Multiple Perspective-Cuts Outer Approximation Method for Risk-Averse Operational Planning of Regional Energy Service Providers

In the smart grid and future energy internet environment, a regional energy service provider (RESP) may be able to integrate multiple energy resources such as generator units, demand response, electrical vehicle charging/swapping stations, and carbon emission trading to participate in the market. By...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:IEEE transactions on industrial informatics Ročník 13; číslo 5; s. 2606 - 2619
Hlavní autori: Yang, Linfeng, Jian, Jinbao, Xu, Yan, Dong, Zhaoyang, Ma, Guodong
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Piscataway IEEE 01.10.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Approximation
Carbon dioxide
Computational modeling
Computer simulation
Conditional value-at-risk
Electricity pricing
Energy management
Energy sources
Generators
Global optimization
Mathematical analysis
Mixed integer
Optimization
outer approximation
perspective-cut
Planning
regional energy service provider
Regional planning
Risk levels
Smart grid
Smart grids
Strategic planning
Uncertainty
ISSN:1551-3203, 1941-0050
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Popis
Shrnutí:In the smart grid and future energy internet environment, a regional energy service provider (RESP) may be able to integrate multiple energy resources such as generator units, demand response, electrical vehicle charging/swapping stations, and carbon emission trading to participate in the market. By imploring a well-known portfolio optimization theory conditional value-at-risk to tackle electricity price uncertainty, this paper formulates the risk-averse day-ahead operational planning for such a RESP as a mixed-integer quadratically constrained programming (MIQCP), named as RA-RESP. A global optimization method, named as multiple perspective-cuts outer approximation method (MPC-OAM) is proposed to solve this model efficiently. A remarkable stronger and tighter mixed integer linear programing master problem is designed to accelerate the convergence of the proposed method. Comprehensive simulation results show that, compared with existing day-ahead planning models, the RA-RESP is a good compromise between profit-based models and cost-based ones. The proposed MPC-OAM can solve complicated RA-RESP problem efficiently, and compared with state-of-the-art solution techniques, the MPC-OAM outperforms in both computing speed and solution quality, especially for scenario which includes more nonlinear factors.
Bibliografia:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1551-3203
1941-0050
DOI:10.1109/TII.2017.2710055