flexible output of nuclear power,thus improving the consumption level of new energy. The system operation is economical and low-carbon.

Abstract:

The grid-connected photovoltaic (PV) systems generally operate in the maximum power mode,where they are unable to fully respond to the adjustment requirements of the power grid. Therefore,research on power reserve control (PRC) for PV systems is needed. The maximum power point estimation (MPPE)-based PRC applies the equivalent model of a PV module to realize power reserve in the PV system,where the MPPE is conducted based on curve fitting. However,with the aging of PV modules,the error in MPPE increases,potentially impacting the stability and security of the system. A PRC method for PV systems that considers the correction of model parameters in MPPE as PV modules age is proposed in this paper. Firstly,a correction method for model parameters in MPPE is proposed based on the sparrow search algorithm. Then,considering the aging characteristics of PV modules and the evolution trend of MPPE error,an improved assessment criterion for the correction of MPPE model and the tuning principle of correction periods are proposed and finally applied to the MPPE-PRC method. Simulation results show that the proposed method can automatically correct the model parameters in MPPE as PV modules age. It can significantly improve the MPPE accuracy and enhance the reliability of PRC in practical applications.

Abstract:

Load curve clustering constitutes the foundational methodology for the analysis of customer load characteristics,enabling the extraction of typical power consumption patterns from a substantial volume of load data. Understanding these patterns is pivotal for applications including demand response,tariff design and power grid planning. In light of the inadequacies of existing clustering methodologies,specifically their insufficient consideration of the unique characteristics of load time periods,an advanced clustering technique based on time series density-changing processing is introduced in this study. The proposed method commences with the application of linear interpolation to augment the density of data points during critical periods,including peak,trough and ramp-up periods,thereby accentuating and amplifying their influence within the clustering framework. Concurrently,the technique incorporates the adaptive piecewise aggregate approximation (APPA) for dimensionality reduction to mitigate the density of superfluous data. Subsequently,a comprehensive index,formulated through the integration of Euclidean distance and correlation distance,is employed to conduct k-medoids clustering analysis of the load curves. The effectiveness of the proposed methodology is validated utilizing actual residential customer data from the UCI dataset. The results of these empirical investigations affirm that the method significantly enhances the efficacy of load clustering,thereby providing an authentic representation of the power consumption characteristics of residential customers.

Abstract:

Modular multi-level converter based solid-state transformer (MMC-SST) has gained wide attention in AC-DC hybrid distribution network due to the availability of ports with multiple voltage levels and voltage patterns. Dual active bridge (DAB)-type MMC-SST has problems such as low power density and high cost,and the tradition-al half bridge structure of DAB-type MMC-SST has failure to clear fault current in case of short-circuit faults at me-dium voltage direct current (MVDC) ports,which affects its application in distribution network. Although full bridge structure of DAB-type MMC-SST has fault blocking capability,it also increases the number of switches. Improve the topology of the traditional DAB-type MMC-SST,then a clamped switch pair integrated submodule (CSPI)-type MMC-SST topology is proposed based on the principle of frequency mixing modulation. The proposed topology not only reduces the number of switching devices but also makes the SST have the capability of clearing MVDC short-circuit faults,as compared to the traditional half bridge and full bridge DAB-type MMC-SST topologies. The power density and power supply reliability of the DAB-type MMC-SST are greatly improved by the proposed topology. The feasibility of the proposed CSPI-type MMC-SST topology and frequency decoupling method is verified through theoretical analysis and simulation.

Abstract:

Because of the integration of large amount of new energy sources,the power flow variation and voltage volatility in regional power system increase and it escalates the risk of equipment overload. In face of the uncertainty of new energy power,quick and accurate identification of the overload risk scenarios,and optimal utilization of various flexible resources from the source-grid-load parties to eliminate potential operational risks,are the urgent demands for the secure operation of the regional power grids. The flexibility evaluation indexes for the regional power grid are proposed,i.e. the flexibility demand index,the flexibility margin index and the flexibility resource utilization index,which comprehensively measure the requirements,resource and operation level of a regional power system for flexible operation. Under the target of the flexibility measurement,the mathematical models and computational method considering multiple risk scenarios are proposed,and the operation mode adjustment and the open-loop points scheduling are taken into account as the control measures. Case studies validate the feasibility and superiority of the proposed flexibility evaluation model,in comparison with the traditional boundary scenario analysis. The test results indicate that the proposed indicators,models,and algorithm can reflect the requirements and capabilities of regional power grids for operational flexibility with consideration of rich risk scenarios. The obtained dispatch solutions take into account both the economic and comprehensive aspects of various flexibility dispatch measures.

