Economic Optimal Scheduling of Integrated Energy System Considering Integrated Demand Response

Xia, Mingchao; Ma, Kerui; Chen, Qifang; Hua, Zhihao

doi:10.1109/ei252483.2021.9712924

Cited by 1 publication

(2 citation statements)

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“…[14] introduces a collaborative optimization method for the operation of an electricity-gas integrated distribution system that considers both electricity and gas demand response, an electricity-gas joint demand response model is integrated into EGIDS, effectively improving the economic efficiency and adaptability of distribution systems with renewable energy sources. To promote the absorption of renewable energy and reduce the operational costs of IES, considering economic, renewable energy consumption, and IDR, an economic optimal dispatch model for IES is developed [15]. From a demand-response standpoint, taking into account the synergy and flexible transformation of multiple energy sources, a community integrated energy system (CIES) stochastic robust optimal operation model based on IDR is established.…”

Section: Introductionmentioning

confidence: 99%

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

Huo,

Yu,

Pang

et al. 2024

IEEE Access

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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.INDEX TERMS Integrated demand response, load management, herd mentality, peak-to-average ratio, genetic simulated annealing algorithm.

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Section: Introductionmentioning

confidence: 99%

“…(2) Contrary to the existing studies on IDR [12], [15], the current model gives due consideration to consumer herd mentality, and the Nash social welfare function serves as a representation of its influence. Assign higher welfare weights to consumers with higher motivation, allowing them to gain more benefits.…”

Section: Introductionmentioning

confidence: 99%