Optimal Bidding Strategy of Demand Response Aggregator Based On Customers’ Responsiveness Behaviors Modeling Under Different Incentives

Lu, Xiaoxing; Ge, Xinxin; Li, Kangping; Wang, Fei; Shen, Hongtao; Tao, Peng; Hu, Junjie; Lai, Jingang; Zhen, Zhao; Shafie‐khah, Miadreza; Catalão, João P.S.

doi:10.1109/tia.2021.3076139

Cited by 66 publications

(22 citation statements)

References 45 publications

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“…Each SEA is dedicated to a specific type of asset and is able to apply strategies (e.g., generation curtailment, load shedding, or flexibility services) selectively to the given asset [40]. Distinct SEAs can be defined for dispatchable distributed generation, renewable energy with storage [41], various types of equipment used for DR [42] including consumer responsiveness [43], electric vehicles [44] and charging stations [45]. Each SEA can handle the specific asset by considering more details in the models and control strategies [46], avoiding the need of designing overall strategies for many assets together.…”

Section: Coordinated Management Of Multiple Aggregatorsmentioning

confidence: 99%

Coordination of specialised energy aggregators for balancing service provision

Diaz-Londono

Flórez

Vuelvas

et al. 2022

Sustainable Energy, Grids and Networks

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Section: Coordinated Management Of Multiple Aggregatorsmentioning

confidence: 99%

Coordination of specialised energy aggregators for balancing service provision

Diaz-Londono

Flórez

Vuelvas

et al. 2022

Sustainable Energy, Grids and Networks

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“…In Ref. [ 26 ], the optimal bidding strategy of the demand response aggregator is discussed based on the modeling of customer response behaviors under different incentives. Reference [ 27 ], proposes a new decision framework for demand response aggregator business in wholesale and retail markets.…”

Section: Introductionmentioning

confidence: 99%

Optimal demand response aggregation in wholesale electricity markets: Comparative analysis of polyhedral; ellipsoidal and box methods for modeling uncertainties

Nojavan,

Hagh,

Taghizad-Tavana

et al. 2024

Heliyon

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“…The typical flexible resources it contains, such as central air conditioning and electric vehicles, have considerable adjustable characteristics and have become an effective alternative resource for grid-side regulation capacity. In addition, distributed wind power, photovoltaic, energy storage and other source storage flexible resources have considerable regulatory potential to be tapped [4][5][6][7] . These multiform flexible resources can provide a variety of auxiliary services for the power system and grid security operation support, and promote new energy consumption and improve the grid operating characteristics.…”

Section: Introductionmentioning

confidence: 99%

Flexible load aggregator optimization scheduling research based on improved seagull algorithm

Liu,

Zhu,

et al. 2023

Second International Conference on Energy, Power, and Electrical Technology (ICEPET 2023)

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Source storage flexible resources such as central air conditioning, electric vehicles, distributed wind power, photovoltaic, and energy storage have considerable regulation potential and are effective alternative resources for grid-side regulation capacity. However, there is no complete theoretical approach for the construction of multi-timescale optimal model and optimization strategy for multi-subject flexible loads. Considering these problems, this paper proposes a multi-timescale model and optimal scheduling strategy for flexible load aggregators based on the quadratic attack of improved seagull algorithm. Firstly, a flexible load hierarchical optimal scheduling architecture is proposed to aggregate flexible load resources; secondly, a generalized aggregation model is established for electric vehicles, temperature-controlled loads and distributed energy storage loads, and in the day-ahead phase, the start-stop schedule of conventional units, optimal charging of electric vehicles and flexible load aggregator operation constraints are considered. In the intra-day phase, the system rotation backup cost and temperature-controlled load constraints are considered to construct an intra-day optimal dispatching model. Then an economically optimal dispatching strategy is proposed to construct a model based on flexible loads such as electric vehicles, temperature-controlled loads, and distributed storage loads, and an improved seagull optimization algorithm based on population optimization and dynamic strategy is proposed to solve the problem. Finally, the correctness and effectiveness of the proposed model algorithm is verified on the improved IEEE33 node system.

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Optimal Bidding Strategy of Demand Response Aggregator Based On Customers’ Responsiveness Behaviors Modeling Under Different Incentives

Cited by 66 publications

References 45 publications

Coordination of specialised energy aggregators for balancing service provision

Coordination of specialised energy aggregators for balancing service provision

Optimal demand response aggregation in wholesale electricity markets: Comparative analysis of polyhedral; ellipsoidal and box methods for modeling uncertainties

Flexible load aggregator optimization scheduling research based on improved seagull algorithm

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