Abstract:Virtual power plant (VPP) is an innovative business mode and provides new technical means for integrating andmanaging distributed energy in power market. At present, The research on VPP mainly concentrates on its operation and optimal dispatch, lacking of research on market mechanism and compefition strategy, and thus the potential of VPP’s commercial value isunderestimated. By centering on the business mechanism and operating mode of VPP considering demand response, the recent researches on participating ways, market organization and structure,bidding strategies, as well as game theoretical market models are introduced. Finally, the commercial valuation of demand response in VPP operation and prospective of its development are conclud?ed. This research can provide reference value for the real operation of VPP in future deregulated market environment in China.

Abstract:Chinese peak valley power load gap is increasingyear by year. Demand side resources can achieve the goal of peak cutting and valley filling by participating in demand response. Demand response can be divided into price based response and incentive basedresponse,whichguideuserstoadjusttheirelectricitycon sumption behavior through price mechanism and incentive measuresrespectively. Demand response practices in the United States andEurope are market oriented obviously, and some provinces in Chinahave also carried out demand response practices. Users can avoidparticipating in the market by the demand response score scheme directly, including price based and incentive score schemes. Price based score scheme gives positive scores to users in the peak loadperiod and negative scores in the low load period；incentive basedscore scheme gives positive or negative scores according to whetherthe response is successful or not. The score scheme adapts to the ini?tial stage of the power system reform. It is conducive to the formation of a good interaction between the power grid and users and construc?tion ofubiquitouspower Internetofthings.

Abstract:The continuous increase of peak load in China hasthreatened the safety and stability of power grid, and air conditioning load has become an important part of the peak load. The abilityto store and transfer energy makes air conditioning load the mostpotential load in the respect of demand response. By reasonable controlling air conditioning load, peak load could be reduced and balance could be achieved between supply and demand at lower cost without affecting users’comfort. The relationship between the electricity price and the temperature set point of air conditioning was described by the consumer psychology theory, and the base line model of the aggregated air conditioning was built on the basis of equivalent thermal parameters(ETP) model. Then a new demand response program called progressive time differentiated peak pricing (PTPP) for air conditioning load was designed accordingly. At last, through simulation example, the implementation effect of the time differentiated peak pricing with that of the conventional critical peak pricing and proved the feasibility of the price mechanism was compared. The influence of different compositions of consumers on simulation results was analyzed, which provided the theoretical basis and reference data for the practical implementation of PTPP.

Abstract:With the explosive growth of power big data, the traditional data processing mode relying on a large amount of manpower and material resources is no longer suitable for the development of modern power systems. Cluster analysis is used to analyze the electricity consumption behavior and daily behaviors of residents in Honghe Prefecture. With the help of the power load data provided by the measurement automation system, and based on user group analysis and recognition, artificial intelligence algorithms such as gray prediction, BP neural network, adaptive BP neural network, PSO algorithm, classified random forest algorithm, and adaptive classification random forest are used to predict the load.Through in?depth research on the consumption habits of local residents and the prediction of power load, theoretical experience and technical support are provided for the application of artificial intelligence to power system customer demand response. The main innovation point is to apply the artificial intelligence algorithm such as adaptive random forest algorithm to the research of customer demand response, reduce the load of the grid during peak period, and adopt the load transfer strategy to reduce the grid operation cost and save energy.

Abstract:In order to analyze the maximal interrupting rate and maximal interrupting capacity of industrial and commercial consumers load finely, the twice classification model is adopted to deal with the consumers’daily load data. The fuzzy C means clustering method is chosen for each classification. The first classification is used to separate the interruption response data from the conventional data. The second classification is used to obtain the refined interruption patterns. The interrupting rate and interrupting capacity are analyzed from the time dimension and industry dimension. The results show that the twice classification model can effectively excavate the users’maximal response rate and maximal interrupting capacity.

Abstract:Residential electric water heater is a typical thermal energy storage load. The hot water generated by electricity has the thermal storage property, which can consume fluctuating wind power. The load group sliding mode control strategy of electric water heater for absorbing wind power is proposed to control the load group of electric water heater in real time. The control rate is related to the number of electric water heaters and the use of hot water,and has strong robustness for absorbing wind power. A simulation on the load group of electric water heater in a residential area shows that the proposed group sliding mode control strategy of electric water heater can effectively absorb the wind power, which verifies the effectiveness of the load group sliding mode control strategy of electric water heater.

Abstract:An adaptive single user flexible load control evaluation algorithm is proposed to design an evaluation scheme adapted to various demand response scenarios and improve users’willingness to participate in regulation and control. Firstly, the identification method of target load curve is proposed, and then the generalized distance between curves according to the characteristics of common evaluation indexes is defined. By adjusting the reserved parameters in the generalized distance, the evaluation scheme can be adapted to different scenes. Then, the method of setting initial parameter values is proposed. Using this method and the neural network, combining with the existing evaluation samples,each parameter in the generalized distance can be confirmed adaptively.Lastly, the effectiveness of this algorithm is verified based on the data of Lvjian area in Changzhou.

