Electric Energy Substitution Research Articles

Summary of Gridding-based Planning Method for Electric Energy Substitution Supporting Network

Electric energy substitution technology is of great significance for optimizing the final energy consumption structure, promoting energy conservation and emission reduction, and preventing air pollution. This paper aims to review the current research status of electric energy substitution technology and related fields, summarize the planning methods of electric energy substitution supporting network, and provide reliable network support for large-scale promotion of electric energy substitution. Firstly, the connotation, strategic significance and characteristics of electric energy substitution technology are summarized, and the basic structure of electric energy substitution technology is proposed. Then, the characteristics of network planning and gridding planning ideas are integrated into the gridding planning framework under the background of electric energy substitution is proposed. Finally, the development challenges of gridding planning methods in the current electric energy substitution background in terms of technology, mechanism and infrastructure are summarized, and looking forward to the development direction of the electric energy replacement supporting network plan under the background of the 14th Five-Year Plan and the new round of power system reform.

Analysis on the Current Situation and Development Trend of China’s Electrification Level and Electric Energy Substitution under the Background of Carbon Neutral

There is still room for improvement in China’s electrification level, and power substitution is an important grasp to improve the level of electrification. The implementation of electric energy substitution can promote energy transformation, realize green development and support the realization of carbon neutral goal. After analysis, the power substitution is still the main force to improve the level of electrification in various fields during the “14th five year plan”.

Modeling analysis of typical equipment and construction of energy supply scenarios for electric energy substitution

This paper studies the design of clean electric energy alternatives based on electric energy alternative equipment. First, sort out the current research status of energy substitution at home and abroad, and determine the research focus of electric energy substitution; list the electric energy substitution equipment that is suitable for construction, industrial, commercial and other fields, analyze its technical characteristics and specific application scenarios; list each device To analyze the performance of the equipment, establish a multi-factor output model for energy storage and production equipment according to the key influencing factors of the equipment performance coefficient; finally, based the above research, consider the substitutability of each equipment With complementary characteristics, the design is suitable for high-clean energy electric energy to replace typical structures.

Market clearing price forecast for power peak shaving auxiliary service

The use of new energy to generate electricity in the power system and the large-scale increase of new energy grid connection has led to increasingly insufficient power system regulation, in order to solve this problem, the peak shaving auxiliary service market came into being.This article comprehensively analyzes the factors those affect the market clearing price of power peak shaving auxiliary services: The macro factors include energy economic policies (renewable energy and electric energy substitution), technological innovation, market operation rules, etc., and the micro factors include the quotation and demand of thermal power plants and wind power generation.The power peak shaving auxiliary service market is an important part of the power market. Its appearance makes the grid operation safer and more reliable, and the reasonable fluctuation of clearing prices and total market costs reflects the market’s sensitivity to peak shaving resource demand.This paper uses the BP neural network model to select 31 consecutive days of peak shaving auxiliary service clearing price data in North China for prediction.

Forecasting method of clean energy development potential considering sector coupling

Sector coupling includes not only the coupling within energy sectors such as electricity, heat and gas, but also the coupling between energy sector and transportation sector, construction sector and industrial sector. This article introduces a method for measuring the development potential of clean energy based on sector coupling. First, the analysis model of electric energy substitution potential is constructed, the analysis object is determined, and the analysis object is quantified. On the basis of the definition of clean energy development potential, an IPAT model for electric energy substitution is constructed to realize the comprehensive evaluation of clean energy. Secondly, based on Markov theory to realize the sub-path calculation of the development potential of clean energy. Finally, based on the IPAT model and the decoupling theoretical model, this paper sets up three different alternative scenarios to make a more comprehensive prediction and analysis of the medium and long-term clean energy development potential, and applies the introduced measurement methods to the calculation of China’s clean energy development potential. The results show the effectiveness of the algorithm in the calculation of the development potential of clean energy based on sector coupling.

