Quantitative Assessment of Demand Response Potential for Various Types of User Loads
With the large-scale integration of renewable energy sources and frequent occurrences of"power shortages"in specific time periods,accurate assessment of demand response(DR)potential on the load side is crucial for the grid operators to formulate DR strategies,which is of great significance for all stakeholders involved in the DR implementation process.The method for assessing demand response potential for multiple types of loads for residential users is proposed based on non-intrusive load monitoring(NILM).Firstly,event detection algorithms and convolutional neural network techniques are employed to monitor and identify user load curves,thus capture user's electricity consumption patterns.Then,by considering subjective factors of users and market prices,a potential assessment indicator system is established to quantify demand-side load resources,explore the utilization potential of scattered load resources.Finally,case studies are conducted by using REDD database.It is shown that the proposed model can accurately identify multiple types of user loads,and the proposed evaluation system offers comprehensive support for DR programs.
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维普