Abstract:

Direct current circuit breakers (DCCBs) are extensively utilized in flexible DC transmission systems,with their cost being intricately related to the breaking current. An adaptive current-limiting control structure tailored for half-bridge modular multilevel converters (MMCs) has been developed with the aim of reducing the breaking current of circuit breakers. By examining the short-circuit current characteristics on DC side of MMC,the variation in the input impedance amplitude of the converter station is utilized to indicate the extent of the fault. The coefficient K_f,which defines the fault depth of the converter station,is determined. K_f is incorporated into the control structure of MMC to align it with the reference value of the bridge arm voltage. A proposed method for adaptive current limiting control addresses DC side short circuit fault of MMCs. The model of the half-bridge MMC flexible DC transmission system is created using power systems computer-aided design/electromagnetic transients including DC (PSCAD/EMTDC) platform to model the clearance of DC side short-circuit faults and validate the effectiveness of current limiting control. The simulation results demonstrate that the proposed adaptive current limiting control technique can effectively implement differentiated current limiting control depending on the diverse fault depths of MMC. The breaking current of DCCB is reduced and the fault clearing speed is improved by this approach.

Abstract:

In recent years,the power electronic transformer (PET) used as the wind energy conversion system at the grid interface has attracted widespread attention for its ability to effectively suppress voltage fluctuations caused by the transient characteristics of wind energy without the need for additional reactive compensation devices. However,the conventional PET structure poses control challenges during grid faults,making it difficult to manage unbalanced grid conditions and compromising system dynamic performance. To enhance dynamic performance and fault tolerance,this paper proposes a novel wind energy conversion system based on the modular multilevel converter (MMC) power electronic transformer,along with its structural design and control strategy. Firstly,a fault-switching control strategy based on passive sliding mode control is designed to handle system operation during faults,incorporating sub-modules with fault protection features to dissipate fault power. Secondly,extensive simulation studies are conducted under various operating conditions using software simulation and semi-physical simulation platforms. Finally,comparative experiments between the proposed wind power generation system and traditional wind power systems validate the advantages of the novel system structure using the proposed control strategy,including reactive power compensation,effective limitation of submodule voltage rise during faults,and improvement in power quality. The results demonstrate the outstanding fault crossing capabilities of the proposed system in meeting the latest requirements for grid operation under fault conditions.

Abstract:

In this paper,the control strategy of modular multilevel matrix converter (M3C) is studied in the scenario of fractional frequency offshore wind power. The M3C system is compared with the traditional rotating synchronous generator system in terms of structural parameters and motion equations,and the feasibility of the M3C inverter to simulate the external characteristics of the synchronous generator is analyzed. With the goal of converter participating in system frequency regulation and stabilizing system voltage,based on the control theory of virtual synchronous generator (VSG),the control scheme design of virtual synchronous generator of M3C converter is completed,and a control strategy suitable for fractional frequency offshore wind power M3C converter is established. Finally,using PSCAD/EMTDC simulation platform,the correctness of this control strategy is verified. With the same system structure and parameters,the control strategy is compared with the decoupling control strategy of double dq coordinate transformation. The results show that the VSG control strategy can make the frequency converter have inertia and damping characteristics. The VSG control can participate in the system frequency regulation,and has good control response characteristics.

Abstract:

The tiered carbon trading mechanism and optimization scheduling model solving algorithm are pivotal for the community integrated energy system (CIES). CIES plays a crucial role in optimizing scheduling,yet existing literature often does not fully consider these two factors. To address this gap,the adoption of the proximal policy optimization (PPO) algorithm is proposed,which incorporates a ladder-type carbon trading mechanism to solve the low-carbon optimization scheduling problem of CIES. This method constructs a reinforcement learning interactive environment based on a low-carbon optimization scheduling model. The intelligent agent's state,action space,and reward function are defined using device status and operating parameters. An intelligent agent capable of generating the optimal policy is obtained through offline training. Case study analysis results demonstrate that the low-carbon optimization scheduling scheme for CIES achieved through the PPO algorithm,effectively leverages the advantages of the tiered carbon trading mechanism,significantly reducing carbon emissions and improving energy utilization efficiency.

