Abstract
Traditional demand response technologies optimize the load profile by cutting or shifting the electrical load, but they affect the customer’s energy experience, and thus the customer’s motivation to participate in demand response and load controllability are limited. For community integrated energy operators, the study of integrated customer demand response can explore their dispatch potential. Based on consumer psychology, we study the alternative energy use behavior of residential customers, establish a customer optimization model and a community integrated energy operator optimization model, and set up a Stackelberg master-slave game model with the operator as the leader and the customer as the follower. The simulation case verifies that the utilization of load-side multi-energy complementary characteristics and integrated demand response behavior can effectively improve the utilization of renewable energy and the efficiency of integrated energy operators.
Highlights
The increasingly serious energy and environmental problems of the earth have attracted widespread attention from all walks of life, and the only solution nowadays is to vigorously develop renewable energy and integrated energy internet, improve energy utilization efficiency, follow the path of sustainable development, and reduce non-renewable energy consumption
A lot of research has been conducted on the role of demand-side management in wind power consumption, the uncertainty of demand response DR (Demand Response) and the application of master-slave game in grid scheduling
In the paper [5], with the objectives of smoothing load fluctuations and reducing vehicle owners' electricity bills, a multi-objective optimization model of wind-electric vehicle cooperative scheduling with DR is established by guiding electric vehicles to the grid through price mechanisms and coordinating and optimizing generation-side resources to consume wind power
Summary
The increasingly serious energy and environmental problems of the earth have attracted widespread attention from all walks of life, and the only solution nowadays is to vigorously develop renewable energy and integrated energy internet, improve energy utilization efficiency, follow the path of sustainable development, and reduce non-renewable energy consumption. In the literature [4], considering the prediction error of new energy output and the characteristics of load DR, a multitimescale scheduling model of power system with wind power containing three stages: day-ahead, intra-day and real-time is constructed to improve the system wind power consumption capacity and reduce the system wind abandonment. In the paper [5], with the objectives of smoothing load fluctuations and reducing vehicle owners' electricity bills, a multi-objective optimization model of wind-electric vehicle cooperative scheduling with DR is established by guiding electric vehicles to the grid through price mechanisms and coordinating and optimizing generation-side resources to consume wind power. The uncertainty of price-based DR is mainly the uncertainty of baseline load and price elasticity of demand curve
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