Abstract:With the increasing intensification of the green-house effect, coping with global climate change and achieving clean and low-carbon development has become one of the common goals of human society. The realization of the dual-carbon goal will put forward new requirements for the development of domestic energy and power and the transformation of the public’s low-carbon energy consumption patterns. The demand for energy and power consumption under the background of“carbon neutrality”is analyzed, and the development direction of energy green consumption transformation and new development models of power consumption from different fields such as industry, construction, transportation, and agriculture are explored.

Abstract:The technical characteristics of direct heating electric boilers, regenerative electric boilers, quantum energy boilers, and air heat pumps are analyzed, and the heating costs are compared. The result shows that regenerative electric boilers are equipped with heat storage devices, which can change the electricity consumption characteristics of heating users and reduce the cost of heating power. However, the configuration of heat storage devices is closely related to the peak and valley electricity price policy. Setting a heating peak and valley electricity price policy can guide the load to use more electricity during the period of new energy generation and improve the grid’s ability to absorb electricity. The research results can provide a reference for clean heating in northern China.

Abstract:Port on-shore power retrofit is an important method to achieve“carbon peak”and“carbon neutrality”. While formulating an on-shore power retrofit plan, it is necessary to consider the government policy and the willingness of ship company to use on - shore power. However, the existing models usually default that all arriving ships use on-shore power, ignoring the independent choice of ships. Also, they usually ignore the differences of ships, without considering the refined processes such as queuing of ships and berth selection. These are the reasons that the on-shore power retrofit is“hot on the shore and cold on the ship side”. Many ports in the middle and lower Yangtze River have low utilization rates of shore power, and it is difficult for ports to recover the cost of shore power transformation. To this end, a decision-making optimization model for on- shore power retrofit is proposed, based on two-stage dynamic game theory. The model allows ships to independently decide whether to use shore power based on factors such as docking time, oil and electricity costs, port conditions, and waiting costs. Based on the algorithm, the optimal number of modified berths and the optimal shore power service fee are calculated. The numerical results of the case show that this method can achieve energy saving and emission reduction under the premise of ensuring the economic benefits of both port and the ship owners. Moreover, the impact of different government policies on the dual-carbon goal is discussed.

Abstract:Heating ventilation and air conditioners（HVAC） in commercial buildings have become important demand side resources providing power system ancillary services. A novel interactive control strategy to coordinate HVACs with power grid is proposed from the perspective of building aggregators. Firstly, a physical modeling and prediction method for the interaction capability of commercial buildings is proposed. Then the interaction capability curve（ICC）of a commercial building is established based on the global temperature adjustment strategy. After that, the aggregation and decomposition algorithms are proposed, based on ICCs of buildings and the idea of bidding and clearing. Simulation results show that the proposed method can be adapted to a variety of commercial buildings. An aggregator can predicate and visualize interaction capabilities of buildings, coordinate buildings to track the control target precisely, and distribute the burden of reduced service level much evenly between all temperature zones.

Abstract:Aiming at the matching characteristics of distribution network and regenerative electric heating load, a matching strategy of regenerative electric heating load and distribution network station area is proposed. According to the temperature set by the users, combined with the regenerative electric heating model, the possible start -stop strategy of the equipment is determined, with the goal of stabilizing the total load curve of distribution network, and the response optimization model is established. Genetic algorithm is used to find the optimal start-stop strategy, so as to realize the matching interaction with the distribution network station area. The results show that the interactive mode between regenerative electric heating and distribution network is improved by direct load control, which is convenient to give full play to the advantages of regenerative technology and popularize the use of regenerative electric heating equipment on a large scale.

Abstract:Electric energy substitution has gradually become a new national development strategy and is an important measure to control air pollution, improve environmental quality and adjust the energy structure. Promoting electric energy substitution needs to combine the characteristics of various fields, analyze the policy status in depth, base on reality and adapt measures to local conditions. Based on data prediction methods such as dynamic programming method, moving average method, and exponential smoothing method, the key technologies of Fujian province electric energy substitution policy simulation are studied. 4 types of electricity replacement policies in Fujian province are sorted out and analyzed, including electricity price category, preferential subsidy category, environmental protection category, development planning category, and establishes the corresponding analysis models. The current status of power replacement policies in the 7 major areas including clean heating, industry, and agriculture are analyzed, and the promotion measures and recommendations are given, providing support for future power replacement projects.

