Positive demand response and multi-hour net benefit test

Elkasrawy, Ayman; Venkatesh, Bala

doi:10.1016/j.epsr.2020.106275

Cited by 4 publications

(3 citation statements)

References 21 publications

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“…The Ref. [39] presented the concept of positive demand response (PDR) to prevailing hourly prices. [40] is another DR power scheduling method with the aim design a questionnaire to assess electricity load shifting technical.…”

Section: Related Workmentioning

confidence: 99%

“…Section III introduces the used DR program. Section IV describes used methodology and the problem formulation of power game-theoretic energy trading × × [33] credit rating management × × [34] digital currency in trading × × [6] operation cost × [35] actual-price × × [36] bilateral trading × × [37] trading prices & cost × × [38] power losses in grid MG × × [39] positive demand response × × [40] power load DR × × Pro.…”

Section: Introductionmentioning

confidence: 99%

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Optimized Power Trading of Reconfigurable Microgrids in Distribution Energy Market

et al. 2021

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Integrating Distributed Energy Resources (DERs) and Micro-Grid (MG) into a system evolved the traditional power system. In spite of their significant advantages, MGs may result in volatility and uncertainty in the power systems. For reliable operation of the grid, energy trading among MGs should be optimized to maintain a fair trading price, maximize participants' profit, and satisfy network constraints. In this paper, the optimal power trading among multiple reconfigurable MGs is formulated as a Mixed-Integer Nonlinear Programming (MINLP) considering all energy resources and their dynamic prices. In spite of the other methods in the literature, the proposed method minimizes the total cost (increase sales and decrease purchases) and transmission loss considering all energy resources in the MGs. In order to flatten the load profile, a time-based load profile is considered for the demand response program. The performance of the proposed model is evaluated on an IEEE 6-bus network as well as a modified IEEE 33-bus test system. The results verify that the proposed method, (i) determines the best configuration among MGs with a switching reduction of about 30%, (ii) optimizes the power generation of energy resources with 12% reduction in energy production, and (iii) optimizes the power trading costs with a 10% reduction in costs compared with the basic model without DR and trade that is introduced as Scen.1 in this paper.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Optimized Power Trading of Reconfigurable Microgrids in Distribution Energy Market

et al. 2021

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“…Moreover, it is shown that the combined model could minimize the energy losses and costs, simultaneously. In contrast to the conventional DRP which makes a load reduction, it is shown in [11] that an effective DRP should also play a boosting role by adding the load demand at off-peak load hours. In fact, positive demand response can reduce the generator ramping needs and thus mitigate the overall prices during peak hours.…”

Section: Introductionmentioning

confidence: 99%

Effective demand response and GANs for optimal constraint unit commitment in solar‐tidal based microgrids

Mobtahej

Esapour

Tajalli

et al. 2021

IET Renewable Power Gen

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A new approach for optimal demand response program (DRP) in the microgrid considering the high penetration of the solar energy and tidal units as significant and popular renewable sources in the system is proposed here. The proposed method makes use of a multi-objective problem (MOP) to not only minimize the total operation cost of the scheduling problem but also mitigate the high risk of the interruption in power delivery due to the components failure rate and long repairing rates. Considering the high complexity and nonlinearity of the formulation, a novel heuristic method based on the firefly algorithm is introduced to solve the problem without any assumption or killing the accuracy. In addition, a dynamic three-phase correction (DPC) formulation is proposed which can help to increase the global search characteristics of the method when boosting the convergence capability of the model. Due to the hard predictability nature of the solar irradiance, a deep learning model based on generative adversarial networks (GAN) is presented to predict the output power of the solar and tidal units properly. The high performance and feasibility of the proposed multi-layer problem are assessed on an IEEE test system.

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How should price-responsive electricity tariffs evolve? An analysis of the German net demand case

Pereira

Marques

2020

Utilities Policy

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Positive demand response and multi-hour net benefit test

Cited by 4 publications

References 21 publications

Optimized Power Trading of Reconfigurable Microgrids in Distribution Energy Market

Optimized Power Trading of Reconfigurable Microgrids in Distribution Energy Market

Effective demand response and GANs for optimal constraint unit commitment in solar‐tidal based microgrids

How should price-responsive electricity tariffs evolve? An analysis of the German net demand case

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