Integrated Demand Response Optimization for Consumer With Herd Mentality: A Genetic Simulated Annealing Approach

Abstract

In this paper, the integrated demand response (IDR) optimization problem is studied under the consideration of herd mentality. The contradiction between power supply and demand is becoming increasingly prominent. IDR can maintain the balance between power supply and demand, ensuring the safe operation of the system. The establishment of an IDR model that takes into account the herd mentality of consumers and the renewable energy supply, fully enhances consumers’ enthusiasm for participating in demand response and input renewable energy into the comprehensive energy system to improve energy conversion rate and supply, which is closer to the actual IDR process. Using the Genetic Simulated Annealing Algorithm (GSA) to solve multi-objective optimization problems with comprehensive energy efficiency, operating costs and peak-to-average ratio as optimization objectives has significant advantages in terms of iteration speed and solution accuracy. The analysis of the simulation shows that the IDR optimization model can not only improve the stability and comprehensive energy efficiency of the system but also reduce the operating cost of the system, which proves the effectiveness of the proposed method.

Keywords

• Integrated demand response
• load management
• herd mentality
• peak-to-average ratio
• genetic simulated annealing algorithm