Electric Energy Substitution Research Articles

Research on Establishment and Application of Evaluation System of Urban Energy Strategy Development Indicators under the Perspective of Carbon Neutrality

A scientific, comprehensive and integrated assessment of urban energy development is of great significance for the establishment of a clean, low-carbon and efficient urban modern energy system. From the perspective of carbon neutrality, this paper sets 25 evaluation indicators in seven dimensions: energy supply, energy consumption, energy efficiency improvement, clean and low-carbon, safety and reliability, low-carbon transport, and scientific and technological innovation, and constructs a secondary indicator system for evaluating the strategic development of urban energy. The system adopts the hierarchical analysis method to determine the weights of the indicators, the double-baseline progression method to standardize the indicator scores, and finally the weighted composite index method to calculate the level of urban energy strategy development. This paper applies the index system to evaluate the current energy development status of Wenzhou city in 2020 and 2022, and to predict the energy strategy development in 2025 and 2030. The scores of Wenzhou city's urban energy strategy development level in the corresponding four periods are 63.56, 70.59, 77.87 and 85.06, indicating that by 2023, Wenzhou city's urban energy development level will go from medium development to high development. Wenzhou City should accelerate the proportion of renewable energy in the future. It is necessary to complement multiple energy sources and improve the integration of heat, electricity, gas and cold. In terms of end consumption, it is necessary to improve the efficiency of energy use, reduce energy intensity, implement electric energy substitution and form an energy consumption pattern centered on electricity.

Multi-scenario investment forecast of new energy projects based on multiple linear regression and comprehensive evaluation model of differentiated project priorities

As China's resource shortage and environmental pollution intensify, the demand for new energy and electric energy substitution is becoming higher and higher. Accurately predicting the investment scale of China's new energy projects is of great practical significance for improving the efficiency of resource allocation and economically meeting energy demand. This paper builds a scientific and precise investment model for new energy projects from both macro and micro perspectives. First, from a macro perspective, considering macro indicators such as the external environment and internal economy, an annual total investment forecast model based on multiple linear regression is constructed, in order to predict the annual total investment scale of new energy investment entities and achieve preliminary accurate investment; second, designed the evaluation index system of different project priorities from three perspectives of external environment, internal development of enterprises and social development, and constructed the comprehensive weight design method based on AN-EWM and the comprehensive evaluation method of TOPSIS, in order to realize the priority of differentiated projects. Sorting; finally, a new energy project located in a city in northern China is selected as the research subject, and a multi-scenario example analysis is carried out. The results show that the new energy project investment scale index system constructed in this paper can effectively evaluate the investment capacity of the main body of the new energy project, and can better predict the total investment of the new energy investment project, so that the deviation rate can be controlled within 5 %, and the priority evaluation model constructed in this paper can provide a complete calculation method and a reference method for the judgement of the investment priority, which can promote accurate investment.

A matrix game‐based coordinated optimisation method of distribution networks with multiple flexible resources

AbstractThe ‘Electric energy substitution’ project in rural areas of northern China aims to replace coal‐fired heating with electric heating. However, this could potentially lead to congestion problems on the local distribution networks (DNs) due to an increase in heating loads. Instead of expanding the lines, flexible resources such as microgrids (MGs) and heat pumps (HPs) could provide auxiliary services in a more cost‐effective manner. A bi‐level optimisation model that coordinates DNs, MGs, and HP clusters is proposed to address this issue. In the lower level, MGs and HP clusters provide auxiliary services through competitive bidding to maximise their own income over multiple periods, considering a series of technical operational constraints and comfort constraints. In the upper level, DNs clear the market based on the bidding information to minimise its operational costs while guaranteeing network constraints. The bi‐level optimisation model is formulated as a multi‐agent matrix game problem, and the Win or Learn Fast‐Policy Hill‐climbing algorithm is used to achieve fast market equilibrium in a decentralised manner. Simulation results demonstrate that the proposed method can improve the revenue of MGs by up to 2.6 times compared to the single period matrix game method, and reduce the convergence time by up to 81.3% compared to the multi‐agent Q‐learning method.

