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Operational reliability of multi-energy customers considering service-based self-scheduling

Wang, S. (author)
Zhejiang University, Hangzhou, China,Zhejiang Univ, Coll Elect Engn, Hangzhou 310058, Zhejiang, Peoples R China.
Shao, C. (author)
Zhejiang University, Hangzhou, China,Zhejiang Univ, Coll Elect Engn, Hangzhou 310058, Zhejiang, Peoples R China.
Ding, Y. (author)
Zhejiang University, Hangzhou, China,Zhejiang Univ, Coll Elect Engn, Hangzhou 310058, Zhejiang, Peoples R China.
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Yan, Jinyue, 1959- (author)
KTH,Mälardalens högskola,Framtidens energi,Royal Institute of Technology, Stockholm, Sweden,Energiprocesser,Malardalen Univ, Sch Business Soc & Energy, Vasteras, Sweden
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Zhejiang University, Hangzhou, China Zhejiang Univ, Coll Elect Engn, Hangzhou 310058, Zhejiang, Peoples R China (creator_code:org_t)
Elsevier Ltd, 2019
2019
English.
In: Applied Energy. - : Elsevier Ltd. - 0306-2619 .- 1872-9118. ; 254
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • The developments of energy storage and substitution techniques have made it possible for customers to self-schedule their energy consumption behaviors, to better satisfy their demands in response to uncertain supply conditions. The interdependency of multiple energies, the chronological characteristics, and uncertainties in the self-scheduling context bring about additional complexities to secure the reliable energy requirements of multi-energy customers. As a necessary and challenging task, the operational reliability of multi-energy customers is tackled in this paper. Considering that the consumed energies eventually come down to the energy-related services, the self-scheduling of multi-energy customers is implemented from the perspective of specific energy-related services rather than energy carriers. Firstly, an optimal self-scheduling model for multi-energy customers is developed with the consideration of chronological service curtailment, service shifting and possible failures during service shifting. In the optimal self-scheduling model, the costs of service curtailment and shifting are formulated based on the proposed evaluation method. The time-sequential Monte Carlo simulation approach is applied to model the chronological volatilities of multi-energy demands over the entire study period, embedded with a scenario reduction technique to reduce the computational efforts. Taking full account of the possible scenarios, the quantitative reliability indices of the multi-energy customers can be obtained. The results in test cases demonstrate that the expected energy not supplied of the multi-energy customer drops significantly by 56.32% with the self-scheduling strategy. It can be also concluded that, the self-scheduling and its inherent uncertainties do have significant impacts on the operational reliability of the multi-energy customer.

Subject headings

TEKNIK OCH TEKNOLOGIER  -- Maskinteknik -- Energiteknik (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Mechanical Engineering -- Energy Engineering (hsv//eng)
TEKNIK OCH TEKNOLOGIER  -- Naturresursteknik -- Energisystem (hsv//swe)
ENGINEERING AND TECHNOLOGY  -- Environmental Engineering -- Energy Systems (hsv//eng)

Keyword

Multi-energy customer
Multi-energy flexible service
Operational reliability
Self-schedule
Time-sequential Monte Carlo simulation
Customer satisfaction
Energy utilization
Intelligent systems
Reliability
Sales
Scheduling
Flexible service
Multi energy
Time sequential Monte Carlo Simulation
Monte Carlo methods
energy efficiency
energy storage
energy use
Monte Carlo analysis
operations technology
reliability analysis
uncertainty analysis

Publication and Content Type

ref (subject category)
art (subject category)

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By the author/editor
Wang, S.
Shao, C.
Ding, Y.
Yan, Jinyue, 195 ...
About the subject
ENGINEERING AND TECHNOLOGY
ENGINEERING AND ...
and Mechanical Engin ...
and Energy Engineeri ...
ENGINEERING AND TECHNOLOGY
ENGINEERING AND ...
and Environmental En ...
and Energy Systems
Articles in the publication
Applied Energy
By the university
Mälardalen University
Royal Institute of Technology

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