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Incentive determination of a demand response program for microgrid
Journal article   Peer reviewed

Incentive determination of a demand response program for microgrid

Y. Astriani, GM. Shafiullah and F. Shahnia
Applied Energy, Vol.292, Art. 116624
2021
DOI: https://doi.org/10.1016/j.apenergy.2021.116624
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Abstract

The return on investment for a microgrid can be accelerated if the microgrid can maximize its profits, either by minimizing the cost of energy production or maximizing the revenue from selling electricity to the microgrid customers. This can be achieved by implementing demand response. Under a demand response program, microgrid loads can be re-scheduled from peak to off-peak periods or shaved and shed during peak periods. Moreover, demand response execution may reduce customers’ comfort; thus, the microgrid operator should offer some compensating incentives to the participants. This study has been conducted from a microgrid owner’s perspective, aiming at determining the demand response incentives for its customers which should be feasible for both demand response participants and the microgrid operator. The incentives are derived from the difference between the microgrid’s profits before implementing the demand response program and its projected benefit before implementation. Due to the effects of controlling customers' loads to the customers comfort and economic aspects, the demand response is also optimized to minimize the number of affected loads and customers’ discomfort. The given incentive varies based on the participants' discomfort level and the load’s economic value. The results show that the microgrid operating under the proposed demand response program is able to increase its profits, part of which is allocated to the consumers as an incentive to participate in the program. Furthermore, the results from the sensitivity analysis show that the pay-back period of the participants’ demand response deployment cost is within the project lifetime.

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UN Sustainable Development Goals (SDGs)

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#7 Affordable and Clean Energy

Source: InCites

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63 Record Views
67 Times Cited - Web of Science

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Collaboration types
International collaboration
Citation topics
4 Electrical Engineering, Electronics & Computer Science
4.18 Power Systems & Electric Vehicles
4.18.204 Smart Grid Optimization
Web Of Science research areas
Energy & Fuels
Engineering, Chemical
ESI research areas
Engineering
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