Deep peak load compensation of energy storage system

What is a deep peak load regulation compensation mechanism of thermal power units?

A deep peak load regulation compensation mechanism of thermal power units is presented to encourage the units to actively participate in peak load regulation and improve their peaking capability. The compensation mechanism consists of two sections.

Why should thermal power units carry out deep peak shaving?

However, when thermal power units carry out deep peak shaving, their economy will be considerably reduced , and the thermal power units face many problems under low load conditions . Only by changing this situation can we achieve deep integration of thermal power generation and renewable energy development.

What is deep peak regulation of thermal power plants?

Therefore, deep peak regulation (DPR) of thermal power plants remains one of the main peak regulation methods for the source side in China. The lower reserve capacity of thermal power plants is used to provide peak regulation power generation rights for renewable energy sources such as wind and solar energy.

Do thermal power units participate in peak regulation auxiliary services?

Owing to China’s energy structure, thermal power accounts for nearly half of the country’s installed power generation capacity. Although the willingness of thermal power units to participate in peak regulation auxiliary services is low, we propose a peak regulation cost compensation and capacity-proportional allocation mechanism.

How to reduce peak regulation pressure of thermal power units?

In order to reduce the peak regulation pressure of thermal power units and maximize the use of resources such as wind, solar, water storage and DR to participate in peak regulation auxiliary services, the minimum fluctuation of thermal power output is taken as the objective function, as shown in Eq. 19.

What is a deep peak regulation auxiliary service bidding strategy?

A deep peak regulation auxiliary service bidding strategy for CHP units based on a risk-averse model and district heating network energy storage. Energies 12 (17), 3314. doi:10.3390/en12173314 Wu, D., Cheng, H., Zhao, J., Geng, J., and Hou, W. (2019). Wind power segmentation and thermal power peak shaving compensation method based on balance cost.