Abstract:

The combination of combined heat and power (CHP) units and virtual power plants (VPP) can effectively improve energy utilization efficiency and enhance the reliability and stability of power system operation. To ensure the flexible,low-carbon,and economical operation of the CHP-VPP,this paper proposes an integrated energy VPP that aggregates wind power,photovoltaics,CHP units,boilers,carbon capture equipment,gas turbines,fuel cells,energy storage,and electricity and heat loads. The low-carbon economic coordinated scheduling issues are also investigated,considering multiple markets such as electricity,heat,spinning reserves,and carbon trading. Specifically,a two-stage robust optimization scheduling model for the CHP-VPP is established with the goal of maximizing the overall revenue in multiple markets at each time period. Then,considering the uncertainties from renewable energy outputs,market prices and loads,Monte Carlo method is used for scenario reduction to minimize system risk and enhance its robustness. Finally,a column and constraint generation algorithm is employed to solve the model,obtaining the optimal economic scheduling scheme in the worst-case scenario. Simulation case studies are carried out. Results show that the proposed integrated energy VPP structure is feasible and can achieve a significant reduction in carbon emissions through dynamically adjusting carbon capture equipment and energy storage batteries to achieve smoothness in renewable energy output fluctuations. Furthermore,the proposed scheduling strategy can effectively ensure the coordinated optimization operation of electricity and heat resources in source-load-storage sides,enhancing the flexibility,economy,and low-carbon performance of VPP.

Abstract:

To further improve the efficiency of biomass energy utilization,a source-load coordinated optimization scheduling strategy considering solar thermal biomass utilization (STBU) under comprehensive demand response incentives is proposed. Firstly,on the source side,an integrated energy system (IES) coupling energy supply model with STBU is constructed,and the STBU is coupled with a power-to-gas system to achieve efficient hydrogen-blended combustion utilization of the STBU device. Secondly,on the load side,both price-based and substitution-based demand responses are introduced to improve the low-carbon performance of the IES through source-load coordinated optimization. Then,a liquid storage carbon capture system and a tiered carbon tax mechanism are introduced in the IES to enhance the system's low-carbon economic benefits,establishing an objective function to maximize the system's total revenue. On this basis,a fuzzy chance-constrained programming model considering multiple uncertainties of the IES is established. Finally,actual data from a northern region is selected to verify the feasibility and effectiveness of the model,and the impact of multiple uncertainties on the operating costs of the IES is analyzed. The results show that the model has good economic and low-carbon performance. An increase in uncertainty raises the interaction costs between the system and the external power grid.

Abstract:

With the increasing penetration rate of renewable energy sources over recent years,voltage fluctuations and violations due to the inherent intermittency of renewable energy sources pose a great challenge to the safe and steady operation of distribution networks. To tackle this problem,the voltage regulation problem in distribution networks is formulated as a state-based potential game and then solved in a distributed manner in this paper. Specifically,the power flow model of radial distribution networks is linearized at first. Then,based on the linearized power flow model,a voltage regulation problem in distribution networks is modeled,whose objective function is the sum of voltage profile deviations and reactive power generation costs. Next,the subproblems for each bus is designed based on the state-based potential game theory,in the solving of which only its local and neighbor information are required,facilitating the design of the distributed voltage regulation algorithm. Further,the proposed algorithm is improved by freezing the states of isolated buses during each iteration,increasing its resilience against random link failures. Simulation results show that the proposed distributed voltage regulation algorithm can achieve fast and effective voltage profile regulation in distribution networks while preserving the privacy of distributed generators,even in the presence of random communication link failures. In addition,compared to other distributed voltage regulation algorithms,the proposed algorithm exhibits a faster convergence rate and better voltage regulation performance.

