Search

When residents participate in demand response, the randomness of residents' electricity consumption behavior can not be ignored in formulating demand response strategy. In this paper, according to the randomness of residential electricity consumption, the demand response control strategy for residential flexible load in China's new urban area is studied by making full use of the detailed residential electricity data available from the power grid. The daily demand response optimization dispatching model for residential flexible load equipment is established for load aggregator. Then the optimal scheduling model is solved.

At present, the research of power system demand response mainly tends to the research of ‘peak shaving and valley filling’, that is, under the premise that some loads on the user side are interruptible or transferable loads, the grid can mobilize the enthusiasm of users directly or indirectly through effective economic or technical means to achieve peak shaving and valley filling. The power grid guides the users to use electricity orderly by means of electric charge compensation, differential electricity price, time of use price and other incentive measures, that is, the power market can reduce the peak valley difference of power grid, reduce the loss of power grid and load impact, and ensure the reliable operation of the power grid. In this paper, according to the research status of demand response, combined with the requirements of the demand response system, the multi user demand response resource address pool is studied and designed. Based on the resource address pool, the rapid query under the demand response demand can be realized.

With the integration of electric vehicle (EV), distributed energy storage and temperature control load into the new generation power system, new challenges and opportunities are presented for power grid dispatching. Large and medium-sized users mainly rely on the operation mode of load aggregators as intermediaries to participate in demand response. Aiming at the demand response allocation problem of aggregators in this mode, and according to the response characteristics of various flexible loads, a scheduling method for flexible load aggregators to participate in power grid is proposed. We proposed a dispatching method aim at flexible load aggregator participating in power grid. Firstly, we have established different flexible load model. Secondly, the demand response strategy under the flexible incentive for personalized customization of user requirements has been studied. Finally, through the analysis of simulation examples, the effectiveness and feasibility of the method of flexible load aggregators participating in power system dispatching operation planning are verified.

In order to reduce industrial pollution, various policies have been issued in many countries and regions encouraging businesses to install pollution control equipment (PCE). However, some businesses do not use PCE as required, which is currently a blind spot for the regulatory authorities. Advanced metering infrastructure (AMI) provides large amount of electrical data which can well characterize the operating states of PCE. To this end, the anomaly detection of pollution control equipment (ADPCE) based on AMI data analytics is proposed in this paper. Clustering and Gaussian models (CGM) are used as the basic tools to identify the abnormal conditions of PCE, and convolutional neural network (CNN) is further introduced to detect the anomalies when the PCE is suspected to be replaced by a similar process equipment. The case study using realistic and simulated data demonstrates the validity of the proposed methods. The achievements made in this paper can effectively help the government supervise the implementation of pollution control by relevant businesses.

Based on the current corresponding indicators for determining overcapacity electricity consumption, the screening rules for suspected overcapacity electricity customers are scientifically formulated with data analysis methods in this paper. Overcapacity Electricity Consumption refers to the electricity customer’s violation of the power supply contract, which exceeds the capacity requested. This is a typical behavior of defaulting electricity and disrupting the normal order of electricity supply and consumption. At present, the inspection system lacks an intuitive visual interface for displaying results analysis and the support from a more scientific and flexible algorithm system. Through the expert’s empirical analysis, we have summarized the characteristic indicators of overcapacity customers and formulated the rules for identifying suspected overcapacity electricity customers.