Emergency demand response for distribution system contingencies

Tyagi, R. K.; Black, Jason

doi:10.1109/tdc.2010.5484598

Cited by 38 publications

(24 citation statements)

References 3 publications

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“…Another similar simulation has shown that volatility of nodal spot price is reduced and reliability of power systems is improved in the presence of demand response in the system [22]. Implementing programs with non-vital residential loads generally stabilize distribution network and prevented blackout [23]. In [24], the concept of DR exchange is proposed which is pooling the consumers with similar interests in their demand reduction to be bought by various buyers of DR like the retailer, transmission system operator (TSO) and the distribution system operator (DSO).…”

Section: Demand Response Experiences Within Smart Grid Environmentmentioning

confidence: 97%

Demand response for sustainable energy systems: A review, application and implementation strategy

Shariatzadeh¹,

Mandal

Srivastava

2015

Renewable and Sustainable Energy Reviews

299

157

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Section: Demand Response Experiences Within Smart Grid Environmentmentioning

confidence: 97%

Demand response for sustainable energy systems: A review, application and implementation strategy

Shariatzadeh¹,

Mandal

Srivastava

2015

Renewable and Sustainable Energy Reviews

299

157

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“…This program is mainly offered to larger users (one megawatt or more); for small users, they need third parties or agents to unite and represent them to bid. 4) Emergency demand reduction: Users are provided incentive payments in reply to their load reductions (on very short notice) during emergency reliability accidents when the grid is out of reserve [22]. Under this program, larger users can provide auxiliary services to the power utility by reducing their demand, behaving as virtual spinning reserves.…”

Section: A Incentive-based Programmentioning

confidence: 99%

“…Incentive-based Program Direct load control (DLC) [19] Interruptible/curtailable load [20] Demand bidding & buyback [21] Emergency demand reduction [22] Price-based Program Time-of-use (ToU) pricing [23] Critical peak pricing (CPP) [24] Real-time pricing (RTP) [25], [26] Inclining block rate (IBR) [27] Demand Response Issues…”

Section: Demand Response Programsmentioning

confidence: 99%

A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches

Deng

Yang

Chow

et al. 2015

IEEE Trans. Ind. Inf.

791

375

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The smart grid is widely considered to be the informationization of the power grid. As an essential characteristic of the smart grid, demand response can reschedule the users' energy consumption to reduce the operating expense from expensive generators and further to defer the capacity addition in the long run. This survey comprehensively explores the four major aspects -programs, issues, approaches, and future extensions -of demand response. Specifically, we first introduce the means/tariffs that the power utility takes to incentivize users to reschedule their energy usage patterns. Then we survey the existing mathematical models and problems in the previous and current literatures, followed by the state-of-the-art approaches and solutions to address these issues. Finally, based on the above overview, we also outline the potential challenges and future research directions in the context of demand response.

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“…In papers [12]- [13], technical and economic advantages of EDR program on electrical load in Iranian power grid is presented. In [14], assessment of EDR in distribution system to pacify the overloading of specific overloaded node is studied. In [15], a coordinated energy management technique in mixed use building is proposed to enable EDR program.…”

Section: Introductionmentioning

confidence: 99%

Optimal decision making model of battery energy storage-assisted electric vehicle charging station considering incentive demand response

Upadhaya

Feng

Zhou

et al. 2019

8th Renewable Power Generation Conference (RPG 2019)

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Considering large scale implementation of electric vehicles (EVs), public EV charging stations are served as fuel tanks for EVs to meet the need of longer travelling distance and overcome the shortage of private charging piles. The allocation of local battery energy storage (BES) can enhance the flexibility of the EV charging station. This paper proposes an optimal decision making model of the BES-assisted EV charging station considering the incentive demand response. Firstly, the detailed models of the BES-assisted EV charging station are presented. Secondly, as a representative incentive demand response, the emergency demand response (EDR) model is introduced. Thirdly, based on the charging load forecast data, an optimal decision making model of the BESassisted EV charging station considering the EDR to maximize the charging station's operating profit is established. Finally, the feasibility of the proposed method is verified through case studies. The conclusions of this paper are as follows: 1) Through the optimal decision making model, correct and profitable EDR participation decision can be determined for the BES-assisted EV charging station effectively. 2) Local BES in the EV charging station can improve the charging station's ability to participate in the EDR.

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Emergency demand response for distribution system contingencies

Cited by 38 publications

References 3 publications

Demand response for sustainable energy systems: A review, application and implementation strategy

Demand response for sustainable energy systems: A review, application and implementation strategy

A Survey on Demand Response in Smart Grids: Mathematical Models and Approaches

Optimal decision making model of battery energy storage-assisted electric vehicle charging station considering incentive demand response

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