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Fair and reasonable allocation of regulated consumption quota ratio (RCQR) of renewable energy is the foundation and key to guarantee the effective implementation of the mechanism associated with renewable energy consumption in China. Given this background, the allocation strategy of RCQR based on game theory is proposed for guaranteeing the consumption of renewable energy in this paper. In the proposed strategy, the RCQR of renewable energy for the market entities is allocated by determining the reasonable weights based on three proportional allocation methods (i.e., electricity consumption, electricity selling profits, and electricity purchasing cost) and the group satisfaction degree method. Then, game theory is used to coordinate the inconsistency of the four methods of determining weights. Finally, an allocation case of RCQR in Anhui, China is taken as an example for demonstration to verify the effectiveness and practicability of the proposed strategy. The simulation results show that the RCQR can be appropriately allocated by the proposed strategy, and it can be obtained that there is still a certain margin between the obliged consumption under the proposed strategy of each market entity and its maximum acceptable consumption.

The orderly release of electricity plan is an important measure for China’s electricity market reform which also lead to excessive pressure for coal power units caused by the low planned electricity quantity. Allowing high-priced units to participate in the market can effectively alleviate the market pressure. However, the participation of high-priced units in electricity market will have an impact on the declaration behavior of other generators. In this context, an evolutionary game model of bidding for two groups of generators considering the market liberalizing degree (MLD) is proposed. Above all, the profit model of two kinds of generators is proposed under two bidding strategies considering the MLD. On this basis, an evolutionary game model of generators’ bidding is built to qualitatively analyze the market equilibrium solution which is affected by the MLD coefficient. Thus, the expected evolutionary stable equilibrium of bidding can be formed spontaneously in electricity market by adjusting the MLD coefficient. The case studies are performed for demonstrating the proposed evolutionary game model of generators’ bidding, and simulation results show that different MLD and the initial state of bidding behavior of generators will influence the final evolutionary stable equilibrium of bidding market, and it also shown that the government can make the electricity market develop towards​ the expected state by adjusting MLD and supervising the bidding behavior of generators.

An energy deviation settlement (EDS) mechanism has been proposed to settle the deviation between consumption and energy contracts in China's forward electricity market. Due to high EDS costs of electricity retailers, a deviation mutual insurance (DMI) mechanism is put forward, representing an option for electricity retailers to reduce the deviation through contract transfer. Given this background, an optimal alliance strategy is proposed to maximize the utility of different types of individual electricity retailers. The alliance income model considers the EDS cost reduction and the cooperation cost analyzed based on transaction cost theory (TCT). An improved income allocation method, which considers distribution indexes selected by game theory and resource dependence theory (RDT), is proposed to ensure the comprehensive and reasonable allocation of alliance income. Considering the expected income and financial risk, an evaluation model using conditional value at risk (CVaR) as the financial risk assessment indicator is presented to measure the stability of alliances. Simulations based on data from a provincial electricity market in China illustrate that the EDS costs of retailers can be reduced by selecting appropriate partners for alliance. In addition, the proposed alliance income allocation method is more reasonable and more targeted than the cooperative game-based methods.

With deregulation of electrical market in the China, the electricity retail companies (ERCs) and the electricity retail market (ERM) experiences fast development in the recent years. Different from the generation and transmission market, the retail market is more open to the participators, and has more competition and higher risk. Considering the risk factors e.g. the business scale, the capital, the employee, and the complaints, an optimization model to reduce the risk of the ERCs and ERM with higher predicted risk is newly proposed in this paper, where the risk factors are normalized by the threshold value and the time before quantifying the risk. The risk optimization problem with constraints to adjustable risk factors is nonlinear and solved by the interior point method. The numerical results validate the optimization effect on the risk of the ERCs and the ERM.

With fast development of the retail market of China in recent years, the risk of the market needs to be quantified. This paper provides a detailed framework to assess and classify the risk of the market. The neural network is used to predict the risk. Time-dependent weight is used to describe cumulative effect. With the S-shaped curve, the risk factors are classified by safety, competition and elimination. The entropy method is used to set weights of the risk factors. The K-means clustering is used to classify the companies or periods. The risk factors, the operational risk, and the risk indicators form a hierarchical framework. The state aggregation based on serial tracking and incidence matrix finds transition rate matrix for early warning and coordination. The numerical results of a market with 9 companies are provided to validate the effectiveness of the proposed model.