Application of Internet Communications in Agricultural Electromechanical Drainage and Irrigation Pumping Station

With the gradual advancement of electric energy substitution, the power consumption of agricultural electromechanical drainage and irrigation pumping station increases rapidly. It is urgent to update and transform the pumping station. Aiming at the substitution scenario of electric energy for agricultural irrigation and drainage, the technology of internet communications are combined in the application. It focuses on the design of two systems: monitoring and warning of operation conditions, and charging management of pumping stations. An electrical control cabinet integrated with power supply and control is designed by using PLC control system. This control cabinet is installed in the pump house of irrigation and drainage area. Some control terminals can be connected to it, and each terminal can be connected with a load that can work or shut down independently. These two systems store and analyse the operation conditions and electricity charge information. They also establish database and exchange data with external power supply companies and water resources management bureaus through internet communications. They are used to realize intelligent control and management. It is of great significance to establish a perfect integrated power supply control system for agricultural irrigation and drainage.

A Parameter Classification Prediction Method Applied to LEAP Model of Electric Energy Substitution Forecasting

As an energy substitution analysis & prediction tool with flexible parameter structure, LEAP model can provide strong support and guidance for guiding the electricity substitution work. On the basis of accurate parameters in LEAP model, this paper proposes a specific parameter classification prediction method. First, a targeted data structure is established, and the parameters that need to be input into the LEAP model are classified into general parameters and scenario parameters according to their degree of certainty. Secondly, predict the general parameters using improved GM(1,1) model by modifying background values and initial conditions. Thirdly, a Grey-Monte Carlo model was proposed to predict scenario parameters and their occurrence probability. Finally, the correctness of the parameter classification and the parameter prediction model are verified through example analysis, and it is proved that the co-application of them improves the accuracy of the parameters and further improves the accuracy of the electric energy substitution prediction.

Study on the forecast model of electricity substitution potential in Beijing-Tianjin-Hebei region considering the impact of electricity substitution policies

In recent years, China has introduced a series of energy substitution policies, aiming to achieve a fundamental change in the way of energy development. Firstly, based on the world energy model constructed by IEA, this paper determines the main driving factors in the field of power substitution, including economy, technology, policy, energy price and environmental factors. Secondly, based on the principle of system dynamics, a causal relationship diagram of five driving factors is constructed to clarify the feedback and linkage relationship between the factors. Finally, this paper proposes a hybrid prediction model combining Salp Swarm Algorithm (SSA) and Least Squares Support Vector Machines (LSSVM), namely SSA-LSSVM, which fully considers the influence of relevant factors of electric energy substitution, while avoiding the subjectivity of model parameter setting. The results show that the future development of electric energy substitution in the Beijing-Tianjin-Hebei region has maintained a rapid pace. The potential for electric energy substitution in the industrial production sector is large, and there is a large space for mining and operation optimization in the residential heating and transportation sectors. This paper provides a basis for the future development and improvement of the strategic plan of electric energy substitution in Beijing-Tianjin-Hebei region.

Design and Development of Two-level Deployed and Multi-level Applied Electric Energy Substitution Effect Improvement and Business Expansion Support Software

With the in-depth promotion of electric energy substitution and the rapid development of grid informationization, the building of systematic and integrated electric energy substitution effect improvement and business expansion support software becomes an important means to further optimize the electric energy consumption management level and realize the overall improvement of electric energy utilization efficiency. This paper introduces the design idea of this software, shows the layer structure of the platform, describes the relationships among all layers, analyzes the key technologies of the system, and researches and designs the general architecture and function modules. This platform provides the strong technical support for the state to promote the lean management of electric energy substitution and for the State Grid to develop the building of electric energy substitution service system.

Analysis of Load Characteristics Changes in the Case of Large-scale Electric Energy Substitution Load Connected-in

Global energy development trends and resource endowments determine that clean substitution and electric energy substitution will be important directions for the sustainable development of world energy. Electricity has the advantages of cleanness, safety, and convenience. The implementation of electric energy substitution is of great significance to promote the energy consumption revolution, implement the national energy strategy, and promote clean energy development. At present, many provincial and municipal governments are committed to promoting electrical energy substitution to complete the energy revolution on the consumer side, which has put the local power system to the test. In this paper, a load characteristic change model based on artificial bee colony algorithm for large-scale access of electric energy substitution load is established. In addition, the power load in a typical area is used as an example, and its load change is also calculated.