Abstract:Under the background of the development of renewable energy, the“source-demand”interactive optimal scheduling strategy taking into account the cost of carbon trading（CT） and green certificate（TGC）is investigated. The proposed model considers generation resources and 3 kinds of flexible loads including shiftable loads, transferable loads, and curtailable loads. The cost considers CT -TGC cost and load scheduling cost. Taking the overall cost as the objective, the optimization model is developed to realize the optimal allocation of generation resources and various flexible loads. Testing examples verifiy the effectiveness of the proposed method.

Abstract:A day-ahead optimal operation model of multi-station fusion system is proposed to improve the operation economy of the fusion station while reducing carbon dioxide emission and ensuring the reliability of power supply. Firstly, the mathematical model of each substation is established. Then, the objective function of optimal operation of the fusion station is established, which mainly includes the minimum daily operation cost and the minimum carbon trading cost of the fusion station. Then, the constraint conditions for the operation of the fusion station are established. Finally, CPLEX is used to solve the model in order to obtain the practical operation strategy quickly. The validity and rationality of the model are verified through the simulation solution. Furthermore, the payback period of the fusion new energy station and the energy storage station is analyzed, which provides a certain theoretical research basis for the subsequent fusion of other substations and the expansion and development of multiple stations.

Abstract:Photovoltaic（PV）power generation can reduce the pollution of primary energy, meeting the demand of power demand side management in China. To solve financing problem in development of PV industry, public -private partnership（PPP）is adopted. Considering tradable green certificate market, investment evaluation of PPP PV power generation project under grid parity policy is analyzed. Firstly, cost model and price range of tradable green certificate under grid parity policy are constructed. Then, combined with characteristics of different PPP financing model, according to benefit model of project, an investment evaluation method for PPP PV power generation projects based on tradable green certificate market is proposed. Finally, case analysis shows that the choice of financing model has a great influence on investment decision. The green certificate market enables enterprises to make immediate investment decisions under the grid parity policy, thereby promoting the development of PV industry. In addition, policy suggestions for government on tradable green certificate market are presented.

Abstract:The sharing of the using right of demand response and energy storage is a practical and feasible regulation method for low-carbon economic dispatching of power grid. Considering the constraints such as renewable energy generation utilization rate and user’s satisfaction degree of electricity payment, taking the maximum net profit of power selling companies and the highest income of energy storage operators as the objectives, a low -carbon economic dispatch model is constructed. On the basis of shared ES control strategy, load demand response is implemented for different types of users, and the multi-objective particle swarm optimization algorithm is used to solve the problem. The effectiveness of the proposed low carbon economic scheduling strategy is verified by an example.

Abstract:The load characteristics of regional power grids are easily affected by the environmental temperature, which often results in large deviations in the load identification results. The temperature-sensitive load identification method based on residual convolutional neural network is studied to effectively improve the accuracy of load identification. Firstly, the benchmark load comparison method is used to construct the benchmark daily load curve of commercial enterprises. Secondly, the Pearson correlation coefficient method is used to screen out temperature-sensitive loads with strong temperature correlation, and a polynomial regression model is used to further analyze the temperature -sensitive load and the law of real-time temperature changes quantifies the degree of influence of temperature factors. Finally, for temperature - sensitive loads, a polynomial regression model coefficient of load and temperature is used to construct a dynamic temperature-sensitive load feature library as the input of the identification model. Comparing the load identification results based on the residual convolutional neural network with the traditional convolutional neural network load identification results, the identification accuracy of the former is greatly improved.

Abstract:With the continuous development of distributed energy technology and the in-depth reform of the power system, the distribution network will show the characteristics of multi -stake- holders. In order to characterize the interest needs and technical characteristics of different stakeholders, while realizing the multi- venergy coupling of cooling, heating, and electricity in the distribution network, as well as the balance of power and electricity, and maintaining the safe and stable operation of the power system, the analysis target cascading theory is adopted to study the problem of collaborative optimization scheduling of network operators, distributed energy suppliers, combined cooling heating and power type load integrators under the market environment. Modeling the technical operating characteristics of the multi-energy elements within each subject, as well as the interrelationship between the subjects and the existence of different interest appeals, each subject performs collaborative optimization by exchanging contact variable information and finally converges. Lastly, the model and algorithm are verified based on the example of IEEE33 distribution network system.