Forecast of rural electric energy substitution potential based on nonlinear regression-neural network

Accurate prediction of electric energy substitution potential in rural areas is of great significance for accelerating rural electrification construction and promoting low-carbon rural development. In this paper, a neural network-nonlinear regression-based prediction model for electric energy substitution potential is established to predict and analyze the longterm electric energy substitution potential in rural areas. The paper first selects four key factors that affect the electric energy substitution potential: rural GDP, rural population growth rate, the proportion of rural power consumption and policy support measures. Then, the BP neural network is used to predict the value of the four key factors. And taking these factors as independent variables, the fitting polynomial algorithm is used to perform nonlinear fitting on the amount of electric energy substitution, so as to obtain the fitted predicted value of electric energy substitution. In order to improve the fitting accuracy, the paper further uses wavelet neural network to intelligently correct the fitting residual sequence, and realizes the effective prediction of electric energy substitution potential in rural areas.

Simulation and economic analysis of the high-temperature heat storage system of thermal power plants oriented to the smart grid

With the continuous increase of the grid-connected proportion of intermittent renewable energy, in order to ensure the reliability of smart grid operation, it is urgent to improve the operational flexibility of thermal power plants. Electric heat storage technology has broad prospects in terms of in-depth peak shaving of power grids, improving new energy utilization rates and improving the environment. It is an important means to promote electric energy substitution. In this study, the economics of technical application scenarios are compared and analyzed, the principle of solid heat storage technology is discussed, and its application in heating fields such as industrial steam, district heating, and deep peak regulation of congeneration units is expounded. The results indicate that in the scenario where the peak shaving subsidy and the heat storage duration are the same, as the unit output increases, the investment recovery period increases. Moreover, the results also indicate that in the 0.3 yuan/kW power market peaking subsidy scenario, only when the unit output is 0 and the heat storage time is greater than 8 h, the investment can be recovered in 5 years, while in the 0.7 yuan/kW power market peaking subsidy scenario, except for the scenario where the unit output is 40% and the heat storage time is 7 h, the investment cannot be recovered; in other scenarios, the investment can be recovered within 5 years.

Electric energy substitution technology suitable for Tibet

With the increase of population and the development of technology, energy use and pollution emissions continue to increase. While focusing on the development of new energy and renewable energy, electricity will continue to rise in future user energy supply ratios, and electrical alternative technology has become an important way for environmental protection and economic development. This paper takes the Tibetan region as an example to study the electrical alternative technology applicable to the Tibetan region. This paper selects the heat pump technology in the electric energy substitution technology, focuses on the analysis of the principle and unit structure of the heat pump technology, evaluates the performance of the heat pump with the performance coefficient and energy efficiency ratio, and analyses the performance of the heat pump through the T-S diagram and lgp-h diagram. It is concluded that with the improvement of the heating and cooling capacity of the single machine, its efficiency is higher and higher, and its energy-saving effect is also better.

Analysis of electric energy substitution potential and research on calculation method of carbon reduction under “carbon neutrality” background

Electric energy substitution is an important means to accelerate energy low-carbon transformation, promote sustainable socio-economic development, and achieve the goal of “carbon peak, carbon neutrality”. Firstly, this paper systematically and comprehensively combs the development status of electric energy substitution, and analyzes the outstanding problems existing in the actual work. Secondly, it analyzes the potential space of electric energy substitution, focusing on the impact of “carbon neutrality” on the development of electric energy substitution, and predicts the development trend of electric energy substitution potential. Thirdly, the calculation method for carbon reduction by electric energy substitution is proposed, and the important contribution of electric energy substitution in the implementation of the “carbon peak and carbon neutral” goal is further quantified. Finally, in order to ensure the sustainable development of electric energy substitution, relevant suggestions such as improving the market mechanism are suggested. The viewpoints and conclusions obtained from the analysis can provide theoretical support for the provinces to carry out the “carbon peak” action.

