Buildings;
Optimal scheduling;
Biological system modeling;
Load modeling;
Transactive energy;
Privacy;
Building energy management;
demand response (DR);
energy optimization;
multiagent system (MAS);
transactive energy;
DEMAND RESPONSE;
D O I:
10.1109/TII.2019.2932109
中图分类号:
TP [自动化技术、计算机技术];
学科分类号:
0812 ;
摘要:
Proper management of building loads and distributed energy resources (DER) can offer grid assistance services in transactive energy (TE) frameworks besides providing cost savings for the consumer. However, most TE models require building loads and DER units to be managed by external entities (e.g., aggregators), and in some cases, consumers need to provide critical information related to their electricity demand and usage, which hampers their privacy. This article introduces a transactive energy management framework for the buildings in a residential neighborhood to address grid overloading and cost optimization of the buildings. The decentralized coordination for the energy management system is realized by using a multiagent system architecture, which provides the consumers with full decision-making authority and preserves their privacy. A new event-triggered transactive market algorithm is developed, where the buildings trade energy to maximize profits, while the regional grid operator procures energy-supply flexibility of active consumers to prevent transformer overloading. A two-stage energy management system is developed for the residential buildings that schedules building loads and DER units in day-ahead stage to minimize cost and inconveniences for the consumer while participating in the real-time transactive market to maximize profits. An optimal bidding model is developed for the buildings that incorporates the degradation of residential storage devices for energy trading. Case studies and analyses with actual Australian building data and electricity tariff structures indicate the efficacy of the proposed methodology for effective mitigation of transformer overloading at a negligible cost compared to transformer replacement cost. Results also indicate that the proposed system can provide 15-20% cost savings for the consumers while minimizing their inconveniences and degradation of storage devices.
机构:
Univ Calif Berkeley, Berkeley, CA 94720 USA
Hong Kong Univ Sci & Technol, Dept Civil & Environm Engn, Hong Kong, Peoples R ChinaUniv Calif Berkeley, Berkeley, CA 94720 USA
Li, Sen
Lian, Jianming
论文数: 0引用数: 0
h-index: 0
机构:
Florida State Univ, Ctr Adv Power Syst, Tallahassee, FL 32306 USA
Pacific Northwest Natl Lab PNNL, Optimizat & Control Grp, Anal Team, Richland, WA 99352 USAUniv Calif Berkeley, Berkeley, CA 94720 USA
Lian, Jianming
Conejo, Antonio J.
论文数: 0引用数: 0
h-index: 0
机构:
Ohio State Univ, Integrated Syst Engn Dept, Columbus, OH 43210 USA
Ohio State Univ, Elect & Comp Engn Dept, Columbus, OH 43210 USAUniv Calif Berkeley, Berkeley, CA 94720 USA
Conejo, Antonio J.
Zhang, Wei
论文数: 0引用数: 0
h-index: 0
机构:
Southern Univ Sci & Technol, Dept Mech & Energy Engn, Shenzhen, Peoples R China
Univ Calif Berkeley, Elect Engn & Comp Sci Dept, Berkeley, CA 94720 USA
Ohio State Univ, Elect & Comp Engn, Columbus, OH 43210 USAUniv Calif Berkeley, Berkeley, CA 94720 USA
Zhang, Wei
IEEE CONTROL SYSTEMS MAGAZINE,
2020,
40
(04):
: 26
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52