This paper forecasts the risk of the electricity retail market (ERM). The risk factors of electricity retail companies (ERCs) includes the market share, capital, employee qualifications are considered. The capital factor includes the circulating capital, the ratio between the asset and liability, the credit deposit, and the net tangible asset. The employees' qualification considers the numbers and the ratio of the proficient employees. The risk factors are normalized to derive the comparable risk indices. The market shares are applied as weights of the risk factors. The risk of the ERC is quantified at two levels. The Gaussian process regression (GPR) was applied to fit the historical risk curve, and forecast the future risk of the ERCs and the ERM. The risk indices and the forecast results of a retail market with 9 retail companies are provided to show the feasibility and accuracy of the proposed model.

With the integration of the ultra-high-voltage direct-current (UHVDC) of large capacity, the scheduled outputs of the power plants are limited, and the direct power purchase (DPP) by large consumers is influenced. The negative impact caused by the failure modes of the UHVDC on the economic dispatch (ED) and the security of the power system is to be studied. Here, the derated capacities of the UHVDC are described together with their state probabilities. To maximise the profit of power plants, an ED model with the DPP is proposed. The relationship between the amount of the DPP and the power transmission by the UHVDC is decided based on two contract strategies for the DPP. The interior-point method is applied to solve the ED problem. The simulation results validate the feasibility and accuracy of the proposed model, which is beneficial to the development of the power market and the UHVDC in China.

The retail electricity market is becoming prosperous in China in the recent years. However, due to many uncertain factors, the retail providers may go bankrupt and have to withdraw from the retail market, thus the customers will suffer from unexpected supply interruption and economic loss, which will disturb the healthy operation of the electricity market. The purpose of the last resort service is to take the responsibility of the bankrupted providers, and maintain the power supply to the customers. This service is often provided by retail electric providers in foreign countries while undertaken by the power grid companies in China. In this paper, the experiences of the last resort service in several foreign countries are investigated. The qualification, pricing, customer allocation, and operating process about the last resort service are investigated. The benefit and risk of the last resort service are analyzed to determine the sharing of the responsibilities, interests, and punishments among the participants of the retail market. Based on the investigation, some practical suggestions to the last resort service are given to the provincial retail market in China.

With the development of power market construction, in order to ensure the effective competition of the power market and the stable operation of the system, under the competitive electricity market mode, it has become an urgent problem to improve the power sales market supervision system. Firstly, the characteristics of the electricity sales market under the competitive electricity market mode is analyzed. Secondly, problems in the surveillance of the electricity sales market are pointed out. Finally, the countermeasures and suggestions for the surveillance of the electricity sales market under the competitive electricity market mode are put forward.

The temperature rise caused by three-phase short current at stator side of doubly fed induction generator (DFIG) may damage DFIG and its adjacent electrical equipment. By using the step-by-step integration, the thermal effect may be quantified, but the contribution of periodic component and aperiodic component of thermal effect cannot be distinguished, and the amount of calculation is large. In this paper, the steady-state component of rotor flux is considered to reduce the error of analytical expression of short current. The components of short current are decomposed and the square of the short current is integrated. The calculation method of equivalent duration of aperiodic component of thermal effect is proposed, and the effect of equivalent duration on different crowbar resistance and stator voltage drop ratio is quantified. The simulation results are provided to validate the accuracy of the proposed models.

With the continuous development of the energy Internet, small and micro market entities are given the right to choose independently. Multiple new entities such as distributed energy, virtual power plants, electric vehicles, interactive energy use enter the power market and participate in power trading, creating an open and shared power market environment. At the same time, with the deepening of China’s power system reform, the focus of market construction will shift from wholesale side to retail side. Therefore, it is urgent to study the business model of power retail market, so as to take necessary preventive measures and avoidance measures as early as possible to avoid and reduce the pressure and risk faced by grid companies.

The increasing capacity of the grid-connected solar system has negative influence on the power grid. This paper focuses on the quality evaluation of the solar power. The quality of the solar power is quantified by the penalty function, which considers the total output, the output fluctuation and the forecast error. Firstly, the K-means clustering technique to cluster the sample data of the indices is applied. Then, the significance test using the F-distribution is applied to validate the effectiveness of the proposed model. Finally, the penalty function is proposed. The logarithmic function, the power function, and the exponential function are applied to compare the influences of each index on the penalty function. The Analytic Hierarchy Process (AHP) and the entropy method are used to determine the weight coefficients. The feasibility and application value of the proposed model are validated by the numerical results.