Bi-Level Multi-Objective Optimal Design of Integrated Energy System Under Low-Carbon Background
| Autor: | Yigu Zhen, Xingyu Yuan, Hongzhi Liu, Jinghui Wang, Jiaquan Yang, Xin Lv, Yang Yang, Zhao Luo |
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| Rok vydání: | 2021 |
| Předmět: |
Optimal design
Mathematical optimization General Computer Science Computer science business.industry 020209 energy 020208 electrical & electronic engineering General Engineering 02 engineering and technology Renewable energy multi-objective low carbon Electricity generation Coupling (computer programming) Greenhouse gas 0202 electrical engineering electronic engineering information engineering General Materials Science lcsh:Electrical engineering. Electronics. Nuclear engineering Electricity Decomposition method (constraint satisfaction) bi-level planning method Energy source business Integrated energy system lcsh:TK1-9971 |
| Zdroj: | IEEE Access, Vol 9, Pp 53401-53407 (2021) |
| ISSN: | 2169-3536 |
| DOI: | 10.1109/access.2021.3070654 |
| Popis: | The integrated energy system can realize the coupling and complementation of various energy sources such as cold, heat and electricity, and plays an important role in the consumption of renewable energy. This paper proposes a bi-level optimal design method for integrated energy system from both economic and carbon emissions aspects. The upper model aims at maximizing the system economy and optimizes the selection and capacity allocation of renewable energy power generation, storage and conversion equipment to meet the demands in the region. The lower model aims at maximizing the environment-protection performance and minimizes the system’s carbon emissions. Since the lower model contains binary variables to characterize trading states and charging and discharging states, the model cannot be transformed into a mathematical program with equilibrium constraints. To effectively handle this problem, the reformulation and decomposition method is adopted. Case studies show that this bi-level model can effectively consider the influence of the objective function in the lower model on the optimal capacity configuration in the upper model, avoid the influence of different objective weights when the multi-objective model is converted to the single-objective model, and obtain the global optimal solution. |
| Databáze: | OpenAIRE |
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