Allocating the cost of demand response compensation in wholesale energy markets

Negash, Ahlmahz I.; Häring, Tobias; Kirschen, Daniel S.

doi:10.1109/pesgm.2015.7285630

Cited by 10 publications

(15 citation statements)

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“…Both of the curtailment and shifting are supposed to be informed to customers in advance. The compensation costs for curtailment and shifting can be determined by the contracts between the electricity utilities and customers or the bids of demand response customers in the energy market [35]. Moreover, the interruption of customers indicate a blackout and it could incur economic loss for customers.…”

Section: B Operation Dispatch Based On Optimal Power Flowmentioning

confidence: 99%

Operating Reliability Evaluation of Power Systems Considering Flexible Reserve Provider in Demand Side

Jia

Ding

Song

et al. 2019

IEEE Trans. Smart Grid

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Section: B Operation Dispatch Based On Optimal Power Flowmentioning

confidence: 99%

Operating Reliability Evaluation of Power Systems Considering Flexible Reserve Provider in Demand Side

Jia

Ding

Song

et al. 2019

IEEE Trans. Smart Grid

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“…In these tables, social welfare of the market, energy purchase cost of the system, total carbon emission of the system, and DSR aggregator profit are studied. Note that the energy purchase cost is the total cost of energy consumption from end users and load managed by the DSR aggregator, which is indicated by f In,s in Section 2 and calculated through (3). It illustrates the social welfare of all energy consumers.…”

Section: Case Studymentioning

confidence: 99%

“…DSR brings in manifold benefits to the power system. By shifting energy consumption, DSR contributes to system operation enhancement through load reduction [3] and ancillary services [4,5]. By energy generation, DSR replaces some of the conventional generation units, thus leading to environmental benefits of the power system [6,7].…”

Section: Introductionmentioning

confidence: 99%

Management and performance evaluation of DSR aggregator based on a bi‐level optimization model

Jiang

Zhang

2018

IEEJ Transactions Elec Engng

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The vast potential of demand-side resources (DSR)-including flexible loads and distributed energy resources-in the optimal operation of a power system is being increasingly recognized. Such potential can be fully realized through the access of a DSR aggregator to the power market. In this paper, a DSR aggregator is introduced for the collective management of DSRs in the power system. A bi-level optimization model consisting of power market clearing and DSR aggregator internal scheduling is formulated and solved through stochastic programing. A thorough evaluation of the DSR aggregator's performance under three different operation modes, namely energy consumer mode, energy prosumer mode, and eco-friendliness mode, is carried out to study its influence on system operation concerning social welfare, system purchase cost, carbon emission, and so on. Simulation results show that even though DSR acquires a segment of the market social welfare, it brings in benefits in economic and environmental operation of the system and contributes to DSR uncertainty alleviation.

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“…The exploitation of these renewables whose generation cost is generally low requires the availability of flexible production capacity as a backup as reserve [1]. The flexibility can be attained from either the supply side such as combined cycle gas turbine (CCGT) units or the demand side, for example demand response [2]- [3]. Furthermore, transmission switching also provides a means of enhancing the transmission network flexibility and improving the effectiveness of market operation [4], [5].…”

Section: Introductionmentioning

confidence: 99%

“…that these equations are equivalent to constraints(3) and(8).On the other hand, if the dispatchable line is out of service, i.e., binary variables zl,t are equal to 0, equations (27)-…”

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confidence: 99%

Co-optimization of transmission topology and generation dispatch incorporating demand response and renewable energy uncertainty in day-ahead electricity markets

Năng¹

2019

jst

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The variability of renewables requires a higher degree of flexibility in power system operation. At present, there are a variety of solutions which are being utilized, particularly demand response and transmission switching. This paper presents a model for co-optimization of transmission topology and generation dispatch based on a two-stage stochastic optimization. Demand response and renewable energy uncertainty are integrated into the proposed model. The uncertainty pertaining to renewable energy sources is presented through a set of scenarios. The model is a mixed-integer linear programming (MILP) problem and can be applied for the day-ahead market clearing. The results implemented using a 5-bus system demonstrate the effectiveness of the proposed model.

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Allocating the cost of demand response compensation in wholesale energy markets

Cited by 10 publications

References 0 publications

Operating Reliability Evaluation of Power Systems Considering Flexible Reserve Provider in Demand Side

Operating Reliability Evaluation of Power Systems Considering Flexible Reserve Provider in Demand Side

Management and performance evaluation of DSR aggregator based on a bi‐level optimization model

Co-optimization of transmission topology and generation dispatch incorporating demand response and renewable energy uncertainty in day-ahead electricity markets

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