Planning Mechanism Design and Benefit Analysis of Electric Energy Substitution: A Case Study of Tobacco Industry in Yunnan Province, China

The problem of fossil energy shortage and pollution has become increasingly prominent. In China, government-led electric energy substitution projects are being carried out in nationwide, aiming at the end of energy consumption links, using electricity instead of coal-fired and oil-fired energy consumption, in order to optimize the energy structure and achieve the goal of energy conservation and emission reduction. Aiming at the planning and benefit sharing of electric energy substitution project, this research first designs the planning mechanism of electric energy substitution for productive users, analyses distribution network planning, transformation subsidy and so on, and puts forward three schemes. Secondly, based on the cooperative game theory, the benefit allocation model of electric energy substitution project is established. Finally, we take the flue-cured tobacco project about replacing coal with electricity in three areas of Yunnan province as an example to analyze, optimize the game strategy, and put forward three indicators to measure the benefits of the participants in the project. The pollution reduction situation that can not be converted into economic benefits is counted. The modeling results show that the density of users geographically will directly affect the cost of the distribution network transformation. The coal flue-cured tobacco heat loss and serious pollution, after optimization, power grid enterprises can quickly recover investment.

Research on discrimination algorithm of electric energy substitution user based on logistic regression model

The current power grid is found with low visiting efficiency, information integration difficulty and other problems in case of promotion of electric energy substitution. The big data technology is featured by high efficiency, high speed and convenience in terms of information processing, so it can realize the precise localization and differentiated marketing objectives of each enterprise. This paper, based on the analysis of energy consumption status of current power grid user and by means of “industry-field-user” architectural analysis, classifies user as per industry and equipment characteristics and combines with existing data of current power grid to exploit the energy consumption and electricity use characteristics of electric energy substitution user and build discrimination model of electric energy substitution user so as to improve the working efficiency and economic benefit of power grid business.

Analysis of Electric Power Substitution Development in Transportation Field and Research on Energy Conservation Efficiency Measurement Method

With the development of electric energy substitution in the field of transportation, related research has been deepened. In this paper, the current situation of electric energy substitution in the field of transportation is analyzed, and the calculation model of charging energy-saving effect of electric vehicles and the calculation model of charging energy-saving effect of ports and shores are constructed. Finally, some suggestions for the future development of electric energy substitution in the field of transportation are put forward. This study can provide theoretical support for further promoting the work of power substitution.

Research on the Substitute Potential of Beijing-Tianjin-Hebei Electric Energy under Multiple Scenarios Based on PSO-SVM Algorithm

To control the haze of Beijing-Tianjin-Hebei, the government has promoted the “electric energy substitution” (EES)strategy of replacing scattered coal and direct fuel with electric energy. In order to explore the potential of EES in Beijing-Tianjin-Hebei region, this paper takes GDP, population, and technological progress as influencing factors, considers multiple scenarios based on the “decoupling” theory, and establishes a regional energy substitution potential prediction model based on particle swarm optimization support vector machine(PSO-SVM). The market potential of electric energy substitution is predicted and analyzed through scenario analysis. Based on the prediction results, suggestions for promoting electric energy replacement strategy are proposed.

Can China achieve its 2030 carbon emissions commitment? Scenario analysis based on an improved general regression neural network

Abstract To determine whether China can achieve the commitment of reducing carbon emission intensity in 2030, a general regression neural network (GRNN) forecasting model based on improved fireworks algorithm (IFWA) optimization is constructed to forecast total carbon emissions (TCE) and carbon emissions intensity (CEI) in 2016–2040. Random forests (RF) method is used to select the important carbon emissions influencing factors to reduce data redundancy. The superiority of IFWA-GRNN forecasting model is verified by historical data from 1990 to 2015. The basic as usual (BAU), policy tightening (PT) and market allocation (ML) scenarios are set to forecast the TCE and CEI. The results show that under the BAU scenario, China’s CEI reduction commitments in 2020 (40%–45%) can be achieved, but the commitment in 2030 (60%–65%) cannot be achieved. Under the PT and ML scenarios, China can achieve its CEI commitments in 2030, and the TCE will decrease gradually after reaching its peak in 2030. Under the existing macro development planning and policy intensity in China, there are still certain pressures to achieve CEI reduction targets. It is necessary to implement policy adjustment and market mechanism incentives for both energy supply and consumption, optimize power supply structure, promote electric energy substitution, and accelerate the construction of a unified national electricity market, carbon market, etc.