Energy efficiency evaluation and economic analysis of agricultural electric power substitute equipment in rural facilities

The reform of agriculture and the development of electric energy have promoted the substitution of electric energy for rural agricultural facilities. The use of electric energy substitution equipment can improve economic benefits and reduce environmental pollution. Starting with the study of agricultural greenhouses and agricultural products drying, as well as photovoltaic and biogas power generation for heating, cooling and energy storage, a cold and thermal power system is formed.

Design of Investment Potential Analysis Model of Integrated Energy Project Based on Deep Learning Neural Network

Under the background of energy conservation and emission reduction and large-scale promotion of electric energy substitution, fully exploring the complementary potential of various energy systems and realizing the optimization of comprehensive energy utilization are the most critical development goals of the current energy system. The key to achieving this goal is the investment potential analysis of integrated energy projects. In order to effectively solve the problems of difficult scientific determination of evaluation index weight and low accuracy of evaluation results in the analysis of investment potential of integrated energy projects, an investment potential analysis model of integrated energy project based on deep learning neural network is designed. The design process of the integrated energy project is summarized. The RBF-BP neural network model is established to obtain the correlation between the factors of the evaluation unit, further analyze and process the training results, and calculate the weight of the evaluation index. The obtained weight is substituted into the TOPSIS comprehensive evaluation model for the investment potential analysis of integrated energy projects. According to the investment potential analysis results, the investment potential analysis value of energy performance contracting (EPC) mode is 0.9122, which is the best operation mode. The results show that the analysis results reflect the investment potential of integrated energy projects more objectively and scientifically.

Analysis of Power Quality Problems in Large-Scale Application of Air-Source Heat Pump

With the implementation of electric energy alternatives, the large-scale application of electric energy substitution represented by air-source heat pumps has replaced traditional coal-fired heating, which is beneficial for the environment and alleviates air pollution. However, the large-scale application of air-source heat pumps has brought power quality problems such as voltage sags, harmonic pollution, and three-phase imbalance to the distribution network. This paper studies the fixed-frequency and variable-frequency air-source heat pump, introduces its working principle, analyzes the mechanism of its power quality problem. Moreover, the paper establishes a simulation model for the fixed-frequency heat pump and variable-frequency heat pump to connect to the distribution network. This research mainly studies the impact of large-scale fixed-frequency heat pumps on the depth of voltage sags in the distribution network and the impact of large-scale variable-frequency heat pumps on the harmonic content of the distribution network under different penetration rates and uses measured data to verify the reliability of the simulation results. This paper uses experimental data for the first time to verify the real power quality problems of large-scale heat pumps, which can provide a reference for determining the power quality standards for heat pumps connected to the power grid. At the same time, it can also provide a reference for the power quality management of the distribution network that is actually connected to electric heating.

Research on Implementation Guidance and Market Mechanism of Electric Energy Substitution in Hebei Province Based on Low-Carbon Energy Planning

In order to achieve the established energy conservation and emission reduction goals of China and Hebei Province, this paper studies the implementation guidance and market mechanism of electric energy substitution under the environment of low-carbon energy planning. Through the analysis of the stakeholders of the electricity substitute market under the background of low-carbon energy planning, the interests of all parties are clarified. For the implementers and promoters of electric energy substitution, three guiding mechanisms for the implementation of electric energy substitution are put forward, including quota policy, new energy feed-in tariff subsidy policy and carbon tax policy. Three main applicable mechanisms of electric energy substitution are mainly put forward, including virtual power plant, auxiliary service and power generation right trading, in order to promote the optimization of energy system structure and low-carbon energy planning in Hebei Province.

