Bi-Level Optimization Scheduling Strategy for Building Integrated Energy System Considering Virtual Energy Storage

doi:10.16183/j.cnki.jsjtu.2024.036

Abstract

Abstract:

Integrated energy systems in buildings are an effective means to achieve low-carbon buildings. To further tap into their demand-side flexibility adjustable potential and carbon reduction potential, and reasonably allocate the interests of various entities in the building integrated energy system, a bi-level optimization scheduling strategy for building integrated energy system considering virtual energy storage in buildings under Stackelberg game framework is proposed. First, the thermal inertia of the cooling and heating system inside the building and the flexibility of the cooling and heating load are considered to leverage the virtual energy storage function of the building and improve system flexibility in the game model. Then, the genetic algorithm is used to solve the upper-level pricing model of energy operators, updating the purchase and sale electricity prices set by upper-level leaders, while the CPLEX solver is used to solve the lower-level problem, optimizing equipment output, demand response, and electricity trading plans. Finally, the proposed model is verified by case studies that it can effectively improve the economic performance and low-carbon characteristics of building integrated energy systems.

Key words: building integrated energy system (BIES), low-carbon building, Stackelberg game, virtual energy storage in bulidings, optimal dispatch

CLC Number:

TM732

LIU Donglin, ZHOU Xia, DAI Jianfeng, XIE Xiangpeng, TANG Yi, LI Juanshi. Bi-Level Optimization Scheduling Strategy for Building Integrated Energy System Considering Virtual Energy Storage[J]. Journal of Shanghai Jiao Tong University, 2026, 60(1): 61-73.

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j	α_j	β_j	γ_j	θ_j	ϕ_j	ω_j
0		0.2112	0.3317
1	0.5721	-0.0243	-0.3169	0.6991	0.1011	0.1998
2	0.0607	-0.0104	0.1741