Optimal Configuration of Electric-Gas-Thermal Multi-Energy Storage System for Regional Integrated Energy System

With the increasing attention of the clean and efficient use of energy, the regional integrated energy system (RIES), as an efficient measure to improve energy efficiency, is tending to play an important role in the field of energy supply. The configuration of multiple energy storage equipment in the RIES can greatly improve the economy of the system, which is an important research direction of RIES planning. However, at present the research on the configuration optimization of electric-gas-thermal multi-energy storage devices in RIES is insufficient. Under this background, a method for configuring the rated capacity and power of various energy storage devices in the RIES under both off-grid and grid-connected operating modes was proposed in this paper, and the configuration optimization model was also established. Firstly, the RIES was divided into four parts: Energy supply, energy conversion, energy storage and the load. Based on the energy hub concept, the four parts were modeled respectively. Secondly, considering the influence of electric energy substitution and operation strategy, the optimal configuration of multi-energy storage devices was modeled as a MILP formulation and solved with the Gurobi optimizer. Finally, a case study verified the effectiveness of the proposed model and the method. Furthermore, the sensitivity analysis was carried out to quantify the influence degree of each factor (such as price, etc.) on the energy storage configuration.

Benefit evaluation of power substitute project for industrial users

Power substitution in industrial field is an important measure for Chinese government to control air pollution, and how to evaluate the benefit of electric energy substitute project effectively is related to the effectiveness of this measure. In this paper, the Comprehensive Benefit evaluation index system of industrial electric energy substitution project is constructed from three dimensions of economy, environment and society, and in order to avoid the deficiency of single comprehensive evaluation method, a combinatorial model based on anp-entropy method and improved TOPSIS method is established. Finally, the rationality of the evaluation method is verified by an example.

Electric Energy Substitution Potential Prediction Based on Logistic Curve Fitting and Improved BP Neural Network Algorithm

In order to predict the potential of electric energy substitution in the next decade in China, this paper proposes a prediction method based on Logistic curve fitting and improved BP neural network algorithm. The amount of electric energy substitution is defined to quantify the potential of electric energy substitution. Then the important influencing factors of electric energy substitution based on the Impact by Population, Affluence and Technology (IPAT) model are established and quantified. For different influencing factors, logistic curve fitting and polynomial function fitting method were used to estimate the data fitting. A two-node output layer model of BP neural network is established and improved with additional momentum factors and adaptive learning rate to learn and train the data related to electric energy substitution from 2003 to 2017, and calculate the amount of electric energy substitution which are substitution potential from 2018 to 2020, 2025 and 2030. The calculation results show that the method has higher computational accuracy and fewer iterations. The prediction results are reasonable and effective, which can be the reference of the research of energy substitution.

Analysis and Suggestions on the Status Quo of Domestic and Foreign Electric Energy Substitution Development

Under the background of the continuous development of social economy, environmental pollution and climate change have become the practical problems that affect human survival and development. Therefore, in order to improve the current energy shortage situation and atmospheric environment and ensure people's quality of life, it is necessary to formulate a corresponding electric energy substitution strategy, clarify the role of electric energy on the terminal energy consumption of the power grid, and increase its proportion. This paper starts with comparing the current situation of electric energy substitution at home and abroad, and takes the specific country as an example to understand its electrification level and analyze the implementation of electric energy substitution policy, so as to propose countermeasures for domestic electric energy substitution according to foreign electric energy substitution experience.

An electric energy substitute planning model with economic cost and environmental constraints

The planning of electric energy substitution is one of the important bases for the decision-making of electric energy substitution propulsion. Nevertheless, there are still some problems in the planning of electric energy substitution, since the planning relies heavily on personal experience and local calculations. In this paper, a comprehensive planning model for electric energy substitute is proposed with considering the air pollution prevention, economic cost and technical feasibility of each region. The proposed planning model could be applied to efficiently and orderly develop the electric energy substitution, and consequently help to realize the energy transformation and the establishment of a green low-carbon society.