| 引用本文: | 贺宁,茹成意,李若夏,蒋德润.计及源荷不确定性的BIPV鲁棒优化调度[J].哈尔滨工业大学学报,2024,56(12):132.DOI:10.11918/202312057 |
| HE Ning,RU Chengyi,LI Ruoxia,JIANG Derun.Robust optimal scheduling for BIPV considering source-load uncertainty[J].Journal of Harbin Institute of Technology,2024,56(12):132.DOI:10.11918/202312057 |
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| 摘要: |
| 为提高光伏建筑一体化(BIPV) 能源系统运行的经济性和鲁棒性,降低光伏出力和电热冷负荷的不确定性对BIPV能源系统经济稳定运行带来的不利影响,提出了一种预测—配置—调度一体化策略实现BIPV能源系统鲁棒优化调度。首先,通过多任务高斯过程(MTGP)综合考虑光伏出力和电、热、冷负荷间的相关性,得到精确的源荷预测结果及其概率信息,以此为基础建立基于MTGP的源荷不确定集。其次,针对建筑类型和负荷需求设计能源系统结构,以系统年投资成本和年运营成本最小化为目标函数建立经济最优容量配置模型并求解。最后,在确定源荷不确定集和设备容量配置的基础上建立BIPV能源系统两阶段鲁棒优化调度模型,通过列与约束生成算法和KKT条件求解模型,得到系统经济最优调度方案。本研究采用美国亚利桑那州州立大学某教学楼电、热、冷负荷数据对所提优化策略进行验证,仿真试验结果表明:所提优化策略可以通过改变不确定集置信度灵活调整调度方案的保守性,在考虑分时电价机制下,储能设备充分发挥削峰填谷作用,降低了系统运营成本,与传统的确定性优化和采用盒式不确定集的鲁棒优化策略相比,调度方案的经济性和鲁棒性均有所提升。 |
| 关键词: 光伏建筑一体化 能源系统 源荷不确定性 多任务高斯过程 容量优化配置 鲁棒优化调度 |
| DOI：10.11918/202312057 |
| 分类号:TM734 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(61903291)；陕西省重点研发计划项目(2022NY-094) |
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| Robust optimal scheduling for BIPV considering source-load uncertainty |
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HE Ning1,RU Chengyi1,LI Ruoxia2,JIANG Derun1
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(1.School of Mechanical and Electrical Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China; 2.College of Information and Control Engineering, Xi’an University of Architecture and Technology, Xi’an 710055, China)
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| Abstract: |
| To improve the economy and robustness of building integrated photovoltaic (BIPV) energy system, and mitigate the negative impacts of uncertainty in photovoltaic output and electric heating and cooling loads on the economic and stable operation of BIPV energy system, this paper proposes an integrated prediction-configuration-scheduling strategy to achieve robust optimal scheduling for BIPV energy systems. Firstly, the correlation between photovoltaic output and electric heating and cooling loads is comprehensively considered by multi-task Gaussian process (MTGP), and the accurate source load prediction results and their probability information are obtained. On this basis, the MTGP-based source load uncertainty set is established. Secondly, the energy system structure is designed according to the building type and load requirements, and the economic optimal capacity allocation model is established and solved with the minimum annual investment cost and annual operational cost of the system as the objective function. Finally, the two-stage robust optimal scheduling model of BIPV energy system is established on the basis of determining the uncertainty set of source-load and equipment capacity allocation. The economic optimal scheduling scheme of the system is obtained by solving the model through column constraint generation algorithm and KKT condition. In this paper, the electric heating and cooling loads data of a teaching building in Arizona State University are used to validate the proposed optimization strategy. The simulation experimental results showed that the proposed optimization strategy can flexibly adjust the conservatism of the scheduling scheme by changing the uncertainty set confidence. Under considering the time-of-use electricity price, the energy storage devices give full play to the role of peak shaving and valley filling, which reduces the system operation cost. The proposed optimization strategy improves the economy and robustness of the scheduling scheme, compared with the traditional deterministic optimization strategy and the robust optimization strategy using box uncertainty sets. |
| Key words: building integrated photovoltaic(BIPV） energy system source-load uncertainty multi-task Gaussian process(MTGP) optimal capacity allocation robust optimization scheduling |
