A Reserve Decision Model for High-Proportional Renew Energy Integrated Power Grid Based on Deep Peak-Shaving and Virtual Storage

doi:10.11930/j.issn.1004-9649.201907134

Abstract

Abstract: With the capacity of renew energy continued to grow rapidly in the northwest China, the contradiction between the consumption demand of renew energy and the characteristics of its inverse peak shaving has become the severe challenges. On the other hand, the gradual marketization of power operation also provides a new way for large-scale consumption of renew energy. Based on this, a market decision model of adjustment standby is proposed based on deep peak-shaving and virtual storage in new energy high-permeability grid. First, this paper proposes a peaking reserve model of new energy with uncertainty participation which consider new energy output volatility. Based on the price sensitivity of user-side resources, an alternate model based on the "charge and discharge" capability of "virtual energy storage" is constructed. Secondly, based on deep peak-shaving technology of thermal power units, the compensation mechanism of different peak regulation depth is determined and the standby model for deep peak shaving of thermal power unit is used. Lastly, taking the new energy consumption as the core, the system peaking and standby cost is the minimum, and the standby decision model of virtual energy storage and thermal power deep participation is built. The simulation of the example showed that the proposed decision model is effective to ensure the capacity of adjustment standby.

Key words: new energy accommodation, deep peak-shaving, virtual storage, reserve of peak-shaving, transactions decisions

CLC Number:

TM73

XUE Chen, REN Jing, ZHANG Xiaodong, CUI Wei, LIU Youbo. A Reserve Decision Model for High-Proportional Renew Energy Integrated Power Grid Based on Deep Peak-Shaving and Virtual Storage[J]. Electric Power, 2019, 52(11): 35-43.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.201907134

https://www.electricpower.com.cn/EN/Y2019/V52/I11/35

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