Master–Slave Game Optimization Scheduling of Multi-Microgrid Integrated Energy System Considering Comprehensive Demand Response and Wind and Storage Combination DOI Creative Commons
Hongbin Sun,

Hongyu Zou,

Jianfeng Jia

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(22), P. 5762 - 5762

Published: Nov. 18, 2024

This paper addresses the critical challenge of scheduling optimization in regional integrated energy systems, characterized by coupling multiple physical streams (electricity, heat, and cooling) participation various stakeholders. To tackle this, a novel multi-load multi-type demand response model is proposed, which fully accounts for heterogeneous characteristics demands different campus environments. A leader–follower two-layer game equilibrium introduced, where system operator acts as leader, load aggregators, storage plants, wind farm operators serve followers. The layer employs an enhanced particle swarm (PSO) algorithm to iteratively adjust sales prices compensation unit prices, influencing user plan through model. In lower layer, charging discharging schedules supply, outputs conversion devices are optimized guide operation. novelty this approach lies integration game-theoretic framework with advanced techniques balance interests all participants enhance coordination. case study conducted evaluate effectiveness proposed strategy, demonstrating significant economic benefits. results show that encourages stakeholders invest infrastructure actively participate coordinated dispatch, leading improved overall efficiency comprehensive revenue enhancement multi-agent system.

Language: Английский

Master-slave game-based optimal scheduling strategy for integrated energy systems with carbon capture considerations DOI

Limeng Wang,

Yuze Ma, Shuo Wang

et al.

Energy Reports, Journal Year: 2024, Volume and Issue: 13, P. 780 - 788

Published: Dec. 26, 2024

Language: Английский

Citations

3
Master–Slave Game Optimization Scheduling of Multi-Microgrid Integrated Energy System Considering Comprehensive Demand Response and Wind and Storage Combination DOI Creative Commons
Hongbin Sun,

Hongyu Zou,

Jianfeng Jia

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(22), P. 5762 - 5762

Published: Nov. 18, 2024

This paper addresses the critical challenge of scheduling optimization in regional integrated energy systems, characterized by coupling multiple physical streams (electricity, heat, and cooling) participation various stakeholders. To tackle this, a novel multi-load multi-type demand response model is proposed, which fully accounts for heterogeneous characteristics demands different campus environments. A leader–follower two-layer game equilibrium introduced, where system operator acts as leader, load aggregators, storage plants, wind farm operators serve followers. The layer employs an enhanced particle swarm (PSO) algorithm to iteratively adjust sales prices compensation unit prices, influencing user plan through model. In lower layer, charging discharging schedules supply, outputs conversion devices are optimized guide operation. novelty this approach lies integration game-theoretic framework with advanced techniques balance interests all participants enhance coordination. case study conducted evaluate effectiveness proposed strategy, demonstrating significant economic benefits. results show that encourages stakeholders invest infrastructure actively participate coordinated dispatch, leading improved overall efficiency comprehensive revenue enhancement multi-agent system.

Language: Английский

Citations

2