Electricity Market In China Research Articles

Electricity market integration in China: The role of government officials’ hometown ties

Market segmentation is common across various sectors, particularly evident in China's electricity market. Meanwhile, officials form a variety of geographic networks due to their innate backgrounds and acquired social connections. An extensive body of studies providing insights into the important role of officials' network ties in resource allocation, but little attention has been paid to the impact of this dynamic process on energy resources. Given that energy plays a significant role in shaping economic growth, our study complements this body of literature by examining how leaders with hometown ties impact inter-provincial electricity trade in China using a gravity model. The gravity model, which has become the traditional framework for estimating the determinants of trade flows, is applicable to the province pairs data structure in our study. Using data on provincial officials' hometown and inter-provincial electricity transactions for 30 provinces in China between 2007 and 2019, the results reveal that a leader whose hometown is i and current jurisdiction is j significantly increases the probability of electricity flowing from i to j, corresponding to a 53.73 % increase, which indicates that they implement a weaker market segmentation on their hometown. Moreover, the results reveal that this effect only occurs in a leader's tenure, and is particularly pronounced when a leader's hometown and current jurisdiction are on the same regional grid, or at least adjacent to each other, or when the current jurisdiction has higher power load levels. The results of mechanism analysis reveal that China's immature electricity market drives officials to leverage hometown ties for market integration, rather than promotion or rent-seeking. Our findings contribute to a deeper understanding of the broader impact of officials' personal ties. It also provides a valuable insight into the factors facilitating the integration of China's electricity market.

Research on Renewable Energy Trading Strategies Based on Evolutionary Game Theory

The authors construct a tripartite evolutionary game model that considers renewable energy, traditional coal-fired power plants, and market users. We propose multiple income matrices under different strategies, conduct evolutionary stability analysis, and form a series of assumptions that meet the stability of the game. We also simulate and analyze the impact of key factors—such as assessment costs, different pricing behaviors of coal-fired power plants, electricity prices of renewable energy, and green electricity demand—on the stability of the game. In addition, the market equilibrium points that can be achieved by optimizing trading strategies and their optimization status in promoting renewable energy consumption are analyzed. Based on the operational characteristics of the Guangxi electricity market in China and the trading situation of renewable energy, an evolutionary game method is applied to conduct empirical research. The trading behavior and evolution of all parties in the market are fully analyzed and are then applied to the construction and mechanism improvement of the electricity market.

Optimization strategy of power purchase and sale for electricity retailers in a two-tier market

Against the backdrop of the gradual advancement of China's electricity market reform, the number of Power Trading Companies in China has been increasing year by year, and as of October 2022, the number has reached more than 10,000. As an important hub connecting the electricity market and users, electricity retailers face double risks from downstream user load fluctuations and electricity market price fluctuations. Therefore, a reasonable power purchase and sale strategy is very important for an electricity retailer. In this study, a block bidding mechanism is adopted to optimize the clearing of the medium-to long-term market and a DA-RBF neural network is established for spot electricity price forecasting model based on numerical feature similarity to improve the accuracy of electricity price forecasting. Furthermore, the model considers the differences in user demand responses and investigates the optimal power purchase and sale strategy, guided by differentiated time-of-use electricity pricing. The case study analysis demonstrated that the proposed power purchase and sale optimization strategy yields favorable results, improving profitability and enhancing the stability of the power system.

A generation and transmission expansion planning model for the electricity market with decarbonization policies

Globally, the power sector must undergo a profound transition to achieve the decarbonization development targets. Various roadmaps are implemented, but only from a macro perspective, lacking the consideration of the electricity market rules. In this paper, we develop and present a market-driven generation and transmission expansion planning (MGTEP) model considering the effectiveness of the electricity market. Specifically, generation and transmission companies incorporate hourly market trading and annual capacity investment into strategic decisions to maximize their profits, with the supply function equilibrium model to analyze bidding behaviors. An equivalent quadratic programming formulation is deployed to solve the trilevel MGTEP model. Meanwhile, the MGTEP model is coupled with decarbonization policies to support the state and federal government in assessing energy transition strategies. We implement the MGTEP model with carbon emission allowance and carbon tax policies for the southern China electricity market to achieve carbon peaking by 2030. Carbon emission allowance adopts an intensity-based cap based on generation companies' historical output. The case study results show that 50 % carbon emission allowance or 400 CNY/t carbon tax is required but with several drawbacks, including unsatisfactory decarbonization effect, excessive economic sacrifice, etc. Finally, the case study is extended to dual-track policies with different combinations of policies. An optimal combination is 70 % carbon emission allowance and 160 CNY/t carbon tax. In this case, the power sector's carbon dioxide emissions and electricity prices in the southern China electricity market would increase to 554.6 Mt and 864.34 CNY/MWh in 2030, respectively, along with a carbon price of 850 CNY/t.

