Abstract:China is in an important stage of electricity market reform. The design of price mechanism in electricity market is one of the core issues of market deregulation. For the bidding mechanism problem which is one of the price mechanism problems, the influence of relative price mechanism and absolute price mechanism on the equilibrium of electricity market is studied.Firstly, a bilevel model is established to simulate the game behaviors in the oligopoly power market under different pricing mechanisms. Subsequently, the model is solved by utilizing the optimality conditions. Finally, based on the case of Guangdong province,scenarios with strategic bidding and without strategic bidding are analyzed. It is found that the relative price mechanism leads to the distortion of unit cost and the increase of generation cost. Compared with the absolute price mechanism, the relative price mechanism can avoid the phenomenon of“free ride”, reduce the demand cost, and inhibit the abusing of market power by strategic generator to some extent.

Abstract:Recenthy, with the development of smart distribution network and ubiquitous Internet of Things, the distribution network projects have attracted much attention. Post -evaluation for power grid projects can find the problems, put forward suggestions for improvement and guide the future project process management,which plays an important role to realize the closed-loop and lean management. Considering the multi-dimensional characteristics of power grid, a post-evaluation method with its index system for power grid projects based on attribute theory is put foward. Considering implementation process, effect and benefit, environment and social benefit, sustainability, a hierarchical multi-dimensional grid project post-evaluation index system is established. Based on attribute theory, a post-evaluation method is proposed, including single index attribute measure, the index weight calculation and multi-attribute post -evaluation comprehensive evaluation method. Through the evaluation and analysis of practical engineering projects, case studies prove that this evaluation method can find out the problems existing in the project and analyze the causes of the problems, which is beneficial to guide the company’s future investment direction and decision-making, and achieve accurate investment.

Abstract:In view of the good energy-saving and demand response potential of commercial buildings, an intelligent energy-using control system for commercial buildings based on cyber physical system（CPS）architecture is proposed. Based on the three-tier architecture of typical CPS system, unit level realizes dynamic information perception, standardized information modeling and control of energy-using systems such as air conditioning, lighting and electric heating through intelligent energy-using terminals. System level implements multi - information fusion and edge calculation through intelligent energy-using gateway to realize building energy efficiency analysis, energy efficiency diagnosis and coordinated control of multi-equipment. Platform level implements aggregation and synergetic optimization of energy response potential of multi-commercial buildings through intelligence. Take a commercial building in Shenzhen as an example, an intelligent control and management system based on CPS architecture is deployed and applied.The results show that responsiveness of energy regulation and control is significantly improved, and energy consumption is signifi-cantly reduced.

Abstract:With the continuous advancement of incremental power distribution business reform, a large number of park pilots are entering the stage of implementation and grid-connected operation. From two aspects, strategic recommendations for power distribution companies to fully mobilize demandside response resources are provided. Firstly, in order to absorb local distributed energy inside, time-of-use price signals are used to guide users to adjust production plans. Based on the net load curve of the park pilots and seasonal production characteristics of industrial users, the peak-to-valley time and implementation cycle are arranged. Then conduct separate research and simulation operations for industrial users who intend to implement time-of-use electricity prices, and customize personalized time-of-use retail power packages for them.Secondly, in order to avoid price risks in a certain period of time in the future power spot market outside, a peak-cutting bidding model suitable for industrial and commercial users of park pilots is established. And a credit assessment link is added, and peak-cut com-pensation fees are paid based on the user’s performance credit coefficient and real-time response. In the end, an example is used to verify the feasibility of the proposed method model, and it can effectively guide users to cut peaks and fill valleys while saving corporate electricity expenses.

Abstract:Load forecasting of large scale distribution network needs to focus on the accuracy and calculation efficiency. Because of the large scale and complex correlation factors, the traditional centralized or simple distributed platform environment is difficult to meet the application requirements. A solution based on the big data platform is proposed. Combined with the characteristics of large-scale distribution network load forecasting application scenario, the technical route of key links such as data storage, data preprocessing, characteristic analysis, forecasting algorithm, etc. is proposed in the scheme. The classified storage of multiple types of data is realized by the application of diversified distributed storage mode；data preprocessing, load characteristic analysis, etc. is realized by the application of machine learning technology；rolling shortterm forecasting based on sliding window operation and medium and long-term forecasting based on stateless operation is realized by the application of spark stream computing technology. The practical application results in a province prove that the solution is effective in improving the forecasting accuracy and calculation efficiency.