Analysis on the Importance of Electric Energy Substitution in Power Grid Enterprises

Analysis on the Importance of Electric Energy Substitution in Power Grid Enterprises

Power flow analysis of integrated energy microgrid considering non‐smooth characteristics

With the development of electric energy substitution technologies such as electric auxiliary heating, the relationship between electric energy and thermal energy is getting closer, and it is of great significance to in-depth study of integrated energy micro-grids containing electricity and heat. However, the integrated energy microgrid power flow (PF) model has non-smooth characteristics such as distributed generations (DGs) limits, converter stations limits and the unknown direction of pipeline mass flow, which can easily lead to the failure of PF convergence. This paper establishes an integrated energy microgrid model including three-phase unbalanced AC/DC hybrid microgrid and heating system. Firstly, the correctness of the converter station model is verified by electromagnetic transient simulation, and then the non-smooth constraint models considering DG and converter station's reactive power limits and pipeline mass flow direction unknown are established based on complementary constraints, and the non-smooth constraints are smoothed by Fischer-Burmeister (FB) function. Finally, the integrated energy microgrid is used for PF analysis, and the results verify the rationality of the model and the effectiveness of the proposed non-smooth characteristics treatment method.

Analysis of the Efficiency of Provincial Electricity Substitution in China Based on a Three-Stage DEA Model

An electricity substitution strategy that replaces fossil fuels such as coal and oil with electricity in end-use energy consumption, can effectively contribute to an energy transition and the early achievement of carbon peaking and carbon neutrality targets. As the benefits of electricity substitution are not synchronized across China’s regions, this paper uses a three-stage data envelopment analysis (DEA) model to measure the efficiency of electric energy substitution in 30 provinces of China in 2017. The results show that both environmental factors and random errors have significant effects on energy efficiency. After eliminating these influences, the efficiency of electrical energy substitution among regions presented the following pattern: “high in the east and low in the west”. According to the evaluation results, this paper proposes corresponding suggestions for the development of electrical energy substitution.

Allocation of Wind-Solar-Battery Under Electric Energy Substitution in Integrated Park Considering Demand Response

Allocation of Wind-Solar-Battery Under Electric Energy Substitution in Integrated Park Considering Demand Response

Optimization scheduling of an integrated energy service system in community under the carbon trading mechanism: A model with reward-penalty and user satisfaction

The carbon trading mechanism is considered an effective method for improving energy efficiency, and reducing pollution. In this regard, two methods of considering reward-penalty on the supply and demand sides as well as user satisfaction are the most effective ways to improve the carbon trading mechanism. Herein, this paper proposes a bilayer optimization model of the community-integrated energy service system. The population in the community is mainly divided into office workers and retirees, and their preferences are fully considered. The user considers electric energy reduction and substitution modes to optimize the energy consumption behavior in the reward stage. And the service provider considers the full consumption of wind and photovoltaic power and optimizes the output of each unit in the penalty stage. The effect of reward-penalty factors on the supply and demand sides is analyzed. The algorithm used to achieve bilayer optimization is the hybrid solution algorithm, which adopts the improved particle swarm optimization algorithm and CPLEX solver. The experimental results show that the costs of office workers and retirees are reduced by an average of 18.2% and 12.2%, respectively. And the service provider's profit is increased by 15.28%. The results also provide site selection strategies for energy supply.

Challenges and Prospects for the Trends of Power Structure Adjustment Under the Goal of Carbon Peak and Neutrality