The Key Issues for China’s Electric Vehicles to Participate the Electricity Market

At present, China has the world's largest number of electric vehicles, and the total amount of charging power from electric vehicles is growing rapidly. Due to the small scale and high dispersion of a single electric vehicle, however, it is difficult for electric vehicles to participate the electricity market directly and share the dividends of electricity reform in China. Reducing electricity prices through the participation of electricity market can effectively encourage consumers to choose and use electric vehicles. Based on the analysis of the current Chinese electricity market, this paper studies the way in which electric vehicles participate in the electricity market in China, and designs corresponding market participation mechanisms.

Market power risk prevention mechanism of China’s electricity spot market based on stochastic evolutionary game dynamics

The construction of China’s power spot market is still in its early stage, with a high concentration on generation-side resources and frequent market power. It is urgent to establish risk prevention mechanisms for the generation of market power. First, the paper establishes a basic framework of the stochastic evolutionary game theory and then builds a “stochastic evolutionary game market-clearing” model for the market regulator and risk units. Second, the work provides a library of multi-dimensional monitoring and evaluation indicators for the regulator and creates a quantitative risk prevention strategy for the power spot market in China. Finally, an evolutionary dynamic analysis is conducted on players’ strategic evolution space and changes in market risks. Based on a simulation of actual data from an electricity market in China, it turns out that the generation-side market power risk prevention mechanism can lower market transaction and operational risks in a variety of power supply–demand scenarios. The study theoretically supports the development of market power risk prevention and provides more realistic insights into China’s power spot market as well.

A self-selection pricing mechanism for residential electricity: Measures of sustainability and equity to balance market mechanisms and government controls

We design a self-selection-pricing mechanism in which an electricity supplier offers its customers an optimal menu of contracts subject to a price ceiling set by the government, a hybrid model of market mechanism and government controls. We calibrate the model using information from a residential electricity market in China. Our mechanism outperforms the tiered-electricity-pricing system in China in terms of environmental and industrial sustainability but comes at the cost of providing less protection for low-income households (i.e., less equity). We conclude by offering measures of sustainability and equity that governments could use when trying to balance the trade-off between the two.

Examining the synergistic diffusion process of carbon capture and renewable energy generation technologies under market environment: A multi-agent simulation analysis

To achieve carbon neutrality, the power industry will vigorously promote renewable energy generation and carbon capture and storage (CCS) technologies. The diffusion of these technologies will vary depending on the incentive policies and market environments. Considering the progressive development of China's electricity market reform, this study constructs a multi-agent simulation model for the long-term low-carbon transformation of power systems, simulating the effects of different market environment and policy tools on the synergistic diffusion process of CCS and renewable energy generation technologies. According to the research results, when the price constraints in the electricity market are relaxed, opting for a differentiated clearing price demonstrates greater benefits for the diffusion of CCS technology and the reduction of carbon emissions compared to using a uniform clearing price. In this situation, the spread of renewable energy generation technologies aids in lowering the average market electricity price, thereby offsetting any potential price hikes resulting from the expansion of CCS technology. Moreover, in the presence of electricity price constraints, policy subsidies are necessary to incentivize the diffusion of CCS technology, with the suitable period for such incentives falling before 2040.