Abstract:

The research of loop closing current assessment has great significance for distribution network feeder loop closing operation to supply power. In order to enhance the accuracy of active distribution network feeder loop closing current calculation,an active distribution network feeder loop closing current assessment research method based on double K2 algorithm and probability load flow (DK2-PLF) is proposed in this paper，which also considers the prediction and distribution characteristics of source-load data. Firstly,Bayesian network based on DK2 algorithm is suggested to characterize the correlation of source-load samples. Secondly,the Cholesky decomposition method is proposed to deal with the predictive source-load samples,and the cumulative probability distributions of the loop closing current are calculated by cumulant method. Thirdly,the security assessment of the loop closing current is evaluated in terms of the success rate and the degree of exceeding the limit. Finally,taking a city in Guizhou as an example,the following conclusions are drawn from the study of 10 kV distribution system. Comparing from the aspects of probability density,cumulative distribution,and maximum error,the probability density and cumulative distribution errors of the DK2 algorithm are smaller than those of the K2 algorithm's predicted values,which verifies the superiority of DK2 algorithm. Comparing from the aspects of cumulative distribution,and maximum error,the cumulative distribution error of the cumulant method with Cholesky decomposition is smaller than that of the cumulant method without Cholesky decomposition and Monte Carlo method. The cumulant method with Cholesky decomposition meets the requirements of active distribution network feeder loop closing current assessment. Comparing from the aspects of loop closing success rate and the degree of exceeding the loop closing limit,the safety index of loop closing current computed by the cumulant method deviates from the simulation results is within 5% of the grid empirical error,which indicates that the active distribution network feeder loop closing current assessment method based on DK2-PLF can provide a reference for loop closing assisted decision-making.

Abstract:

The multi-terminal flexible DC distribution system has developed rapidly and has obvious advantages in integrating new energy. However,rapid and reliable fault identification is one of the challenges in its development. To address the issue of the inconspicuous high-resistance fault characteristics of multi-terminal flexible DC distribution lines and the associated protection difficulties,this paper proposes a single-ended protection scheme for flexible DC distribution lines based on measuring voltage Fréchet distance by analyzing the transient voltage fault characteristics before the converter station blocking. Firstly,the protection start-up criterion is constructed based on the transient change rates of voltage and current measured by the positive and negative electrodes. Secondly,single-pole and bipolar faults are distinguished by the voltage change rate measured by the positive and negative electrodes. Finally,the internal and external faults in the unipolar and bipolar regions are identified by using the single and bipolar measurement voltage Fréchet distance to construct the integral,and the unipolar fault is selected according to the positive electrode voltage change rate. The PSCAD/EMTDC simulation results show that this scheme can simultaneously meet the requirements for rapidity and sensitivity in protection,and has good resistance to transition resistance,which is not affected by the distributed capacitance of the line.

Abstract:

The operation and maintenance management of transformers has accumulated a large amount of unstructured defect recording data in the form of text. However,the lack of effective mining method has led to an extremely low utilization rate. A text mining method for transformer defect recording text based on a character-word level ensemble integrated model is proposed in this paper. Firstly,the transformer defect recording texts are preprocessed with text segmentation,stop word removal,text augmentation,and text feature representation to convert the data into mathematical vectors for input. By integrating multiple word- and character-level classification models,the method can realize accurate identification and classification of transformer defect types through the synergistic and complementary effects of meta-learners on the individual base learners. Compared to single-text classification algorithms,this method can obtain the semantic features of the text more comprehensively,achieving a classification precision of 91% and F₁ score of 0.9,which is the comprehensive evaluation score for model precision and recall. By applying natural language processing technology to precise power equipment defect recoding text classification and efficient fault recognition,data resources are awakened,and the intelligent management level of power transformers is significantly improved.