Introduction Carbon peak and neutrality is an important strategic decision to promote the transformation of China's energy economy and build a community of shared future for mankind. China is a big energy consuming country and the whole society is facing huge challenges under the carbon peak and neutrality goal. The realization of the goal requires the guidance of correct theoretical methods and scientific deployment. Method For this reason， based on China's energy development situation， the essence of the carbon peak and neutrality goal was analyzed， the fundamental way to achieve the goal was given from a macro level， the development trends of power load such as zero-carbon energy power generation load composition and load demand indicators under the carbon peak and neutrality were predicted from the perspective of the energy supply side， and a new concept of equivalent electric energy substitution was proposed in this article. Result Based on the resource endowments of nuclear energy， hydropower， wind energy， solar energy and other resources， the power structure adjustment scheme under the carbon peak and neutrality goal was given， and the system operation characteristics problems caused by the power structure adjustment were analyzed， and measures to solve the problems were provided. Conclusion The carbon peak and neutrality goal may set off a new generation of energy revolution and a comprehensive industrial revolution. The four main zero-carbon energy resources of water， wind， light， and nuclear can meet the needs of China's sustainable social and economic development， and new energy will usher in an era of rapid development. This article discusses the development trend of future energy from many aspects， and gives constructive opinions on the adjustment of power structure， which has important theoretical guiding significance for the realization of the carbon peak and neutrality goal.

Analysis of the Financing Structure of China’s Listed New Energy Companies under the Goal of Peak CO2 Emissions and Carbon Neutrality

Under China’s “Dual Carbon” strategic goal, electric energy substitution on the energy consumption side and clean substitution on the energy supply side have become an important path to achieve peak CO2 emissions and carbon neutrality. Adjusting the energy structure and encouraging new energy to replace traditional energy is an important manifestation of China’s energy supply revolution. Therefore, China’s new energy companies have grown rapidly over the past decade. The development and growth of this industry is inseparable from government policy support. The profitability and economy are essential for the new energy industry to support its sustainable development., especially the choice of business models such as operation model and financing structures. Therefore, we build extended panel vector autoregression (PVAR) models with two-step system GMM(SYS-GMM) estimator which introduced predetermined and strictly exogenous variables to explore the dynamic correlation between financing structure and economic performance of China’s new energy public companies. The number of patent approvals and financial leverage are introduced as exogenous control variables. The results show that although the increase in costs caused by financing behavior will have a negative impact on the company’s return on equity in the short term, with the rational investment and utilization of funds, the negative impact will gradually weaken. Listed new energy companies can effectively use financing funds, and the use of different financing tools has different effects on company performance. Although debt financing can help promote the company’s profitability, it is detrimental to its future growth capacity.

Research and application of a hybrid model for mid-term power demand forecasting based on secondary decomposition and interval optimization

Accurate forecast of mid-term power demand ensures the stable and efficient operation of power systems, and is essential for the construction of energy interconnections and renewable energy microgrids. However, the implementation of strategies aimed at reducing carbon emissions such as electric energy substitution increases the uncertainty of power demand. In order to effectively extract the changing characteristics of electricity demand, this paper firstly proposes a secondary decomposition model based on a seasonal-trend decomposition procedure based on Loess (STL) and variational mode decomposition (VMD) to reduce sequence complexity. Then, different models such as grey wolf optimized support vector regression (GWO-SVR) for different sequences were used to achieve the best prediction effect. In addition, this study used the Markov chain model to further improve the prediction accuracy based on interval optimization. To verify the effectiveness of the hybrid model, a case study was conducted on the monthly electricity consumption in Zhejiang Province, China. The results show that the proposed model effectively extracts the characteristics of changes in electricity demand and greatly improves the forecast accuracy.

Research on carbon emission reduction calculation and user subsidy mechanism of electric vehicles

Under the goal of carbon neutralization and carbon peak, China’s electric vehicle industry will usher in a high-speed development stage. Electric vehicles can achieve carbon emission reduction from two aspects of electric energy substitution and clean energy substitution. In this paper, the carbon emission reduction benchmark of electric vehicles is determined, and the Bass model is used to predict the number of electric vehicles. On this basis, the carbon dioxide emissions reduced when electric vehicles replace fuel vehicles to meet the travel requirements and the carbon dioxide emissions of electric vehicles with different proportions of renewable energy generation are analyzed. Finally, the benefits of carbon emission reduction under decentralized and centralized modes are studied to determine the subsidy range of electric vehicle users.