Effect of market structure on renewable energy Development—A simulation study of a regional electricity market in China

To achieve the carbon-neutral goal set for 2060, China has promoted renewable energy development for more than two decades. Meanwhile, China's electricity market is undergoing a new round of reform by introducing more market-oriented mechanisms and changing the market structure. This paper investigates the impact of three electric utility market structures experimented with in China on promoting renewable energy through a simulation model. The three market structures are vertical monopoly, weak monopoly (separation of power generators and grids), and monopolistic competition (Cournot-Nash competition). The model is calibrated with the actual data of the regional utility network in Beijing, Tianjin, and Tangshan areas. The simulation results show that the electricity market structure plays a vital role in renewable electricity, and the competition among utilities tends to benefit renewable energy development (wind power here). The study's conclusions are helpful to our understanding of further reforms in the electric utility industry and the long-term clean energy target in China.

Model selection and mechanism design for electricity markets in hydropower‐rich regions: Adaptation study

AbstractThe development of foreign electricity markets has been relatively complete, while China's electricity market started late and the design of the market mechanism needs to be improved, so the selection of a suitable market model and the design of the market mechanism in hydropower‐rich regions is conducive to the healthy development of the electricity market. While most of the first eight pilot regions in China have entered the long‐period continuous operation stage, and all the second batch of six power spot pilots have started the simulation trial run. However, the construction of power markets in hydropower‐rich regions of China, Sichuan, and Yunnan, still faces multiple problems to be solved, such as ensuring the reliability of medium‐ and long‐term power supply, improving the efficiency of hydropower resources utilization and consumption scale, and maintaining the stability of market prices. In this paper, the authors establish a multi‐scale joint clearing model for different market models considering both long‐term and short‐term operation strategies, and conduct simulations of different market models at different time scales to compare and analyze the optimization results and electricity price fluctuations of different market models. It can stabilize the market price and reasonably reflect the true value of hydropower, and also promote the consumption of clean energy and guarantee the reliability of power supply in the medium and long terms. Finally, suggestions are made for the selection of electricity market models, the security of energy supply and the design of sustainable development mechanisms for hydropower in hydropower‐rich regions such as Yunnan and Sichuan in China, with a view to providing useful references for the construction of China's electricity market.

The synergistic effect between Renewable Portfolio Standards and carbon emission trading system: A perspective of China

Renewable Portfolio Standards (RPS) and carbon emission trading (CET) system are the top-level system design of China's energy low-carbon transformation, which have great strategic significance for realizing the “carbon peak in 2030 and carbon neutrality in 2060”. At present, China's tradable green certificates market and CET market are still in the initial stage. The implementation single system may have diverse trials and errors in its initial stage, and the market activity and transaction frequency are low. Therefore, this paper aims to explore whether the synergistic effect between the two systems can effectively promote China's energy low-carbon transformation. This paper establishes the system dynamic model of the synergistic effect between the RPS and CET in China's electricity market to reveal the influence mechanism and the synergistic effect. The results show that: (1) There is a positive synergistic effect between the RPS and CET, which will change with the institutional parameters. (2) The simultaneous implementation of the RPS and CET can effectively stimulate market vitality and promote the development of the renewable energy industry. (3) Higher quota and lower benchmark price can optimize power source structure, and improve social welfare and institutional performance.

MRL-Based Model for Diverse Bidding Decision-Makings of Power Retail Company in the Wholesale Electricity Market of China

Power retail companies in the electricity market make profits through buying and selling power energy in the wholesale and retail markets, respectively. Traditionally, they are assumed to bid in the wholesale market with the same objective, i.e., maximize the profit. This paper proposes a multiagent reinforcement learning (MRL)-based model to simulate the diverse bidding decision-making concerning various operation objectives and the profit-sharing modes of power retail companies in China’s wholesale electricity market, which contributes to a more realistic modeling and simulation of the retail companies. Specifically, three types of operation objectives and five types of profit-sharing modes are mathematically formulated. After that, a complete electricity market optimization model is established, and a case study with 30 retail companies is carried out. The simulation results show that the proposed method can effectively model the diverse bidding decision-making of the power retail companies, which can further assist their decision-making and further contribute to the analysis and simulations of the electricity market.

Construction of an evaluation index system for power market considering economic-environmental multi-objectives

At present, China's electricity market has been initially built, direct trading of electricity continues to increase, and the mode of "multiple purchase and multiple sale" has emerged in the market, which enables the electricity market to compete effectively and make the optimal allocation of resources. Therefore, it is necessary to evaluate the operation of the electricity market. The article firstly studied the indicators of power market operation from three aspects: economic value, green value and security value; secondly, established a three-level evaluation index system of power system; on this basis, proposed a comprehensive evaluation model of power market based on fuzzy comprehensive evaluation. It provides a reference basis for the evaluation of China's power grid operation and is of great significance to promote the healthy development of China's power market.

