Redesign of Virtual Power Plant-led Electricity Demand Response Program

As the scale of renewable energy on the demand side continues to grow, a new demand response program (DRP), the virtual power plant (VPP), pays a rebate to the consumer and purchases his rooftop solar electricity. This electricity is dispatched to areas of electricity shortages, which is vital in balancing electricity loads and avoiding energy waste. However, the new DRP differs from the traditional DRP in terms of paying rebates. The traditional DRP requires consumers to respond above a specified baseline to receive a rebate. In contrast, in the new DRP, consumers can receive a rebate even if their response is small (i.e., no baseline). There is no research that addresses this divergence. Therefore, we construct a supply chain consisting of a consumer and a VPP for this novel DRP and analyze the strategic interactions between them in two situations where a baseline is not set/set. Our results show room for improvement in the DRP that dispatches electricity generated from rooftop solar. If the consumer generates more electricity from rooftop solar, the baseline, rather than frustrating the consumer, motivates the consumer to be more responsive. While the baseline also discourages the demand response process, it reduces the emissions generated from the consumer’s over-responsiveness. Additionally, our study suggests that a baseline, whether it facilitates or hinders the DRP, could benefit the VPP, depending on the business model of the VPP. In addition, we add several extensions to demonstrate the robustness of our model.

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Publication Details

Journal
Production and Operations Management
Published
2024-11-28
DOI
https://doi.org/10.1177/10591478241305859
Citations
2
Primary Topic
Smart Grid Energy Management
Type
article
Field-Weighted Citation Impact
0.42

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article

Redesign of Virtual Power Plant-led Electricity Demand Response Program

Jingxian Chen, Xuanyu Wu, Liang Liang, Min Yang
2 citations
Production and Operations Management
Smart Grid Energy Management
0.42
article

Redesign of Virtual Power Plant-led Electricity Demand Response Program

Jingxian Chen, Xuanyu Wu, Liang Liang, Min Yang
article en
2 citations

Abstract

As the scale of renewable energy on the demand side continues to grow, a new demand response program (DRP), the virtual power plant (VPP), pays a rebate to the consumer and purchases his rooftop solar electricity. This electricity is dispatched to areas of electricity shortages, which is vital in balancing electricity loads and avoiding energy waste. However, the new DRP differs from the traditional DRP in terms of paying rebates. The traditional DRP requires consumers to respond above a specified baseline to receive a rebate. In contrast, in the new DRP, consumers can receive a rebate even if their response is small (i.e., no baseline). There is no research that addresses this divergence. Therefore, we construct a supply chain consisting of a consumer and a VPP for this novel DRP and analyze the strategic interactions between them in two situations where a baseline is not set/set. Our results show room for improvement in the DRP that dispatches electricity generated from rooftop solar. If the consumer generates more electricity from rooftop solar, the baseline, rather than frustrating the consumer, motivates the consumer to be more responsive. While the baseline also discourages the demand response process, it reduces the emissions generated from the consumer’s over-responsiveness. Additionally, our study suggests that a baseline, whether it facilitates or hinders the DRP, could benefit the VPP, depending on the business model of the VPP. In addition, we add several extensions to demonstrate the robustness of our model.

Production and Operations ManagementVol. 34(7)
Ministry of Education of the People's Republic of China (CN), Hefei University of Technology (CN), Institute of Intelligent Machines (CN), Development Fund (NO)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 36%
Smart Grid Energy Management
0.42
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