The Virtual Power Plants containing Distributed Energy Resources are classified into two main categories of Commercial Virtual Power Plant and Technical Virtual Power Plant as a suitable way to manage industrial environments. Here, Industrial Technical Virtual Power Plant is defined as a scheduling unit containing loads and generations located in an industrial grid. A comprehensive framework is proposed here for normal and contingency conditions for various Virtual Power Plants participating in a short-term market. This framework performs a day-ahead and intra-day generation scheduling by selecting the best Demand Response programs. In this framework, the wind generations and the day-ahead and intra-day electricity market prices are considered as the stochastic parameters. A risk-management aspect is noticed in the proposed stages for contingency conditions. Then, some element changes such as seasonal load change and single-line outage are trained in the system to accredit the proposed solution in the contingency condition. Hereof, an appropriate technique is defined to represent the proposed model and solution. To specify the effectiveness and efficiency of the proposed methodology, the modified Isfahan Regional Electric Power Company network in Iran is experimented to test the method and to assess some encouraging aspects as well. By the proposed approach, attractiveness of Demand Response programs is revealed in industrial grids and the lower cost will be imposed. Also the improvement percentage of load shedding can be gained by performing the proposed scheduling that is so important for industrial processes. (C) 2017 Elsevier Ltd. All rights reserved.
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Korea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South KoreaKorea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South Korea
Jang, Dongsik
;
Eom, Jiyong
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Korea Adv Inst Sci & Technol, Grad Sch Green Growth, Coll Business, Seoul, South KoreaKorea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South Korea
Eom, Jiyong
;
Kim, Moon Gyu
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Korea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South KoreaKorea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South Korea
Kim, Moon Gyu
;
Rho, Jae Jeung
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Korea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South KoreaKorea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South Korea
机构:
Korea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South KoreaKorea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South Korea
Jang, Dongsik
;
Eom, Jiyong
论文数: 0引用数: 0
h-index: 0
机构:
Korea Adv Inst Sci & Technol, Grad Sch Green Growth, Coll Business, Seoul, South KoreaKorea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South Korea
Eom, Jiyong
;
Kim, Moon Gyu
论文数: 0引用数: 0
h-index: 0
机构:
Korea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South KoreaKorea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South Korea
Kim, Moon Gyu
;
Rho, Jae Jeung
论文数: 0引用数: 0
h-index: 0
机构:
Korea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South KoreaKorea Adv Inst Sci & Technol, Dept Business & Technol Management, Taejon 305701, South Korea