{"title":"A stochastic iterative peer-to-peer energy market clearing in smart energy communities considering participation priorities of prosumers","authors":"","doi":"10.1016/j.scs.2024.105728","DOIUrl":null,"url":null,"abstract":"<div><p>The penetration of distributed energy resources (DERs) has changed the role of a consumer to a prosumer, i.e., producer and consumer. This new role provides the opportunity for peer-to-peer(P2P) energy trading. In this paper, a three-stage iterative framework is proposed to clear the price and quantity of trading in P2P markets while addressing price and DER uncertainties by the Monte Carlo simulation (MCS) method. Initially, bids and offers of customers are determined by implementing an advanced satisfaction-based home energy management system (HEMS) at each home. Subsequently, the market operator prioritizes bids and offers according to the amount of customers’ participation in the market. Finally, the P2P market is cleared by application of the alternating direction method of multipliers (ADMM), and the market clearing prices (MCPs) are determined. MCPs are used as a parameter to repeat the three stages, and the procedure is redone until the stopping rule is met. The proposed method's effectiveness has been investigated in communities with 8, 50, and 100 prosumers. Results indicate a 69.51 % cost reduction in a smart energy community with 50 homes through P2P energy market participation. The proposed market clearing method is compared with the common mid-market rate (MMR) and Stackelberg game methods and demonstrates over 25 % reduction in community costs.</p></div>","PeriodicalId":48659,"journal":{"name":"Sustainable Cities and Society","volume":null,"pages":null},"PeriodicalIF":10.5000,"publicationDate":"2024-08-04","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/S2210670724005535","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}
引用次数: 0
Abstract
The penetration of distributed energy resources (DERs) has changed the role of a consumer to a prosumer, i.e., producer and consumer. This new role provides the opportunity for peer-to-peer(P2P) energy trading. In this paper, a three-stage iterative framework is proposed to clear the price and quantity of trading in P2P markets while addressing price and DER uncertainties by the Monte Carlo simulation (MCS) method. Initially, bids and offers of customers are determined by implementing an advanced satisfaction-based home energy management system (HEMS) at each home. Subsequently, the market operator prioritizes bids and offers according to the amount of customers’ participation in the market. Finally, the P2P market is cleared by application of the alternating direction method of multipliers (ADMM), and the market clearing prices (MCPs) are determined. MCPs are used as a parameter to repeat the three stages, and the procedure is redone until the stopping rule is met. The proposed method's effectiveness has been investigated in communities with 8, 50, and 100 prosumers. Results indicate a 69.51 % cost reduction in a smart energy community with 50 homes through P2P energy market participation. The proposed market clearing method is compared with the common mid-market rate (MMR) and Stackelberg game methods and demonstrates over 25 % reduction in community costs.
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;