Collaborative Optimization of Capacity Scheduling for Near Zero-Carbon Public Building Co-Generation System

This paper constructs a near-zero carbon co-generation system using environmental protection equipment, and further puts forward the operation strategy of cooperative optimization of system capacity and scheduling. The outer layer of the optimization model takes the cost and carbon emission minimization as the objective of multi-objective capacity optimization, and uses NSGAII algorithm to solve it. In the inner layer, the operation strategy is optimized with the goal of minimum power deviation, and the solution is solved by mixed integer linear programming. The case study verifies the economy and environmental protection of the proposed system, and verifies the superiority of the proposed strategy over the rule-based optimization method.

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Publication Details

Published
2024-10-25
DOI
https://doi.org/10.1109/appeec61255.2024.10922456
Primary Topic
Building Energy and Comfort Optimization
Type
article
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Collaborative Optimization of Capacity Scheduling for Near Zero-Carbon Public Building Co-Generation System

Tianxiao Yan, Ran Dai, Hao Sun, Su Guo et al.
Building Energy and Comfort Optimization
article

Collaborative Optimization of Capacity Scheduling for Near Zero-Carbon Public Building Co-Generation System

Tianxiao Yan, Ran Dai, Hao Sun, Su Guo, Ting Gong, Huiying Fan
article en

Abstract

This paper constructs a near-zero carbon co-generation system using environmental protection equipment, and further puts forward the operation strategy of cooperative optimization of system capacity and scheduling. The outer layer of the optimization model takes the cost and carbon emission minimization as the objective of multi-objective capacity optimization, and uses NSGAII algorithm to solve it. In the inner layer, the operation strategy is optimized with the goal of minimum power deviation, and the solution is solved by mixed integer linear programming. The case study verifies the economy and environmental protection of the proposed system, and verifies the superiority of the proposed strategy over the rule-based optimization method.

Hohai University (CN)
Openalex Percentile: Top 70%
Building Energy and Comfort Optimization
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Collaborative Optimization of Capacity Scheduling for Near Zero-Carbon Public Building Co-Generation System — Tianxiao Yan, Ran Dai, et al. · (2024) | TGRS Research Map | TGRS