Abstract:Accurate load forecasting plays a very important role in the operation of power selling companies in the power market. However, the load of enterprise users is unstable under the influence of various factors. Therefore, a short-term load forecasting method based on the seasonal Holt-Winters model of discrete wavelet decomposition and particle swarm optimization is proposed. In view of the unsteady periodicity of the original load sequence, the discrete wavelet transform is used to decompose the original load sequence, and the seasonal Holt-Winters model is adopted for prediction. Meanwhile, wavelet denoising and particle swarm optimization algorithm are used to further improve the accuracy of the prediction model. Wavelet denoising not only eliminates the potential noise in the original data, but also smoothes the data, and particle swarm optimization allows Holt-Winters model to find the optimal parameters during training. The model is used for short-term prediction of load data with different variation characteristics, and the experimental results show that the model has good prediction accuracy and can be applied to short-term load prediction of users with different power consumption types.

Abstract:According to the two stage of subsidy decline and grid parity, a model of system dynamics is constructed. Firstly, based on the analysis of the decline of subsidies in the past few years, it is predicted of the installed capacity, investment willingness and unit installed cost of residential photovoltaic in the process of subsidy decline according to a certain reduction ratio. Then, the development trend of each index after it enters the stage of grid parity is simulated. The simulation results of residential photovoltaic development from 2020 to 2028 are obtained. Finally, an example is used to verify the validity of the model. The example shows that residential photovoltaic will change from subsidy decline to the stage of grid parity in 2022, and it will officially transition from the adaptation stage to the development stage of grid parity access by around 2025.

Abstract:Based on the reasoning and decision-making function of the expert system, a set of intelligent diagnosis system of line loss abnormality in the station area is designed. In this intelligent diagnosis system, the original data of power consumption in the station area is loaded into the expert system for intelligent diagnosis of line loss abnormality. The station area with abnormal line loss is identified and the cause of the abnormal line loss in the station area is analyzed. Then, the abnormal line loss information is stored in the database of abnormal line loss in the station area. Managers of electric power enterprises can view the abnormal information of line loss on the human-computer interface of the system. The application of the system improves the diagnosis speed and efficiency of line loss abnormality, and improves the intelligent management level of power grid.

Abstract:With the in -depth implementation of the national energy Internet strategy, power demand side management has been endowed with new connotations such as green power and smart power, and the research interest continues unabated. Firstly, the business requirements of the demand side management platform is analyzed. Secondly, the platform architecture is designed from four aspects：overall architecture, business architecture, application architecture and technical architecture. Then, the key technologies and their application methods that support platform construction are analyzed. Finally, the effect of the platform’s online operation in the State Grid Hebei Electric Power Company is analyzed. The demand side management platform proposed can effectively alleviate the imbalance of regional power supply and demand, and the effect of peak shaving and valley filling is significant.

Abstract:Power demand response is a crucial means of regulating power supply and demand. Firstly, the national and local electricity demand response policies of domestic are summarized. It is clear that power demand response will achieve demand side resource coordination and optimization in a more effective way in the market. Secondly, the implementation rules of peak electricity price and bidding incentive power demand response are specially analyzed. Then, the implementation of incentive power demand response is analyzed from the scope of implementation, operating mechanisms, supporting technologies, business models, funding sources, compensation standards, user types, practical reasons, and practical effects. Finally, it provides feasible suggestions to the problems in practice and reference for the regions where are about to conduct power demand response.

Abstract:Frequency regulation auxiliary service is of great significance for maintaining the stability of the system frequency and ensuring the safe and reliable operation of the system. At present, the types of frequency regulation auxiliary service products in China are simple and fixed price settlement is mostly adopted, which is not conducive to the optimal allocation of frequency regulation resources. The product type, operation mode, price and settlement mechanism of the frequency regulation auxiliary service market in the three mature power markets of PJM in USA, the UK and Nordic are deeply studied, and the characteristics of the above three typical frequency regulation auxiliary service markets are compared and analyzed. On this basis, combined with the domestic actual situation, suggestions for the development of the domestic frequency regulation auxiliary service market are put forward, hoping to provide a useful reference for the construction of the domestic frequency regulation auxiliary service market.