Abstract
For the integrated energy system of coupling electrical, cool and heat energy and gas and other forms of energy, the medium- and long-term integrated demand response of flexible load, energy storage and electric vehicles and other demand side resources is studied. It is helpful to mine the potentials of demand response of various energy sources in the medium- and long-term, stimulate the flexibility of integrated energy system, and improve the efficiency of energy utilization. Firstly, based on system dynamics, the response mode of demand response resources is analyzed from different time dimensions, and the long-term, medium-term and short-term behaviors of users participating in integrated demand response are considered comprehensively. An integrated demand response model based on medium-and long-term time dimension is established. Then the integrated demand response model of integrated energy system scheduling and flexible load, energy storage and electric vehicles as the main participants is established to simulate the response income of users participating in the integrated demand response project, and to provide data sources for the medium- and long-term integrated demand response system dynamics model. Finally, an example is given to analyze the differences in response behaviors of flexible load, energy storage and electric vehicle users in different time dimensions under the conditions of policy subsidy, regional location and user energy preferences in different stages of the integrated energy system.
Highlights
In recent years, in order to improve energy use efficiency and deal with problems such as the deterioration of the ecological environment, an integrated energy system [1,2,3] for the energy interconnected network has been established, and the mutual conversion between different energy sources [4,5] has become a hot topic for research in various countries around the world [6,7,8]
In the short-term time scale, an integrated demand response model of integrated energy system scheduling and flexible loads, energy storage, and electric vehicles were established as participants
Made.IfIfthe theuser userhas hasalso alsoinvested invested integrated energy equipment, contact compared with other users who have not made long-term decisions, the long-term integrated demand the compared with other users who have not made long-term decisions, the long-term integrated responseresponse potentialpotential and medium-term integrated demand demand responseresponse potentialpotential are higher, this user demand and medium-term integrated areand higher, and has more respond this user has more capacity
Summary
In order to improve energy use efficiency and deal with problems such as the deterioration of the ecological environment, an integrated energy system [1,2,3] for the energy interconnected network has been established, and the mutual conversion between different energy sources [4,5] has become a hot topic for research in various countries around the world [6,7,8]. Most of them are based on the typical load day or random scenarios to establish the IDR model and analyze its impact on planning and operation It is a short-term integrated demand response, and there is not much research on the medium- and long-term integrated demand response. In response to the above problems, based on the existing research, based on system dynamics, this paper analyzes the response methods of demand response resources in different time dimensions, comprehensively considers the user’s long-term investment, updates and behaviors of integrated energy equipment, whether to sign integrated demand response contracts in the medium- term. In the short-term time scale, an integrated demand response model of integrated energy system scheduling and flexible loads, energy storage, and electric vehicles were established as participants. Based on the long-term incentives of policy subsidy, the example analyzes the policy subsidy at different stages of the integrated energy system, regional location, and user energy preferences; flexible load, energy storage, and response behavior of electric vehicle users in different time dimensions
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