Abstract:

Conducting vibration measurement is important for detecting potential defects in gas insulated switchgear (GIS). However,the vibration signals of the GIS body are affected by the base vibration,measurement noise,and environmental noise,which leads to poor performance in on-site GIS vibration live detection and mechanical defect diagnosis. In response to the current situation,an on-site vibration signal denoising diagnosis algorithm based on the singular value decomposition (SVD)-improve adaptive chirp mode decomposition (IACMD) algorithm is proposed. Firstly,SVD is used to preprocess the original vibration signals to filter out low-frequency base vibrations and measurement noise. Subsequently,the osprey optimization algorithm (OOA) is used for adaptive modal decomposition of the processed signals,resulting in decomposed intrinsic mode functions (IMF). Then,the correlation coefficient is used to screen effective components for reconstructing the vibration signal. Test results from simulated and field signals demonstrate that,compared to OOA-adaptive chirp mode decomposition (ACMD) and SVD-variational mode decomposition (VMD),the proposed SVD-IACMD algorithm can remove base vibrations,measurement noise,and environmental noise while preserving the fundamental frequency and harmonic components of the GIS body vibration. Technical support for on-site anti-interference detection of GIS vibration and mechanical defect diagnosis is provided.

Abstract:

In response to the challenges posed by imbalanced samples leading to low recognition accuracy and high feature redundancy in AC contactor,a novel composite recognition methodology which is leverages embedded random forest (ERF) and Bayesian optimization-support vector classification (BO-SVC) is introduced. Firstly,the extraction of contactor state features from the full life testing platform designed for contactor is initiated. To counteract the low recognition accuracy caused by the imbalance among different state samples,a sample balancing strategy based on the weighted method is proposed. Subsequently,the ERF is employed to perform feature selection and reduction on the balanced samples. This process leads to the extraction of optimal features that represent the dynamic patterns of AC contactor state changes. Following the feature extraction step,the selected optimal features are fed into BO-SVC recognition model. A comprehensive evaluation of BO-SVC's fault recognition capabilities is undertaken，compared with two other representative models,the performance of each model is evaluated based on three indicators: accuracy,recall,and F1-score. The results of the proposed method reaches 95.22%,98.91%,and 97.01%,respectively,all of which are higher than the comparison models. Using F1-score as an indicator,the performance of each model is tested on four sets of samples,and the results showed that the F1-score of the proposed method is on average 0.56% and 27.28% higher than the compared models,respectively. The research in the article effectively solves the problems of redundant characteristics and low fault recognition accuracy of AC contactors.

Abstract:

Configuring a reactive power compensation capacitors as a resonant-free C-type filter is a common method to suppress reactive power compensation capacitors resonance. It can also be used to reduce the amplification of harmonic voltage caused by resonance and the power loss of the filter. However,the parameter selection range of resonant-free C-type filters is limited when the low frequency harmonic resonance needs to be suppressed,making it challenging to achieve low frequency harmonic resonance suppression economically. To address this issue,an optimal design method of a resonant-free C-type filter is proposed. Firstly,an improved C-type filter structure is designed to eliminate potential low frequency resonance points by incorporating a low frequency harmonic resonance suppression unit into the C-type filter. Next,a configuration model of the filter's element parameter is established,which takes into account the cost,power loss,the performance of resonant suppression and the selection range of element parameters. The optimal value of the improved C-type filter element parameters can be determined by the configuration model. The simulation and comparison results show that the filter designed by the method in this paper reduces the harmonic amplification ratio significantly and it has better performance of resonant suppression based on controlling the cost and power loss.

Abstract:

Power transformers are critical devices in power grid systems,with windings as their core components. To perform state detection on online windings,this paper establishes a nonlinear model between vibration amplitude and current based on the relationship between winding structural parameters and load variations. The numerical relationship between structural stiffness and model parameters is proved,and a winding clamping force evaluation method based on the nonlinear characteristics of vibrations is proposed. In the experiment,the relationship between current and vibration amplitude is obtained by adjusting the axial clamping force of windings and performing short-circuit load tests. The experimental results show that the nonlinear characteristics of vibrations are significant when the winding clamping force is small,and the characteristic parameter C₃ accurately reflects the equivalent stiffness change of the winding structure. In practical applications,the vibration characteristics of oil tank surface corresponding to normal windings and loose windings are compared,and the results are presented in the form of two-dimensional contour plot. The results indicate that the vibration characteristics of the tank reflect the structural state of the winding near the measurement point. The above results demonstrate that the parameter C₃ is a monotonic function of clamping force,and there is structural degradation in the winding when this value is greater than 0.5.