Efficiency vs. equity as China's national carbon market meets provincial electricity markets

Emissions reduction in the electricity sector is critical in achieving China's carbon neutrality target. While a national carbon trading market that covers the electricity sector has been established, its effectiveness depends on how this sector evolves into being a more integrated market. This study evaluated the impact of China's electricity market integration on the cost-effectiveness of carbon pricing. An integrated (regional electricity market) and a segmented (provincial electricity market) market scenario were used to identify possible reform paths going forward. Using high-frequency datasets of the five southern provinces in 2018, we assessed the impact of electricity market integration on the abatement potential and cost-effectiveness of carbon pricing. We found that carbon prices need to be as high as 200 yuan/ton to begin achieving overall carbon reduction. In this context, the regional market is more cost-effective in reducing emissions than the provincial one, as the abatement costs are saved by around 60% compared to the latter under the same emission reduction targets. However, the regional market may also raise potential equity issues. The provincial-level distribution of carbon emission reductions, as well as the withdrawal of coal power, are more concentrated in the regional market than in the provincial one, which indicates an inequitable social-economic-environmental impacts of market integration. Our research findings would help to improve policymakers' understanding of the interaction between carbon pricing and electricity market reforms. This would then assist them in coordinating an effective design of both the carbon and electricity markets, in addition to supporting China's carbon neutrality target.

Bi-level planning model of distributed PV-energy storage system connected to distribution network under the coordinated operation of electricity-carbon market

The disordered connection of Distributed PV-Energy Storage Systems (DPVES) in the Distribution Network (DN) will have negative impacts, such as voltage deviation and increased standby costs, which will affect the demand of urban consumers for reliable and sustainable power consumption. Therefore, reasonable planning of the location and capacity of the DPVES in the DN is one of the key measures to reduce these negative impacts, while promoting the consumption of renewable energy and protecting the income of the DPVES. In this paper, under the background of coordinated operation of China's electricity market and carbon market, considering the uncertainty of distributed photovoltaic (DPV) output power and the demand response (DR) behavior of users, a bi-level planning model of DPVES in DN is established. The upper-level model aims at the maximum revenue of the DPVES in the DN and the highest local consumption rate of DPV, and the decision variables are the connection location and capacity of the DPVES. The lower-level model aims at the minimum average voltage deviation of the DN nodes, and the decision variables are the implementation of load-side DR and the output power of the DPVES. Then, the solution method and process of the model are given. Finally, four planning scenarios are set up in the IEEE-33 node distribution system, and the planning results of different scenarios are analyzed and discussed. The research results show that the bi-level planning model proposed in this paper can reduce the average voltage deviation of DN nodes while effectively increasing the average return of the DPVES and improving the local consumption rate of DPV.

Optimal bidding for large-scale hydropower stations serving multiple power grids in multi-regional monthly electricity markets

Driven by the development of the multi-level and unified electricity market in China, large-scale hydropower stations serving multiple power grids (LHSMPGs) have recently been required to enter into multiple regional electricity transactions. However, due to the multiple uncertainties of runoff and electricity prices, complex operation constraints, and difficulties in quantifying opportunity costs, formulating reliable bidding strategies for multi-regional monthly auction markets to maximize profits presents a challenge for LHSMPGs in China. Accordingly, in this study, we propose a tractable bidding optimization method for LHSMPGs in multi-regional monthly electricity markets. First, a scenario-based method is developed to describe the uncertainties in runoff and multi-regional electricity prices, as well as their cross-correlations. Then, a stochastic programming model is developed to coordinately optimize the piecewise bidding curves in multi-regional auction markets. The model considers the opportunity cost of bid quantities and complex monthly electricity allocation requirements during the whole time horizon of a year. Moreover, a monthly-rolling solution framework is designed to solve the stochastic programming model to ensure that the latest actual data can be dynamically considered to improve the accuracy of declaration. The application of the proposed method is verified through two cases based on the Xiluodu Hydropower Station, which ranks fourth in the world in terms of installed capacity. The results demonstrate that optimizing bidding curves in multi-regional monthly auction markets coordinately can enhance gross revenues and electricity sales. Moreover, a sensitivity analysis reveals that an excessively large or small allocation proportion of electricity between annual and monthly markets would weaken the guiding role of monthly auction markets in optimizing the allocation of hydropower resources and exacerbate the uneven distribution of hydropower generation between flood and dry seasons.

