{"title":"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","authors":"Xinbin Liang, Wei Ge, Zheming Zhang, Fei Zheng, Xinqiao Jin, Zhimin Du","doi":"10.1016/j.scs.2024.105919","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":"116 ","pages":"Article 105919"},"PeriodicalIF":10.5000,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Two-stage optimal scheduling for flexibility and resilience tradeoff of PV-battery building via smart grid communication\",\"authors\":\"Xinbin Liang, Wei Ge, Zheming Zhang, Fei Zheng, Xinqiao Jin, Zhimin Du\",\"doi\":\"10.1016/j.scs.2024.105919\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>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.</div></div>\",\"PeriodicalId\":48659,\"journal\":{\"name\":\"Sustainable Cities and Society\",\"volume\":\"116 \",\"pages\":\"Article 105919\"},\"PeriodicalIF\":10.5000,\"publicationDate\":\"2024-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sustainable Cities and Society\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2210670724007431\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"CONSTRUCTION & BUILDING TECHNOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Cities and Society","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2210670724007431","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CONSTRUCTION & BUILDING TECHNOLOGY","Score":null,"Total":0}
Two-stage optimal scheduling for flexibility and resilience tradeoff of PV-battery building via smart grid communication
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.
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;