<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>In recent years, electricity consumption has been increasing, while the supply of electricity is relatively lagging, and power shortages often occur. Therefore, the management of organized power consumption is an urgent task for the current power industry. Based on the characteristics of power load, this paper constructs a decision-making management framework for orderly power consumption by considering four aspects: generation, grid side, demand side, and social benefit. Through the various types of flexible load resources aggregated within the virtual power plant, it participates in regulating its power, effectively reduces the peak-valley difference, and realizes refined, orderly power consumption management. Finally, based on the multi-objective optimization model, refined decision-making for orderly power consumption with the participation of virtual power plants is constructed and compared to traditional decision-making for orderly power consumption. The results show that compared with conventional decision-making, the peak-to-valley difference is reduced by 8.7789 WM, the economic benefit of the power enterprise is improved by 228,300 yuan, and customer satisfaction is enhanced by 0.1613, which verifies the effectiveness of the decision-making method of the sequential power consumption in this paper.</p>
</abstract>

In recent years, electricity consumption has been increasing, while the supply of electricity is relatively lagging, and power shortages often occur. Therefore, the management of organized power consumption is an urgent task for the current power industry. Based on the characteristics of power load, this paper constructs a decision-making management framework for orderly power consumption by considering four aspects: generation, grid side, demand side, and social benefit. Through the various types of flexible load resources aggregated within the virtual power plant, it participates in regulating its power, effectively reduces the peak-valley difference, and realizes refined, orderly power consumption management. Finally, based on the multi-objective optimization model, refined decision-making for orderly power consumption with the participation of virtual power plants is constructed and compared to traditional decision-making for orderly power consumption. The results show that compared with conventional decision-making, the peak-to-valley difference is reduced by 8.7789 WM, the economic benefit of the power enterprise is improved by 228,300 yuan, and customer satisfaction is enhanced by 0.1613, which verifies the effectiveness of the decision-making method of the sequential power consumption in this paper.

A refined decision-making method for orderly power consumption in virtual power plants considering load characteristics

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

In recent years, electricity consumption has been increasing, while the supply of electricity is relatively lagging, and power shortages often occur....

A refined decision-making method for orderly power consumption in virtual power plants considering load characteristics

Online veröffentlicht: 03. Juni 2024

Seitenbereich: -

Eingereicht: 17. Feb. 2024

Akzeptiert: 30. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1356

Schlüsselwörter
Orderly power consumption, Load characteristics, Virtual power plant, Power system, Multi-objective optimization

© 2024 Hao Guo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

A refined decision-making method for orderly power consumption in virtual power plants considering load characteristics

Online veröffentlicht: 03. Juni 2024

Seitenbereich: -

Eingereicht: 17. Feb. 2024

Akzeptiert: 30. Apr. 2024

DOI: https://doi.org/10.2478/amns-2024-1356

SchlüsselwörterOrderly power consumption, Load characteristics, Virtual power plant, Power system, Multi-objective optimization

© 2024 Hao Guo et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Orderly power consumption, Load characteristics, Virtual power plant, Power system, Multi-objective optimization