Day-ahead wind power forecasting plays an essential role in the safe and economic use of wind energy, the comprehending- intrinsic complexity of the behavior of wind is considered as the main challenge faced in improving forecasting accuracy. To improve forecasting accuracy, this paper focuses on two aspects: ①proposing a novel hybrid method using Boosting algorithm and a multi-step forecast approach to improve the forecasting capacity of traditional ARMA model; ②calculating the existing error bounds of the proposed method. To validate the effectiveness of the novel hybrid method, one-year period of real data are used for test, which were collected from three operating wind farms in the east coast of Jiangsu Province, China. Meanwhile conventional ARMA model and persistence model are both used as benchmarks with which the proposed method is compared. Test results show that the proposed method achieves a more accurate forecast.

With the explosion of on-road EVs, private EVs become the most majority of the EV population, and also turns out to have the most flexible dispatching potential for power system. Accurate potential analysis of the flexibility has great significance for charging infrastructure upgrade, power system operation and market mechanism design. A probabilistic evaluation method of household EVs dispatching potential is proposed here considering users' multiple travel needs. Based on a realistic investigation on driving pattern of domestic cars, the probability distributions of multiple trip parameters are fitted with a proposed least-square-estimation based parameter optimization method. Sequentially, the sampling of random trip parameters is conducted considering the plug-in rate and coupling characteristics of trip parameters with a copula based sampling method. Based on evaluating the shifting potential of EV charging load, the influence on the shifted load, brought by the implementation of time-of-use (TOU) price mechanism, is quantified by taking residential energy-consumption behavior into account. Numerical result shows the accuracy and rationality to simulate the charging load considering multiple daily travel needs and the effectiveness of TOU price on EV load shifting based on the dispatching potential evaluation.

Energy decarbonization has been recognized as a crucial measure for addressing the challenge of global climate change. The user side is the primary cause of energy consumption and carbon emissions. Besides, user behavior can directly affect the energy efficiency and carbon emissions of energy-use (EU) systems, as well as the hosting capacity to accommodate renewable energy. Therefore, more attention should be paid to the user side for driving a green and low-carbon energy transition. Based on analyzing the driving mechanisms of the green and low-carbon energy transition from the user side, the author proposed to assign users EU rights (EURs) to describe the right and responsibility of using every EU resource in 2016. Based on the EUR trading, economic value is utilized to drive the flexible resources of EU systems to promote green and low-carbon EU. Moreover, EUR trading involves the allocation and operation of energy resources across multiple stages, as well as mutual conversions among various forms of energy. Considering that, an energy element model, which is used as a unit for measurement and transaction settlement of EUR commodities, is proposed to characterize energy equivalent and value in the EUR trading. Finally, through the integration of the Industrial Internet in the energy sector and the Consumer Internet, an Energy-Use Net and its friendly interaction with the power grid is proposed. The proposed Energy-Use Net uses energy elements as the basic circulation units, to achieve energy efficiency improvement and carbon reduction, thereby promoting the green and low-carbon transition of the whole energy system.

In order to encourage hybrid generation of multiple wind/solar/hydro power stakeholders, synergistic gains from hybrid generation should be allocated fairly, efficiently and reasonably to all power stakeholders. This paper explores how cooperative game theory resolves conflicts among multiple wind/solar/hydro power stakeholders. Elaborate allocation processes of the nucleolus, Shapley value and MCRS methods are presented in resolve synergistic gains allocation problems of wind–solar–hydro hybrid generation system with cascade hydropower. By analyzing properties such as existence, uniqueness and rationality, we find that both the Shapley value and MCRS methods are fair, efficient and rational allocation methods whereas the nucleolus method is limited by reservoir volume of hydro power stakeholders. Analyses on computational feasibility show that the Shapley value method may induce combinational explosion problem with the integration of more power stakeholders. A further application in Yalong River basin demonstrates that, compared with the Shapley value method, the MCRS method significantly simplifies allocating process and improves computational efficiency. Therefore, the MCRS method is recommend as a fair, efficient, rational and computational feasible allocation method for hybrid generation system with large number of wind/solar/hydro power stakeholders.

Demand response is recognized as an effective solution for eliminating power fluctuations and satisfying capacity constraints in power systems. A growing customer base equipped with energy storage and intelligent power meter on the demand side has resulted in the strong interest of China's power companies in demand response. However, most exiting demand response programs in China are based on a centralized framework, which is easier for management, but cannot support a large number of scattered small‐scale users' participation effectively. Therefore, taking the desired features of blockchain technology, such as decentralization, trustworthiness, trackability, and immutability into consideration, the applicability of blockchain in demand response is analyzed. On this basis, a new blockchain‐based framework of China's typical demand response programs is proposed, in which consensus mechanism, encryption algorithm, and smart contract of blockchain are applied to the process of invitation, bidding, and settlement in demand response. Furthermore, the development suggestions of China's demand response based on blockchain technology are put forward from the aspects of trading products, credit management, and platform construction at the end of this work.