Abstract:Traditional electric power credit research and application are mainly based on negative evaluation such as electricity behavior, payment behavior dishonesty, lacking of positive evaluation and incentive application, only applied to customer management and electricity risk prevention, no cross border application in society.Firstly, the power credit indices of high voltage enterprise customers are concentrated on two aspects: trustworthy ability and trustworthy behavior. A comprehensive evaluation index system for power credit of high voltage enterprise customers based on big data is designed, which includes six evaluation dimensions: power consumption value, power grid interaction value, payment behavior,power consumption behavior, service interaction behavior and power market transaction integrity. Secondly, the process of calculating, revising the credit rating and credit score of electric power is designed. Taking nearly 290 thousand high voltage enterprise customers of a provincial power grid as examples,the scientificity and standardization of the established method are proved. Finally,based on the electric power credit rating, the differentiated reward and punishment measures are designed, which can effectively guard against internal risks, tap high quality customers and realize the export of electric power credit valuel.

Abstract:In the context of the development of smart grids, a home energy management system（HEMS）designed to meet users’energy saving requirements and respond to grid demand response has emerged. For the traditional HEMS static scheduling based on the overall optimization method can not flexibly adapt to the dynamic changes of the external environment, the basic structure of the HEMS is established, and a real?time adaptive dynamic schedulingbased home energy management system environment adaptive scheduling scheme is proposed. On the basis of the overall optimized dispatching plan, according to the real time collected information such as electricity price, air temperature, and photovoltaic output,the environmental status of the period is determined. The dynamic decision model is used to modify the dispatching plan in real time,and an environmental adaptive dispatching plan that meets actual needs is provided. Verified by simulation, this scheme can make the best decision meeting the users’needs in dynamic dispatching, inheriting the superior economics of traditional HEMS dispatching,andadaptingtothedynamicenvironmentwithlargechange.

Abstract:Aiming at the interaction between supply and demand of power grid, based on fine grained electricity consumption behavior measurement data collected by non household terminals and network behavior statistics of marketing system, the research on resident user portrait method is carried out. A user multi?source feature label system is established from three dimensions: user behavior, power consumption characteristics and consumption habits,and extraction methods of each feature label is proposed. Based on Euclidean distance and Manhattan distance, an improved k means clustering algorithm is proposed, and the improved k means clustering algorithm is used to divide the overall control clusters of power customers as the basis for precise positioning of target users.The system of feature labels and the results of the overall control cluster partition are used to synthetically portray and visualize the users. At last, 1 500 residential users in Jinji Lake demonstration area of Suzhou were used to analyze their portraits and applications.

Abstract:With the constant adjustment of the industrial structure in China, the users’characteristics are changing, and the users’electricity behavior gradually develops into individuation.Firstly, the discrete wavelet transform is used to extract the characteristics of user load data. Secondly, the improved fast density peaks clustering algorithm is used to cluster the users into load groups with different power consumption behaviors, and then the time distribution characteristics of the load groups are analyzed.The mutual information method is used to analyze the correlation between electricity consumption data, economy, temperature, industry key indicators and so on, and the key influencing factors are extracted. Finally, the simulation results of a typical user in an industry in a province verify the effectiveness of the proposed method.

Abstract:The problems of energy supply, climate and environment, new energy development and Internet information technology and technology changes have a great impact on the global energy industry. The comprehensive use of Internet thinking to transform the traditional energy supply and demand system and providing users with quality energy service is an important direction for future development. The relationship between the information flow,energy flow and value flow of the key elements of the energy Internet is fistly analyzed, and then the use of Internet thinking to transform the existing energy sector business model is explored. Finally,the energy Internet innovation business model is proposed from the three dimensions of energy production and consumption, asset investment and transaction, and value added services.

Abstract:Considering the special electrical characteristics and grid structure of AC/DC hybrid microgrid, the optimal management model of AC/DC hybrid microgrid is established. According to the different load characteristics of AC/DC hybrid microgrid in AC and DC area, the direct load control and load interruption is used for AC area load, while the load translation is used for DC area load. A numerical example shows that proposed model is suitable for AC/DC hybrid microgrid and can fully use demand side management technology to improve the economy of microgrid and the reliability of power supply.

Abstract:With the development of electricity market, it is possible for pumped storage units to participant in spot market or auxiliary service market. Driven by policies such as environmental assessment and clean energy consumption, pumped storage units have space to exert their market power. The problems such as high proportion of intermittent energy fluctuations, equipment failures,large fluctuations in load, and slow climb of large units are analyzed.Thetypicalscenariosandmechanismof the distributed pumpedstorages’market power are clarified. Based on the optimal power flow and probability methods, the market power of the distributed pumpedstoragesystemisquantitativelyevaluated.

Abstract:Based on the comparative analysis of relevant policies, documents, work reports and demonstration projects at home and abroad, the implementation modes of demand response between China and America are compared around the types, time scales of America, as well as the start up conditions, advanced notification time at home. The implementation scale between China and America is compared by analyzing implementation effects such as load reduction, the number of participant users, the scale of subsidies or incentives. The policy advantages and urgent technical requirements of developing demand response business at present are analyzed, and the key problem to be solved about development of demand response in the future is pointed out, hoping to provide some references for the development of domestic demand response business, especially for the research of key technology of demand response and the design of business model.

Abstract:At present, the global energy conservation industry is still in its intial stage, among which China, USA, Europe and Japan are the most active regional markets. On the basis of sorting out the development status of energy conservation service industry in USA, Europe and Japan, the development features and trend of energy conservation service industries in these countries are studied, energy conservation service industry development experience are summarized, and relevant suggestions for the development of Chinese energy conservation service industry are provided.