Abstract:Accurate and fast prediction of V2G power capacity is the key to realize the energy storage of aggregated batteries of electric vehicles（EVs）as a buffer for power grid and renewable energy. However, the randomness and uncertainty of charging and discharging behavior of electric vehicles make it difficult to predict V2G power accurately. With the development of the Internet of Things（IOT）and the large-scale access of electric vehicles, the charging and discharging data of electric vehicles have increased explosively, which provides a large amount of data support for the accurate V2G power capacity, but also brings large data processing problems. A parallel prediction model of V2G power capacity is established based on the parallel random forest algorithm by using a large amount of historical and meteorological data to construct the prediction feature vector. Thus, the influence of user behavior on prediction results is avoided. In addition, a distributed big data platform based on Spark is built to realize rapid prediction of V2G power capacity. Finally, the proposed method is compared with SVM algorithm which is used in predicting V2G power capacity on traditional stand-alone platform. The experimental results show that using the parallel random forest algorithm is not only 1.75% more accurate than using the traditional SVM, but also more than 6 times faster.

Abstract:In order to overcome the problems of multi-depart-ment coordination, multi-task combination, and repeated power outages in the traditional power outage management and control mode,an overall design scheme for a multi-dimensional power outage plan intelligent management and control system is proposed. Firstly, the concept of multi-dimensional blackout plan data pool is proposed, and the blackout plan management and control rule base is established. Based on this, intelligent optimization of multi-cycle blackout plans is automatically carried out by constructing a plan optimization algorithm model that meets the actual needs, including annual blackout plans intelligent optimization and rolling revision of the monthly power outage plan, and through the closed-loop management of the power outage plan to ensure the rigidity of the power outage plan. On this basis, the basic architecture and functional plan of the multi-dimensional power outage plan intelligent management and control system are proposed, and the design plan is implemented. The calculation example shows that the designed scheme is effective and feasible.

Abstract:Dealing with large-scale projects, traditional database analysis and design methods cannot reflect the actual business requirements to the most extent, which will lead to the difficulty in extending and maintaining the system. Based on domain-driven design, business requirements can be accurately mapped into computer languages, and guide the development of micro services by abstracting complex business into clearly defined domains.Through the demand analysis, business object identification and aggregation division of the power distribution and sale, a business domain with high aggregation and low coupling is formed, which makes the complexity of the subsequent development system modules controllable, reusable and easy to change.

Abstract:Smart meters can collect power consumption data of consumers in real time, and will be widely popularized in the future digital power distribution system. In the context of the further liberalization of domestic electricity sales market and its gradual prosperity, electricity retailers can analyze the mass electricity consumption data of the consumers to grasp the electricity consumption behavior, thereby achieving better services. The feature extraction method for user behavior analysis of electricity sales market is discussed. K- means, fuzzy clustering, hierarchical clustering and other clustering algorithms are adopted to achieve the pattern extraction of typical user electricity behavior, and the basic features of electricity consumption behavior of different users are analyzed.An empirical analysis is conducted on the public electricity data of 6 445 consumers in Ireland. The result proves that the proposed method can effectively extract the patterns of behaviors, and distinguish the differences and similarities among users.

Abstract:The market operation model and trading mechanism should be coordinated development with the pilot projects of incremental distribution network. Different market roles lead to different ways of market participation. Firstly in the view of electricity retailers and combined with the different market background, the business model and transaction mechanism of purchasing and selling electricity of incremental distribution network with distributed generation are put forward. Then, in the view of load aggregators,considering the sensitivity of consumers to the real-time electricity price in the spot market, the transaction mechanism of participating in demand response for incremental distribution network as a consumer agent is put forward. Finally, aiming at the development status of incremental distribution network and the problems coming in the future integrated operation mode, the main technical difficulties are analyzed to provide references for the future research of incremental distribution network.

Abstract:The calculation of avoidable costs is the core technology of power demand side management project evaluation and the main basis for measuring demand side management projects.The processes of evaluating the benefits of DSM projects are also the processes of evaluating the avoidable costs of power system. A comprehensive unit avoidable cost model of power system is established in which the transmission and distribution unit avoidable cost takes the allocation factor into consideration to reflect the different value of the load reduced in different time. The avoidable costs model of the power generation company, the power company and the community is also established, and a case is used to analyze the profit of the power generation company, the power company and community in different DSM investment projects.

Abstract:In recent years, many entities such as power grid utilities, power producer and heating companies have been widely involved in the field of integrated energy services（IES）. A competitive landscape in which different interests of different stakeholders are coupled with each other is formed. It is urgent to achieve healthy development under the guidance of multiple factors such as technology, market and policy. Therefore, clarfying the stakeholders involved in the park level IES, and the characteristics is of great importance to each stakeholder, participation enthusiasm, internal driving force, and the interest coupling relationship between different stakeholders. The main stakeholders of the park level IES is sorted out, and the demand for integrated energy services in different park scenarios is analyzed. The interest demands and participation methods of various stakeholders are summarized. The coupling relationship of various stakeholders in IES from the competition of power supply and heating is studied. The cooperation and competition relationship among the various stakeholders in the industrial and commercial scenario is obtained. Finally, the overall interest pattern of park level IES is proposed.

