Abstract
This article mainly analyze the shortcomings of the inherent peak shaving auxiliary service mechanism in the high-proportion of new energy access scenarios in Northeast China, which restricts the enthusiasm of thermal power units to participate in peak shaving. For this reason, a dynamic peak shaving compensation benchmark is proposed which follows load changes. At the same time, in order to standardize market behavior and facilitate market supervision, a guiding formula is proposed for quotation of thermal power units. Based on the above, a dynamic auxiliary service market mechanism is established which used actual operating data of Liaoning province power grid as a calculation example to verify that the mechanism can effectively improve the enthusiasm of thermal power units to participate in peak shaving, which is conducive to market operation and supervision as well.
Highlights
The Northeast Energy Regulatory Bureau issued the "Operation Rules for the Northeast Electric Power Auxiliary Service Market" in November 2016
In response to the predicament of Northeast Power Grid peak shaving, this paper has proposed a dynamic paid peak-shaving benchmark based on load fluctuations, established a bidding mechanism which is conducive to market supervision, and established a multiobjective bidding dispatch model and peak shaving auxiliary service market
We use the actual data of the Liaoning Province power grid as an example to perform calculation and analysis to verify the superiority of the new dynamic PSAS market bidding mechanism
Summary
The Northeast Energy Regulatory Bureau issued the "Operation Rules for the Northeast Electric Power Auxiliary Service Market" in November 2016. Literature [1] studies the existing methods and efficiency analysis of new energy consumption. Literature [2] aims at maximizing the expected revenue of wind power plants and proposes a day-ahead market dispatch model that considers source load and peak shaving. In response to the predicament of Northeast Power Grid peak shaving, this paper has proposed a dynamic paid peak-shaving benchmark based on load fluctuations, established a bidding mechanism which is conducive to market supervision, and established a multiobjective bidding dispatch model and peak shaving auxiliary service (hereinafter referred to as PSAS) market. We use the actual data of the Liaoning Province power grid as an example to perform calculation and analysis to verify the superiority of the new dynamic PSAS market bidding mechanism (hereinafter referred to as the dynamic mechanism)
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