Resilient Configuration Approach of Integrated Community Energy System Considering Integrated Demand Response Under Uncertainty

Integrated community energy system (ICES) enables multi-energy synergy and impulses interaction of integrated demand response (IDR) from the demand side. Nevertheless, the randomness lies in IDR resources and renewable generation in the ICES configuration issue still lacks thorough analysis. Further...

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Published in:IEEE access Vol. 7; pp. 87513 - 87533
Main Authors: Guo, Zun, Li, Gengyin, Zhou, Ming, Feng, Wei
Format: Journal Article
Language:English
Published: Piscataway IEEE 2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Biological system modeling
Blackout
Cogeneration
Configurations
Decision making
Emergency plans
Energy management
Ice
Indexes
Integer programming
Integrated community energy system
integrated demand response
Linear programming
Load modeling
Mixed integer
Planning
Randomness
Reliability
Reliability analysis
Resilience
Resistance heating
Risk levels
two-stage stochastic chance-constrained programming
vulnerability indicator
WCVaR theory
ISSN:2169-3536, 2169-3536
Online Access:Get full text
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Summary:Integrated community energy system (ICES) enables multi-energy synergy and impulses interaction of integrated demand response (IDR) from the demand side. Nevertheless, the randomness lies in IDR resources and renewable generation in the ICES configuration issue still lacks thorough analysis. Furthermore, the widely focused concern of resiliency urges more proactive consideration of potential emergencies at the planning stage of ICES. To this end, this paper proposed a resilience-oriented stochastic ICES configuration framework considering IDR influence. First, generalized IDR models are set up in detail with elaborate fuzzy feature analysis of price-responsive multi-energy loads. Then, the vulnerability indicators of tie lines and converting devices of the ICES are first introduced to demonstrate the occasional outage in the normal operation and blackout in the emergent case. In addition, the worst-case conditional value-at-risk (WCVaR) theory is innovatively integrated to the traditional risk-neutral model, which is formulated as a two-stage stochastic chance-constrained programming problem, aiming to combine portfolio with minimizing the worst-case cost caused by a disaster. The models are then transformed into mixed-integer linear programming problems via several linearization techniques. Finally, the results of the case studies showed the established model's superiority in improving the overall economy (reduce 6.94% of the worst-case cost) and system resiliency (decrease the value-at-risk by 3.20%) against an unforeseen hurricane. Meanwhile, the ICES reliability was also improved by declining 25.65% of unintended load curtailment faced with an emergency. The proposed approach provided an efficient preventive portfolio scheme of the IDR-integrated ICES for decision-makers' different risk preferences of natural hazards.
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ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2019.2924828