The power trading system has the characteristics of nonlinearity, dynamics, and complexity. Part of the business data in the trading system needs to be exposed to numerous external business systems. The traditional centralized power trading model has some problems, such as low data security and trust crisis of regulators. Blockchain technology provides prominent ideas for solving these problems. Firstly, the improved AdaBoost algorithm is used to predict the supply and demand gap of power trading nodes. Secondly, based on the fact that the information on the blockchain is only open to the power supply side, a two-stage game model of asymmetric information between the power supply side and the power user is constructed to capture the price competition behavior between them in order to find the Nash equilibrium price in two stages. Finally, the US PJM market electricity market data are used to carry out an example analysis to verify the effectiveness of the algorithm and model.

Researcher and analyst are often interested in estimating the effect of an intervention or treatment, which takes place at the aggregate level and affect one single unit, such as country and region. Thus, comparative case studies would be their first choice in practice. However, comparative case studies could fail to yield an estimate in the effect that is unbiased and consistent, as in some contexts; there are not suitable control units that are similar to the treated. The econometric literature has taken synthetic control methods and panel data approaches to this problem. In this study, we developed a principal covariate regression estimator, which exploits the cross-sectional correlation, as well as the temporal dependency, to reproduce the dynamics of the treated in the absence of an event or policy. From a theoretical perspective, we introduce the statistical literature on dimensional reduction to make a causal inference. From a technique perspective, we combine the vertical regression and the horizontal regression. We constructed an annual panel of 38 states, to evaluate the effect of Proposition 99 on beer sales in California, using the principal covariate regression estimator proposed here. We find that California’s tobacco control program had a significant negative and robust effect on local beer consumption, suggesting that policymakers could reduce the use of cigarette and alcohol in the public using one common behavioral intervention.

Fossil energy power generation still plays a key role in the power generation industry, especially for countries where thermal power generation still dominates. With such potential considerable impact, this article aims to analyze the drivers of peak and valley electricity prices from the perspective of thermal power fuel. Specifically, the study uses data from the highly market-oriented US PJM power market to conduct an empirical analysis and focused on the links with coal, crude oil, and natural gas. Applying the Barunik and Krehlik index method to measure the spillover effect, we find that there is an obvious two-way spillover effect between the thermal power fuels and the electricity market. Besides, such an effect mainly occurs in the short time horizon, and natural gas plays a key role in transmitting the information to electricity prices. At last, this paper further builds a connectedness network based on the results of the pairwise spillovers, thereby visually displaying the cross-market connections.

With the continuing advance of electricity market reforms, China is currently in the transition stage from a dual-track electricity price system to a market-based single-track system. The new electricity price system, which is based on market transaction electricity prices and transmission and distribution prices; and the original electricity price system, which is based on the feed-in tariffs price and catalog electricity prices, are dual-track operation. Based on the evolution path of China’s macro development, this paper clarifies the connotation and settlement mechanism of China’s dual-track electricity price system and discusses the differences and connections between the dual-track system settlement, planned settlement, and market-based settlement. Then, by adopting an adjusted Computable General Equilibrium (CGE) model, this paper quantitatively evaluates the economic and social benefits of the dual-track electricity price system. Based on these results, this paper further analyses the subsequent challenges and countermeasures of the transition from the dual-track electricity price system to the market-oriented price system.

The mismatch between energy distribution and power load in China can be alleviated by inter-regional and inter-provincial power transactions. However, it also brings challenges to transaction settlement. In the new round of electric power reform, the transaction settlement deviation quantity needs to be more standardized. Based on the analysis of the related work, this article used the analytical framework of the analytic hierarchy process to calculate the transaction type weight, the inter-regional, and the inter-provincial weight, respectively, and accordingly, quantifies the amount of deviation quantity allocated by the corresponding trading subjects. According to the size and volatility of the trading quantity, we further propose a comprehensive weighting method based on kernel density and entropy weight to quantify the deviation quantity of inter-regional and inter-provincial trading subjects of different trading types. Specifically, this article first used the kernel function weighting method to calculate the weights of different transaction types that measure the transaction quantity, and then the improved entropy weight method was used to calculate the weights of different transaction types that reflect the volatility of the transaction quantity. Then, the comprehensive weights were constructed by considering the influence of the above two dimensions on the distribution of the deviation electricity simultaneously. The deviation electricity responsibility determination model was used to clarify the transaction subject's deviated electricity responsibility, and the deviated electric quantity calculation model was used for quantification. At last, the validity and practicability of the method were verified through the analysis of examples using the inter-regional and inter-provincial power transaction data from China.

Along with the progress of the electricity market reform, the formulation of electricity prices and the bidding in the electricity market have become hot issues. Given that electricity price contains a variety of information in the electricity market and reflects market changes, insufficient understanding of electricity prices or improper response will not only affect the revenue of power supply companies, but also have adverse effects on consumers in the downstream of the electricity market. Taking Zhejiang Province as an example, this paper uses a Multi-objective optimization based on genetic algorithm to calculate the optimal power structure of Zhejiang Province under a competitive electricity market environment and evaluate the impact of the market. The results show that as the market reduces the transaction cost of purchased power, the purchased power to Zhejiang Province has a significant positive role in power cost, stability and cleanliness. The electricity cost could be cut down by 18.3 billion yuan, which is 0.04 yuan/kWh. In terms of cleanliness and stability of electricity consumption, the competitive electricity market will also bring about benefits by 2.43% and 1.64% respectively.