Abstract:The rapid development of agricultural economy and power distribution network automation technology provides possiblility for fine management of electric irrigation load and participation in grid regulation. Firstly, the electricity characteristics of electric irrigation load are analyzed. Then the optimum operation strategy of electric irrigation load under the influence of timeshared electricity price is calculated with LINGO model. On this basis, the particle swarm optimization algorithm is used to calculate the optimal operation strategy of distribution network, which takes into account the influence of electric irrigation load. The example based on the IEEE33 is analyzed, which verifies the effectiveness of the operation optimization strategy proposed.

Abstract:In recent years, with the increasing proportion of distributed power supply, electric vehicles and smart appliances accessing to the user side, the demand side resources that can be mobilized are more and more abundant. The impact of multiple variables on demand side response is explored, a multi-order grey prediction model based on grey correlation degree and a prediction method combining Markov chain fuzzy matrix are proposed to predict long-term demand side response ability. The multi-order grey forecasting model adopted mainly takes into account the time-space characteristics of load independent variables and the correlation of multiple external variables. When the state variables and time variables are discrete data, Markov chain has a good effect on adjusting the errors in the process of accumulating grey theory.Therefore, Markov chain fuzzy matrix is used to correct the prediction errors, and improves the prediction accuracy of long-term demand side response ability.Combining with the load data of Shanghai in recent 10 years, the validity of the forecasting method is verified.

Abstract:Demand side resources have been increasingly important in the regulation of supply-demand balance of power grid.Taking thermostatically controlled load（TCL）as an example, combination control methods of several kinds of load are researched.Firstly, according to the user’s electricity differential constraints of electric water heaters（EWHs）and air conditioners（ACs）, a normalized constraints evaluation method based on fuzzy membership model is proposed. Then, a potential model of multi -TCLs cluster regulation is constructed, and a collaborative regulation method combining EWHs and ACs is proposed. Lastly, the proposed collaborative control method is applied to wind power absorption scenarios to achieve accurate load control. The simulation results verified that the proposed method can get the balance and fairness of control, and also achieve good absorption effect on the basis of taking account of users’power-using satisfaction.

Abstract:Developing the electric vehicle industry vigorously is a new measure to alleviate the fossil energy crisis, but its disordered charging mode will aggravate the load peak-valley difference and affect the safe and stable operation of the power system. In order to solve the above problems, an orderly charging and discharging strategy for EV considering user charge delay time is proposed. A multi-objective optimization model with standard deviation of load and user cost is established, taking the remaining electricity and charge and discharging limit of adjacent time intervals as constraints. A non-dominated sorting genetic algorithm-II with elite strategy is used to solve the mode. Finally, its optimal compromise solution is obtained. The example shows that the optimal delay time can be obtained by the model under different constraints. The peak-valley difference of load can be reduced within the limited charging time of users, and user cost can be reduced due to the time-sharing tariff.

Abstract:As one of the key points of the new round of power system reform, the power-sale-side reform will lead to major changes in the terminal sales model of domestic power market. In this background, aiming at the problems of improving the competitiveness of electricity retail service, firstly, the overall pattern of the future power market and the business models of the power sale company under the background of the new electricity market reform are discussed. Secondly, the factors which influence on the competitiveness of the power service and their action paths are analyzed, and the structural equation model is also constructed. Finally, through model fitting, the key factors and their action mechanisms of affecting the competitiveness of domestic electricity retail service are empirically studied. The research results show that under the opening electricity retail environment, for a power sale company it is the key point to enhance the competitiveness to develop personalized and comprehensive value-added services to enhance the competiveness.

Abstract:The processing of deviation power is a key link in the settlement of power transactions across provinces and regions.Firstly, the deviation settlement models of typical power markets at home and abroad is summarized, and then the three commonly used methods for allocation and settlement of deviation power to summarize their advantages and disadvantages are analyzed. And the problems of the current deviation settlement method with the development of the southern regional market are analyzed. In order to connect well with the spot market settlement mechanism and give full play to the role of market pricing, a separate pricing and settlement method for offset power is proposed, and the design of offset pricing and offset cost allocation mechanism is given. Finally, according to the settlement requirements of different development stages of the southern regional market, the reasonable selection of deviation settlement methods is put forward, and the prospect of how to improve the inter-provincial and inter-regional settlement mechanism of the southern region is expected.