Abstract:

As the increasing proportion of renewable energy and power electronic devices in the power grid,voltage fluctuations are becoming frequent. In response to the current voltage regulation and reactive power compensation requirements of the distribution network,a new type of flexible on-load tap changer is designed that integrates traditional transformers and power electronic converters. This novel transformer can simultaneously provide voltage regulation and reactive power compensation capabilities. Firstly,the principles of voltage regulation and reactive power compensation on the series and parallel sides of the power electronic converter are analyzed. Then,considering the operation of the on-load tap changer,two series parallel voltage and reactive power coordination control strategies based on minimum voltage amplitude and minimum active power loss are proposed to achieve continuous voltage regulation while providing maximum range of reactive power. Finally,the structural rationality of the on-load tap changer and the correctness of the voltage and reactive power coordination control strategy are verified through simulation and experiments. The stepless voltage regulation and reactive power compensation under multiple objectives can be realized by the voltage and reactive power coordinated control strategy for flexible on-load tap changer.

Abstract:

Grid-forming energy storage can not only have the conventional energy storage function,but also be able to improve the system inertia to meet the demand for rapid frequency and voltage regulation of microgrid with high renewable penetration. Therefore,the grid-forming energy storage technology is an important form to promote the development of microgrid technology. In this paper,to investigate the impact of energy storage control strategy,an optimal operation model of microgrids considering stabilized expansion of grid-forming energy storage is proposed. Firstly,a microgrid cluster architecture with two sub-microgrids is built. The efficiency model of each component of the microgrid cluster is determined,and different energy storage control strategies are analyzed. Based on the different energy storage control strategies,different start-up modes of diesel generators constraints are set. Secondly,with the operating cost of microgrids as the optimization objective and the diesel generator start-up mode constraints,the optimized operation model of microgrids considering stabilized expansion of grid-forming energy storage is constructed,and it is solved by the CPLEX solver. Finally,different photovoltaic penetration scenarios are set up for arithmetic. The simulation is conducted to verify that the grid-forming energy storage can effectively improve the microgrids operation economy and environmental protection. Meanwhile,appropriately increasing the microgrid cluster contact line power limit can improve the system operation economy.

Abstract:

Transmission line temperature is an important indicator to evaluate the capacity of transmission lines,which can be used as the basis for dynamic capacity expansion and guide the real-time scheduling decision of power grid. Based on the measurement and heat balance equations,a real-time estimation model of transmission line temperature is proposed. The line temperature is taken as a state variable and the dynamic heat balance equation is introduced as a pseudo measurement. The heat balance equation is discretized,and then the alternating approach and simultaneous approach are used to solve the differential-algebraic equations. Considering the complexity of meteorological condition along the long transmission line,a more refined method for segmented temperature estimation of transmission lines is proposed by introducing virtual nodes into the segmented transmission lines. A two-port network equation is used to calculate the measurement of virtual nodes. The effectiveness of the proposed algorithm is verified by the improved IEEE 5-bus,IEEE 39-bus systems and a real line. The results show that the proposed algorithm can adapt to various scenarios and estimate line temperatures quickly. With the segmentation of lines,it is possible to accurately estimate the real-time temperature trajectory of each line section,which shows strong practicality.

Abstract:

In order to reduce the carbon emission of the integrated energy system in the park and to increase the new energy consumption,a novel planning method to optimize the carbon capture-energy storage joint system is proposed in this paper. Firstly,the operating principle and plan method of a carbon capture-energy storage joint system is introduced. Secondly,the Kullback-Leibler divergence (KLD) is used to illustrate the uncertainty of the new energy. Based on this,the optimal planning model of the carbon capture-energy storage joint system for the integrated energy system is proposed from the aspects of system investment,the operation and maintenance cost,the penalties of tripping the wind and photovoltaic power and the carbon trading cost. In the planning model,the overall cost of the integrated energy system is the main goal and the investment and maintenance cost of the carbon capture-energy storage joint system is the sub-goal. Finally,the distributed robust optimization method is utilized to solve the model,and the advantages of the proposed model on carbon emission reduction and new energy consumption are demonstrated by comparing the economy,emission reduction and new energy tripped under different scenarios.