Study of Legal Adaptation in China's Wind Power Development

Legal adaptation is considered a crucial part and one of the most effective tools of the global energy transition. The energy transition process promotes the rise of the renewable energy industry and brings a tremendous challenge to the law. How could or should the law adapt to the challenge of this global trend? This article will start this study from the case of Chinese wind energy development.China is one of the fastest-growing countries in the world for renewable energy. Although the large-scale development of wind energy started in 2000, China's wind power installed capacity reached 300 million kilowatts by 2021, and power generation accounted for about 7% of the total electricity consumption . This year's installed capacity of coal power is approximately 1 billion kilowatts, but its power generation accounted for 71.27% of the whole country . Two energy sources with three times the difference in installed capacity have ten times the difference in power generation. Why is China's electricity market so biased towards traditional energy? How did the large-scale wind curtailment in China occur? And what role should the law play in China's energy transition game to adapt and regulate the development of the electricity market and guide China's energy transition?This paper will use game theory to analyze China's power pricing system and the operation of China's national electricity transmission grid, so as to explore how the law has and should adapt to China's renewable energy development under its unique power market system and power administrative management system, to minimize the rent-seeking behavior generated in power transmission and support the development of wind energy. This paper will propose solutions to the problem of wind curtailment in China's energy transition from a legal adaptation perspective and provide a reference for other countries.

Grid company income analysis based on pumped storage participating the spot market with various bidding strategies

With the development of the electricity market in China, regulations are updated quickly and models adapted to the latest policies need to be developed urgently. This paper proposes a combined clearing model to make pumped storage units participate the spot market. Three income models of the grid companies are developed as well. A 39-bus test system is introduced for simulation and the results show that pumped storage could increase its revenue and bring cost reduction for the system when participating the spot market. The income of the grid company would experience a 35% increase after adopting the possible future policy.

Dynamic tariffs and climate policy interaction: An economic analysis of welfare implications in retail electricity markets

Retail tariffs reform in electricity markets is attracting huge attention as policymakers seek to ensure that the marginal cost of electricity generation matches with the marginal value of demand. Notwithstanding, it is increasingly recognized that in order to appropriately reflect the marginal cost principle in electricity markets, the negative externalities of electricity generation should be fully captured in retail tariffs. Therefore, taking Fujian electricity market of China as a case, this study examines how a retail rate of time-of-use (TOU) tariffs interacts with climate policy. We calibrate a dynamic partial equilibrium model of this market and finds that interacting climate policy with TOU tariffs leads to i) increase in rate structures, ii) increase in demand response or load shifting, iii) increase in producer rent, iv) decrease in consumer rent, and v) decrease in overall welfare. Our results suggest that even though TOU tariffs and climate policy interaction in electricity markets can offer social and environmental benefits, the resulting losses to consumer rent and overall welfare may potentially undermine this approach. Therefore, in order to enhance the feasibility of transitioning towards a competitive and low-carbon electricity market globally, the cost of compliance to climate policy will have to be significantly reduced.

The Architecture of an Intelligent Technical Support System for Electricity Spot Market

With the accelerating pace of China's electricity market reform, the construction of the electricity spot market has been put on the agenda. However, as the number and scope of market participants gradually expand, the market-oriented transaction power continues to rise, and the intraprovincial and interprovincial transaction varieties are increasingly abundant. How to design an intelligent and powerful system that can meet the performance requirements of high concurrency and high-frequency transactions in the future market is a major problem in power reform. Based on the research of theoretical research results, this paper builds the front-end interaction platform of the southern spot electricity system based on the regional center to provide a data declaration interface for market users, including market management, market declaration, market release, market evaluation, intelligent analysis, front-end data interface, security protection, and other functional modules, provide declaration information and some market evaluation results to the southern regional spot power system platform, and obtain clearance results and published information from this platform.