Two-stage optimal scheduling for flexibility and resilience tradeoff of PV-battery building via smart grid communication

IF 10.5 1区 工程技术 Q1 CONSTRUCTION & BUILDING TECHNOLOGY
Xinbin Liang, Wei Ge, Zheming Zhang, Fei Zheng, Xinqiao Jin, Zhimin Du
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Abstract

Energy flexibility and energy resilience are now becoming new key features of building energy systems under the context of climate change and energy transition. During the system operation phase, these two performance indexes might be contradictory and require tradeoff. The main contribution of this study is to propose a two-stage mixed-integer linear programming (MILP) model to optimally tradeoff between flexibility and resilience. Its main idea is to improve the resilience of building energy system with minimum constraints on system flexibility using the outage risk information provided by smart grid. Two new concepts are considered in the proposed method, including self-sufficient requirement and continuous outage probability. The insight is to add additional penalty for the time step in which its battery state of charge (SOC) is far from self-sufficient requirement while the corresponding continuous outage probability is high. To validate our proposed method, a probabilistic outage simulation model is developed using sigmoid function and Markov Chain. Comprehensive numerical studies are conducted to compare the proposed method with traditional economic mode and backup mode under two outage patterns. The results demonstrate that the proposed method only uses 6.7 % additional operation cost such that 78.3 % of baseload curtailment and 81.1 % of user discomfort are reduced. The proposed MILP model can provide practical guideline for the flexibility and resilience tradeoff of distributed energy resources.
通过智能电网通信对光伏电池建筑的灵活性和复原力进行两阶段优化调度
在气候变化和能源转型的背景下,能源灵活性和能源复原力正成为建筑能源系统新的关键特征。在系统运行阶段,这两项性能指标可能存在矛盾,需要进行权衡。本研究的主要贡献在于提出了一个两阶段混合整数线性规划(MILP)模型,以优化权衡灵活性和恢复力。其主要思想是利用智能电网提供的停电风险信息,在系统灵活性受到最小约束的情况下,提高建筑能源系统的恢复能力。所提出的方法考虑了两个新概念,包括自给自足要求和连续停电概率。其原理是在电池充电状态(SOC)远未达到自给自足要求,而相应的连续停电概率较高的时间步骤中增加额外的惩罚。为了验证我们提出的方法,使用 sigmoid 函数和马尔可夫链开发了一个概率停电仿真模型。在两种停电模式下,对所提出的方法与传统的经济模式和备用模式进行了全面的数值研究比较。结果表明,所提方法仅增加了 6.7% 的运行成本,从而减少了 78.3% 的基荷削减和 81.1% 的用户不适感。所提出的 MILP 模型可为分布式能源资源的灵活性和弹性权衡提供实用指导。
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来源期刊
Sustainable Cities and Society
Sustainable Cities and Society Social Sciences-Geography, Planning and Development
CiteScore
22.00
自引率
13.70%
发文量
810
审稿时长
27 days
期刊介绍: Sustainable Cities and Society (SCS) is an international journal that focuses on fundamental and applied research to promote environmentally sustainable and socially resilient cities. The journal welcomes cross-cutting, multi-disciplinary research in various areas, including: 1. Smart cities and resilient environments; 2. Alternative/clean energy sources, energy distribution, distributed energy generation, and energy demand reduction/management; 3. Monitoring and improving air quality in built environment and cities (e.g., healthy built environment and air quality management); 4. Energy efficient, low/zero carbon, and green buildings/communities; 5. Climate change mitigation and adaptation in urban environments; 6. Green infrastructure and BMPs; 7. Environmental Footprint accounting and management; 8. Urban agriculture and forestry; 9. ICT, smart grid and intelligent infrastructure; 10. Urban design/planning, regulations, legislation, certification, economics, and policy; 11. Social aspects, impacts and resiliency of cities; 12. Behavior monitoring, analysis and change within urban communities; 13. Health monitoring and improvement; 14. Nexus issues related to sustainable cities and societies; 15. Smart city governance; 16. Decision Support Systems for trade-off and uncertainty analysis for improved management of cities and society; 17. Big data, machine learning, and artificial intelligence applications and case studies; 18. Critical infrastructure protection, including security, privacy, forensics, and reliability issues of cyber-physical systems. 19. Water footprint reduction and urban water distribution, harvesting, treatment, reuse and management; 20. Waste reduction and recycling; 21. Wastewater collection, treatment and recycling; 22. Smart, clean and healthy transportation systems and infrastructure;
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